references.bib

@inproceedings{mckee_relationship_1993,
  address = {Anaheim},
  title = {The {Relationship} of {Drought} {Frequency} and {Duration} to {Time} {Scales}},
  language = {en},
  booktitle = {8th {Conference} on {Applied} {Climatology}, {Am}. {Meteorol}. {Soc}.},
  publisher = {American Meteorological Society},
  author = {McKee, Thomas B. and Doesken, Nolan J. and Kleist, John},
  year = {1993}
}


@book{gladstones_viticulture_1992,
  address = {Adelaide},
  title = {Viticulture and {Environment}},
  isbn = {1-875130-12-3},
  publisher = {Winetitles},
  author = {Gladstones, John},
  year = {1992}
}


@book{gladstones_wine_2011,
  address = {Adelaide},
  title = {{Wine}, {Terroir} and {Climate Change}},
  isbn = {978-1-74305-032-3},
  publisher = {Wakefield Press},
  author = {Gladstones, John},
  year = {2011}
}


@incollection{huglin_nouveau_1978,
  address = {Constança, Roumanie},
  series = {1},
  title = {Nouveau mode d'évaluation des possibilités héliothermiques d'un milieu viticole},
  booktitle = {Symposium {International} sur l'Écologie de la {Vigne}},
  publisher = {Ministère de l'Agriculture et de l'Industrie Alimentaire},
  author = {Huglin, Pierre},
  language = {fr},
  year = {1978},
  pages = {89--98}
}


@book{huglin_biologie_1998,
  address = {Paris, France},
  title = {Biologie et {Écologie} de la {Vigne}},
  isbn = {978-2743002602},
  author = {Huglin, Pierre and Schneider, Christophe},
  publisher = {Tec et Doc},
  language = {fr},
  year = {1998},
  month = {aug},
  pages = {1--370}
}


@article{tonietto_multicriteria_2004,
  title = {A multicriteria climatic classification system for grape-growing regions
    worldwide},
  volume = {124},
  issn = {0168-1923},
  url = {https://www.sciencedirect.com/science/article/pii/S0168192304000115},
  doi = {10.1016/j.agrformet.2003.06.001},
  abstract = {This study concerns firstly the methodology to describe the climate of
    vineyards, on a macroclimate scale of viticultural regions worldwide. Three synthetic
    and complementary viticultural climatic indices (potential water balance of the soil
    over the growing cycle, heliothermal conditions over the growing cycle and night
    temperature during maturation), validated as descriptors, are used: (1) dryness index
    (DI) which corresponds to the potential water balance of the soil of Riou’s index, here
    adapted using precise conditions to calculate it, as an indicator of the level of
    presence-absence of dryness; (2) heliothermal index (HI) which corresponds to Huglin’s
    heliothermal index; (3) cool night index (CI) an index developed as an indicator of
    night temperature conditions during maturation. These indices are representative of the
    variability of the viticultural climate worldwide, related to the requirements of
    varieties, vintage quality (sugar, colour, aroma), and typeness of the wines. A
    Multicriteria Climatic Classification System (Géoviticulture MCC System) for the
    grape-growing regions worldwide is formulated based on classes for each of the three
    climate indices, with elements to explain the results. Three formulated concepts
    provide the system base: viticultural climate, climatic group and viticultural climate
    with intra-annual variability (for warm regions with more than one harvest a year in
    natural climate conditions). The application of the Géoviticulture Multicriteria
    Climatic Classification System is presented for 97 grape-growing regions in 29
    countries. The system is a research tool for grape-growing and wine-making zoning. It
    also enables work at different levels on the scale, on a world-wide scale or larger –
    the large grape-growing region, the small grape-growing region, as shown by the studies
    performed. It allows relating the viticultural climate to the elements of grape quality
    and the typeness of the wines considering the climatic zone.},
  number = {1–2},
  urldate = {2014-02-19},
  journal = {Agricultural and Forest Meteorology},
  author = {Tonietto, Jorge and Carbonneau, Alain},
  month = {jul},
  year = {2004},
  keywords = {Climate classification, Climate models, Vineyard, Water balance, Zoning},
  pages = {81--97}
}


@article{jackson_prediction_1988,
  title = {Prediction of a {District}'s {Grape}-{Ripening} {Capacity} {Using} a
    {Latitude}-{Temperature} {Index} ({LTI})},
  volume = {39},
  url = {https://www.ajevonline.org/content/39/1/19.abstract},
  abstract = {A district's grape-ripening capacity has previously been related to the
    area's growing degree days (DD) or the mean temperature of the warmest month (MTWM). It
    has been observed that grape cultivars ripened in parts of New Zealand where they did
    not fulfill the DD or MTWM criteria used for Europe or North America; thus, an attempt
    was made to find a more universal index. Cultivars were divided into four distinct
    groups, based on their ripening requirements, and 14 indices were tested for their
    ability to relate the groups to the districts in which they are known to ripen.
    Seventy-eight locations in Europe, North America, Australia, and New Zealand were used.
    Three groups of locations were adequately separated using DD or MTWM and a different
    three by latitude. All groups were separated, by an index combining latitude and MTWM.
    This is termed the latitude-temperature index (LTI) and has more general usefulness for
    all areas than any other index tested. LTI = MTWM (60 - latitude).},
  number = {1},
  urldate = {2022-11-16},
  journal = {American Journal of Enology and Viticulture},
  author = {Jackson, D. I. and Cherry, N. J.},
  month = {jan},
  year = {1988},
  keywords = {climate, degree days, Grapes, Grapevines, heat units, latitude-temperature
    index, LTI, Vitis vinifera},
  pages = {19--28}
}


@article{hall_spatial_2010,
  title = {Spatial analysis of climate in winegrape-growing regions in {Australia}},
  volume = {16},
  copyright = {© 2010 Australian Society of Viticulture and Oenology Inc.},
  issn = {1755-0238},
  url = {https://onlinelibrary.wiley.com/doi/10.1111/j.1755-0238.2010.00100.x/abstract},
  doi = {10.1111/j.1755-0238.2010.00100.x},
  abstract = {Background and Aims: Temperature-based indices are commonly used to indicate
    long-term suitability of climate for commercially viable winegrape production of
    different grapevine cultivars, but their calculation has been inconsistent and often
    inconsiderate of within-region spatial variability. This paper (i) investigates and
    quantifies differences between four such indices; and (ii) quantifies the within-region
    spatial variability for each Australian wine region. Methods and Results: Four commonly
    used indices describing winegrape growing suitability were calculated for each
    Australian geographic indication (GI) using temperature data from 1971 to 2000.
    Within-region spatial variability was determined for each index using a geographic
    information system. The sets of indices were compared with each other using first- and
    second-order polynomial regression. Heat-sum temperature indices were strongly related
    to the simple measure of mean growing season temperature, but variation resulted in
    some differences between indices. Conclusion: Temperature regime differences between
    the same region pairs varied depending upon which index was employed. Spatial
    variability of the climate indices within some regions led to significant overlap with
    other regions; knowledge of the climate distribution provides a better understanding of
    the range of cultivar suitability within each region. Significance of the Study:
    Within-region spatial variability and the use of different indices over inconsistent
    time periods to describe temperature regimes have, before now, made comparisons of
    climates between viticulture regions difficult. Consistent calculations of indices, and
    quantification of spatial variability, enabled comparisons of Australian GIs to be made
    both within Australia and with American Viticultural Areas in the western United
    States.},
  language = {en},
  number = {3},
  urldate = {2016-07-08},
  journal = {Australian Journal of Grape and Wine Research},
  author = {Hall, A. and Jones, Gregory V.},
  month = {oct},
  year = {2010},
  keywords = {Australian geographic indication, climate, degree-day, viticulture, wine},
  pages = {389--404}
}


@article{qian_observed_2010,
  title = {Observed {Long}-{Term} {Trends} for {Agroclimatic} {Conditions} in {Canada}},
  volume = {49},
  issn = {1558-8424, 1558-8432},
  url = {https://journals.ametsoc.org/view/journals/apme/49/4/2009jamc2275.1.xml},
  doi = {10.1175/2009JAMC2275.1},
  abstract = {{\textless}section class="abstract"{\textgreater}{\textless}h2
    class="abstractTitle text-title my-1"
    id="d46601001e91"{\textgreater}Abstract{\textless}/h2{\textgreater}{\textless}p{\textgreater}A
    set of agroclimatic indices representing Canadian climatic conditions for field crop
    production are analyzed for long-term trends during 1895–2007. The indices are
    categorized for three crop types: cool season, warm season, and overwintering. Results
    indicate a significant lengthening of the growing season due to a significantly earlier
    start and a significantly later end of the growing season. Significant positive trends
    are also observed for effective growing degree-days and crop heat units at most
    locations across the country. The occurrence of extremely low temperatures has become
    less frequent during the nongrowing season, implying a more favorable climate for
    overwinter survival. In addition, the total numbers of cool days, frost days, and
    killing-frost days within a growing season have a decreasing trend. This means that
    crops may also be less vulnerable to cold stress and injury during the growing season.
    Extreme daily precipitation amounts and 10-day precipitation totals during the growing
    season have been increasing. Significant trends associated with increased availability
    of water during the growing season are identified by the standardized precipitation
    index and seasonal water deficits. The benefit of the increased precipitation may have
    been offset by an upward trend in evaporative demand; however, this would depend on the
    amount of growth and productivity resulting from increased actual
    evapotranspiration.{\textless}/p{\textgreater}{\textless}/section{\textgreater}},
  language = {EN},
  number = {4},
  urldate = {2021-08-02},
  journal = {Journal of Applied Meteorology and Climatology},
  author = {Qian, Budong and Zhang, Xuebin and Chen, Kai and Feng, Yang and O’Brien, Ted},
  month = {apr},
  year = {2010},
  note = {Publisher: American Meteorological Society Section: Journal of Applied
    Meteorology and Climatology},
  pages = {604--618}
}


@article{bootsma_impacts_2005,
  title = {Impacts of potential climate change on selected agroclimatic indices in
    {Atlantic} {Canada}},
  volume = {85},
  issn = {0008-4271, 1918-1841},
  url = {https://cdnsciencepub.com/doi/10.4141/S04-019},
  doi = {10.4141/S04-019},
  abstract = {Bootsma, A., Gameda, S. and McKenney, D. W. 2005. Impacts of potential
    climate change on selected agroclimatic indices in Atlantic Canada. Can. J. Soil Sci.
    85: 329–343. Agroclimatic indices (heat units and water deficits) were determined for
    the Atlantic region of Canada for a baseline climate (1961 to 1990 period) and for two
    future time periods (2010 to 2039 and 2040 to 2069). Climate scenarios for the future
    periods were primarily based on outputs from the Canadian General Circulation Model
    (GCM) that included the effects of aerosols (CGCMI-A), but variability introduced by
    multiple GCM experiments was also examined. Climatic data for all three periods were
    interpolated to a grid of about 10 to 15 km. Agroclimatic indices were computed and
    mapped based on the gridded data. Based on CGCMI-A scenarios interpolated to the fine
    grid, average crop heat units (CHU) would increase by 300 to 500 CHU for the 2010 to
    2039 period and by 500 to 700 CHU for the 2040 to 2069 period in the main agricultural
    areas of the Atlantic region. However, increases in CHU for the 2040 to 2069 period
    typically varied from 450 to 1650 units in these regions when variability among GCM
    experiments was considered, resulting in a projected range of 2650 to 4000 available
    CHU. Effective growing degree-days above 5°C (EGDD) typically increased by about 400
    units for the 2040 to 2069 period in the main agricultural areas, resulting in
    available EGDD from 1800 to over 2000 units. Uncertainty introduced by multiple GCMs
    increased the range from 1700 to 2700 EGDD. A decrease in heat units (cooling) is
    anticipated along part of the coast of Labrador. Anticipated changes in water deficits
    (DEFICIT), defined as the amount by which potential evapotranspiration exceeded
    precipitation over the growing season, typically ranged from +50 to –50 mm for both
    periods, but this range widened from +50 to –100 mm when variability among GCM
    experiments was considered. The greatest increases in deficits were expected in the
    central region of New Brunswick for the 2040 to 2069 period. Our interpolation
    procedures estimated mean winter and summer temperature changes that were 1.4°C on
    average lower than a statistical downscaling procedure (SDSM) for four locations.
    Increases in precipitation during summer and autumn averaged 20\% less than SDSM.
    During periods when SDSM estimated relatively small changes in temperature or
    precipitation, our interpolation procedure tended to produce changes that were larger
    than SDSM. Additional investigations would be beneficial that explore the impact of a
    range of scenarios from other GCM models, other downscaling methods and the potential
    effects of change in climate variability on these agroclimatic indices. Potential
    impacts of these changes on crop yields and production in the region also need to be
    explored.},
  language = {en},
  number = {2},
  urldate = {2022-11-16},
  journal = {Canadian Journal of Soil Science},
  author = {Bootsma, A. and Gameda {and} D.W. McKenney, S.},
  month = {may},
  year = {2005},
  pages = {329--343}
}


@article{kenny_assessment_1992,
  title = {An assessment of a latitude-temperature index for predicting climate suitability
    for grapes in {Europe}},
  volume = {67},
  issn = {0022-1589},
  url = {https://doi.org/10.1080/00221589.1992.11516243},
  doi = {10.1080/00221589.1992.11516243},
  abstract = {The climatic suitability of wine grape classes in Europe was mapped using a
    latitude- temperature index. It was found necessary to superimpose a constraint based
    on a minimum temperature of the coldest month of —3°C to exclude those areas where
    winters are too severe for vine survival. The index, combined with this constraint,
    proved a useful indicator of current climatic potential of wine grapes. A sensitivity
    analysis, using arbitrary adjustments to temperature, suggested that even a 1°C warming
    could lead to a significant expansion in potential of viticulture. More critical
    examination, using GCM projections of global warming, and more site or region specific
    studies are recommended.},
  number = {2},
  urldate = {2021-06-16},
  journal = {Journal of Horticultural Science},
  author = {Kenny, G. J. and Shao, J.},
  month = {jan},
  year = {1992},
  note = {Publisher: Taylor \& Francis \_eprint:
    https://doi.org/10.1080/00221589.1992.11516243},
  pages = {239--246}
}


@unpublished{gregory_cf_2003,
  address = {Centre for Global Atmospheric Modelling, Department of Meteorology, University
    of Reading, UK, and Met Office Hadley Centre, Exeter, UK},
  type = {Proposal},
  title = {The {CF} {Metadata} {Standard}},
  url = {http://cfconventions.org/Data/cf-documents/overview/article.pdf},
  language = {en},
  urldate = {2019-07-03},
  author = {Gregory, Jonathan},
  month = {nov},
  year = {2003}
}


@techreport{eaton_netcdf_nodate,
  title = {{NetCDF} {Climate} and {Forecast} ({CF}) {Metadata} {Conventions}},
  url = {http://cfconventions.org/Data/cf-conventions/cf-conventions-1.7/cf-conventions.pdf},
  language = {en},
  urldate = {2019-07-03},
  author = {Eaton, Brian and Gregory, Jonathan and Drach, Bob and Taylor, Karl and Hankin,
    Steve and Blower, Jon and Caron, John and Signell, Rich and Bentley, Phil and Rappa,
    Greg and Höck, Heinke and Pamment, Alison and Juckes, Martin and Raspaud, Martin},
  pages = {156}
}


@misc{environment_and_climate_change_canada_about_nodate,
  title = {About — {Climate} {Data} {Canada}},
  url = {https://climatedata.ca/about/},
  urldate = {2019-07-02},
  author = {{Environment and Climate Change Canada}}
}


@article{casati_regional_2013,
  title = {Regional {Climate} {Projections} of {Extreme} {Heat} {Events} in {Nine} {Pilot}
    {Canadian} {Communities} for {Public} {Health} {Planning}},
  volume = {52},
  issn = {1558-8424},
  url = {https://journals.ametsoc.org/doi/full/10.1175/JAMC-D-12-0341.1},
  doi = {10.1175/JAMC-D-12-0341.1},
  abstract = {Public health planning needs the support of evidence-based information on
    current and future climate, which could be used by health professionals and decision
    makers to better understand and respond to the health impacts of extreme heat. Climate
    models provide information regarding the expected increase in temperatures and extreme
    heat events with climate change and can help predict the severity of future health
    impacts, which can be used in the public health sector for the development of
    adaptation strategies to reduce heat-related morbidity and mortality. This study
    analyzes the evolution of extreme temperature indices specifically defined to
    characterize heat events associated with health risks, in the context of a changing
    climate. The analysis is performed by using temperature projections from the Canadian
    Regional Climate Model. A quantile-based statistical correction is applied to the
    projected temperatures, in order to reduce model biases and account for the
    representativeness error. Moreover, generalized Pareto distributions are used to extend
    the temperature distribution upper tails and extrapolate the statistical correction to
    extremes that are not observed in the present but that might occur in the future. The
    largest increase in extreme daytime temperatures occurs in southern Manitoba, Canada,
    where the already overly dry climate and lack of soil moisture can lead to an
    uncontrolled enhancement of hot extremes. The occurrence of warm nights and heat waves,
    on the other hand, is already large and will increase substantially in the communities
    of the Great Lakes region, characterized by a humid climate. Impact and adaptation
    studies need to account for the temperature variability due to local effects, since it
    can be considerably larger than the model natural variability.},
  language = {en},
  number = {12},
  urldate = {2019-07-02},
  journal = {Journal of Applied Meteorology and Climatology},
  author = {Casati, Barbara and Yagouti, Abderrahmane and Chaumont, Diane},
  month = {jul},
  year = {2013},
  pages = {2669--2698}
}


@article{beniston_trends_2009,
  title = {Trends in joint quantiles of temperature and precipitation in {Europe} since
    1901 and projected for 2100},
  volume = {36},
  copyright = {Copyright 2009 by the American Geophysical Union.},
  issn = {1944-8007},
  url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2008GL037119},
  doi = {10.1029/2008GL037119},
  abstract = {This study assesses the changes in the exceedances of joint extremes of
    temperature and precipitation quantiles for a number of sites in Europe. The
    combination of cool/dry, cool/wet, warm/dry and warm/wet modes reveals a systematic
    change at all locations investigated in the course of the 20th century, with
    significant declines in the frequency of occurrence of the “cold” modes and a sharp
    rise in that of the “warm” modes. The changing behavior of these four modes is also
    accompanied by changes in the particular conditions of temperature and precipitation
    associated with each mode; for example, the average amount of precipitation during
    cool/wet events decreases while that during warm/wet events increases, even though mean
    precipitation at most locations shows no significant trend. In a “greenhouse climate”,
    the “cool” modes are almost totally absent by 2100 whereas the warm/dry and warm/wet
    modes pursue the progression already observed in the 20th century.},
  language = {en},
  number = {7},
  urldate = {2019-07-02},
  journal = {Geophysical Research Letters},
  author = {Beniston, Martin},
  year = {2009},
  keywords = {climate extremes, quantiles}
}


@misc{dask_development_team_dask:_2016,
  title = {Dask: {Library} for dynamic task scheduling},
  url = {https://dask.org},
  author = {{Dask Development Team}},
  year = {2016}
}


@article{hoyer_xarray:_2017,
  title = {xarray: {N}-{D} labeled {Arrays} and {Datasets} in {Python}},
  volume = {5},
  issn = {2049-9647},
  shorttitle = {xarray},
  url = {https://openresearchsoftware.metajnl.com/articles/10.5334/jors.148/},
  doi = {10.5334/jors.148},
  language = {en},
  urldate = {2022-11-16},
  journal = {Journal of Open Research Software},
  author = {Hoyer, Stephan and Hamman, Joseph J.},
  month = {apr},
  year = {2017},
  pages = {10}
}


@techreport{project_team_eca&d_algorithm_2013,
  address = {De Bilt, Netherlands},
  type = {Project {Description}},
  title = {Algorithm {Theoretical} {Basis} {Document} ({ATBD})},
  language = {en},
  number = {EPJ029135},
  institution = {Royal Netherlands Meteorological Institute KNMI},
  author = {{Project team ECA\&D} and {KNMI}},
  month = {sep},
  year = {2013},
  pages = {46}
}


@article{rizzo_energy_2016,
  title = {Energy distance},
  volume = {8},
  issn = {1939-0068},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/wics.1375},
  doi = {10.1002/wics.1375},
  abstract = {Energy distance is a metric that measures the distance between the
    distributions of random vectors. Energy distance is zero if and only if the
    distributions are identical, thus it characterizes equality of distributions and
    provides a theoretical foundation for statistical inference and analysis. Energy
    statistics are functions of distances between observations in metric spaces. As a
    statistic, energy distance can be applied to measure the difference between a sample
    and a hypothesized distribution or the difference between two or more samples in
    arbitrary, not necessarily equal dimensions. The name energy is inspired by the close
    analogy with Newton's gravitational potential energy. Applications include testing
    independence by distance covariance, goodness-of-fit, nonparametric tests for equality
    of distributions and extension of analysis of variance, generalizations of clustering
    algorithms, change point analysis, feature selection, and more. WIREs Comput Stat 2016,
    8:27–38. doi: 10.1002/wics.1375 This article is categorized under: Statistical and
    Graphical Methods of Data Analysis {\textgreater} Multivariate Analysis Statistical and
    Graphical Methods of Data Analysis {\textgreater} Nonparametric Methods},
  language = {en},
  number = {1},
  urldate = {2022-07-15},
  journal = {WIREs Computational Statistics},
  author = {Rizzo, Maria L. and Székely, Gábor J.},
  year = {2016},
  note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/wics.1375},
  keywords = {DISCO, distance correlation, goodness-of-fit, independence, Multivariate},
  pages = {27--38}
}


@article{szekely_testing_2004,
  title = {Testing for equal distributions in high dimension},
  volume = {5},
  abstract = {We propose a new nonparametric test for equality of two or more multivariate
    distributions based on Euclidean distance between sample elements. Several consistent
    tests for comparing multivariate distribu-tions can be developed from the underlying
    theoretical results. The test procedure for the multisample problem is developed and
    applied for testing the composite hypothesis of equal distributions, when
    dis-tributions are unspecified. The proposed test is universally consistent against all
    fixed alternatives (not necessarily continuous) with finite second moments. The test is
    implemented by conditioning on the pooled sample to obtain an approximate permutation
    test, which is distribution free. Our Monte Carlo power study suggests that the new
    test may be much more sensitive than tests based on nearest neighbors against several
    classes of alternatives, and performs particularly well in high dimension.
    Computational complexity of our test procedure is independent of dimension and number
    of populations sampled. The test is applied in a high dimensional problem, testing
    microarray data from cancer samples.},
  journal = {InterStat},
  author = {Szekely, Gabor and Rizzo, Maria},
  month = {nov},
  year = {2004}
}


@book{audet_atlas_2012,
  address = {Québec},
  title = {Atlas agroclimatique du {Québec}. Évaluation des opportunités et des risques
    agroclimatiques dans un climat en évolution.},
  isbn = {978-2-89146-817-6},
  url = {https://espace.inrs.ca/id/eprint/2406/},
  language = {fr},
  urldate = {2022-07-29},
  publisher = {INRS, Centre Eau, Terre et Environnement},
  author = {Audet, René and Côté, Hélène and Bachand, Denise and Mailhot, Alain},
  month = {jun},
  year = {2012},
  note = {Issue: R1518 Number: R1518}
}


@misc{xu_anuclim_2010,
  title = {{ANUCLIM} {Version} 6.1 {User} {Guide}},
  url = {https://fennerschool.anu.edu.au/files/anuclim61.pdf},
  language = {en},
  urldate = {2022-07-29},
  publisher = {The Australian National University},
  author = {Xu, Tingbao and Hutchinson, Michael},
  year = {2010}
}


@article{mekis_observed_2015,
  title = {Observed {Trends} in {Severe} {Weather} {Conditions} {Based} on {Humidex},
    {Wind} {Chill}, and {Heavy} {Rainfall} {Events} in {Canada} for 1953–2012},
  volume = {53},
  issn = {0705-5900, 1480-9214},
  url = {https://www.tandfonline.com/doi/full/10.1080/07055900.2015.1086970},
  doi = {10.1080/07055900.2015.1086970},
  abstract = {Observed trends in severe weather conditions based on public alert statements
    issued by Environment Canada are examined for Canada. Changes in extreme heat and
    extreme cold events represented by various humidex and wind chill indices are analyzed
    for 1953–2012 at 126 climatological stations. Changes in heavy rainfall events based on
    rainfall amounts provided by tipping bucket rainfall gauges are analyzed for 1960–2012
    at 285 stations. The results show that extreme heat events, defined as days with at
    least one hourly humidex value above 30, have increased significantly at more than 36\%
    of the stations, most of which are located south of 55°N; days with nighttime hourly
    humidex values remaining above 20 have increased significantly at more than 52\% of the
    stations, most of which are located south of 50°N. Extreme cold events represented by
    days with at least one hourly wind chill value below −30 have decreased significantly
    at more than 76\% of the stations across the country. No consistent changes were found
    in heavy rainfall events. Because city residents are very vulnerable to severe weather
    events, detailed results on changes in extreme heat, extreme cold, and heavy rainfall
    events are also provided for ten urban centres.},
  language = {en},
  number = {4},
  urldate = {2022-11-16},
  journal = {Atmosphere-Ocean},
  author = {Mekis, Éva and Vincent, Lucie A. and Shephard, Mark W. and Zhang, Xuebin},
  month = {aug},
  year = {2015},
  pages = {383--397}
}


@article{osczevski_new_2005,
  title = {The {New} {Wind} {Chill} {Equivalent} {Temperature} {Chart}},
  volume = {86},
  issn = {0003-0007, 1520-0477},
  url = {https://journals.ametsoc.org/view/journals/bams/86/10/bams-86-10-1453.xml},
  doi = {10.1175/BAMS-86-10-1453},
  abstract = {The formula used in the U.S. and Canada to express the combined effect of
    wind and low temperature on how cold it feels was changed in November 2001. Many had
    felt that the old formula for equivalent temperature, derived in the 1960s from Siple
    and Passel's flawed but quite useful Wind Chill Index, unnecessarily exaggerated the
    severity of the weather. The new formula is based on a mathematical model of heat flow
    from the upwind side of a head-sized cylinder moving at walking speed into the wind.
    The paper details the assumptions that were made in generating the new wind chill
    charts. It also points out weaknesses in the concept of wind chill equivalent
    temperature, including its steady-state character and a seemingly paradoxical effect of
    the internal thermal resistance of the cylinder on comfort and equivalent temperature.
    Some improvements and alternatives are suggested.},
  language = {en},
  number = {10},
  urldate = {2022-07-29},
  journal = {Bulletin of the American Meteorological Society},
  author = {Osczevski, Randall and Bluestein, Maurice},
  month = {oct},
  year = {2005},
  note = {Publisher: American Meteorological Society Section: Bulletin of the American
    Meteorological Society},
  pages = {1453--1458}
}


@misc{us_department_of_commerce_wind_nodate,
  title = {Wind {Chill} {Questions}},
  copyright = {https://www.weather.gov/disclaimer},
  url = {https://www.weather.gov/safety/cold-faqs},
  abstract = {Wind Chill Questions},
  language = {EN-US},
  urldate = {2022-11-16},
  author = {US Department of Commerce, NOAA},
  note = {Publisher: NOAA's National Weather Service}
}


@article{clausius_ueber_1850,
  title = {Ueber die bewegende {Kraft} der {Wärme} und die {Gesetze}, welche sich daraus
    für die {Wärmelehre} selbst ableiten lassen},
  volume = {155},
  issn = {1521-3889},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/andp.18501550403},
  doi = {10.1002/andp.18501550403},
  language = {en},
  number = {4},
  urldate = {2022-07-29},
  journal = {Annalen der Physik},
  author = {Clausius, R.},
  year = {1850},
  note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/andp.18501550403},
  pages = {500--524}
}


@article{baier_estimation_1965,
  title = {Estimation of latent evaporation from simple weather observations},
  volume = {45},
  issn = {0008-4220},
  url = {https://cdnsciencepub.com/doi/abs/10.4141/cjps65-051},
  doi = {10.4141/cjps65-051},
  number = {3},
  urldate = {2022-07-29},
  journal = {Canadian Journal of Plant Science},
  author = {Baier, W. and Robertson, Geo. W.},
  month = {may},
  year = {1965},
  note = {Publisher: NRC Research Press},
  pages = {276--284}
}


@article{george_h_hargreaves_reference_1985,
  title = {Reference {Crop} {Evapotranspiration} from {Temperature}},
  volume = {1},
  issn = {0883-8542},
  doi = {10.13031/2013.26773},
  abstract = {MEASURED lysimeter evapotranspiration of Alta fescue grass (a cool season
    grass) is taken as an index of reference crop evapotranspiration (ETo). An equation is
    presented that estimates ETo from measured values of daily or mean values of maximum
    and minimum temperature. This equation is compared with various other methods for
    estimating ETo. The equation was developed using eight years of daily lysimeter data
    from Davis, California and used to estimate values of ETo for other locations.
    Comparisons with other methods with measured cool season grass evapotranspiration at
    Aspendale, Australia; Lompoc, California; and Seabrook, New Jersey; with lysimeter data
    from Damin, Haiti; and with the modified Penman for various locations in Bangladesh
    indicated that the method usually does not require local calibration and that the
    estimated values are probably as reliable and useable as those from the other
    estimating methods used for comparison. Considering the scarcity of complete and
    reliable climatic data for estimating crop water requirements in developing countries,
    this proposed method can do much to improve irrigation planning design and scheduling
    in the developing countries.},
  language = {English},
  number = {2},
  journal = {Applied engineering in agriculture},
  author = {{George H. Hargreaves} and {Zohrab A. Samani}},
  year = {1985},
  note = {PubAg AGID: 5662005},
  keywords = {Australia, Bangladesh, California, cool season grasses, developing countries,
    equations, evapotranspiration, Festuca, Haiti, irrigation, lysimeters, New Jersey,
    planning, temperature},
  pages = {96--99}
}


@article{tanguy_historical_2018,
  title = {Historical gridded reconstruction of potential evapotranspiration for the {UK}},
  volume = {10},
  issn = {1866-3508},
  url = {https://essd.copernicus.org/articles/10/951/2018/},
  doi = {10.5194/essd-10-951-2018},
  abstract = {{\textless}p{\textgreater}Potential evapotranspiration (PET) is a necessary
    input data for most hydrological models and is often needed at a daily time step. An
    accurate estimation of PET requires many input climate variables which are, in most
    cases, not available prior to the 1960s for the UK, nor indeed most parts of the world.
    Therefore, when applying hydrological models to earlier periods, modellers have to rely
    on PET estimations derived from simplified methods. Given that only monthly observed
    temperature data is readily available for the late 19th and early 20th century at a
    national scale for the UK, the objective of this work was to derive the best possible
    UK-wide gridded PET dataset from the limited data available.{\textless}/p{\textgreater}
    {\textless}p{\textgreater}To that end, firstly, a combination of (i) seven
    temperature-based PET equations, (ii) four different calibration approaches and (iii)
    seven input temperature data were evaluated. For this evaluation, a gridded daily PET
    product based on the physically based Penman–Monteith equation (the CHESS PET dataset)
    was used, the rationale being that this provides a reliable “ground truth” PET dataset
    for evaluation purposes, given that no directly observed, distributed PET datasets
    exist. The performance of the models was also compared to a “naïve method”, which is
    defined as the simplest possible estimation of PET in the absence of any available
    climate data. The “naïve method” used in this study is the CHESS PET daily long-term
    average (the period from 1961 to 1990 was chosen), or CHESS-PET daily
    climatology.{\textless}/p{\textgreater} {\textless}p{\textgreater}The analysis revealed
    that the type of calibration and the input temperature dataset had only a minor effect
    on the accuracy of the PET estimations at catchment scale. From the seven equations
    tested, only the calibrated version of the McGuinness–Bordne equation was able to
    outperform the “naïve method” and was therefore used to derive the gridded,
    reconstructed dataset. The equation was calibrated using 43 catchments across Great
    Britain.{\textless}/p{\textgreater} {\textless}p{\textgreater}The dataset produced is a
    5\ km gridded PET dataset for the period 1891 to 2015, using the Met Office
    5\ km monthly gridded temperature data available for that time period as input
    data for the PET equation. The dataset includes daily and monthly PET grids and is
    complemented with a suite of mapped performance metrics to help users assess the
    quality of the data spatially.{\textless}/p{\textgreater}
    {\textless}p{\textgreater}This dataset is expected to be particularly valuable as input
    to hydrological models for any catchment in the UK.{\textless}/p{\textgreater}
    {\textless}p{\textgreater}The data can be accessed at {\textless}a
    href="https://doi.org/10.5285/17b9c4f7-1c30-4b6f-b2fe-f7780159939c"{\textgreater}https://doi.org/10.5285/17b9c4f7-1c30-4b6f-b2fe-f7780159939c{\textless}/a{\textgreater}.{\textless}/p{\textgreater}},
  language = {English},
  number = {2},
  urldate = {2022-07-29},
  journal = {Earth System Science Data},
  author = {Tanguy, Maliko and Prudhomme, Christel and Smith, Katie and Hannaford, Jamie},
  month = {jun},
  year = {2018},
  note = {Publisher: Copernicus GmbH},
  pages = {951--968}
}


@techreport{mcguinness_comparison_1972,
  title = {A {Comparison} of {Lysimeter}-{Derived} {Potential} {Evapotranspiration} {With}
    {Computed} {Values}},
  url = {https://ideas.repec.org/p/ags/uerstb/171893.html},
  abstract = {No abstract is available for this item.},
  language = {en},
  number = {171893},
  urldate = {2022-07-29},
  institution = {United States Department of Agriculture, Economic Research Service},
  author = {McGuinness, J. L. and Borone, Erich F.},
  year = {1972},
  note = {Publication Title: Technical Bulletins},
  keywords = {Crop Production/Industries, Production Economics}
}


@article{thornthwaite_approach_1948,
  title = {An {Approach} toward a {Rational} {Classification} of {Climate}},
  volume = {38},
  issn = {0016-7428},
  url = {https://www.jstor.org/stable/210739},
  doi = {10.2307/210739},
  number = {1},
  urldate = {2023-01-31},
  journal = {Geographical Review},
  author = {Thornthwaite, C. W.},
  year = {1948},
  note = {Publisher: [American Geographical Society, Wiley]},
  pages = {55--94}
}


@misc{brode_utci_2009,
  title = {{UTCI}},
  copyright = {MIT License},
  url = {http://www.utci.org/public/UTCI%20Program%20Code/UTCI_a002.f90},
  abstract = {Program for calculating UTCI Temperature (UTCI) released for public use after
    termination of COST Action 730},
  author = {Bröde, Peter},
  month = {oct},
  year = {2009}
}


@article{blazejczyk_introduction_2013,
  title = {An introduction to the {Universal} {Thermal} {Climate} {Index} ({UTCI})},
  volume = {86},
  url = {    https://repository.lboro.ac.uk/articles/journal_contribution/An_introduction_to_the_Universal_Thermal_Climate_Index_UTCI_/9347024/1},
  doi = {10.7163/GPol.2013.1},
  abstract = {The assessment of the thermal environment is one of the main issues in
    bioclimatic research, and more than 100 simple bioclimatic indices have thus far been
    developed to facilitate it. However, most of these indices have proved to be of limited
    applicability, and do not portroy the actual impacts of thermal conditions on human
    beings. Indices derived from human heatbalance models (one- or two-node) have been
    found to offer a better representation of the environmental impact in question than do
    simple ones. Indeed, the new generation of multi-node models for human heat balance do
    allow full account to be taken of heat transfer and exchange, both within the human
    body and between the body surface and the surrounding air layer. In this paper, it is
    essential background information regarding the newly-developed Universal Thermal
    Climate Index UTCI that is presented, this in fact deriving from the Fiala multi-node
    model of human heatbalance. The UTCI is defined as the air temperature (Ta) of the
    reference condition causing the same model response as actual conditions. UTCI was
    developed in 2009 by virtue of international co-operation between leading experts in
    the areas of human thermophysiology, physiological modelling, meteorology and
    climatology. The necessary research for this had been conducted within the framework of
    a special commission of the International Society of Biometeorology (ISB) and European
    COST Action 730.},
  language = {en},
  number = {1},
  urldate = {2022-07-29},
  journal = {Geographica Polonica},
  author = {Błażejczyk, Krzysztof and Jendritzky, Gerd and Bröde, Peter and Fiala, Dusan
    and Havenith, George and Epstein, Yoram and Psikuta, Agnes and Kampmann, Bernhardt},
  month = {jan},
  year = {2013},
  note = {Publisher: Loughborough University},
  pages = {5--10}
}


@article{liljegren_modeling_2008,
  title = {Modeling the wet bulb globe temperature using standard meteorological
    measurements},
  volume = {5},
  issn = {1545-9632},
  doi = {10.1080/15459620802310770},
  abstract = {The U.S. Army has a need for continuous, accurate estimates of the wet bulb
    globe temperature to protect soldiers and civilian workers from heat-related injuries,
    including those involved in the storage and destruction of aging chemical munitions at
    depots across the United States. At these depots, workers must don protective clothing
    that increases their risk of heat-related injury. Because of the difficulty in making
    continuous, accurate measurements of wet bulb globe temperature outdoors, the authors
    have developed a model of the wet bulb globe temperature that relies only on standard
    meteorological data available at each storage depot for input. The model is composed of
    separate submodels of the natural wet bulb and globe temperatures that are based on
    fundamental principles of heat and mass transfer, has no site-dependent parameters, and
    achieves an accuracy of better than 1 degree C based on comparisons with wet bulb globe
    temperature measurements at all depots.},
  language = {eng},
  number = {10},
  journal = {Journal of Occupational and Environmental Hygiene},
  author = {Liljegren, James C. and Carhart, Richard A. and Lawday, Philip and Tschopp,
    Stephen and Sharp, Robert},
  month = {oct},
  year = {2008},
  pmid = {18668404},
  keywords = {Data Collection, Environmental Monitoring, Heat Stress Disorders, Hot
    Temperature, Humans, Occupational Diseases, Occupational Exposure, Protective Clothing,
    United States, Weather},
  pages = {645--655}
}


@article{kong_explicit_2022,
  title = {Explicit {Calculations} of {Wet}-{Bulb} {Globe} {Temperature} {Compared} {With}
    {Approximations} and {Why} {It} {Matters} for {Labor} {Productivity}},
  volume = {10},
  issn = {2328-4277},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2021EF002334},
  doi = {10.1029/2021EF002334},
  abstract = {Wet-bulb globe temperature (WBGT) is a widely applied heat stress index.
    However, most applications of WBGT within the heat stress impact literature that do not
    use WBGT at all, but use one of the ad hoc approximations, typically the simplified
    WBGT (sWBGT) or the environmental stress index (ESI). Surprisingly, little is known
    about how well these approximations work for the global climate and climate change
    settings that they are being applied to. Here, we assess the bias distribution as a
    function of temperature, humidity, wind speed, and radiative conditions of both sWBGT
    and ESI relative to a well-validated, explicit physical model for WBGT developed by
    Liljegren, within an idealized context and the more realistic setting of ERA5
    reanalysis data. sWBGT greatly overestimates heat stress in hot-humid areas. ESI has
    much smaller biases in the range of standard climatological conditions. Over
    subtropical dry regions, both metrics can substantially underestimate extreme heat. We
    show systematic overestimation of labor loss by sWBGT over much of the world today. We
    recommend discontinuing the use of sWBGT. ESI may be acceptable for assessing average
    heat stress or integrated impact over a long period like a year, but less suitable for
    health applications, extreme heat stress analysis, or as an operational index for heat
    warning, heatwave forecasting, or guiding activity modification at the workplace.
    Nevertheless, Liljegren's approach should be preferred over these ad hoc approximations
    and we provide a fast Python implementation to encourage its widespread use.},
  language = {en},
  number = {3},
  urldate = {2022-07-29},
  journal = {Earth's Future},
  author = {Kong, Qinqin and Huber, Matthew},
  year = {2022},
  note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021EF002334},
  keywords = {bias assessment, environmental stress index, heat stress, labor productivity,
    simplified wet-bulb globe temperature, wet-bulb globe temperature},
  pages = {e2021EF002334}
}


@article{di_napoli_mean_2020,
  title = {Mean radiant temperature from global-scale numerical weather prediction models},
  volume = {64},
  issn = {1432-1254},
  url = {https://doi.org/10.1007/s00484-020-01900-5},
  doi = {10.1007/s00484-020-01900-5},
  abstract = {In human biometeorology, the estimation of mean radiant temperature (MRT) is
    generally considered challenging. This work presents a general framework to compute the
    MRT at the global scale for a human subject placed in an outdoor environment and
    irradiated by solar and thermal radiation both directly and diffusely. The proposed
    framework requires as input radiation fluxes computed by numerical weather prediction
    (NWP) models and generates as output gridded globe-wide maps of MRT. It also considers
    changes in the Sun’s position affecting radiation components when these are stored by
    NWP models as an accumulated-over-time quantity. The applicability of the framework was
    demonstrated using NWP reanalysis radiation data from the European Centre for
    Medium-Range Weather Forecasts. Mapped distributions of MRT were correspondingly
    computed at the global scale. Comparison against measurements from radiation monitoring
    stations showed a good agreement with NWP-based MRT (coefficient of determination
    greater than 0.88; average bias equal to 0.42 °C) suggesting its potential as a proxy
    for observations in application studies.},
  language = {en},
  number = {7},
  urldate = {2022-07-29},
  journal = {International Journal of Biometeorology},
  author = {Di Napoli, Claudia and Hogan, Robin J. and Pappenberger, Florian},
  month = {jul},
  year = {2020},
  keywords = {Human comfort, Mean radiant temperature, Numerical weather prediction,
    Radiation, Validation},
  pages = {1233--1245}
}


@misc{brimicombe_thermofeel_2021,
  title = {thermofeel: a python thermal comfort indices library},
  url = {https://doi.org/10.21957/mp6v-fd16},
  publisher = {ECMWF},
  author = {Brimicombe, C. and Di Napoli, C., C. and Quintino, T. and Pappenberger, F. and
    Cornforth, R. and Cloke, H.},
  month = {jul},
  year = {2021}
}


@article{baker_new_2004,
  title = {A {New} {Flashiness} {Index}: {Characteristics} and {Applications} to
    {Midwestern} {Rivers} and {Streams1}},
  volume = {40},
  issn = {1752-1688},
  shorttitle = {A {New} {Flashiness} {Index}},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1752-1688.2004.tb01046.x},
  doi = {10.1111/j.1752-1688.2004.tb01046.x},
  abstract = {ABSTRACT: The term flashiness reflects the frequency and rapidity of short
    term changes in streamflow, especially during runoff events. Flashiness is an important
    component of a stream's hydrologic regime. A variety of land use and land management
    changes may lead to increased or decreased flashiness, often to the detriment of
    aquatic life. This paper presents a newly developed flashiness index, which is based on
    mean daily flows. The index is calculated by dividing the pathlength of flow
    oscillations for a time interval (i.e., the sum of the absolute values of day-to-day
    changes in mean daily flow) by total discharge during that time interval. This index
    has low interannual variability, relative to most flow regime indicators, and thus
    greater power to detect trends. Index values were calculated for 515 Midwestern streams
    for the 27-year period from 1975 through 2001. Statistically significant increases were
    present in 22 percent of the streams, primarily in the eastern portion of the study
    area, while decreases were present in 9 percent, primarily in the western portion.
    Index values tend to decrease with increasing watershed area and with increasing unit
    area ground water inputs. Area compensated index values often shift at ecoregion
    boundaries. Potential index applications include evaluation of programs to restore more
    natural flow regimes.},
  language = {en},
  number = {2},
  urldate = {2022-07-29},
  journal = {JAWRA Journal of the American Water Resources Association},
  author = {Baker, David B. and Richards, R. Peter and Loftus, Timothy T. and Kramer, Jack
    W.},
  year = {2004},
  note = {\_eprint:
    https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1752-1688.2004.tb01046.x},
  keywords = {agricultural hydrology, flashiness index, Indicators of Hydrological
    Alteration, stormwater management, stream flashiness, surface water hydrology,
    watershed management},
  pages = {503--522}
}


@article{robinson_definition_2001,
  title = {On the {Definition} of a {Heat} {Wave}},
  volume = {40},
  issn = {1520-0450, 0894-8763},
  url = {    https://journals.ametsoc.org/view/journals/apme/40/4/1520-0450_2001_040_0762_otdoah_2.0.co_2.xml},
  doi = {https://doi.org/10.1175/1520-0450%282001%29040<0762:OTDOAH>2.0.CO;2},
  abstract = {Abstract Heat waves are a major cause of weather-related deaths. With the
    current concern for global warming it is reasonable to suppose that they may increase
    in frequency, severity, duration, or areal extent in the future. However, in the
    absence of an adequate definition of a heat wave, it is impossible to assess either
    changes in the past or possible consequences for the future. A set of definitions is
    proposed here, based on the criteria for heat stress forecasts developed by the
    National Weather Service (NWS). Watches or warnings are issued when thresholds of
    daytime high and nighttime low heat index (Hi) values are exceeded for at least two
    consecutive days. The heat index is a combination of ambient temperature and humidity
    that approximates the environmental aspect of the thermal regime of a human body, with
    the NWS thresholds representing a generalized estimate of the onset of physiological
    stress. These thresholds cannot be applied directly nationwide. In hot and humid
    regions, physical, social, and cultural adaptations will require that the thresholds be
    set higher to ensure that only those events perceived as stressful are identified. In
    other, cooler, areas the NWS criteria may never be reached even though unusually hot
    events may be perceived as heat waves. Thus, it is likely that a similar number of
    perceived heat events will occur in all regions, with the thresholds varying
    regionally. Hourly Hi for 178 stations in the coterminous United States was analyzed
    for the 1951–90 period to determine appropriate threshold criteria. Use of the NWS
    criteria alone indicated that much of the nation had less than three heat waves per
    decade, and this value was adopted as the baseline against which to establish suitable
    thresholds. For all areas, a percentile threshold approach was tested. Using all
    available data, daytime high and nighttime low thresholds were established separately
    for each specific percentile. Heat waves were treated as occurring when conditions
    exceeded both the daytime high and the nighttime low thresholds of the same percentile
    for two consecutive days. Several thresholds were tested. For much of the South, 1\%
    thresholds produced appropriate values. Consequently, a heat wave was defined as a
    period of at least 48 h during which neither the overnight low nor the daytime high Hi
    falls below the NWS heat stress thresholds (80° and 105°F, respectively), except at
    stations for which more than 1\% of both the annual high and low Hi observations exceed
    these thresholds, in which case the 1\% values are used as the heat wave thresholds. As
    an extension, “hot spells” were similarly defined, but for events falling between the
    1\% values and NWS thresholds, with “warm spells” occurring between the 2\% and 1\%
    values. Again, stations for which the 1\% or 2\% Hi values exceed the NWS thresholds
    were given modified definitions. The preliminary investigation of the timing and
    location of heat waves resulting from these definitions indicated that they correctly
    identified major epidemiological events. A tentative climatic comparison also suggests
    that heat waves are becoming less frequent in the southern and more frequent in the
    midwestern and eastern parts of the nation.},
  language = {EN},
  number = {4},
  urldate = {2022-07-29},
  journal = {Journal of Applied Meteorology and Climatology},
  author = {Robinson, Peter J.},
  month = {apr},
  year = {2001},
  note = {Publisher: American Meteorological Society Section: Journal of Applied
    Meteorology and Climatology},
  pages = {762--775}
}


@article{alexander_global_2006,
  title = {Global observed changes in daily climate extremes of temperature and
    precipitation},
  volume = {111},
  issn = {2156-2202},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2005JD006290},
  doi = {10.1029/2005JD006290},
  abstract = {A suite of climate change indices derived from daily temperature and
    precipitation data, with a primary focus on extreme events, were computed and analyzed.
    By setting an exact formula for each index and using specially designed software,
    analyses done in different countries have been combined seamlessly. This has enabled
    the presentation of the most up-to-date and comprehensive global picture of trends in
    extreme temperature and precipitation indices using results from a number of workshops
    held in data-sparse regions and high-quality station data supplied by numerous
    scientists world wide. Seasonal and annual indices for the period 1951–2003 were
    gridded. Trends in the gridded fields were computed and tested for statistical
    significance. Results showed widespread significant changes in temperature extremes
    associated with warming, especially for those indices derived from daily minimum
    temperature. Over 70\% of the global land area sampled showed a significant decrease in
    the annual occurrence of cold nights and a significant increase in the annual
    occurrence of warm nights. Some regions experienced a more than doubling of these
    indices. This implies a positive shift in the distribution of daily minimum temperature
    throughout the globe. Daily maximum temperature indices showed similar changes but with
    smaller magnitudes. Precipitation changes showed a widespread and significant increase,
    but the changes are much less spatially coherent compared with temperature change.
    Probability distributions of indices derived from approximately 200 temperature and 600
    precipitation stations, with near-complete data for 1901–2003 and covering a very large
    region of the Northern Hemisphere midlatitudes (and parts of Australia for
    precipitation) were analyzed for the periods 1901–1950, 1951–1978 and 1979–2003.
    Results indicate a significant warming throughout the 20th century. Differences in
    temperature indices distributions are particularly pronounced between the most recent
    two periods and for those indices related to minimum temperature. An analysis of those
    indices for which seasonal time series are available shows that these changes occur for
    all seasons although they are generally least pronounced for September to November.
    Precipitation indices show a tendency toward wetter conditions throughout the 20th
    century.},
  language = {en},
  number = {D5},
  urldate = {2022-07-29},
  journal = {Journal of Geophysical Research: Atmospheres},
  author = {Alexander, L. V. and Zhang, X. and Peterson, T. C. and Caesar, J. and Gleason,
    B. and Klein Tank, A. M. G. and Haylock, M. and Collins, D. and Trewin, B. and
    Rahimzadeh, F. and Tagipour, A. and Rupa Kumar, K. and Revadekar, J. and Griffiths, G.
    and Vincent, L. and Stephenson, D. B. and Burn, J. and Aguilar, E. and Brunet, M. and
    Taylor, M. and New, M. and Zhai, P. and Rusticucci, M. and Vazquez-Aguirre, J. L.},
  year = {2006},
  note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2005JD006290},
  keywords = {climate extremes, observations, precipitation, temperature, trends}
}


@article{woollings_variability_2010,
  title = {Variability of the {North} {Atlantic} eddy-driven jet stream},
  volume = {136},
  issn = {1477-870X},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/qj.625},
  doi = {10.1002/qj.625},
  abstract = {Much of the atmospheric variability in the North Atlantic sector is
    associated with variations in the eddy-driven component of the zonal flow. Here we
    present a simple method to specifically diagnose this component of the flow using the
    low-level wind field (925–700 hpa ). We focus on the North Atlantic winter season in
    the ERA-40 reanalysis. Diagnostics of the latitude and speed of the eddy-driven jet
    stream are compared with conventional diagnostics of the North Atlantic Oscillation
    (NAO) and the East Atlantic (EA) pattern. This shows that the NAO and the EA both
    describe combined changes in the latitude and speed of the jet stream. It is therefore
    necessary, but not always sufficient, to consider both the NAO and the EA in
    identifying changes in the jet stream. The jet stream analysis suggests that there are
    three preferred latitudinal positions of the North Atlantic eddy-driven jet stream in
    winter. This result is in very good agreement with the application of a statistical
    mixture model to the two-dimensional state space defined by the NAO and the EA. These
    results are consistent with several other studies which identify four European/Atlantic
    regimes, comprising three jet stream patterns plus European blocking events. Copyright
    © 2010 Royal Meteorological Society},
  language = {en},
  number = {649},
  urldate = {2022-07-29},
  journal = {Quarterly Journal of the Royal Meteorological Society},
  author = {Woollings, Tim and Hannachi, Abdel and Hoskins, Brian},
  year = {2010},
  note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/qj.625},
  keywords = {East Atlantic pattern, North Atlantic Oscillation, weather regimes},
  pages = {856--868}
}


@techreport{chaumont_elaboration_2017,
  address = {Montreal, Quebec},
  type = {Rapport présenté au {Ministère} de la forêt, de la faune et des parcs},
  title = {Élaboration du portrait bioclimatique futur du {Nunavik} – {Tome} {II}},
  url = {    https://mffp.gouv.qc.ca/documents/forets/inventaire/Portrait_bioclimatique_Nunavik_Tome_2.pdf},
  language = {fr},
  urldate = {2022-07-29},
  institution = {MFFP},
  author = {Chaumont, Diane and Mailhot, Alain and Diaconescu, Emilia P. and Fournier,
    Élyse and Logan, Travis},
  year = {2017},
  pages = {215}
}


@techreport{cbcl_climate_2020,
  address = {Ottawa, Ontario},
  title = {Climate {Projections} for the {National} {Capital} {Region}, {Volume} 1:
    {Results} and {Interpretation} for {Key} {Climate} {Indices}},
  language = {en},
  number = {193600.00},
  institution = {CBCL},
  author = {{CBCL}},
  year = {2020}
}


@article{matthews_planning_2017,
  title = {Planning for {Winter} {Road} {Maintenance} in the {Context} of {Climate}
    {Change}},
  volume = {9},
  issn = {1948-8327, 1948-8335},
  url = {https://journals.ametsoc.org/view/journals/wcas/9/3/wcas-d-16-0103_1.xml},
  doi = {10.1175/WCAS-D-16-0103.1},
  abstract = {Abstract Winter weather creates mobility challenges for most northern
    jurisdictions, leading to significant expenditures on winter road maintenance (WRM)
    activities. While the science and practice of snow and ice control is continually
    evolving, climate change presents particular challenges for the strategic planning of
    WRM. The purpose of this study is 1) to develop a winter severity index (WSI) to better
    understand how winter weather translates into interannual variations in WRM activities
    and 2) to apply the WSI to future climate change projections to assist a northern
    community in preparing for climate change. A new method for creating a WSI model is
    explored, using readily available data from maintenance records and meteorological
    stations. The WSI is created by optimizing values for three levels of snowfall as well
    as potential icing events and is shown to have high predictive accuracy for WRM
    (coefficient of determination R2 of 0.93). The WSI is then applied to historic and
    future climate data in a municipality located in central British Columbia, Canada.
    Findings reveal that much of the variability in WRM can be attributed to weather. The
    results of the climate change analysis show that winter precipitation in the region is
    expected to increase by 5.2\%–12.3\%, and winter average temperatures are projected to
    increase by 1.5°–2.8°C in the 2050s, compared to the 1976–2000 baseline based on 65
    GCMs. Based on the midrange (25th to 75th percentiles) of the 65 GCM projections,
    annual demand for WRM activities is estimated to decrease by 13.0\%–22.0\%.},
  language = {EN},
  number = {3},
  urldate = {2022-07-29},
  journal = {Weather, Climate, and Society},
  author = {Matthews, Lindsay and Andrey, Jean and Picketts, Ian},
  month = {jul},
  year = {2017},
  note = {Publisher: American Meteorological Society Section: Weather, Climate, and Society},
  pages = {521--532}
}


@misc{nsidc_frequently_2008,
  title = {Frequently {Asked} {Questions} on {Arctic} sea ice},
  url = {https://nsidc.org/arcticseaicenews/faq/},
  language = {en-US},
  urldate = {2022-07-29},
  journal = {Arctic Sea Ice News and Analysis},
  author = {{NSIDC}},
  month = {jun},
  year = {2008}
}


@misc{cantin_canadian_2014,
  title = {Canadian {Forest} {Fire} {Danger} {Rating} {System} ({CFFDRS})},
  copyright = {GPL v2},
  url = {https://r-forge.r-project.org/projects/cffdrs/},
  author = {Cantin, Alan and Wang, Xianli and Parisien, Marc-André and Wotton, Mike and
    Anderson, Kerry and Moore, Brett and Schiks, Tom and Flannigan, Mike},
  year = {2014}
}


@techreport{wang_updated_2015,
  address = {Northern Forestry Centre},
  type = {Information {Report}},
  title = {Updated source code for calculating fire danger indices in the {Canadian}
    {Forest} {Fire} {Weather} {Index} {System}.},
  url = {https://cfs.nrcan.gc.ca/publications?id=36461},
  language = {English},
  number = {NOR-X-424},
  urldate = {2022-11-16},
  institution = {Canadian Forest Service},
  author = {Wang, Y. and Anderson, K. R. and Suddaby, R. M.},
  year = {2015},
  note = {ISSN: 0831-8247}
}


@misc{natural_resources_canada_data_nodate,
  title = {Data {Sources} and {Methods} for {Daily} {Maps}},
  url = {https://cwfis.cfs.nrcan.gc.ca/background/dsm/fwi},
  language = {eng},
  urldate = {2022-07-29},
  journal = {Canadian Wildland Fire Information System},
  author = {{Natural Resources Canada}}
}


@article{wotton_length_1993,
  title = {Length of the fire season in a changing climate},
  volume = {69},
  issn = {0015-7546},
  url = {https://pubs.cif-ifc.org/doi/abs/10.5558/tfc69187-2},
  doi = {10.5558/tfc69187-2},
  number = {2},
  urldate = {2022-07-29},
  journal = {The Forestry Chronicle},
  author = {Wotton, B. M. and Flannigan, M. D.},
  month = {apr},
  year = {1993},
  note = {Publisher: Canadian Institute of Forestry},
  pages = {187--192}
}


@techreport{lawson_weather_2008,
  address = {Northern Forestry Centre},
  title = {Weather {Guide} for the {Canadian} {Forest} {Fire} {Danger} {Rating} {System}},
  url = {https://cfs.nrcan.gc.ca/pubwarehouse/pdfs/29152.pdf},
  abstract = {The Weather Guide for the Canadian Forest Fire Danger Rating System is
    intended primarily for operational wildland fire management personnel and forest fire
    weather practitioners responsible for gathering, processing, and forecasting fire
    weather information in support of safe and effective suppression and use of fire.
    Accurate and representative weather observations that meet prescribed standards and
    specifications are necessary for accurate and representative calculation of all
    components of the Canadian Forest Fire Danger Rating System. Weather-dependent
    components or modules are calculated or computed for effective use of the system’s two
    main subsystems, the Canadian Forest Fire Weather Index (FWI) System and the Canadian
    Forest Fire Behavior Prediction (FBP) System. This weather guide includes detailed
    specifications for locating and instrumenting fire weather stations, taking weather
    observations, and overwintering the Drought Code component of the FWI System. The
    sensitivity of the FWI System components to weather elements is represented
    quantitatively. The importance of weather that is not directly observable is discussed
    in the context of fuel moisture and fire behavior. Current developments in the
    observation and measurement of fire weather and the forecasting of fire danger are
    discussed, along with the implications for the reporting of fire weather of
    increasingly automated fire management information systems.},
  language = {en},
  number = {C2009-980001-2},
  urldate = {2022-07-29},
  institution = {Canadian Forest Service},
  author = {Lawson, B. D. and Armitage, O. B.},
  year = {2008},
  note = {ISSN 0831-8247},
  pages = {87}
}


@article{field_development_2015,
  title = {Development of a {Global} {Fire} {Weather} {Database}},
  volume = {15},
  issn = {1561-8633},
  url = {https://nhess.copernicus.org/articles/15/1407/2015/},
  doi = {10.5194/nhess-15-1407-2015},
  abstract = {{\textless}p{\textgreater}{\textless}strong
    class="journal-contentHeaderColor"{\textgreater}Abstract.{\textless}/strong{\textgreater}
    The Canadian Forest Fire Weather Index (FWI) System is the mostly widely used fire
    danger rating system in the world. We have developed a global database of daily FWI
    System calculations, beginning in 1980, called the Global Fire WEather Database (GFWED)
    gridded to a spatial resolution of 0.5° latitude by 2/3° longitude. Input weather data
    were obtained from the NASA Modern Era Retrospective-Analysis for Research and
    Applications (MERRA), and two different estimates of daily precipitation from rain
    gauges over land. FWI System Drought Code calculations from the gridded data sets were
    compared to calculations from individual weather station data for a representative set
    of 48 stations in North, Central and South America, Europe, Russia, Southeast Asia and
    Australia. Agreement between gridded calculations and the station-based calculations
    tended to be most different at low latitudes for strictly MERRA-based calculations.
    Strong biases could be seen in either direction: MERRA DC over the Mato Grosso in
    Brazil reached unrealistically high values exceeding DC = 1500 during the dry season
    but was too low over Southeast Asia during the dry season. These biases are consistent
    with those previously identified in MERRA's precipitation, and they reinforce the need
    to consider alternative sources of precipitation data. GFWED can be used for analyzing
    historical relationships between fire weather and fire activity at continental and
    global scales, in identifying large-scale atmosphere–ocean controls on fire weather,
    and calibration of FWI-based fire prediction models.{\textless}/p{\textgreater}},
  language = {English},
  number = {6},
  urldate = {2022-07-29},
  journal = {Natural Hazards and Earth System Sciences},
  author = {Field, R. D. and Spessa, A. C. and Aziz, N. A. and Camia, A. and Cantin, A. and
    Carr, R. and de Groot, W. J. and Dowdy, A. J. and Flannigan, M. D. and Manomaiphiboon,
    K. and Pappenberger, F. and Tanpipat, V. and Wang, X.},
  month = {jun},
  year = {2015},
  note = {Publisher: Copernicus GmbH},
  pages = {1407--1423}
}


@inproceedings{van_wagner_drought_1985,
  address = {Detroit, Michigan},
  title = {Drought, {Timelag}, and {Fire} {Danger} {Rating}},
  url = {https://cfs.nrcan.gc.ca/pubwarehouse/pdfs/23550.pdf},
  abstract = {This paper considers several principles of the construction and presentation
    of long-term moisture indexes in forest fire danger rating. Five different "drought"
    indexes are compared as to rate of moisture loss and gain, reservoir size, temperature
    effect, and whether presented on an absolute or comparative basis. The role of timelag
    in deciding whether the index should be computed continuously from one fire season to
    the next is tested. The purpose of the index will determine whether it should be
    presented in terms of the moisture content of some identifiable component of the fuel
    complex, or in some other form such as the content of a soil reservoir. Its role in
    fire danger rating is distinctly subsidiary, and not to be confused wi th the principal
    short-term indicators of fire ignition potential and rate of spread.},
  language = {en},
  urldate = {2022-11-16},
  booktitle = {Society of {American} {Foresters}},
  author = {Van Wagner, C. E.},
  month = {may},
  year = {1985},
  pages = {178--185}
}


@article{mcelhinny_high-resolution_2020,
  title = {A high-resolution reanalysis of global fire weather from 1979 to 2018 –
    overwintering the {Drought} {Code}},
  volume = {12},
  issn = {1866-3508},
  url = {https://essd.copernicus.org/articles/12/1823/2020/},
  doi = {10.5194/essd-12-1823-2020},
  abstract = {{\textless}p{\textgreater}{\textless}strong
    class="journal-contentHeaderColor"{\textgreater}Abstract.{\textless}/strong{\textgreater}
    We present a global high-resolution calculation of the Canadian Fire Weather Index
    (FWI) System indices using surface meteorology from the ERA5 HRES reanalysis for
    1979–2018. ERA5 HRES represents an improved dataset compared to several other
    reanalyses in terms of accuracy, as well as spatial and temporal coverage. The FWI
    calculation is performed using two different procedures for setting the start-up value
    of the Drought Code (DC) at the beginning of the fire season. The first procedure,
    which accounts for the effects of inter-seasonal drought, overwinters the DC by
    adjusting the fall DC value with a fraction of accumulated overwinter precipitation.
    The second procedure sets the DC to its default start-up value (i.e. 15) at the start
    of each fire season. We validate the FWI values over Canada using station observations
    from Environment and Climate Change Canada and find generally good agreement (mean
    Spearman correlation of 0.77). We also show that significant differences in early
    season DC and FWI values can occur when the FWI System calculation is started using the
    overwintered versus default DC values, as is highlighted by an example from 2016 over
    North America. The FWI System moisture codes and fire behaviour indices are made
    available for both versions of the calculation at {\textless}a
    href="https://doi.org/10.5281/zenodo.3626193"{\textgreater}https://doi.org/10.5281/zenodo.3626193{\textless}/a{\textgreater}
    (McElhinny et al., 2020), although we recommend using codes and indices calculated with
    the overwintered DC, unless specific research requirements dictate
    otherwise.{\textless}/p{\textgreater}},
  language = {English},
  number = {3},
  urldate = {2022-07-29},
  journal = {Earth System Science Data},
  author = {McElhinny, Megan and Beckers, Justin F. and Hanes, Chelene and Flannigan, Mike
    and Jain, Piyush},
  month = {aug},
  year = {2020},
  note = {Publisher: Copernicus GmbH},
  pages = {1823--1833}
}


@article{spencer_fourier_1971,
  title = {Fourier series representation of the position of the sun},
  volume = {2},
  url = {https://cir.nii.ac.jp/crid/1571980074286566912},
  number = {5},
  urldate = {2022-07-29},
  journal = {Search},
  author = {Spencer, J. W.},
  year = {1971},
  pages = {172}
}


@incollection{kalogirou_chapter_2014,
  address = {Boston},
  title = {Chapter 2 - {Environmental} {Characteristics}},
  isbn = {978-0-12-397270-5},
  url = {https://www.sciencedirect.com/science/article/pii/B9780123972705000029},
  abstract = {Chapter 2 gives an analysis of the environmental characteristics of solar
    radiation and in particular the reckoning of time and solar angles. In the latter the
    basic solar geometry equations are given including declination, hour angle, altitude
    angle, azimuth angle as well as the incidence angle for stationary and moving surfaces,
    sun path diagrams, and shadow determination including the way to calculate shading
    effects. This is followed by a description of the basic principles of solar radiation
    heat transfer including transparent plates, radiation exchange between surfaces,
    extraterrestrial solar radiation, atmospheric attenuation, terrestrial irradiation, and
    total radiation on tilted surfaces. It concludes with a review of the solar radiation
    measuring instruments and the way to construct typical meteorological year files.},
  language = {en},
  urldate = {2022-07-29},
  booktitle = {Solar {Energy} {Engineering} ({Second} {Edition})},
  publisher = {Academic Press},
  author = {Kalogirou, Soteris A.},
  editor = {Kalogirou, Soteris A.},
  month = {jan},
  year = {2014},
  doi = {10.1016/B978-0-12-397270-5.00002-9},
  keywords = {Atmospheric attenuation, Extraterrestrial radiation, Radiation exchange
    between surfaces, Shadow determination, Solar angles, Solar radiation, Solar radiation
    measuring instruments, Terrestrial irradiation, Total radiation on tilted surfaces,
    Typical meteorological year},
  pages = {51--123}
}


@article{matthes_solar_2017,
  title = {Solar forcing for {CMIP6} (v3.2)},
  volume = {10},
  issn = {1991-959X},
  url = {https://gmd.copernicus.org/articles/10/2247/2017/},
  doi = {10.5194/gmd-10-2247-2017},
  abstract = {{\textless}p{\textgreater}{\textless}strong
    class="journal-contentHeaderColor"{\textgreater}Abstract.{\textless}/strong{\textgreater}
    This paper describes the recommended solar forcing dataset for CMIP6 and highlights
    changes with respect to CMIP5. The solar forcing is provided for radiative properties,
    namely total solar irradiance (TSI), solar spectral irradiance (SSI), and the F10.7
    index as well as particle forcing, including geomagnetic indices Ap and Kp, and
    ionization rates to account for effects of solar protons, electrons, and galactic
    cosmic rays. This is the first time that a recommendation for solar-driven particle
    forcing has been provided for a CMIP exercise. The solar forcing datasets are provided
    at daily and monthly resolution separately for the CMIP6 preindustrial control,
    historical (1850–2014), and future (2015–2300) simulations. For the preindustrial
    control simulation, both constant and time-varying solar forcing components are
    provided, with the latter including variability on 11-year and shorter timescales but
    no long-term changes. For the future, we provide a realistic scenario of what solar
    behavior could be, as well as an additional extreme Maunder-minimum-like sensitivity
    scenario. This paper describes the forcing datasets and also provides detailed
    recommendations as to their implementation in current climate
    models.{\textless}br{\textgreater}{\textless}br{\textgreater}For the historical
    simulations, the TSI and SSI time series are defined as the average of two solar
    irradiance models that are adapted to CMIP6 needs: an empirical one (NRLTSI2–NRLSSI2)
    and a semi-empirical one (SATIRE). A new and lower TSI value is recommended: the
    contemporary solar-cycle average is now 1361.0 W m$^{\textrm{−2}}$. The slight negative
    trend in TSI over the three most recent solar cycles in the CMIP6 dataset leads to only
    a small global radiative forcing of −0.04 W m$^{\textrm{−2}}$. In the 200–400 nm
    wavelength range, which is important for ozone photochemistry, the CMIP6 solar forcing
    dataset shows a larger solar-cycle variability contribution to TSI than in CMIP5 (50 \%
    compared to 35 \%).{\textless}br{\textgreater}{\textless}br{\textgreater}We compare the
    climatic effects of the CMIP6 solar forcing dataset to its CMIP5 predecessor by using
    time-slice experiments of two chemistry–climate models and a reference radiative
    transfer model. The differences in the long-term mean SSI in the CMIP6 dataset,
    compared to CMIP5, impact on climatological stratospheric conditions (lower shortwave
    heating rates of −0.35 K day$^{\textrm{−1}}$ at the stratopause), cooler stratospheric
    temperatures (−1.5 K in the upper stratosphere), lower ozone abundances in the lower
    stratosphere (−3 \%), and higher ozone abundances (+1.5 \% in the upper stratosphere
    and lower mesosphere). Between the maximum and minimum phases of the 11-year solar
    cycle, there is an increase in shortwave heating rates (+0.2 K day$^{\textrm{−1}}$ at
    the stratopause), temperatures ( ∼ 1 K at the stratopause), and ozone (+2.5 \% in the
    upper stratosphere) in the tropical upper stratosphere using the CMIP6 forcing dataset.
    This solar-cycle response is slightly larger, but not statistically significantly
    different from that for the CMIP5 forcing
    dataset.{\textless}br{\textgreater}{\textless}br{\textgreater}CMIP6 models with a
    well-resolved shortwave radiation scheme are encouraged to prescribe SSI changes and
    include solar-induced stratospheric ozone variations, in order to better represent
    solar climate variability compared to models that only prescribe TSI and/or exclude the
    solar-ozone response. We show that monthly-mean solar-induced ozone variations are
    implicitly included in the SPARC/CCMI CMIP6 Ozone Database for historical simulations,
    which is derived from transient chemistry–climate model simulations and has been
    developed for climate models that do not calculate ozone interactively. CMIP6 models
    without chemistry that perform a preindustrial control simulation with time-varying
    solar forcing will need to use a modified version of the SPARC/CCMI Ozone Database that
    includes solar variability. CMIP6 models with interactive chemistry are also encouraged
    to use the particle forcing datasets, which will allow the potential long-term effects
    of particles to be addressed for the first time. The consideration of particle forcing
    has been shown to significantly improve the representation of reactive nitrogen and
    ozone variability in the polar middle atmosphere, eventually resulting in further
    improvements in the representation of solar climate variability in global
    models.{\textless}/p{\textgreater}},
  language = {English},
  number = {6},
  urldate = {2022-07-29},
  journal = {Geoscientific Model Development},
  author = {Matthes, Katja and Funke, Bernd and Andersson, Monika E. and Barnard, Luke and
    Beer, Jürg and Charbonneau, Paul and Clilverd, Mark A. and Dudok de Wit, Thierry and
    Haberreiter, Margit and Hendry, Aaron and Jackman, Charles H. and Kretzschmar, Matthieu
    and Kruschke, Tim and Kunze, Markus and Langematz, Ulrike and Marsh, Daniel R. and
    Maycock, Amanda C. and Misios, Stergios and Rodger, Craig J. and Scaife, Adam A. and
    Seppälä, Annika and Shangguan, Ming and Sinnhuber, Miriam and Tourpali, Kleareti and
    Usoskin, Ilya and van de Kamp, Max and Verronen, Pekka T. and Versick, Stefan},
  month = {jun},
  year = {2017},
  note = {Publisher: Copernicus GmbH},
  pages = {2247--2302}
}


@book{coles_introduction_2001,
  address = {London, UK},
  series = {Springer {Series} in {Statistics}},
  title = {An {Introduction} to {Statistical} {Modeling} of {Extreme} {Values}},
  isbn = {978-1-85233-459-8},
  url = {https://link.springer.com/book/10.1007/978-1-4471-3675-0},
  abstract = {Directly oriented towards real practical application, this book develops both
    the basic theoretical framework of extreme value models and the statistical inferential
    techniques for using these models in practice. Intended for statisticians and
    non-statisticians alike, the theoretical treatment is elementary, with heuristics often
    replacing detailed mathematical proof. Most aspects of extreme modeling techniques are
    covered, including historical techniques (still widely used) and contemporary
    techniques based on point process models. A wide range of worked examples, using
    genuine datasets, illustrate the various modeling procedures and a concluding chapter
    provides a brief introduction to a number of more advanced topics, including Bayesian
    inference and spatial extremes. All the computations are carried out using S-PLUS, and
    the corresponding datasets and functions are available via the Internet for readers to
    recreate examples for themselves. An essential reference for students and researchers
    in statistics and disciplines such as engineering, finance and environmental science,
    this book will also appeal to practitioners looking for practical help in solving real
    problems. Stuart Coles is Reader in Statistics at the University of Bristol, UK, having
    previously lectured at the universities of Nottingham and Lancaster. In 1992 he was the
    first recipient of the Royal Statistical Society's research prize. He has published
    widely in the statistical literature, principally in the area of extreme value
    modeling.},
  language = {en},
  urldate = {2022-07-29},
  publisher = {Springer-Verlag},
  author = {Coles, Stuart},
  month = {aug},
  year = {2001},
  keywords = {Mathematics / Probability \& Statistics / General, Mathematics / Probability
    \& Statistics / Stochastic Processes, Medical / Biostatistics}
}


@book{cohen_parameter_2019,
  title = {Parameter {Estimation} in {Reliability} and {Life} {Span} {Models}},
  isbn = {978-0-367-40334-8},
  abstract = {Offers an applications-oriented treatment of parameter estimation from both
    complete and censored samples; contains notations, simplified formats for estimates,
    graphical techniques, and numerous tables and charts allowing users to calculate
    estimates and analyze sample data quickly and easily. Furnishing numerous practical
    examples, this resource serves as a handy reference for statisticians, biometricians,
    medical researchers, operations research and quality control practitioners, reliability
    and design engineers, and all others involved in the analysis of sample data from
    skewed distributions, as well as a text for senior undergraduate and graduate students
    in statistics, quality control, operations research, mathematics and biometry courses.},
  publisher = {CRC Press},
  author = {Cohen, A Clifford and Whitten, Betty Jones},
  month = {sep},
  year = {2019}
}


@article{deque_frequency_2007,
  series = {Extreme {Climatic} {Events}},
  title = {Frequency of precipitation and temperature extremes over {France} in an
    anthropogenic scenario: {Model} results and statistical correction according to
    observed values},
  volume = {57},
  issn = {0921-8181},
  shorttitle = {Frequency of precipitation and temperature extremes over {France} in an
    anthropogenic scenario},
  url = {https://www.sciencedirect.com/science/article/pii/S0921818106002748},
  doi = {10.1016/j.gloplacha.2006.11.030},
  abstract = {Météo-France atmospheric model ARPEGE/Climate has been used to simulate
    present climate (1961–1990) and a possible future climate (2071–2100) through two
    ensembles of three 30-year numerical experiments. In the scenario experiment, the
    greenhouse gas and aerosol concentrations are prescribed by the so-called SRES-A2
    hypotheses, whereas the sea surface temperature and sea ice extent come from an earlier
    ocean–atmosphere coupled simulation. The model covers the whole globe, with a variable
    resolution reaching 50 to 60 km over France. Model responses on daily minimum and
    maximum temperature and precipitation are analyzed over France. The distribution of
    daily values is compared with observed data from the French climatological network. The
    extreme cold temperatures and summer heavy precipitations are underestimated by the
    model. A correction technique is proposed in order to adjust the simulated values
    according to the observed ones. This process is applied to both reference and scenario
    simulation. Synthetic indices of extreme events are calculated with corrected
    simulations. The number of heavy rain ({\textgreater}10 mm) days increases by one
    quarter in winter. The maximum length of summer dry episodes increases by one half in
    summer. The number of heat wave days is multiplied by 10. The response in precipitation
    is less when only the change in the mean is considered. Such a corrected simulation is
    useful to feed impact models which are sensitive to threshold values, but the
    correction does not reduce, and may enhance in some cases, the uncertainty about the
    climate projections. Using several models and scenarios is the appropriate technique to
    deal with uncertainty.},
  language = {en},
  number = {1},
  urldate = {2022-07-29},
  journal = {Global and Planetary Change},
  author = {Déqué, Michel},
  month = {may},
  year = {2007},
  keywords = {extreme values, numerical simulation, regional climate, scenario},
  pages = {16--26}
}


@article{cannon_bias_2015,
  title = {Bias {Correction} of {GCM} {Precipitation} by {Quantile} {Mapping}: {How} {Well}
    {Do} {Methods} {Preserve} {Changes} in {Quantiles} and {Extremes}?},
  volume = {28},
  issn = {0894-8755, 1520-0442},
  shorttitle = {Bias {Correction} of {GCM} {Precipitation} by {Quantile} {Mapping}},
  url = {https://journals.ametsoc.org/view/journals/clim/28/17/jcli-d-14-00754.1.xml},
  doi = {10.1175/JCLI-D-14-00754.1},
  abstract = {Abstract Quantile mapping bias correction algorithms are commonly used to
    correct systematic distributional biases in precipitation outputs from climate models.
    Although they are effective at removing historical biases relative to observations, it
    has been found that quantile mapping can artificially corrupt future model-projected
    trends. Previous studies on the modification of precipitation trends by quantile
    mapping have focused on mean quantities, with less attention paid to extremes. This
    article investigates the extent to which quantile mapping algorithms modify global
    climate model (GCM) trends in mean precipitation and precipitation extremes indices.
    First, a bias correction algorithm, quantile delta mapping (QDM), that explicitly
    preserves relative changes in precipitation quantiles is presented. QDM is compared on
    synthetic data with detrended quantile mapping (DQM), which is designed to preserve
    trends in the mean, and with standard quantile mapping (QM). Next, methods are applied
    to phase 5 of the Coupled Model Intercomparison Project (CMIP5) daily precipitation
    projections over Canada. Performance is assessed based on precipitation extremes
    indices and results from a generalized extreme value analysis applied to annual
    precipitation maxima. QM can inflate the magnitude of relative trends in precipitation
    extremes with respect to the raw GCM, often substantially, as compared to DQM and
    especially QDM. The degree of corruption in the GCM trends by QM is particularly large
    for changes in long period return values. By the 2080s, relative changes in excess of
    +500\% with respect to historical conditions are noted at some locations for 20-yr
    return values, with maximum changes by DQM and QDM nearing +240\% and +140\%,
    respectively, whereas raw GCM changes are never projected to exceed +120\%.},
  language = {EN},
  number = {17},
  urldate = {2022-07-29},
  journal = {Journal of Climate},
  author = {Cannon, Alex J. and Sobie, Stephen R. and Murdock, Trevor Q.},
  month = {sep},
  year = {2015},
  note = {Publisher: American Meteorological Society Section: Journal of Climate},
  pages = {6938--6959}
}


@misc{roy_juliaclimateclimatetoolsjl_2021,
  title = {{JuliaClimate}/{ClimateTools}.jl: v0.23.1},
  shorttitle = {{JuliaClimate}/{ClimateTools}.jl},
  url = {https://zenodo.org/record/5399172},
  abstract = {ClimateTools v0.23.1 Diff since v0.23.0 Closed issues: possible test failure
    in upcoming Julia version 1.5 (\#148) Merged pull requests: CompatHelper: bump compat
    for "DataFrames" to "1.0" (\#191) (@github-actions[bot]) CompatHelper: bump compat for
    "GeoStats" to "0.25" (\#193) (@github-actions[bot]) CompatHelper: bump compat for
    "Reexport" to "1" (\#194) (@github-actions[bot]) CompatHelper: bump compat for Reexport
    to 1, (keep existing compat) (\#196) (@github-actions[bot]) CompatHelper: bump compat
    for Interpolations to 0.13, (keep existing compat) (\#197) (@github-actions[bot])
    CompatHelper: bump compat for NCDatasets to 0.11, (keep existing compat) (\#198)
    (@github-actions[bot]) CompatHelper: bump compat for GeoStats to 0.26, (keep existing
    compat) (\#199) (@github-actions[bot]) CompatHelper: bump compat for NetCDF to 0.11,
    (keep existing compat) (\#201) (@github-actions[bot]) CompatHelper: bump compat for
    ClimateBase to 0.13, (keep existing compat) (\#202) (@github-actions[bot])
    CompatHelper: bump compat for Distances to 0.10, (keep existing compat) (\#204)
    (@github-actions[bot]) CompatHelper: bump compat for Shapefile to 0.7, (keep existing
    compat) (\#205) (@github-actions[bot]) fix for extreme bug (\#206) (@Balinus)},
  urldate = {2022-07-29},
  publisher = {Zenodo},
  author = {Roy, Philippe and Smith, Trevor James and Kelman, Tony and Nolet-Gravel, Éloïse
    and Saba, Elliot and Thomet, Fidel and TagBot, Julia and Forget, Gael},
  month = {sep},
  year = {2021},
  doi = {10.5281/zenodo.5399172}
}


@article{schmidli_downscaling_2006,
  title = {Downscaling from {GCM} precipitation: a benchmark for dynamical and statistical
    downscaling methods},
  volume = {26},
  issn = {1097-0088},
  shorttitle = {Downscaling from {GCM} precipitation},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/joc.1287},
  doi = {10.1002/joc.1287},
  abstract = {A precipitation downscaling method is presented using precipitation from a
    general circulation model (GCM) as predictor. The method extends a previous method from
    monthly to daily temporal resolution. The simplest form of the method corrects for
    biases in wet-day frequency and intensity. A more sophisticated variant also takes
    account of flow-dependent biases in the GCM. The method is flexible and simple to
    implement. It is proposed here as a correction of GCM output for applications where
    sophisticated methods are not available, or as a benchmark for the evaluation of other
    downscaling methods. Applied to output from reanalyses (ECMWF, NCEP) in the region of
    the European Alps, the method is capable of reducing large biases in the precipitation
    frequency distribution, even for high quantiles. The two variants exhibit similar
    performances, but the ideal choice of method can depend on the GCM/reanalysis and it is
    recommended to test the methods in each case. Limitations of the method are found in
    small areas with unresolved topographic detail that influence higher-order statistics
    (e.g. high quantiles). When used as benchmark for three regional climate models (RCMs),
    the corrected reanalysis and the RCMs perform similarly in many regions, but the added
    value of the latter is evident for high quantiles in some small regions. Copyright ©
    2006 Royal Meteorological Society.},
  language = {en},
  number = {5},
  urldate = {2022-07-29},
  journal = {International Journal of Climatology},
  author = {Schmidli, Jürg and Frei, Christoph and Vidale, Pier Luigi},
  year = {2006},
  note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/joc.1287},
  keywords = {European alps, precipitation statistics, reanalysis, regional climate model,
    statistical downscaling},
  pages = {679--689}
}


@article{hnilica_multisite_2017,
  title = {Multisite bias correction of precipitation data from regional climate models},
  volume = {37},
  issn = {1097-0088},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/joc.4890},
  doi = {10.1002/joc.4890},
  abstract = {The characteristics of precipitation in regional climate model simulations
    deviate considerably from those of the observed data; therefore, bias correction is a
    standard part of most climate change impact assessment studies. The standard approach
    is that the corrections are calibrated and applied separately for individual spatial
    points and meteorological variables. For this reason, the correlation and covariance
    structures of the observed and corrected data differ, although the individual observed
    and corrected data sets correspond well in their statistical indicators. This
    inconsistency may affect impact studies using corrected simulations. This study
    presents a new approach to the bias correction utilizing principal components in
    combination with quantile mapping, which allows for the correction of multivariate data
    sets. The proposed procedure significantly reduces the bias in covariance and
    correlation structures, as well as that in the distribution of individual variables.
    This is in contrast to standard quantile mapping, which only corrects the individual
    distributions, and leaves the dependence structure biased.},
  language = {en},
  number = {6},
  urldate = {2022-07-29},
  journal = {International Journal of Climatology},
  author = {Hnilica, Jan and Hanel, Martin and Puš, Vladimír},
  year = {2017},
  note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/joc.4890},
  keywords = {bias correction, correlation, covariance, multisite correction, multivariate
    data, precipitation, principal components, regional climate model},
  pages = {2934--2946}
}


@article{alavoine_distinct_2022,
  title = {The distinct problems of physical inconsistency and of multivariate bias
    involved in the statistical adjustment of climate simulations},
  issn = {1097-0088},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/joc.7878},
  doi = {10.1002/joc.7878},
  abstract = {Bias adjustment of numerical climate model simulations involves several
    arguments wherein the notion of physical inconsistency is referred to, either for
    rejecting the legitimacy of bias adjustment in general or for justifying the necessity
    of sophisticated multivariate techniques. However, this notion is often mishandled, in
    part because the literature generally proceeds without defining it. In this context,
    the central objective of this study is to clarify and illustrate the distinction
    between physical inconsistency and multivariate bias, by investigating the effect of
    bias adjustment on two different kinds of intervariable relationships, namely a
    physical constraint expected to hold at every step of a time series and statistical
    properties that emerge with potential bias over a climatic timescale. To this end, 18
    alternative bias adjustment techniques are applied on 10 climate simulations at 12
    sites over North America. Adjusted variables are temperature, pressure, relative
    humidity and specific humidity, linked by a thermodynamic constraint. The analysis
    suggests on the one hand that a clear instance of potential physical inconsistency can
    be avoided with either a univariate or a multivariate technique, if and only if the
    bias adjustment strategy explicitly considers the physical constraint to be preserved.
    On the other hand, it also suggests that sophisticated multivariate techniques alone
    are not complete adjustment strategies in presence of a physical constraint, as they
    cannot replace its explicit consideration. By involving common bias adjustment
    procedures with likely effects on diverse basic statistical properties, this study may
    also help guide climate information users in the determination of adequate bias
    adjustment strategies for their research purposes.},
  language = {en},
  urldate = {2022-11-16},
  journal = {International Journal of Climatology},
  author = {Alavoine, Mégane and Grenier, Patrick},
  month = {sep},
  year = {2022},
  note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/joc.7878},
  keywords = {bias adjustment techniques, climate simulations, multivariate biases,
    physical relationships},
  pages = {1--23}
}


@article{cannon_multivariate_2018,
  title = {Multivariate quantile mapping bias correction: an {N}-dimensional probability
    density function transform for climate model simulations of multiple variables},
  volume = {50},
  issn = {1432-0894},
  shorttitle = {Multivariate quantile mapping bias correction},
  url = {https://doi.org/10.1007/s00382-017-3580-6},
  doi = {10.1007/s00382-017-3580-6},
  abstract = {Most bias correction algorithms used in climatology, for example quantile
    mapping, are applied to univariate time series. They neglect the dependence between
    different variables. Those that are multivariate often correct only limited measures of
    joint dependence, such as Pearson or Spearman rank correlation. Here, an image
    processing technique designed to transfer colour information from one image to
    another—the N-dimensional probability density function transform—is adapted for use as
    a multivariate bias correction algorithm (MBCn) for climate model
    projections/predictions of multiple climate variables. MBCn is a multivariate
    generalization of quantile mapping that transfers all aspects of an observed continuous
    multivariate distribution to the corresponding multivariate distribution of variables
    from a climate model. When applied to climate model projections, changes in quantiles
    of each variable between the historical and projection period are also preserved. The
    MBCn algorithm is demonstrated on three case studies. First, the method is applied to
    an image processing example with characteristics that mimic a climate projection
    problem. Second, MBCn is used to correct a suite of 3-hourly surface meteorological
    variables from the Canadian Centre for Climate Modelling and Analysis Regional Climate
    Model (CanRCM4) across a North American domain. Components of the Canadian Forest Fire
    Weather Index (FWI) System, a complicated set of multivariate indices that
    characterizes the risk of wildfire, are then calculated and verified against observed
    values. Third, MBCn is used to correct biases in the spatial dependence structure of
    CanRCM4 precipitation fields. Results are compared against a univariate quantile
    mapping algorithm, which neglects the dependence between variables, and two
    multivariate bias correction algorithms, each of which corrects a different form of
    inter-variable correlation structure. MBCn outperforms these alternatives, often by a
    large margin, particularly for annual maxima of the FWI distribution and spatiotemporal
    autocorrelation of precipitation fields.},
  language = {en},
  number = {1},
  urldate = {2022-07-29},
  journal = {Climate Dynamics},
  author = {Cannon, Alex J.},
  month = {jan},
  year = {2018},
  keywords = {Bias correction, Climate model, Fire weather, Model output statistics,
    Multivariate, Post-processing, Precipitation, Quantile mapping},
  pages = {31--49}
}


@misc{cannon_mbc_2020,
  title = {{MBC}: {Multivariate} {Bias} {Correction} of {Climate} {Model} {Outputs}},
  copyright = {GPL-2},
  shorttitle = {{MBC}},
  url = {https://CRAN.R-project.org/package=MBC},
  abstract = {Calibrate and apply multivariate bias correction algorithms for climate model
    simulations of multiple climate variables. Three methods described by Cannon (2016)
    {\textless}doi:10.1175/JCLI-D-15-0679.1{\textgreater} and Cannon (2018)
    {\textless}doi:10.1007/s00382-017-3580-6{\textgreater} are implemented — (i) MBC
    Pearson correlation (MBCp), (ii) MBC rank correlation (MBCr), and (iii) MBC
    N-dimensional PDF transform (MBCn) — as is the Rank Resampling for Distributions and
    Dependences (R2D2) method.},
  urldate = {2022-07-29},
  author = {Cannon, Alex J.},
  month = {oct},
  year = {2020},
  keywords = {Hydrology}
}


@misc{mezzadri_how_2007,
  title = {How to generate random matrices from the classical compact groups},
  url = {https://arxiv.org/abs/math-ph/0609050},
  doi = {10.48550/arXiv.math-ph/0609050},
  abstract = {We discuss how to generate random unitary matrices from the classical compact
    groups U(N), O(N) and USp(N) with probability distributions given by the respective
    invariant measures. The algorithm is straightforward to implement using standard linear
    algebra packages. This approach extends to the Dyson circular ensembles too. This
    article is based on a lecture given by the author at the summer school on Number Theory
    and Random Matrix Theory held at the University of Rochester in June 2006. The
    exposition is addressed to a general mathematical audience.},
  urldate = {2022-11-16},
  publisher = {arXiv},
  author = {Mezzadri, Francesco},
  month = {feb},
  year = {2007},
  note = {arXiv:math-ph/0609050 version: 2},
  keywords = {1502,15A52, 65F25, Mathematical Physics, Mathematics - Numerical Analysis}
}


@inproceedings{pitie_n-dimensional_2005,
  title = {N-dimensional probability density function transfer and its application to color
    transfer},
  volume = {2},
  doi = {10.1109/ICCV.2005.166},
  abstract = {This article proposes an original method to estimate a continuous
    transformation that maps one N-dimensional distribution to another. The method is
    iterative, non-linear, and is shown to converge. Only 1D marginal distribution is used
    in the estimation process, hence involving low computation costs. As an illustration
    this mapping is applied to color transfer between two images of different contents. The
    paper also serves as a central focal point for collecting together the research
    activity in this area and relating it to the important problem of automated color
    grading},
  language = {en},
  booktitle = {Tenth {IEEE} {International} {Conference} on {Computer} {Vision} ({ICCV}'05)
    {Volume} 1},
  author = {Pitie, F. and Kokaram, A.C. and Dahyot, R.},
  month = {oct},
  year = {2005},
  note = {ISSN: 2380-7504},
  keywords = {Color, Computational efficiency, Density functional theory, Distributed
    computing, Educational institutions, Image converters, Iterative methods, Rendering
    (computer graphics), Statistical distributions, Statistics},
  pages = {1434--1439 Vol. 2}
}


@article{cleveland_robust_1979,
  title = {Robust {Locally} {Weighted} {Regression} and {Smoothing} {Scatterplots}},
  volume = {74},
  issn = {0162-1459},
  url = {https://www.tandfonline.com/doi/abs/10.1080/01621459.1979.10481038},
  doi = {10.1080/01621459.1979.10481038},
  abstract = {The visual information on a scatterplot can be greatly enhanced, with little
    additional cost, by computing and plotting smoothed points. Robust locally weighted
    regression is a method for smoothing a scatterplot, (x i , y i ), i = 1, …, n, in which
    the fitted value at z k is the value of a polynomial fit to the data using weighted
    least squares, where the weight for (x i , y i ) is large if x i is close to x k and
    small if it is not. A robust fitting procedure is used that guards against deviant
    points distorting the smoothed points. Visual, computational, and statistical issues of
    robust locally weighted regression are discussed. Several examples, including data on
    lead intoxication, are used to illustrate the methodology.},
  number = {368},
  urldate = {2022-07-29},
  journal = {Journal of the American Statistical Association},
  author = {Cleveland, William S.},
  month = {dec},
  year = {1979},
  note = {Publisher: Taylor \& Francis \_eprint:
    https://www.tandfonline.com/doi/pdf/10.1080/01621459.1979.10481038},
  keywords = {Graphics, Nonparametric regression, Robust estimation, Scatterplots,
    Smoothing},
  pages = {829--836}
}


@article{themesl_empirical-statistical_2012,
  title = {Empirical-statistical downscaling and error correction of regional climate
    models and its impact on the climate change signal},
  volume = {112},
  issn = {1573-1480},
  url = {https://doi.org/10.1007/s10584-011-0224-4},
  doi = {10.1007/s10584-011-0224-4},
  abstract = {Realizing the error characteristics of regional climate models (RCMs) and the
    consequent limitations in their direct utilization in climate change impact research,
    this study analyzes a quantile-based empirical-statistical error correction method
    (quantile mapping, QM) for RCMs in the context of climate change. In particular the
    success of QM in mitigating systematic RCM errors, its ability to generate “new
    extremes” (values outside the calibration range), and its impact on the climate change
    signal (CCS) are investigated. In a cross-validation framework based on a RCM control
    simulation over Europe, QM reduces the bias of daily mean, minimum, and maximum
    temperature, precipitation amount, and derived indices of extremes by about one order
    of magnitude and strongly improves the shapes of the related frequency distributions.
    In addition, a simple extrapolation of the error correction function enables QM to
    reproduce “new extremes” without deterioration and mostly with improvement of the
    original RCM quality. QM only moderately modifies the CCS of the corrected parameters.
    The changes are related to trends in the scenarios and magnitude-dependent error
    characteristics. Additionally, QM has a large impact on CCSs of non-linearly derived
    indices of extremes, such as threshold indices.},
  language = {en},
  number = {2},
  urldate = {2022-07-29},
  journal = {Climatic Change},
  author = {Themeßl, Matthias Jakob and Gobiet, Andreas and Heinrich, Georg},
  month = {may},
  year = {2012},
  keywords = {Climate Change Signal, Pacific Decadal Oscillation, Precipitation Amount,
    Quantile Mapping, Regional Climate Model},
  pages = {449--468}
}


@article{baringhaus_new_2004,
  title = {On a new multivariate two-sample test},
  volume = {88},
  issn = {0047-259X},
  url = {https://www.sciencedirect.com/science/article/pii/S0047259X03000794},
  doi = {10.1016/S0047-259X(03)00079-4},
  abstract = {In this paper we propose a new test for the multivariate two-sample problem.
    The test statistic is the difference of the sum of all the Euclidean interpoint
    distances between the random variables from the two different samples and one-half of
    the two corresponding sums of distances of the variables within the same sample. The
    asymptotic null distribution of the test statistic is derived using the projection
    method and shown to be the limit of the bootstrap distribution. A simulation study
    includes the comparison of univariate and multivariate normal distributions for
    location and dispersion alternatives. For normal location alternatives the new test is
    shown to have power similar to that of the t- and T2-Test.},
  language = {en},
  number = {1},
  urldate = {2022-07-29},
  journal = {Journal of Multivariate Analysis},
  author = {Baringhaus, L. and Franz, C.},
  month = {jan},
  year = {2004},
  keywords = {Bootstrapping, Cramér test, Multivariate two-sample test, Orthogonal
    invariance, Projection method},
  pages = {190--206}
}


@misc{jalbert_extreme_2022,
  title = {Extreme value analysis package for {Julia}.},
  url = {https://github.com/jojal5/Extremes.jl},
  abstract = {Extreme value analysis package for Julia},
  urldate = {2022-07-29},
  author = {Jalbert, Jonathan},
  month = {jun},
  year = {2022},
  note = {original-date: 2019-01-20T03:26:32Z}
}


@article{roy_probabilistic_2017,
  title = {Probabilistic climate change scenarios for viticultural potential in {Québec}},
  volume = {143},
  issn = {1573-1480},
  url = {https://doi.org/10.1007/s10584-017-1960-x},
  doi = {10.1007/s10584-017-1960-x},
  abstract = {Climate conditions for Québec’s viticultural potential (VP) during upcoming
    decades are estimated through high-resolution probabilistic climate scenarios (PCS)
    based on a large ensemble of simulations from the Coupled Model Intercomparison Project
    Phase 5 (CMIP5). VP is investigated through four temperature-related indices identified
    as current limiting factors for cold, northern latitudes: length of frost-free season
    (CNFD), growing degree-days (DDB10), annual winter minimum temperature (AWMT), and
    annual number of very cold days (ANVCD). Results show that by 2040–2050, most of
    southern Québec can reasonably expect favorable climatic conditions, with enough
    consecutive frost-free days and growing degree-days for growing current hybrid-grape
    varieties, as well as some Vitis vinifera grape varieties. Regions with new VP are
    identified, for example southern Outaouais and along the St-Lawrence River. Cold winter
    temperatures remain problematic, but technical solutions to this limiting factor exist.},
  language = {en},
  number = {1},
  urldate = {2022-07-29},
  journal = {Climatic Change},
  author = {Roy, Philippe and Grenier, Patrick and Barriault, Evelyne and Logan, Travis and
    Blondlot, Anne and Bourgeois, Gaétan and Chaumont, Diane},
  month = {jul},
  year = {2017},
  keywords = {Climate Index, Grape Variety, Pinot Noir, Representative Concentration
    Pathway, Wine Industry},
  pages = {43--58}
}


@article{grenier_assessment_2013,
  title = {An {Assessment} of {Six} {Dissimilarity} {Metrics} for {Climate} {Analogs}},
  volume = {52},
  issn = {1558-8424, 1558-8432},
  url = {https://journals.ametsoc.org/view/journals/apme/52/4/jamc-d-12-0170.1.xml},
  doi = {10.1175/JAMC-D-12-0170.1},
  abstract = {Abstract Spatial analog techniques consist in identifying locations whose
    historical climate is similar to the anticipated future climate at a reference
    location. In the process of identifying analogs, one key step is the quantification of
    the dissimilarity between two climates separated in time and space, which involves the
    choice of a metric. In this study, six a priori suitable metrics are described (the
    standardized Euclidean distance, the Kolmogorov–Smirnov statistic, the nearest-neighbor
    distance, the Zech–Aslan energy statistic, the Friedman–Rafsky runs statistic, and the
    Kullback–Leibler divergence) and criteria are proposed and investigated in an attempt
    to identify the best metric for selecting spatial analogs. The case study involves the
    use of numerical simulations performed with the Canadian Regional Climate Model (CRCM,
    version 4.2.3), from which three annual indicators (total precipitation, heating
    degree-days, and cooling degree-days) are calculated over 30-yr periods (1971–2000 and
    2041–70). It is found that the six metrics identify comparable analog regions at a
    relatively large scale but that best analogs may differ substantially. For best
    analogs, it is shown that the uncertainty stemming from the metric choice does not
    generally exceed that stemming from the simulation or model choice. On the basis of the
    set of criteria considered in this study, the Zech–Aslan energy statistic stands out as
    the most recommended metric for analog studies, whereas the Friedman–Rafsky runs
    statistic is the least recommended.},
  language = {EN},
  number = {4},
  urldate = {2022-07-29},
  journal = {Journal of Applied Meteorology and Climatology},
  author = {Grenier, Patrick and Parent, Annie-Claude and Huard, David and Anctil, François
    and Chaumont, Diane},
  month = {apr},
  year = {2013},
  note = {Publisher: American Meteorological Society Section: Journal of Applied
    Meteorology and Climatology},
  pages = {733--752}
}


@inproceedings{zech_multivariate_2003,
  address = {SLAC, Stanford, California, USA},
  title = {A {Multivariate} {Two}-{Sample} {Test} {Based} on the {Concept} of {Minimum}
    {Energy}},
  url = {    https://www.semanticscholar.org/paper/A-Multivariate-Two-Sample-Test-Based-on-the-Concept-Zech-Aslan/60e8b69d6f91a64231a0ab6bf1ddef1e88fb03f6},
  abstract = {We introduce a new statistical quantity the energy to test whether two
    samples originate from the same distributions. The energy is a simple logarithmic
    function of the distances of the observations in the variate space. The distribution of
    the test statistic is determined by a resampling method. The power of the energy test
    in one dimension was studied for a variety of dieren t test samples and compared to
    several nonparametric tests. In two and four dimensions a comparison was performed with
    the Friedman-Rafsky and nearest neighbor tests. The two-sample energy test is
    especially powerful in multidimensional applications.},
  language = {en},
  urldate = {2022-07-29},
  booktitle = {Statistical {Problems} in {Particle} {Physics}, {Astrophysics} and
    {Cosmology}},
  author = {Zech, G. and Aslan, B.},
  year = {2003},
  pages = {97--100}
}


@misc{aslan_new_2003,
  title = {A new class of binning free, multivariate goodness-of-fit tests: the energy
    tests},
  shorttitle = {A new class of binning free, multivariate goodness-of-fit tests},
  url = {https://arxiv.org/abs/hep-ex/0203010},
  doi = {10.48550/arXiv.hep-ex/0203010},
  abstract = {We present a new class of multivariate binning-free and nonparametric
    goodness-of-fit tests. The test quantity {\textbackslash}emph\{energy\} is a function
    of the distances of observed and simulated observations in the variate space. The
    simulation follows the probability distribution function \$f\_\{0\}\$ of the null
    hypothesis. The distances are weighted with a weighting function which can be adjusted
    to the variations of \$f\_\{0\}\$. We have investigated the power of the test for a
    uniform and a Gaussian distribution of one or two variates, respectively and compared
    it to that of conventional tests. The energy test with a Gaussian weighting function is
    closely related to the Pearson \${\textbackslash}chi {\textasciicircum}\{2\}\$ test but
    is more powerful in most applications and avoids arbitrary bin boundaries. The test is
    especially powerful in the multivariate case.},
  urldate = {2022-11-16},
  publisher = {arXiv},
  author = {Aslan, B. and Zech, G.},
  month = {apr},
  year = {2003},
  note = {arXiv:hep-ex/0203010},
  keywords = {High Energy Physics - Experiment, Physics - Data Analysis, Statistics and
    Probability}
}


@inproceedings{perez-cruz_kullback-leibler_2008,
  address = {Toronto, ON, Canada},
  title = {Kullback-{Leibler} divergence estimation of continuous distributions},
  isbn = {978-1-4244-2256-2},
  url = {https://ieeexplore.ieee.org/document/4595271/},
  abstract = {We present a method for estimating the KL divergence between continuous
    densities and we prove it converges almost surely. Divergence estimation is typically
    solved estimating the densities first. Our main result shows this intermediate step is
    unnecessary and that the divergence can be either estimated using the empirical cdf or
    k-nearest-neighbour density estimation, which does not converge to the true measure for
    finite k. The convergence proof is based on describing the statistics of our estimator
    using waiting-times distributions, as the exponential or Erlang. We illustrate the
    proposed estimators and show how they compare to existing methods based on density
    estimation, and we also outline how our divergence estimators can be used for solving
    the two-sample problem.},
  booktitle = {2008 {IEEE} {International} {Symposium} on {Information} {Theory}},
  publisher = {IEEE},
  author = {Perez-Cruz, Fernando},
  month = {jun},
  year = {2008},
  note = {ISSN: 2157-8117},
  keywords = {Approximation methods, Convergence, Density measurement, Entropy, Estimation,
    Exponential distribution, Random variables},
  pages = {1666--1670}
}


@article{friedman_multivariate_1979,
  title = {Multivariate {Generalizations} of the {Wald}-{Wolfowitz} and {Smirnov}
    {Two}-{Sample} {Tests}},
  volume = {7},
  issn = {0090-5364, 2168-8966},
  url = {    https://projecteuclid.org/journals/annals-of-statistics/volume-7/issue-4/Multivariate-Generalizations-of-the-Wald-Wolfowitz-and-Smirnov-Two-Sample/10.1214/aos/1176344722.full},
  doi = {10.1214/aos/1176344722},
  abstract = {Multivariate generalizations of the Wald-Wolfowitz runs statistic and the
    Smirnov maximum deviation statistic for the two-sample problem are presented. They are
    based on the minimal spanning tree of the pooled sample points. Some null distribution
    results are derived and a simulation study of power is reported.},
  number = {4},
  urldate = {2022-07-29},
  journal = {The Annals of Statistics},
  author = {Friedman, Jerome H. and Rafsky, Lawrence C.},
  month = {jul},
  year = {1979},
  note = {Publisher: Institute of Mathematical Statistics},
  keywords = {05C05, 62G10, 62G30, 62H15, 62H20, Minimal spanning trees, multivariate
    observations, nonparametric two-sample tests, Runs, Smirnov test, Wald-Wolfowitz test},
  pages = {697--717}
}


@article{fasano_multidimensional_1987,
  title = {A multidimensional version of the {Kolmogorov}–{Smirnov} test},
  volume = {225},
  issn = {0035-8711},
  url = {https://doi.org/10.1093/mnras/225.1.155},
  doi = {10.1093/mnras/225.1.155},
  abstract = {We discuss a generalization of the classical Kolmogorov–Smirnov test, which
    is suitable to analyse random samples defined in two or three dimensions. This test
    provides some improvements with respect to an earlier version proposed by Peacock. In
    particular: (i) it is faster, by a factor equal to the sample size, n, and then usable
    to analyse quite sizeable samples; (ii) it fully takes into account the dependence of
    the test statistics on the degree of correlation of data points and on the sample size;
    (iii) it allows for a generalization to the three-dimensional case which is still
    viable as regards computing time. Supported by a large number of Monte Carlo
    simulations, we are ensured that this test is sufficiently distribution-free for any
    practical purposes. We also give a simple analytic expression to make easier the
    calculation of the critical values of the test probability distribution. To illustrate
    how the test works, we use it to analyse models of the cosmological evolution of X-ray
    selected active galactic nuclei and we show that it is a much more sensitive
    goodness-of-fit test than the χ2.},
  number = {1},
  urldate = {2022-07-29},
  journal = {Monthly Notices of the Royal Astronomical Society},
  author = {Fasano, G. and Franceschini, A.},
  month = {mar},
  year = {1987},
  pages = {155--170}
}


@article{cannon_selecting_2015,
  title = {Selecting {GCM} {Scenarios} that {Span} the {Range} of {Changes} in a
    {Multimodel} {Ensemble}: {Application} to {CMIP5} {Climate} {Extremes} {Indices}},
  volume = {28},
  issn = {0894-8755, 1520-0442},
  shorttitle = {Selecting {GCM} {Scenarios} that {Span} the {Range} of {Changes} in a
    {Multimodel} {Ensemble}},
  url = {https://journals.ametsoc.org/view/journals/clim/28/3/jcli-d-14-00636.1.xml},
  doi = {10.1175/JCLI-D-14-00636.1},
  abstract = {Abstract Logistical constraints can limit the number of global climate model
    (GCM) simulations considered in a climate change impact assessment. When dealing with
    annual or seasonal variables, one can visualize and manually select GCM scenarios to
    cover as much of the ensemble’s range of changes as possible. Most environmental
    systems are sensitive to climate conditions (e.g., extremes) that cannot be described
    by a small number of variables. Instead, algorithms like k-means clustering have been
    used to select representative ensemble members. Clustering algorithms are, however,
    biased toward high-density regions of climate variable space and tend to select
    scenarios that describe the central tendency rather than the full spread of an
    ensemble. Also, scenarios selected via clustering may not be ordered: that is,
    scenarios in the five-cluster solution may not appear in the six-cluster solution,
    which makes recommending a consistent set of scenarios to researchers with different
    needs difficult. Alternatively, an automated procedure based on a cluster
    initialization algorithm is proposed and applied to changes in 27 climate extremes
    indices between 1986–2005 and 2081–2100 from a large ensemble of phase 5 of the Coupled
    Model Intercomparison Project (CMIP5) simulations. Selections by the method are ordered
    and are designed to span the overall range of the ensemble. The number of scenarios
    required to account for changes spanned by at least 90\% of the CMIP5 ensemble members
    is reported for 21 regions of the globe and compared with k-means clustering. On
    average, the proposed method requires 40\% fewer scenarios to meet this threshold than
    k-means clustering does.},
  language = {EN},
  number = {3},
  urldate = {2022-07-29},
  journal = {Journal of Climate},
  author = {Cannon, Alex J.},
  month = {feb},
  year = {2015},
  note = {Publisher: American Meteorological Society. Section: Journal of Climate},
  pages = {1260--1267}
}


@article{casajus_objective_2016,
  title = {An {Objective} {Approach} to {Select} {Climate} {Scenarios} when {Projecting}
    {Species} {Distribution} under {Climate} {Change}},
  volume = {11},
  issn = {1932-6203},
  url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0152495},
  doi = {10.1371/journal.pone.0152495},
  abstract = {An impressive number of new climate change scenarios have recently become
    available to assess the ecological impacts of climate change. Among these impacts,
    shifts in species range analyzed with species distribution models are the most widely
    studied. Whereas it is widely recognized that the uncertainty in future climatic
    conditions must be taken into account in impact studies, many assessments of species
    range shifts still rely on just a few climate change scenarios, often selected
    arbitrarily. We describe a method to select objectively a subset of climate change
    scenarios among a large ensemble of available ones. Our k-means clustering approach
    reduces the number of climate change scenarios needed to project species distributions,
    while retaining the coverage of uncertainty in future climate conditions. We first
    show, for three biologically-relevant climatic variables, that a reduced number of six
    climate change scenarios generates average climatic conditions very close to those
    obtained from a set of 27 scenarios available before reduction. A case study on
    potential gains and losses of habitat by three northeastern American tree species shows
    that potential future species distributions projected from the selected six climate
    change scenarios are very similar to those obtained from the full set of 27, although
    with some spatial discrepancies at the edges of species distributions. In contrast,
    projections based on just a few climate models vary strongly according to the initial
    choice of climate models. We give clear guidance on how to reduce the number of climate
    change scenarios while retaining the central tendencies and coverage of uncertainty in
    future climatic conditions. This should be particularly useful during future climate
    change impact studies as more than twice as many climate models were reported in the
    fifth assessment report of IPCC compared to the previous one.},
  language = {en},
  number = {3},
  urldate = {2022-07-29},
  journal = {PLOS ONE},
  author = {Casajus, Nicolas and Périé, Catherine and Logan, Travis and Lambert,
    Marie-Claude and Blois, Sylvie de and Berteaux, Dominique},
  month = {mar},
  year = {2016},
  note = {Publisher: Public Library of Science},
  keywords = {Anthropogenic climate change, Climate change, Climate modeling, Forecasting,
    k means clustering, Probability distribution, Statistical distributions, Statistical
    models},
  pages = {e0152495}
}


@incollection{collins_long-term_2013,
  address = {Cambridge, United Kingdom and New York, NY, USA},
  title = {Long-term {Climate} {Change}: {Projections}, {Commitments} and {Irreversibility}},
  language = {en},
  booktitle = {Climate {Change} 2013: {The} {Physical} {Science} {Basis}. {Contribution} of
    {Working} {Group} {I} to the {Fifth} {Assessment} {Report} of the {Intergovernmental}
    {Panel} on {Climate} {Change}},
  publisher = {Cambridge University Press},
  author = {Collins, Matthew and Knutti, Reto and Arblaster, Julie and Dufresne, Jean-Louis
    and Fichefet, Thierry and Gao, Xuejie and Jr, William J Gutowski and Johns, Tim and
    Krinner, Gerhard and Shongwe, Mxolisi and Weaver, Andrew J and Wehner, Michael and
    Allen, Myles R and Andrews, Tim and Beyerle, Urs and Bitz, Cecilia M and Bony, Sandrine
    and Booth, Ben B B and Brooks, Harold E and Brovkin, Victor and Browne, Oliver and
    Brutel-Vuilmet, Claire and Cane, Mark and Chadwick, Robin and Cook, Ed and Cook, Kerry
    H and Eby, Michael and Fasullo, John and Forest, Chris E and Forster, Piers and Good,
    Peter and Goosse, Hugues and Gregory, Jonathan M and Hegerl, Gabriele C and Hezel, Paul
    J and Hodges, Kevin I and Holland, Marika M and Huber, Markus and Joshi, Manoj and
    Kharin, Viatcheslav and Kushnir, Yochanan and Lawrence, David M and Lee, Robert W and
    Liddicoat, Spencer and Lucas, Christopher and Lucht, Wolfgang and Marotzke, Jochem and
    Massonnet, François and Matthews, H Damon and Meinshausen, Malte and Morice, Colin and
    Otto, Alexander and Patricola, Christina M and Philippon, Gwenaëlle and Rahmstorf,
    Stefan and Riley, William J and Saenko, Oleg and Seager, Richard and Sedláček, Jan and
    Shaffrey, Len C and Shindell, Drew and Sillmann, Jana and Stevens, Bjorn and Stott,
    Peter A and Webb, Robert and Zappa, Giuseppe and Zickfeld, Kirsten and Joussaume,
    Sylvie and Mokssit, Abdalah and Taylor, Karl and Tett, Simon},
  year = {2013},
  pages = {1029--1136}
}


@article{tebaldi_mapping_2011,
  title = {Mapping model agreement on future climate projections},
  volume = {38},
  issn = {1944-8007},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2011GL049863},
  doi = {10.1029/2011GL049863},
  abstract = {Climate change projections are often based on simulations from multiple
    global climate models and are presented as maps with some form of stippling or measure
    of robustness to indicate where different models agree on the projected
    anthropogenically forced changes. The criteria used to determine model agreement,
    however, often ignore the presence of natural internal variability. We demonstrate that
    this leads to misleading presentations of the degree of model consensus on the sign and
    magnitude of the change if the ratio of the signal from the externally forced change to
    internal variability is low. We present a simple alternative method of depicting
    multimodel projections which clearly separates lack of climate change signal from lack
    of model agreement by assessing the degree of consensus on the significance of the
    change as well as the sign of the change. Our results demonstrate that the common
    interpretation of lack of model agreement in precipitation projections is largely an
    artifact of the large noise from climate variability masking the signal, an issue
    exacerbated by performing analyses at the grid point scale. We argue that separating
    more clearly the case of lack of agreement from the case of lack of signal will add
    valuable information for stake-holders' decision making, since adaptation measures
    required in the two cases are potentially very different.},
  language = {en},
  number = {23},
  urldate = {2022-07-29},
  journal = {Geophysical Research Letters},
  author = {Tebaldi, Claudia and Arblaster, Julie M. and Knutti, Reto},
  year = {2011},
  note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1029/2011GL049863},
  keywords = {future projections, model agreement, natural variability, significance}
}


@article{knutti_robustness_2013,
  title = {Robustness and uncertainties in the new {CMIP5} climate model projections},
  volume = {3},
  copyright = {2012 Nature Publishing Group},
  issn = {1758-6798},
  url = {https://www.nature.com/articles/nclimate1716},
  doi = {10.1038/nclimate1716},
  abstract = {Updated models are being used for the new assessment report from the
    Intergovernmental Panel on Climate Change. This study compares projections from the
    latest models with those from earlier versions. The spread of results has not changed
    significantly, and some of the spread will always remain due to the internal
    variability of the climate system. As models improve, they are able to represent more
    processes in greater detail, allowing for greater confidence in their projections, in
    spite of model spread.},
  language = {en},
  number = {4},
  urldate = {2022-07-29},
  journal = {Nature Climate Change},
  author = {Knutti, Reto and Sedláček, Jan},
  month = {apr},
  year = {2013},
  note = {Number: 4 Publisher: Nature Publishing Group},
  keywords = {Climate sciences, Theoretical ecology},
  pages = {369--373}
}


@article{agbazo_characterizing_2020,
  title = {Characterizing and avoiding physical inconsistency generated by the application
    of univariate quantile mapping on daily minimum and maximum temperatures over {Hudson}
    {Bay}},
  volume = {40},
  issn = {1097-0088},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/joc.6432},
  doi = {10.1002/joc.6432},
  abstract = {Quantile mapping (QM) is a technique often used for statistical
    post-processing (SPP) of climate model simulations, in order to adjust their biases
    relative to a selected reference product and/or to downscale their resolution. However,
    when QM is applied in univariate mode, there is a risk of generating other problems,
    like intervariable physical inconsistency (PI). Here, such a risk is investigated with
    daily temperature minimum (Tmin) and maximum (Tmax), for which the relationship Tmin
    {\textgreater} Tmax would be inconsistent with the definition of the variables. QM is
    applied to an ensemble of 78 daily CMIP5 simulations over Hudson Bay for the
    application period 1979–2100, with Climate Forecast System Reanalysis (CFSR) selected
    as the reference product during the calibration period 1979–2010. This study's specific
    objectives are as follows: to investigate the conditions under which PI situations are
    generated; to test whether PI may be prevented simply by tuning some of the QM
    technique's numerical choices; and to compare the suitability of alternative approaches
    that hinder PI by design. Primary results suggest that PI situations appear
    preferentially for small values of the initial (simulated) diurnal temperature range
    (DTR), but the differential between the respective biases of Tmin and Tmax also plays
    an important role; one cannot completely prevent the generation of PI simply by
    adjusting QM parameters and options, but forcing preservation of the simulated
    long-term trends generates fewer PI situations; for avoiding PI between Tmin and Tmax,
    the present study supports a previous recommendation to directly post-process Tmax and
    DTR before deducing Tmin.},
  language = {en},
  number = {8},
  urldate = {2022-08-03},
  journal = {International Journal of Climatology},
  author = {Agbazo, Médard Noukpo and Grenier, Patrick},
  year = {2020},
  note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/joc.6432},
  keywords = {bias adjustment, climate simulations, physical inconsistency, univariate
    quantile mapping},
  pages = {3868--3884}
}


@article{grenier_two_2018,
  title = {Two {Types} of {Physical} {Inconsistency} to {Avoid} with {Univariate}
    {Quantile} {Mapping}: {A} {Case} {Study} over {North} {America} {Concerning} {Relative}
    {Humidity} and {Its} {Parent} {Variables}},
  volume = {57},
  issn = {1558-8424, 1558-8432},
  shorttitle = {Two {Types} of {Physical} {Inconsistency} to {Avoid} with {Univariate}
    {Quantile} {Mapping}},
  url = {https://journals.ametsoc.org/view/journals/apme/57/2/jamc-d-17-0177.1.xml},
  doi = {10.1175/JAMC-D-17-0177.1},
  abstract = {Abstract Univariate quantile mapping (QM), a technique often used to
    statistically postprocess climate simulations, may generate physical inconsistency.
    This issue is investigated here by classifying physical inconsistency into two types.
    Type I refers to the attribution of an impossible value to a single variable, and type
    II refers to the breaking of a fixed intervariable relationship. Here QM is applied to
    relative humidity (RH) and its parent variables, namely, temperature, pressure, and
    specific humidity. Twelve sites representing various climate types across North America
    are investigated. Time series from an ensemble of ten 3-hourly simulations are
    postprocessed, with the CFSR reanalysis used as the reference product. For type I,
    results indicate that direct postprocessing of RH generates supersaturation values
    ({\textgreater}100\%) at relatively small frequencies of occurrence. Generated
    supersaturation amplitudes exceed observed values in fog and clouds. Supersaturation
    values are generally more frequent and higher when RH is deduced from postprocessed
    parent variables. For type II, results show that univariate QM practically always
    breaks the intervariable thermodynamic relationship. Heuristic proxies are designed for
    comparing the initial bias with physical inconsistency of type II, and results suggest
    that QM generates a problem that is arguably lesser than the one it is intended to
    solve. When physical inconsistency is avoided by capping one humidity variable at its
    saturation level and deducing the other, statistical equivalence with the reference
    product remains much improved relative to the initial situation. A recommendation for
    climate services is to postprocess RH and deduce specific humidity rather than the
    opposite.},
  language = {EN},
  number = {2},
  urldate = {2022-08-03},
  journal = {Journal of Applied Meteorology and Climatology},
  author = {Grenier, Patrick},
  month = {feb},
  year = {2018},
  note = {Publisher: American Meteorological Society Section: Journal of Applied
    Meteorology and Climatology},
  pages = {347--364}
}


@article{hoffmann_meteorologically_2012,
  title = {Meteorologically consistent bias correction of climate time series for
    agricultural models},
  volume = {110},
  issn = {1434-4483},
  url = {https://doi.org/10.1007/s00704-012-0618-x},
  doi = {10.1007/s00704-012-0618-x},
  abstract = {Conventional bias correction of simulated climate time series for impact
    models is done separately for climate variables and hence leads to inconsistencies
    between them. However, agricultural models mostly use several variables, and
    meteorological consistency is essential. The present work points out meteorological
    inconsistency due to quantile mapping and describes a new method of consistent bias
    correction by an optimization approach. Time series of hourly precipitation and global
    radiation from the regional model REMO5.7 (Run UBA C20/A1B\_1) were corrected with site
    observations from the German Meteorological Service. The results urge to check
    conventionally corrected series for consistency before using them for multidimensional
    models. Here, quantile mapping resulted in underestimation of diffuse radiation at
    hours with precipitation. This deficit was minimized by the developed procedure.},
  language = {en},
  number = {1},
  urldate = {2022-08-03},
  journal = {Theoretical and Applied Climatology},
  author = {Hoffmann, Holger and Rath, Thomas},
  month = {oct},
  year = {2012},
  keywords = {Bias Correction, Diffuse Radiation, Global Radiation, Quantile Mapping,
    Simulated Time Series},
  pages = {129--141}
}


@article{thrasher_technical_2012,
  title = {Technical {Note}: {Bias} correcting climate model simulated daily temperature
    extremes with quantile mapping},
  volume = {16},
  issn = {1027-5606},
  shorttitle = {Technical {Note}},
  url = {https://hess.copernicus.org/articles/16/3309/2012/},
  doi = {10.5194/hess-16-3309-2012},
  abstract = {{\textless}p{\textgreater}{\textless}strong
    class="journal-contentHeaderColor"{\textgreater}Abstract.{\textless}/strong{\textgreater}
    When applying a quantile mapping-based bias correction to daily temperature extremes
    simulated by a global climate model (GCM), the transformed values of maximum and
    minimum temperatures are changed, and the diurnal temperature range (DTR) can become
    physically unrealistic. While causes are not thoroughly explored, there is a strong
    relationship between GCM biases in snow albedo feedback during snowmelt and bias
    correction resulting in unrealistic DTR values. We propose a technique to bias correct
    DTR, based on comparing observations and GCM historic simulations, and combine that
    with either bias correcting daily maximum temperatures and calculating daily minimum
    temperatures or vice versa. By basing the bias correction on a base period of 1961–1980
    and validating it during a test period of 1981–1999, we show that bias correcting DTR
    and maximum daily temperature can produce more accurate estimations of daily
    temperature extremes while avoiding the pathological cases of unrealistic DTR
    values.{\textless}/p{\textgreater}},
  language = {English},
  number = {9},
  urldate = {2022-08-03},
  journal = {Hydrology and Earth System Sciences},
  author = {Thrasher, B. and Maurer, E. P. and McKellar, C. and Duffy, P. B.},
  month = {sep},
  year = {2012},
  note = {Publisher: Copernicus GmbH},
  pages = {3309--3314}
}


@article{pierce_statistical_2014,
  title = {Statistical {Downscaling} {Using} {Localized} {Constructed} {Analogs} ({LOCA})},
  volume = {15},
  issn = {1525-7541, 1525-755X},
  url = {https://journals.ametsoc.org/view/journals/hydr/15/6/jhm-d-14-0082_1.xml},
  doi = {10.1175/JHM-D-14-0082.1},
  abstract = {Abstract A new technique for statistically downscaling climate model
    simulations of daily temperature and precipitation is introduced and demonstrated over
    the western United States. The localized constructed analogs (LOCA) method produces
    downscaled estimates suitable for hydrological simulations using a multiscale spatial
    matching scheme to pick appropriate analog days from observations. First, a pool of
    candidate observed analog days is chosen by matching the model field to be downscaled
    to observed days over the region that is positively correlated with the point being
    downscaled, which leads to a natural independence of the downscaling results to the
    extent of the domain being downscaled. Then, the one candidate analog day that best
    matches in the local area around the grid cell being downscaled is the single analog
    day used there. Most grid cells are downscaled using only the single locally selected
    analog day, but locations whose neighboring cells identify a different analog day use a
    weighted combination of the center and adjacent analog days to reduce edge
    discontinuities. By contrast, existing constructed analog methods typically use a
    weighted average of the same 30 analog days for the entire domain. By greatly reducing
    this averaging, LOCA produces better estimates of extreme days, constructs a more
    realistic depiction of the spatial coherence of the downscaled field, and reduces the
    problem of producing too many light-precipitation days. The LOCA method is more
    computationally expensive than existing constructed analog techniques, but it is still
    practical for downscaling numerous climate model simulations with limited computational
    resources.},
  language = {EN},
  number = {6},
  urldate = {2022-08-03},
  journal = {Journal of Hydrometeorology},
  author = {Pierce, David W. and Cayan, Daniel R. and Thrasher, Bridget L.},
  month = {dec},
  year = {2014},
  note = {Publisher: American Meteorological Society Section: Journal of Hydrometeorology},
  pages = {2558--2585}
}


@article{hyndman_sample_1996,
  title = {Sample {Quantiles} in {Statistical} {Packages}},
  volume = {50},
  issn = {0003-1305},
  url = {https://www.tandfonline.com/doi/abs/10.1080/00031305.1996.10473566},
  doi = {10.1080/00031305.1996.10473566},
  abstract = {There are a large number of different definitions used for sample quantiles
    in statistical computer packages. Often within the same package one definition will be
    used to compute a quantile explicitly, while other definitions may be used when
    producing a boxplot, a probability plot, or a QQ plot. We compare the most commonly
    implemented sample quantile definitions by writing them in a common notation and
    investigating their motivation and some of their properties. We argue that there is a
    need to adopt a standard definition for sample quantiles so that the same answers are
    produced by different packages and within each package. We conclude by recommending
    that the median-unbiased estimator be used because it has most of the desirable
    properties of a quantile estimator and can be defined independently of the underlying
    distribution.},
  number = {4},
  urldate = {2022-08-03},
  journal = {The American Statistician},
  author = {Hyndman, Rob J. and Fan, Yanan},
  month = {nov},
  year = {1996},
  note = {Publisher: Taylor \& Francis \_eprint:
    https://www.tandfonline.com/doi/pdf/10.1080/00031305.1996.10473566},
  keywords = {Percentiles, Quartiles, Sample quantiles, Statistical computer packages.},
  pages = {361--365}
}


@article{zhang_avoiding_2005,
  title = {Avoiding {Inhomogeneity} in {Percentile}-{Based} {Indices} of {Temperature}
    {Extremes}},
  volume = {18},
  issn = {0894-8755, 1520-0442},
  url = {https://journals.ametsoc.org/view/journals/clim/18/11/jcli3366.1.xml},
  doi = {10.1175/JCLI3366.1},
  abstract = {Abstract Using a Monte Carlo simulation, it is demonstrated that
    percentile-based temperature indices computed for climate change detection and
    monitoring may contain artificial discontinuities at the beginning and end of the
    period that is used for calculating the percentiles (base period). This would make
    these exceedance frequency time series unsuitable for monitoring and detecting climate
    change. The problem occurs because the threshold calculated in the base period is
    affected by sampling error. On average, this error leads to overestimated exceedance
    rates outside the base period. A bootstrap resampling procedure is proposed to estimate
    exceedance frequencies during the base period. The procedure effectively removes the
    inhomogeneity.},
  language = {EN},
  number = {11},
  urldate = {2022-08-03},
  journal = {Journal of Climate},
  author = {Zhang, Xuebin and Hegerl, Gabriele and Zwiers, Francis W. and Kenyon, Jesse},
  month = {jun},
  year = {2005},
  note = {Publisher: American Meteorological Society Section: Journal of Climate},
  pages = {1641--1651}
}


@book{bohren_atmospheric_1998,
  title = {Atmospheric {Thermodynamics}},
  isbn = {978-0-19-509904-1},
  abstract = {This comprehensive text is based on the authors' course notes, refined and
    updated over 15 years of teaching. The core of the text focuses on water and its
    transformations. Four chapters lay the foundation, from energy conservation to the
    ideal gas law, specific heat capacities, adiabaticprocesses, and entropy. An extensive
    chapter treats phase transitions of water, and a lengthy discussion of the van der
    Waals equation sets the stage for phase diagrams. Free energy is applied to determining
    the effect of dissolved substances, total pressure, and size on vapor pressure. The
    chapteron moist air and clouds discusses wet-bulb and virtual temperatures, isentropic
    ascent of saturated air, thermodynamic diagrams, stability, and cloud formation. The
    final chapter covers energy, momentum, and mass transfer, topics not usually considered
    part of thermodynamics. Measurements areincluded and experiments and observations are
    suggested, all with the aim of breathing life into equations. The authors are careful
    to recognize and unafraid to criticize the treatments of thermodynamics that have been
    unchanged for more than a hundred years.Atmospheric Thermodynamics contains over 200
    exercises, mostly applications of basic principles to concrete problems. Often inspired
    by inquisitive students and colleagues, the exercises cover everything from automobiles
    and airplanes to baseball, wind turbines, and ground hogs. The authors weavehistory
    into the text by drawing on original writings rather than using textbook anecdotes, and
    molecular interpretations are given wherever possible. Assumptions and approximations
    are carefully laid out, derivations are detailed, and equations are interpreted
    physically and applied. No previousknowledge of thermodynamics or kinetic theory is
    assumed, although students are expected to be well-grounded in calculus, differential
    equations, vector analysis, and classical mechanics.},
  language = {en},
  publisher = {Oxford University Press},
  author = {Bohren, Craig F. and Albrecht, Bruce A.},
  year = {1998},
  note = {Google-Books-ID: SSJJ\_RWJGe8C},
  keywords = {Science / Earth Sciences / Meteorology \& Climatology}
}


@article{lawrence_relationship_2005,
  title = {The {Relationship} between {Relative} {Humidity} and the {Dewpoint}
    {Temperature} in {Moist} {Air}: {A} {Simple} {Conversion} and {Applications}},
  volume = {86},
  issn = {0003-0007, 1520-0477},
  shorttitle = {The {Relationship} between {Relative} {Humidity} and the {Dewpoint}
    {Temperature} in {Moist} {Air}},
  url = {https://journals.ametsoc.org/view/journals/bams/86/2/bams-86-2-225.xml},
  doi = {10.1175/BAMS-86-2-225},
  abstract = {The relative humidity (RH) and the dewpoint temperature (td) are two widely
    used indicators of the amount of moisture in air. The exact conversion from RH to td,
    as well as highly accurate approximations, are too complex to be done easily without
    the help of a calculator or computer. However, there is a very simple rule of thumb
    that can be very useful for approximating the conversion for moist air (RH
    {\textgreater} 50\%), which does not appear to be widely known by the meteorological
    community: td decreases by about 1°C for every 5\% decrease in RH (starting at td= t,
    the dry bulb temperature, when RH = 100\%). This article examines the mathematical
    basis and accuracy of this and other relationships between the dewpoint and relative
    humidity. Several useful applications of the simple conversion are presented, in
    particular the computation of the cumulus cloud-base level (or lifting condensation
    level) as zLCL {\textgreater}{\textgreater} (20 + t/5)(100 – RH), where zLCL is in
    meters when t is in degrees Celcius and RH in percent. Finally, a historical
    perspective is given with anecdotes about some of the early work in this field.},
  language = {en},
  number = {2},
  urldate = {2022-08-03},
  journal = {Bulletin of the American Meteorological Society},
  author = {Lawrence, Mark G.},
  month = {feb},
  year = {2005},
  note = {Publisher: American Meteorological Society Section: Bulletin of the American
    Meteorological Society},
  pages = {225--234}
}


@book{world_meteorological_organization_guide_2008,
  address = {Geneva, Switzerland},
  title = {Guide to meteorological instruments and methods of observation.},
  isbn = {978-92-63-10008-5},
  abstract = {This guide lays down the basic standards of instrument and observing
    practices required by present-day international meteorology and provides the basis for
    the preparation by individual Meteorological Services of detailed instrument manuals
    for use by observers.--Publisher's description.},
  language = {en},
  publisher = {World Meteorological Organization},
  author = {{World Meteorological Organization}},
  year = {2008},
  note = {OCLC: 288915903}
}


@misc{melton_atmosphericvarscalcf90_2019,
  title = {{atmosphericVarsCalc}.f90},
  url = {https://gitlab.com/cccma/classic/-/blob/master/src/atmosphericVarsCalc.f90},
  abstract = {The Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) is
    the land surface component of the CanESM. CLASSIC's component models are the Canadian
    Land Surface Scheme (CLASS) \&amp;...},
  language = {en},
  urldate = {2022-08-03},
  journal = {GitLab},
  author = {Melton, Joe},
  month = {oct},
  year = {2019}
}


@misc{verseghy_class_2009,
  title = {{CLASS} – {The} {Canadian} {Land} {Surface} {Scheme} ({Version} 3.4),
    {Technical} {Documentation}},
  url = {    https://wiki.usask.ca/download/attachments/223019286/CLASS_v3.6_Documentation.pdf?version=1&modificationDate=1478106693000&api=v2},
  publisher = {Environment Canada, Climate Research Division, Science and Technology Branch},
  author = {Verseghy, Diana},
  year = {2009},
  note = {Version 1.1}
}


@article{katsavounidis_new_1994,
  title = {A new initialization technique for generalized {Lloyd} iteration},
  volume = {1},
  issn = {1558-2361},
  url = {https://ieeexplore.ieee.org/document/329844/},
  abstract = {The generalized Lloyd algorithm plays an important role in the design of
    vector quantizers (VQ) and in feature clustering for pattern recognition. In the VQ
    context, this algorithm provides a procedure to iteratively improve a codebook and
    results in a local minimum that minimizes the average distortion function. We propose
    an efficient method to obtain a good initial codebook that can accelerate the
    convergence of the generalized Lloyd algorithm and achieve a better local minimum as
    well.{\textless}{\textgreater}},
  number = {10},
  journal = {IEEE Signal Processing Letters},
  author = {Katsavounidis, I. and Jay Kuo, C.-C. and Zhang, Zhen},
  month = {oct},
  year = {1994},
  note = {Conference Name: IEEE Signal Processing Letters},
  keywords = {Acceleration, Algorithm design and analysis, Convergence, Distortion
    measurement, Image coding, Iterative algorithms, Partitioning algorithms, Pattern
    recognition, Product codes, Signal processing algorithms},
  pages = {144--146}
}


@misc{lopker_yamale_2022,
  title = {Yamale (ya·ma·lē)},
  copyright = {MIT},
  url = {https://github.com/23andMe/Yamale},
  abstract = {A schema and validator for YAML.},
  urldate = {2022-08-03},
  publisher = {23andMe},
  author = {Lopker, Bo},
  month = {aug},
  year = {2022},
  note = {original-date: 2014-01-27T09:30:25Z},
  keywords = {python, schema, yaml}
}


@article{zhang_indices_2011,
  title = {Indices for monitoring changes in extremes based on daily temperature and
    precipitation data},
  volume = {2},
  issn = {1757-7799},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/wcc.147},
  doi = {10.1002/wcc.147},
  abstract = {Indices for climate variability and extremes have been used for a long time,
    often by assessing days with temperature or precipitation observations above or below
    specific physically-based thresholds. While these indices provided insight into local
    conditions, few physically based thresholds have relevance in all parts of the world.
    Therefore, indices of extremes evolved over time and now often focus on relative
    thresholds that describe features in the tails of the distributions of meteorological
    variables. In order to help understand how extremes are changing globally, a subset of
    the wide range of possible indices is now being coordinated internationally which
    allows the results of studies from different parts of the world to fit together
    seamlessly. This paper reviews these as well as other indices of extremes and documents
    the obstacles to robustly calculating and analyzing indices and the methods developed
    to overcome these obstacles. Gridding indices are necessary in order to compare
    observations with climate model output. However, gridding indices from daily data are
    not always straightforward because averaging daily information from many stations tends
    to dampen gridded extremes. The paper describes recent progress in attribution of the
    changes in gridded indices of extremes that demonstrates human influence on the
    probability of extremes. The paper also describes model projections of the future and
    wraps up with a discussion of ongoing efforts to refine indices of extremes as they are
    being readied to contribute to the IPCC's Fifth Assessment Report. WIREs Clim Change
    2011, 2:851–870. doi: 10.1002/wcc.147 This article is categorized under: Paleoclimates
    and Current Trends {\textgreater} Modern Climate Change},
  language = {en},
  number = {6},
  urldate = {2022-08-03},
  journal = {WIREs Climate Change},
  author = {Zhang, Xuebin and Alexander, Lisa and Hegerl, Gabriele C. and Jones, Philip and
    Tank, Albert Klein and Peterson, Thomas C. and Trewin, Blair and Zwiers, Francis W.},
  year = {2011},
  note = {\_eprint: https://onlinelibrary.wiley.com/doi/pdf/10.1002/wcc.147},
  pages = {851--870}
}


@misc{wikipedia_contributors_growing_2021,
  title = {Growing degree-day},
  copyright = {Creative Commons Attribution-ShareAlike License},
  url = {https://en.wikipedia.org/w/index.php?title=Growing_degree-day&oldid=1062329362},
  abstract = {Growing degree days (GDD), also called growing degree units (GDUs), are a
    heuristic tool in phenology. GDD are a measure of heat accumulation used by
    horticulturists, gardeners, and farmers to predict plant and animal development rates
    such as the date that a flower will bloom, an insect will emerge from dormancy, or a
    crop will reach maturity.},
  language = {en},
  urldate = {2022-08-03},
  journal = {Wikipedia},
  author = {{Wikipedia Contributors}},
  month = {dec},
  year = {2021},
  note = {Page Version ID: 1062329362}
}


@misc{gramfort_lowess_2015,
  title = {{LOWESS} : {Locally} weighted regression},
  copyright = {BSD 3-Clause},
  shorttitle = {{LOWESS}},
  url = {https://gist.github.com/agramfort/850437},
  abstract = {LOWESS : Locally weighted regression. GitHub Gist: instantly share code,
    notes, and snippets.},
  urldate = {2022-08-05},
  author = {Gramfort, Alexandre},
  month = {oct},
  year = {2015}
}


@article{sirangelo_combining_2020,
  title = {Combining stochastic models of air temperature and vapour pressure for the
    analysis of the bioclimatic comfort through the {Humidex}},
  volume = {10},
  copyright = {2020 The Author(s)},
  issn = {2045-2322},
  url = {https://www.nature.com/articles/s41598-020-68297-4},
  doi = {10.1038/s41598-020-68297-4},
  abstract = {Several studies evidenced the importance of the knowledge of the bioclimatic
    comfort for improving people’s quality of life. Temperature and relative humidity are
    the main variables related to climatic comfort/discomfort, influencing the
    environmental stress in the human body. In this study, a stochastic approach is
    proposed for characterizing the bioclimatic conditions through the Humidex values in
    six sites of Calabria (southern Italy), a region often hit by heat waves in summer
    months. The stochastic approach is essential, because the available time series of
    temperature and relative humidity are not long enough and present several missing
    values. The model allowed the characterization of sequences of extreme values of the
    Humidex. Results showed different behaviours between inner and coastal stations. For
    example, a sequence of 20 consecutive days with maximum daily Humidex values greater
    than 35 has a return period ranging from 10 to 20 years for the inner stations, while
    it exceeds 100 years for the coastal ones. The maximum yearly Humidex values for the
    inner stations have a larger range (40–50) than the coastal ones (38–45), reaching
    higher occurrence probabilities of serious danger conditions. Besides, the different
    influence of temperature and relative humidity on the Humidex behaviour has been
    evidenced.},
  language = {en},
  number = {1},
  urldate = {2022-08-08},
  journal = {Scientific Reports},
  author = {Sirangelo, Beniamino and Caloiero, Tommaso and Coscarelli, Roberto and Ferrari,
    Ennio and Fusto, Francesco},
  month = {jul},
  year = {2020},
  note = {Number: 1 Publisher: Nature Publishing Group},
  keywords = {Hydrology, Natural hazards},
  pages = {11395}
}


@book{masterton_humidex_1979,
  address = {Downsview, Ontario, Canada},
  series = {{CLI}},
  title = {Humidex : a {Method} of {Quantifying} {Human} {Discomfort} {Due} to {Excessive}
    {Heat} and {Humidity}},
  shorttitle = {Humidex},
  language = {en},
  publisher = {Environment Canada, Atmospheric Environment},
  author = {Masterton, J. M. and Richardson, F. A.},
  year = {1979},
  note = {Google-Books-ID: qzPbOAAACAAJ}
}


@misc{canada_glossary_2011,
  title = {Glossary - {Climate} - {Environment} and {Climate} {Change} {Canada}},
  url = {https://climate.weather.gc.ca/glossary_e.html},
  abstract = {Glossary of the Climate data web site, which is a gateway to information on
    matters such as past weather, climate normals, historical radar, almanac averages and
    extremes, and engineering climate data. Past weather data includes: temperature, snow,
    snow on ground, precipitation, rain, wind speed and direction, heating and cooling
    degree days, visibility, and relative humidity, humidex and wind chill in Canada.},
  language = {en},
  urldate = {2022-08-08},
  author = {Canada, Environment {and} Climate Change},
  month = {oct},
  year = {2011},
  note = {Last Modified: 2022-05-25}
}


@article{blazejczyk_comparison_2012,
  title = {Comparison of {UTCI} to selected thermal indices},
  volume = {56},
  issn = {1432-1254},
  url = {https://doi.org/10.1007/s00484-011-0453-2},
  doi = {10.1007/s00484-011-0453-2},
  abstract = {Over the past century more than 100 indices have been developed and used to
    assess bioclimatic conditions for human beings. The majority of these indices are used
    sporadically or for specific purposes. Some are based on generalized results of
    measurements (wind chill, cooling power, wet bulb temperature) and some on the
    empirically observed reactions of the human body to thermal stress (physiological
    strain, effective temperature). Those indices that are based on human heat balance
    considerations are referred to as "rational indices". Several simple human heat balance
    models are known and are used in research and practice. This paper presents a
    comparative analysis of the newly developed Universal Thermal Climate Index (UTCI), and
    some of the more prevalent thermal indices. The analysis is based on three groups of
    data: global data-set, synoptic datasets from Europe, and local scale data from special
    measurement campaigns of COST Action 730. We found the present indices to express
    bioclimatic conditions reasonably only under specific meteorological situations, while
    the UTCI represents specific climates, weather, and locations much better. Furthermore,
    similar to the human body, the UTCI is very sensitive to changes in ambient stimuli:
    temperature, solar radiation, wind and humidity. UTCI depicts temporal variability of
    thermal conditions better than other indices. The UTCI scale is able to express even
    slight differences in the intensity of meteorological stimuli.},
  language = {en},
  number = {3},
  urldate = {2022-08-08},
  journal = {International Journal of Biometeorology},
  author = {Blazejczyk, Krzysztof and Epstein, Yoram and Jendritzky, Gerd and Staiger,
    Henning and Tinz, Birger},
  month = {may},
  year = {2012},
  keywords = {Bioclimatic indices, Heat stress, Meteorological variables, Microclimatic
    differentiation, Synoptic data, UTCI},
  pages = {515--535}
}


@inproceedings{goff_low-pressure_1946,
  address = {New York, NY},
  series = {The 52nd annual meeting of the {American} {Society} of {Heating} and
    {Ventilating} {Engineers}},
  title = {Low-pressure properties of water from -160 to 212 °{F}},
  language = {en},
  booktitle = {Transactions of the {American} {Society} of {Heating} and {Ventilating}
    {Engineers}},
  author = {Goff, J. A. and Gratch, S.},
  year = {1946},
  pages = {95--122}
}


@misc{vomel_saturation_2016,
  title = {Saturation vapoor pressure formulations},
  url = {https://cires1.colorado.edu/~voemel/vp.html},
  language = {en},
  urldate = {2022-08-08},
  journal = {Water Vapor Pressure Formulations},
  author = {Vömel, Holger},
  month = {dec},
  year = {2016}
}


@article{tetens_uber_1930,
  title = {Über einige meteorologische {Begriffe}},
  volume = {6},
  language = {de},
  journal = {Zeitschrift für Geophysik},
  author = {Tetens, Otto},
  year = {1930},
  note = {Google-Books-ID: ey5UtAEACAAJ},
  pages = {297--309}
}


@article{sonntag_important_1990,
  title = {Important new values of the physical constants of 1986, vapour pressure
    formulations based on the {ITS}-90, and psychrometer formulae},
  volume = {40},
  issn = {0084-5361},
  number = {5},
  journal = {Zeitschrift für Meteorologie},
  author = {SONNTAG, D},
  year = {1990},
  note = {Place: Berlin Publisher: Akademie-Verlag},
  pages = {340--344}
}


@inproceedings{hardy_its-90_1998,
  title = {{ITS}-90 {FORMULATIONS} {FOR} {VAPOR} {PRESSURE}, {FROSTPOINT} {TEMPERATURE},
    {DEWPOINT} {TEMPERATURE}, {AND} {ENHANCEMENT} {FACTORS} {IN} {THE} {RANGE} –100 {TO}
    +100 {C}},
  url = {https://www.thunderscientific.com/wp-content/uploads/2022/12/its90formulas.pdf},
  abstract = {With the change in the temperature scale of ITS-90, new temperature dependent
    equations were required which predict saturation vapor pressure over water and ice,
    enhancement factor over water and ice, frostpoint temperature, and dewpoint
    temperature. Internationally recognized formulas based on the previous temperature
    scale, viewed as selfconsistent data sets for vapor pressures and enhancement factors,
    were chosen as initial defining equations. These formulas, coupled with those defining
    the temperature difference between the two scales, were used to compute new data sets
    consistent with the temperature scale of ITS-90. These new data sets were then fitted
    to equations of the original form, yielding new ITS-90 compatible coefficients to the
    familiar vapor pressure and enhancement factor equations. In addition, the resulting
    vapor pressure equations were used to produce a set of inverse approximating equations
    to yield frostpoint and dewpoint temperatures when the vapor pressure is known. The
    resulting coefficients, equations, and the conversion methods that produced them are
    presented.},
  language = {en},
  booktitle = {The {Proceedings} of the {Third} {International} {Symposium} on {Humidity}
    \& {Moisture}},
  author = {Hardy, Bob},
  year = {1998},
  pages = {1--8}
}


@article{veloz_identifying_2012,
  title = {Identifying climatic analogs for {Wisconsin} under 21st-century climate-change
    scenarios},
  volume = {112},
  issn = {1573-1480},
  url = {https://doi.org/10.1007/s10584-011-0261-z},
  doi = {10.1007/s10584-011-0261-z},
  abstract = {There is a deep disconnect between scientific and public concern about
    climate change. One reason is that global climate change is a fairly abstract concept
    with little perceived relevance, so a key challenge is to translate climate-change
    projections into locally concrete examples of potential impacts. Here we use climate
    analog analyses as an alternative method for identifying and communicating
    climate-change impacts. Our analysis uses multiple downscaled general circulation
    models for the state of Wisconsin, at 0.1 decimal degree resolution, and identifies
    contemporary locations in North America that are the most similar to the projected
    future climates for Wisconsin. We assess the uncertainties inherent in climate-change
    projections among greenhouse gas emission scenarios, time windows (mid-21st century vs.
    late 21st-century) and different combinations of climate variables. For all future
    scenarios and simulations, contemporary climatic analogs within North America were
    found for Wisconsin’s future climate. Closest analogs are primarily 200–500 km to the
    south-southwest of their Wisconsin reference location. Temperature has the largest
    effect on choice of climatic analog, but precipitation is the greatest source of
    uncertainty. Under the higher-end emission scenarios, the contemporary climatic analogs
    for Wisconsin’s end-21st-century climates are almost entirely outside the state.
    Climate-analog analyses offer a place-based means of assessing climate impacts that is
    complementary to the species-based approaches of species distributional models, and
    carries no assumptions about the characterization and conservatism of species niches.
    The analog method is simple and flexible, and can be readily extended to other regions
    and other environmental variables.},
  language = {en},
  number = {3},
  urldate = {2022-08-08},
  journal = {Climatic Change},
  author = {Veloz, Samuel and Williams, John W. and Lorenz, David and Notaro, Michael and
    Vavrus, Steve and Vimont, Daniel J.},
  month = {jun},
  year = {2012},
  keywords = {Climate Projection, Emission Scenario, Future Climate, General Circulation
    Model, Reference Location},
  pages = {1037--1058}
}


@article{henze_multivariate_1988,
  title = {A {Multivariate} {Two}-{Sample} {Test} {Based} on the {Number} of {Nearest}
    {Neighbor} {Type} {Coincidences}},
  volume = {16},
  issn = {0090-5364, 2168-8966},
  url = {    https://projecteuclid.org/journals/annals-of-statistics/volume-16/issue-2/A-Multivariate-Two-Sample-Test-Based-on-the-Number-of/10.1214/aos/1176350835.full},
  doi = {10.1214/aos/1176350835},
  abstract = {For independent \$d\$-variate random samples \$X\_1, {\textbackslash}cdots,
    X\_\{n\_1\}\$ i.i.d. \$f(x), Y\_1, {\textbackslash}cdots, Y\_\{n\_2\}\$ i.i.d.
    \$g(x)\$, where the densities \$f\$ and \$g\$ are assumed to be continuous a.e.,
    consider the number \$T\$ of all \$k\$ nearest neighbor comparisons in which
    observations and their neighbors belong to the same sample. We show that, if \$f = g\$
    a.e., the limiting (normal) distribution of \$T\$, as \${\textbackslash}min(n\_1, n\_2)
    {\textbackslash}rightarrow {\textbackslash}infty, n\_1/(n\_1 + n\_2)
    {\textbackslash}rightarrow {\textbackslash}tau, 0 {\textless} {\textbackslash}tau
    {\textless} 1\$, does not depend on \$f\$. An omnibus procedure for testing the
    hypothesis \$H\_0: f = g\$ a.e. is obtained by rejecting \$H\_0\$ for large values of
    \$T\$. The result applies to a general distance (generated by a norm on
    \${\textbackslash}mathbb\{R\}{\textasciicircum}d\$) for determining nearest neighbors,
    and it generalizes to the multisample situation.},
  number = {2},
  urldate = {2022-08-08},
  journal = {The Annals of Statistics},
  author = {Henze, Norbert},
  month = {jun},
  year = {1988},
  note = {Publisher: Institute of Mathematical Statistics},
  keywords = {62G10, 62H15, Multivariate two-sample test, nearest neighbor-type
    coincidences},
  pages = {772--783}
}


@techreport{bootsma_risk_1999,
  address = {Ottawa, Ontario},
  type = {Monographe},
  title = {Risk analyses of heat units available for corn and soybean production in
    {Quebec}},
  url = {https://publications.gc.ca/pub?id=9.647569&sl=0},
  abstract = {The results of this study should provide a useful basis for making decisions
    with respect to the selection of corn hybrids and soybean varieties which are best
    adapted to each region. The information on risk or probability levels will help to
    assess the probability that corn hybrids of a specified maturity (CHU) rating will
    reach an acceptable level of maturity before killing frost},
  language = {en;fr},
  number = {Technical Bulletin No. 991396},
  urldate = {2022-08-11},
  institution = {Eastern Cereal and Oilseed Research Centre, Agriculture and Agri-Food
    Canada},
  author = {Bootsma, Andrew and Tremblay,, Gilles and Filion, Pierre},
  year = {1999},
  pages = {127}
}


@article{finkele_2006,
  title = {National gridded drought factors and comparison of two soil moisture deficit
    formulations used in prediction of Forest Fire Danger Index in Australia},
  author = {Finkele, Klara and Mills, Graham A and Beard, Grant and Jones, David A},
  journal = {Australian Meteorological Magazine},
  volume = {55},
  language = {en},
  number = {3},
  pages = {183--197},
  year = {2006},
  publisher = {Citeseer}
}


@book{keetch_1968,
  title = {A drought index for forest fire control},
  author = {Keetch, John James and Byram, George Marsden},
  volume = {38},
  language = {en},
  year = {1968},
  publisher = {US Department of Agriculture, Forest Service, Southeastern Forest
    Experiment~…}
}


@article{holgate_2017,
  title = {Using alternative soil moisture estimates in the McArthur Forest Fire Danger
    Index},
  author = {Holgate, Chiara M and Van DIjk, Albert IJM and Cary, Geoffrey J and Yebra,
    Marta},
  journal = {International Journal of Wildland Fire},
  volume = {26},
  language = {en},
  number = {9},
  pages = {806--819},
  year = {2017},
  publisher = {CSIRO Publishing}
}


@article{dolling_2005,
  title = {A climatological study of the Keetch/Byram drought index and fire activity in
    the Hawaiian Islands},
  author = {Dolling, Klaus and Chu, Pao-Shin and Fujioka, Francis},
  journal = {Agricultural and Forest Meteorology},
  volume = {133},
  language = {en},
  number = {1-4},
  pages = {17--27},
  year = {2005},
  publisher = {Elsevier}
}


@article{griffiths_1999,
  title = {Improved formula for the drought factor in McArthur's Forest Fire Danger Meter},
  author = {Griffiths, Deryn},
  journal = {Australian Forestry},
  volume = {62},
  language = {en},
  number = {2},
  pages = {202--206},
  year = {1999},
  publisher = {Taylor \& Francis}
}


@article{noble_1980,
  title = {McArthur's fire-danger meters expressed as equations},
  author = {Noble, IR and Gill, AM and Bary, GAV},
  journal = {Australian Journal of Ecology},
  volume = {5},
  language = {en},
  number = {2},
  pages = {201--203},
  year = {1980},
  publisher = {Wiley Online Library}
}


@article{dowdy_2018,
  title = {Climatological variability of fire weather in Australia},
  author = {Dowdy, Andrew J},
  journal = {Journal of Applied Meteorology and Climatology},
  volume = {57},
  language = {en},
  number = {2},
  pages = {221--234},
  year = {2018}
}


@techreport{allen_crop_1998,
  address = {Rome, Italy},
  type = {{FAO} {Irrigation} and {Drainage} {Paper}},
  title = {Crop evapotranspiration: {Guidelines} for computing crop water requirements},
  url = {https://www.unirc.it/documentazione/materiale_didattico/1462_2016_412_24101.pdf},
  language = {en},
  number = {56},
  urldate = {2022-08-19},
  institution = {FAO},
  author = {Allen, Richard G. and Pereira, Luis S. and Raes, Dirk and Smith, Martin},
  year = {1998},
  pages = {326}
}


@book{perrin_estimation_1975,
  title = {Estimation {Des} {Ressources} {Energetiques} {Solaires} en {France}},
  language = {fr},
  publisher = {Association francaise pour l'etude et le developpement des applications de
    l'energie solaire},
  author = {Perrin, De Brichambaut C.},
  year = {1975}
}


@techreport{riou_determinisme_1994,
  type = {report},
  title = {Le déterminisme climatique de la maturation du raisin : application au zonage de
    la teneur en sucre dans la {Communauté} {Européenne}},
  shorttitle = {Le déterminisme climatique de la maturation du raisin},
  url = {https://hal.inrae.fr/hal-02843898},
  language = {fr},
  urldate = {2022-11-10},
  institution = {Commission Européenne},
  author = {Riou, C.},
  year = {1994}
}


@article{roy_extremeprecip_2023,
  title = {Climate scenarios of extreme precipitation using a combination of parametric and
    non-parametric bias correction methods in the province of Québec},
  url = {https://www.tandfonline.com/doi/full/10.1080/07011784.2023.2220682},
  doi = {10.1080/07011784.2023.2220682},
  language = {English},
  journal = {Canadian Water Resources Journal},
  author = {Roy, Philippe and Rondeau-Genesse, Gabriel and Jalbert, Jonathan and Fournier,
    Élyse},
  month = {june},
  year = {2023}
}


@article{francois_multivariate_2020,
  title = {Multivariate bias corrections of climate simulations: which benefits for which
    losses?},
  volume = {11},
  issn = {2190-4979},
  shorttitle = {Multivariate bias corrections of climate simulations},
  url = {https://esd.copernicus.org/articles/11/537/2020/},
  doi = {10.5194/esd-11-537-2020},
  language = {English},
  number = {2},
  urldate = {2022-04-27},
  journal = {Earth System Dynamics},
  author = {François, Bastien and Vrac, Mathieu and Cannon, Alex J. and Robin, Yoann and
    Allard, Denis},
  month = {jun},
  year = {2020},
  note = {Publisher: Copernicus GmbH},
  pages = {537--562}
}


@article{vrac_multivariate_2018,
  title = {Multivariate bias adjustment of high-dimensional climate simulations: the {Rank}
    {Resampling} for {Distributions} and {Dependences} ({R2D2}) bias correction},
  shorttitle = {Multivariate bias adjustment of high-dimensional climate simulations},
  doi = {10.5194/HESS-22-3175-2018},
  journal = {Hydrology and Earth System Sciences},
  author = {Vrac, M.},
  year = {2018}
}


@article{yip_2011,
  abstract = {A simple and coherent framework for partitioning uncertainty in multimodel
    climate ensembles is presented. The analysis of variance (ANOVA) is used to decompose a
    measure of total variation additively into scenario uncertainty, model uncertainty, and
    internal variability. This approach requires fewer assumptions than existing methods
    and can be easily used to quantify uncertainty related to model–scenario
    interaction—the contribution to model uncertainty arising from the variation across
    scenarios of model deviations from the ensemble mean. Uncertainty in global mean
    surface air temperature is quantified as a function of lead time for a subset of the
    Coupled Model Intercomparison Project phase 3 ensemble and results largely agree with
    those published by other authors: scenario uncertainty dominates beyond 2050 and
    internal variability remains approximately constant over the twenty-first century. Both
    elements of model uncertainty, due to scenario-independent and scenario-dependent
    deviations from the ensemble mean, are found to increase with time. Estimates of model
    deviations that arise as by-products of the framework reveal significant differences
    between models that could lead to a deeper understanding of the sources of uncertainty
    in multimodel ensembles. For example, three models show a diverging pattern over the
    twenty-first century, while another model exhibits an unusually large variation among
    its scenario-dependent deviations.},
  author = {Yip, Stan and Ferro, Christopher A. T. and Stephenson, David B. and Hawkins, Ed},
  doi = {10.1175/2011JCLI4085.1},
  issn = {0894-8755},
  journal = {Journal of Climate},
  month = {sep},
  number = {17},
  pages = {4634--4643},
  title = {{A Simple, Coherent Framework for Partitioning Uncertainty in Climate
    Predictions}},
  url = {https://journals.ametsoc.org/doi/10.1175/2011JCLI4085.1},
  volume = {24},
  year = {2011}
}


@article{northrop_2014,
  abstract = {A simple statistical model is used to partition uncertainty from different
    sources, in projections of future climate from multimodel ensembles. Three major
    sources of uncertainty are considered: the choice of climate model, the choice of
    emissions scenario, and the internal variability of the modeled climate system. The
    relative contributions of these sources are quantified for mid- and
    late-twenty-first-century climate projections, using data from 23 coupled
    atmosphere–ocean general circulation models obtained from phase 3 of the Coupled Model
    Intercomparison Project (CMIP3). Similar investigations have been carried out recently
    by other authors but within a statistical framework for which the unbalanced nature of
    the data and the small number (three) of scenarios involved are potentially
    problematic. Here, a Bayesian analysis is used to overcome these difficulties. Global
    and regional analyses of surface air temperature and precipitation are performed. It is
    found that the relative contributions to uncertainty depend on the climate variable
    considered, as well as the region and time horizon. As expected, the uncertainty due to
    the choice of emissions scenario becomes more important toward the end of the
    twenty-first century. However, for midcentury temperature, model internal variability
    makes a large contribution in high-latitude regions. For midcentury precipitation,
    model internal variability is even more important and this persists in some regions
    into the late century. Implications for the design of climate model experiments are
    discussed.},
  author = {Northrop, Paul J. and Chandler, Richard E.},
  doi = {10.1175/JCLI-D-14-00265.1},
  issn = {0894-8755},
  journal = {Journal of Climate},
  month = {dec},
  number = {23},
  pages = {8793--8808},
  title = {{Quantifying Sources of Uncertainty in Projections of Future Climate*}},
  url = {http://journals.ametsoc.org/doi/10.1175/JCLI-D-14-00265.1},
  volume = {27},
  year = {2014}
}


@article{goldenson_2018,
  author = {Goldenson, N. and Mauger, G. and Leung, L. R. and Bitz, C. M. and Rhines, A.},
  doi = {10.1002/2017GL076297},
  issn = {0094-8276},
  journal = {Geophysical Research Letters},
  month = {jan},
  number = {2},
  pages = {926--934},
  title = {{Effects of Ensemble Configuration on Estimates of Regional Climate
    Uncertainties}},
  url = {https://onlinelibrary.wiley.com/doi/10.1002/2017GL076297},
  volume = {45},
  year = {2018}
}


@article{lehner_2020,
  author = {Lehner, Flavio and Deser, Clara and Maher, Nicola and Marotzke, Jochem and
    Fischer, Erich M. and Brunner, Lukas and Knutti, Reto and Hawkins, Ed},
  doi = {10.5194/esd-11-491-2020},
  issn = {2190-4987},
  journal = {Earth System Dynamics},
  month = {may},
  number = {2},
  pages = {491--508},
  title = {{Partitioning climate projection uncertainty with multiple large ensembles and
    CMIP5/6}},
  url = {https://esd.copernicus.org/articles/11/491/2020/},
  volume = {11},
  year = {2020}
}


@article{evin_2019,
  abstract = {The quantification of uncertainty sources in ensembles of climate projections
    obtained from combinations of different scenarios and climate and impact models is a
    key issue in climate impact studies. The small size of the ensembles of simulation
    chains and their incomplete sampling of scenario and climate model combinations makes
    the analysis difficult. In the popular single-time ANOVA approach for instance, a
    precise estimate of internal variability requires multiple members for each simulation
    chain (e.g., each emission scenario–climate model combination), but multiple members
    are typically available for a few chains only. In most ensembles also, a precise
    partition of model uncertainty components is not possible because the matrix of
    available scenario/models combinations is incomplete (i.e., projections are missing for
    many scenario–model combinations). The method we present here, based on data
    augmentation and Bayesian techniques, overcomes such limitations and makes the
    statistical analysis possible for single-member and incomplete ensembles. It provides
    unbiased estimates of climate change responses of all simulation chains and of all
    uncertainty variables. It additionally propagates uncertainty due to missing
    information in the estimates. This approach is illustrated for projections of regional
    precipitation and temperature for four mountain massifs in France. It is applicable for
    any kind of ensemble of climate projections, including those produced from ad hoc
    impact models.},
  author = {Evin, Guillaume and Hingray, Benoit and Blanchet, Juliette and Eckert, Nicolas
    and Morin, Samuel and Verfaillie, Deborah},
  doi = {10.1175/JCLI-D-18-0606.1},
  issn = {0894-8755},
  journal = {Journal of Climate},
  month = {apr},
  number = {8},
  pages = {2423--2440},
  title = {{Partitioning Uncertainty Components of an Incomplete Ensemble of Climate
    Projections Using Data Augmentation}},
  url = {http://journals.ametsoc.org/doi/10.1175/JCLI-D-18-0606.1},
  volume = {32},
  year = {2019}
}


@article{hawkins_2009,
  author = {Hawkins, Ed and Sutton, Rowan},
  doi = {10.1175/2009BAMS2607.1},
  issn = {0003-0007},
  journal = {Bulletin of the American Meteorological Society},
  month = {aug},
  number = {8},
  pages = {1095--1108},
  title = {{The Potential to Narrow Uncertainty in Regional Climate Predictions}},
  url = {https://journals.ametsoc.org/doi/10.1175/2009BAMS2607.1},
  volume = {90},
  year = {2009}
}


@article{hawkins_2011,
  author = {Hawkins, Ed and Sutton, Rowan},
  doi = {10.1007/s00382-010-0810-6},
  issn = {0930-7575},
  journal = {Climate Dynamics},
  month = {jul},
  number = {1-2},
  pages = {407--418},
  title = {{The potential to narrow uncertainty in projections of regional precipitation
    change}},
  url = {http://link.springer.com/10.1007/s00382-010-0810-6},
  volume = {37},
  year = {2011}
}


@article{sivakumar_predicting_1998,
  title = {Predicting rainy season potential from the onset of rains in Southern Sahelian
    and Sudanian climatic zones of West Africa},
  journal = {Agricultural and Forest Meteorology},
  volume = {42},
  number = {4},
  pages = {295-305},
  year = {1988},
  issn = {0168-1923},
  doi = {https://doi.org/10.1016/0168-1923(88)90039-1},
  url = {https://www.sciencedirect.com/science/article/pii/0168192388900391},
  author = {Sivakumar, M.V.K.},
  abstract = {Analysis of long-term daily rainfall data for 58 locations in the Southern
    Sahelian and Sudanian climatic zones of West Africa showed that a significant
    relationship exists between the date of onset of rains and the length of the growing
    season. Early onset of rains, relative to the computed mean date of onset for a given
    location, resulted in a longer growing season. Probabilities of growing season lengths
    for early, normal and delayed onset of rains have been computed for all the locations.
    This analysis has important applications in crop planning as well as disaster planning
    and forms an initial step in concepts such as “Response Farming” or “Weather-responsive
    Crop Management Tactics” for drought-prone West Africa.}
}


@article{sturm_swe_2010,
  author = {Matthew  Sturm and Brian  Taras and Glen E.  Liston and Chris  Derksen and
    Tobias  Jonas and Jon  Lea},
  title = {Estimating Snow Water Equivalent Using Snow Depth Data and Climate Classes},
  journal = {Journal of Hydrometeorology},
  year = {2010},
  publisher = {American Meteorological Society},
  address = {Boston MA, USA},
  volume = {11},
  number = {6},
  doi = {10.1175/2010JHM1202.1},
  pages = {1380 - 1394},
  url = {https://journals.ametsoc.org/view/journals/hydr/11/6/2010jhm1202_1.xml}
}


@article{frei_snowfall_2018,
  author = {Frei, P. and Kotlarski, S. and Liniger, M. A. and Schär, C.},
  title = {Future snowfall in the Alps: projections based on the EURO-CORDEX regional
    climate models},
  journal = {The Cryosphere},
  volume = {12},
  year = {2018},
  number = {1},
  pages = {1--24},
  url = {https://tc.copernicus.org/articles/12/1/2018/},
  doi = {10.5194/tc-12-1-2018}
}


@article{dawson_plant_1991,
  title = {Plant {Hardiness} {Zones} for {Australia}},
  volume = {89},
  url = {https://www.cpbr.gov.au/gardens/research/hort.research/zones.html},
  language = {en},
  number = {8},
  urldate = {2023-06-16},
  journal = {Australian Horticulture},
  author = {Dawson, Iain A.},
  year = {1991},
  pages = {37 -- 39}
}


@misc{usda_2012,
  title = {{USDA} {Plant} {Hardiness} {Zone} {Map}},
  url = {https://planthardiness.ars.usda.gov/},
  abstract = {The 2012 USDA Plant Hardiness Zone Map allows gardeners and growers to
    determine which plants are most likely to thrive at a location. The map is based on the
    average annual minimum winter temperature, divided into 10-degree F zones.},
  language = {en-ca},
  urldate = {2023-06-16},
  author = {{USDA Agricultural Research Service}},
  year = {2012}
}


@article{chen_2020,
  title = {Impacts of climate change on wind resources over North America based on
    NA-CORDEX},
  journal = {Renewable Energy},
  volume = {153},
  pages = {1428-1438},
  year = {2020},
  issn = {0960-1481},
  doi = {https://doi.org/10.1016/j.renene.2020.02.090},
  url = {https://www.sciencedirect.com/science/article/pii/S0960148120302858},
  author = {Liang Chen},
  keywords = {Climate change, Wind energy, NA-CORDEX, North America}
}


@article{tobin_2018,
  doi = {10.1088/1748-9326/aab211},
  url = {https://dx.doi.org/10.1088/1748-9326/aab211},
  year = {2018},
  month = {apr},
  publisher = {IOP Publishing},
  volume = {13},
  number = {4},
  pages = {044024},
  author = {I Tobin and W Greuell and S Jerez and F Ludwig and R Vautard and M T H van
    Vliet and F-M Bréon},
  title = {Vulnerabilities and resilience of European power generation to 1.5°C, 2°C and
    3°C warming},
  journal = {Environmental Research Letters}
}


@inbook{ipccatlas_ar6wg1,
  place = {Cambridge},
  title = {Atlas},
  DOI = {10.1017/9781009157896.021},
  booktitle = {Climate Change 2021 – The Physical Science Basis: Working Group I
    Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate
    Change},
  publisher = {Cambridge University Press},
  author = {Intergovernmental Panel on Climate Change (IPCC)},
  year = {2023},
  pages = {1927–2058}
}


@article{Lafferty2023,
  abstract = {Efforts to diagnose the risks of a changing climate often rely on downscaled
    and bias-corrected climate information, making it important to understand the
    uncertainties and potential biases of this approach. Here, we perform a variance
    decomposition to partition uncertainty in global climate projections and quantify the
    relative importance of downscaling and bias-correction. We analyze simple climate
    metrics such as annual temperature and precipitation averages, as well as several
    indices of climate extremes. We find that downscaling and bias-correction often
    contribute substantial uncertainty to local decision-relevant climate outcomes, though
    our results are strongly heterogeneous across space, time, and climate metrics. Our
    results can provide guidance to impact modelers and decision-makers regarding the
    uncertainties associated with downscaling and bias-correction when performing
    local-scale analyses, as neglecting to account for these uncertainties may risk
    overconfidence relative to the full range of possible climate futures.},
  author = {David C. Lafferty and Ryan L. Sriver},
  doi = {10.1038/s41612-023-00486-0},
  issn = {2397-3722},
  issue = {1},
  journal = {npj Climate and Atmospheric Science 2023 6:1},
  keywords = {Atmospheric science,Climate,Climate and Earth system modelling,Projection and
    prediction,change impacts},
  month = {9},
  pages = {1-13},
  publisher = {Nature Publishing Group},
  title = {Downscaling and bias-correction contribute considerable uncertainty to local
    climate projections in CMIP6},
  volume = {6},
  url = {https://www.nature.com/articles/s41612-023-00486-0},
  year = {2023}
}


@article{thom_1958,
  title = {A Note on the Gamma Distribution},
  author = {Thom, H. C. S.},
  year = {1958},
  journal = {Monthly Weather Review},
  volume = {86},
  number = {4},
  pages = {117--122},
  publisher = {{American Meteorological Society}},
  issn = {1520-0493, 0027-0644},
  doi = {10.1175/1520-0493(1958)086<0117:ANOTGD>2.0.CO;2},
  abstract = {Abstract The general properties of the gamma distribution, which has several
    applications in meteorology, are discussed. A short review of the general properties of
    good statistical estimators is given. This is applied to the gamma distribution to show
    that the maximum likelihood estimators are jointly sufficient. A new, simple
    approximation of the likelihood solutions is given, and the efficiency of the fitting
    procedure is computed.},
  chapter = {Monthly Weather Review}
}


@article{brode_utci_2012,
  author = {Bröde, Peter and Fiala, Dusan and Błażejczyk, Krzysztof and Holmér, Ingvar and
    Jendritzky, Gerd and Kampmann, Bernhard and Tinz, Birger and Havenith, George},
  title = {Deriving the operational procedure for the Universal Thermal Climate Index
    (UTCI)},
  journal = {International Journal of Biometeorology},
  year = {2012},
  month = {May},
  day = {01},
  volume = {56},
  number = {3},
  pages = {481-494},
  abstract = {The Universal Thermal Climate Index (UTCI) aimed for a one-dimensional
    quantity adequately reflecting the human physiological reaction to the
    multi-dimensionally defined actual outdoor thermal environment. The human reaction was
    simulated by the UTCI-Fiala multi-node model of human thermoregulation, which was
    integrated with an adaptive clothing model. Following the concept of an equivalent
    temperature, UTCI for a given combination of wind speed, radiation, humidity and air
    temperature was defined as the air temperature of the reference environment, which
    according to the model produces an equivalent dynamic physiological response.
    Operationalising this concept involved (1) the definition of a reference environment
    with 50{\%} relative humidity (but vapour pressure capped at 20 hPa), with calm air and
    radiant temperature equalling air temperature and (2) the development of a
    one-dimensional representation of the multivariate model output at different exposure
    times. The latter was achieved by principal component analyses showing that the linear
    combination of 7 parameters of thermophysiological strain (core, mean and facial skin
    temperatures, sweat production, skin wettedness, skin blood flow, shivering) after 30
    and 120 min exposure time accounted for two-thirds of the total variation in the
    multi-dimensional dynamic physiological response. The operational procedure was
    completed by a scale categorising UTCI equivalent temperature values in terms of
    thermal stress, and by providing simplified routines for fast but sufficiently accurate
    calculation, which included look-up tables of pre-calculated UTCI values for a grid of
    all relevant combinations of climate parameters and polynomial regression equations
    predicting UTCI over the same grid. The analyses of the sensitivity of UTCI to
    humidity, radiation and wind speed showed plausible reactions in the heat as well as in
    the cold, and indicate that UTCI may in this regard be universally useable in the major
    areas of research and application in human biometeorology.},
  issn = {1432-1254},
  doi = {10.1007/s00484-011-0454-1},
  url = {https://doi.org/10.1007/s00484-011-0454-1}
}


@article{muralidhar_1992,
  title = {A {{Simple Minimum}}-{{Bias Percentile Estimator}} of the {{Location Parameter}}
    for the {{Gamma}}, {{Weibull}}, and {{Log}}-{{Normal Distributions}}},
  author = {Muralidhar, Krishnamurty and Zanakis, Stelios H.},
  year = {1992},
  month = {jul},
  journal = {Decision Sciences},
  volume = {23},
  number = {4},
  pages = {862--879},
  issn = {0011-7315, 1540-5915},
  doi = {10.1111/j.1540-5915.1992.tb00423.x}
}


@article{cooke_1979,
  title = {Statistical Inference for Bounds of Random Variables},
  author = {Cooke, Peter},
  year = {1979},
  journal = {Biometrika},
  volume = {66},
  number = {2},
  pages = {367--374},
  issn = {0006-3444, 1464-3510},
  doi = {10.1093/biomet/66.2.367}
}


@article{droogers2002,
  author = {Droogers, Peter and Allen, Richard G.},
  title = {Estimating reference evapotranspiration under inaccurate data conditions},
  year = {2002},
  journal = {Irrigation and Drainage Systems},
  volume = {16},
  number = {1},
  pages = {33 – 45},
  doi = {10.1023/A:1015508322413},
  url = {    https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036464359&doi=10.1023%2fA%3a1015508322413&partnerID=40&md5=7322aaa4c6874878f5b1dab3c73c1718},
  type = {Article}
}


@article{addor2018,
  author = {Addor, Nans and Nearing, Grey and Prieto, Cristina and Newman, A. and Le Vine,
    Nataliya and Clark, Martyn},
  year = {2018},
  month = {11},
  pages = {},
  title = {A Ranking of Hydrological Signatures Based on Their Predictability in Space},
  journal = {Water Resources Research},
  doi = {10.1029/2018WR022606}
}


@article{Clausen2000,
  author = {Clausen, B and Biggs, Barry},
  year = {2000},
  month = {11},
  pages = {184-197},
  title = {Flow variables for ecological studies in temperate streams: Groupings based on
    covariance},
  volume = {237},
  journal = {Journal of Hydrology},
  doi = {10.1016/S0022-1694(00)00306-1}
}


@article{Olden2003,
  author = {Olden, Julian and Poff, N.},
  year = {2003},
  month = {03},
  pages = {101 - 121},
  title = {Redundancy and the Choice of Hydrologic Indices for Characterizing Stream Flow
    Regimes},
  volume = {19},
  journal = {River Research and Applications},
  doi = {10.1002/rra.700}
}


@article{robin_2019,
  author = {Robin, Y. and Vrac, M. and Naveau, P. and Yiou, P.},
  title = {Multivariate stochastic bias corrections with optimal transport},
  journal = {Hydrology and Earth System Sciences},
  volume = {23},
  year = {2019},
  number = {2},
  pages = {773--786},
  url = {https://hess.copernicus.org/articles/23/773/2019/},
  doi = {10.5194/hess-23-773-2019}
}


@misc{robin_2021,
  title = {{SBCK}: {Statistical} {Bias} {Correction} {Kit}},
  copyright = {GPL-3},
  shorttitle = {{SBCK}},
  url = {https://github.com/yrobink/SBCK-python},
  urldate = {2024-07-03},
  author = {Robin, Yoann},
  year = {2021}
}


@article{higham_1988,
  title = {Computing a nearest symmetric positive semidefinite matrix},
  journal = {Linear Algebra and its Applications},
  volume = {103},
  pages = {103-118},
  year = {1988},
  issn = {0024-3795},
  doi = {https://doi.org/10.1016/0024-3795(88)90223-6},
  url = {https://www.sciencedirect.com/science/article/pii/0024379588902236},
  author = {Nicholas J. Higham},
  abstract = {The nearest symmetric positive semidefinite matrix in the Frobenius norm to
    an arbitrary real matrix A is shown to be (B + H)/2, where H is the symmetric polar
    factor of B=(A + AT)/2. In the 2-norm a nearest symmetric positive semidefinite matrix,
    and its distance δ2(A) from A, are given by a computationally challenging formula due
    to Halmos. We show how the bisection method can be applied to this formula to compute
    upper and lower bounds for δ2(A) differing by no more than a given amount. A key
    ingredient is a stable and efficient test for positive definiteness, based on an
    attempted Choleski decomposition. For accurate computation of δ2(A) we formulate the
    problem as one of zero finding and apply a hybrid Newton-bisection algorithm. Some
    numerical difficulties are discussed and illustrated by example.}
}


@article{knol_1989,
  title = {Least-squares approximation of an improper correlation matrix by a proper one},
  abstract = {An algorithm is presented for the best least-squares fitting correlation
    matrix approximating a given missing value or improper correlation matrix. The proposed
    algorithm is based upon a solution for Mosier's oblique Procrustes rotation problem
    offered by ten Berge and Nevels. A necessary and sufficient condition is given for a
    solution to yield the unique global minimum of the least-squares function. Empirical
    verification of the condition indicates that the occurrence of non-optimal solutions
    with the proposed algorithm is very unlikely. A possible drawback of the optimal
    solution is that it is a singular matrix of necessity. In cases where singularity is
    undesirable, one may impose the additional nonsingularity constraint that the smallest
    eigenvalue of the solution be δ, where δ is an arbitrary small positive constant.
    Finally, it may be desirable to weight the squared errors of estimation differentially.
    A generalized solution is derived which satisfies the additional nonsingularity
    constraint and also allows for weighting. The generalized solution can readily be
    obtained from the standard “unweighted singular” solution by transforming the observed
    improper correlation matrix in a suitable way.},
  keywords = {Missing value correlation, indefinite correlation matrix, IR-85889,
    tetrachoric correlation, constrained least-squares approximation},
  author = {Knol, {Dirk L.} and {ten Berge}, {Jos M.F.}},
  year = {1989},
  doi = {10.1007/BF02294448},
  language = {Undefined},
  volume = {54},
  pages = {53--61},
  journal = {Psychometrika},
  issn = {0033-3123},
  publisher = {Springer},
  number = {1}
}


@article{vicente-serrano_2012,
  author = {Sergio M. Vicente-Serrano  and Juan I. López-Moreno  and Santiago Beguería  and
    Jorge Lorenzo-Lacruz  and Cesar Azorin-Molina  and Enrique Morán-Tejeda},
  title = {Accurate Computation of a Streamflow Drought Index},
  journal = {Journal of Hydrologic Engineering},
  volume = {17},
  number = {2},
  pages = {318-332},
  year = {2012},
  doi = {10.1061/(ASCE)HE.1943-5584.0000433},
  URL = {https://ascelibrary.org/doi/abs/10.1061/%28ASCE%29HE.1943-5584.0000433},
  eprint = {https://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29HE.1943-5584.0000433},
  abstract = {In this study, the authors investigated an approach to calculate the
    standardized streamflow index (SSI), which allows accurate spatial and temporal
    comparison of the hydrological conditions of a stream or set of streams. For this
    purpose, the capability of six three-parameter distributions (lognormal, Pearson Type
    III, log-logistic, general extreme value, generalized Pareto, and Weibull) and two
    different approaches to select the most suitable distribution the best monthly fit
    (BMF) and the minimum orthogonal distance (MD), were tested by using a monthly
    streamflow data set for the Ebro Basin (Spain). This large Mediterranean basin is
    characterized by high variability in the magnitude of streamflows and in seasonal
    regimes. The results show that the most commonly used probability distributions for
    flow frequency analysis provided good fits to the streamflow series. Thus, the visual
    inspection of the L-moment diagrams and the results of the Kolmogorov-Smirnov test did
    not enable the selection of a single optimum probability distribution. However, no
    single probability distribution for all the series was suitable for obtaining a robust
    standardized streamflow series because each of the distributions had one or more
    limitations. The BMF and MD approaches improved the results in the expected average,
    standard deviation, and the frequencies of extreme events of the SSI series in relation
    to the selection of a unique distribution for each station. The BMF and MD approaches
    involved using different probability distributions for each gauging station and month
    of the year to calculate the SSI. Both approaches are easy to apply and they provide
    very similar results in the quality of the obtained hydrological drought indexes. The
    proposed procedures are very flexible for analyses involving contrasting hydrological
    regimes and flow characteristics.}
}


@article{bloomfield_2013,
  AUTHOR = {Bloomfield, J. P. and Marchant, B. P.},
  TITLE = {Analysis of groundwater drought building on the standardised precipitation index
    approach},
  JOURNAL = {Hydrology and Earth System Sciences},
  VOLUME = {17},
  YEAR = {2013},
  NUMBER = {12},
  PAGES = {4769--4787},
  URL = {https://hess.copernicus.org/articles/17/4769/2013/},
  DOI = {10.5194/hess-17-4769-2013}
}


@article{luedeling_chill_2009,
  title = {Climate change impacts on winter chill for temperate fruit and nut production: A
    review},
  journal = {Scientia Horticulturae},
  volume = {144},
  pages = {218-229},
  year = {2012},
  issn = {0304-4238},
  doi = {https://doi.org/10.1016/j.scienta.2012.07.011},
  url = {https://www.sciencedirect.com/science/article/pii/S0304423812003305},
  author = {Eike Luedeling},
  keywords = {Adaptation, Chilling Hours, Chill Portions, Climate analogues, Dynamic Model,
    Tree dormancy},
  abstract = {Temperate fruit and nut species require exposure to chilling conditions in
    winter to break dormancy and produce high yields. Adequate winter chill is an important
    site characteristic for commercial orchard operations, and quantifying chill is crucial
    for orchard management. Climate change may impact winter chill. With a view to adapting
    orchards to climate change, this review assesses the state of knowledge in modelling
    winter chill and the performance of various modelling approaches. It then goes on to
    present assessments of past and projected future changes in winter chill for fruit
    growing regions and discusses potential adaptation strategies. Some of the most common
    approaches to modelling chill, in particular the Chilling Hours approach, are very
    sensitive to temperature increases, and have also been found to perform poorly,
    especially in warm growing regions. The Dynamic Model offers a more complex but also
    more accurate alternative, and use of this model is recommended. Chill changes
    projected with the Dynamic Model are typically much less severe than those estimated
    with other models. Nevertheless, projections of future chill consistently indicate
    substantial losses for the warmest growing regions, while temperate regions will
    experience relatively little change, and cold regions may even see chill increases.
    Growers can adapt to lower chill by introducing low-chill cultivars, by influencing
    orchard microclimates and by applying rest-breaking chemicals. Given substantial
    knowledge gaps in tree dormancy, accurate models are still a long way off. Since timely
    adaptation is essential for growers of long-lived high-value perennials, alternative
    ways of adaptation planning are needed. Climate analogues, which are present-day
    manifestations of future projected climates, can be used for identifying and testing
    future-adapted species and cultivars. Horticultural researchers and practitioners
    should work towards the development and widespread adoption of better chill
    accumulation and dormancy models, for facilitating quantitatively appropriate
    adaptation planning.}
}


@article{fishman_chill_1987,
  title = {The temperature dependence of dormancy breaking in plants: Mathematical analysis
    of a two-step model involving a cooperative transition},
  journal = {Journal of Theoretical Biology},
  volume = {124},
  number = {4},
  pages = {473-483},
  year = {1987},
  issn = {0022-5193},
  doi = {https://doi.org/10.1016/S0022-5193(87)80221-7},
  url = {https://www.sciencedirect.com/science/article/pii/S0022519387802217},
  author = {Svetlana Fishman and A. Erez and G.A. Couvillon},
  abstract = {A two-step model describing the thermal dependence of the dormancy breaking
    phenomenon is developed. The model assumes that the level of dormancy completion is
    proportional to the amount of a certain dormancy breaking factor which accumulates in
    plants by a two-step process. The first step represents a reversible process of
    formation of a precursor for the dormancy breaking factor at low temperatures and its
    destruction at high temperatures. The rate constants of this process are assumed to be
    dependent upon the temperature according to the Arrhenius law. The second step is an
    irreversible cooperative transition from the unstable precursor to a stable dormancy
    breaking factor. The transition is assumed to occur when a critical level of the
    precursor is accumulated. The two-step scheme is analysed mathematically. This model
    explains qualitatively the main observations on dormancy completion made under
    controlled temperature conditions and relates the parameters of the theory to the
    measurable characteristics of the system.}
}


@article{richardson_chill_1974,
  author = {E. Arlo Richardson and Schuyler D. Seeley and David R. Walker},
  title = {A Model for Estimating the Completion of Rest for ‘Redhaven’ and ‘Elberta’ Peach
    Trees1},
  journal = {HortScience},
  year = {1974},
  publisher = {American Society for Horticultural Science},
  address = {Washington, DC},
  volume = {9},
  number = {4},
  doi = {10.21273/HORTSCI.9.4.331},
  pages = {331 - 332},
  url = {https://journals.ashs.org/hortsci/view/journals/hortsci/9/4/article-p331.xml}
}


@article{russo_magnitude_2014,
  title = {Magnitude of Extreme Heat Waves in Present Climate and Their Projection in a
    Warming World},
  author = {Russo, Simone and Dosio, Alessandro and Graversen, Rune G. and Sillmann, Jana
    and Carrao, Hugo and Dunbar, Martha B. and Singleton, Andrew and Montagna, Paolo and
    Barbola, Paulo and Vogt, J{\"u}rgen V.},
  year = {2014},
  journal = {Journal of Geophysical Research: Atmospheres},
  volume = {119},
  number = {22},
  pages = {12,500--12,512},
  issn = {2169-8996},
  doi = {10.1002/2014JD022098},
  urldate = {2024-10-03},
  langid = {english},
  keywords = {climate extremes,climate indices,global models,heat waves}
}


@article{zhang_high_2022,
  title = {High {{Sensitivity}} of {{Compound Drought}} and {{Heatwave Events}} to {{Global
    Warming}} in the {{Future}}},
  author = {Zhang, Qin and She, Dunxian and Zhang, Liping and Wang, Gangsheng and Chen, Jie
    and Hao, Zengchao},
  year = {2022},
  month = {nov},
  journal = {Earth's Future},
  volume = {10},
  number = {11},
  pages = {e2022EF002833},
  issn = {2328-4277, 2328-4277},
  doi = {10.1029/2022EF002833},
  urldate = {2024-10-03},
  langid = {english}
}


@article{huntington_2018,
  title = {A new indicator framework for quantifying the intensity of the terrestrial water
    cycle},
  journal = {Journal of Hydrology},
  volume = {559},
  pages = {361-372},
  year = {2018},
  issn = {0022-1694},
  doi = {https://doi.org/10.1016/j.jhydrol.2018.02.048},
  url = {https://www.sciencedirect.com/science/article/pii/S0022169418301276},
  author = {Thomas G. Huntington and Peter K. Weiskel and David M. Wolock and Gregory J.
    McCabe},
  keywords = {Intensification of the water cycle, Water cycle intensity, Water-balance
    model, Evapotranspiration, Aridification}
}


@article{spinoni_2018,
  author = {Spinoni, Jonathan and Vogt, Jürgen V. and Barbosa, Paulo and Dosio, Alessandro
    and McCormick, Niall and Bigano, Andrea and Füssel, Hans-Martin},
  title = {Changes of heating and cooling degree-days in Europe from 1981 to 2100},
  journal = {International Journal of Climatology},
  volume = {38},
  number = {S1},
  pages = {e191-e208},
  keywords = {climate change, degree-days, energy demand, Europe, CORDEX, population
    weighting},
  doi = {https://doi.org/10.1002/joc.5362},
  url = {https://rmets.onlinelibrary.wiley.com/doi/abs/10.1002/joc.5362},
  eprint = {https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.5362},
  abstract = {ABSTRACT During the last decades, the effects of global warming have become
    apparent also in Europe, causing relevant impacts in many sectors. Under projected
    future global warming, such a tendency can be expected to persist until the end of this
    century and beyond. Identifying which climate-related impacts are likely to increase,
    and by how much, is an important element of any effective strategy for managing future
    climate risks. This study investigates whether energy demand for cooling and heating
    buildings can be expected to increase or decrease under climate change. Two indicators
    of weather-related energy consumption for heating and cooling buildings are considered:
    heating degree-days (HDD) and cooling degree-days (CDD). The evolution of these
    indicators has been analysed based on 11 high-resolution bias-adjusted EURO-CORDEX
    simulations for two emission representative concentration pathways (RCP4.5 and RCP8.5).
    Both indicators have been validated over the period 1981–2010 using an independent data
    set that contains more than 4000 station data, showing very high correlation over most
    of Europe. Trends of HDD and CDD from 1981 to 2100, together with their uncertainties,
    are analysed. For both RCPs, all simulations project a significant decrease for HDD,
    especially over Scandinavia and European Russia, and an increase of CDD which peaks
    over the Mediterranean region and the Balkans. Overall, degree-day trends do not show
    remarkable differences if population weighting is applied. If a constant population
    scenario is considered, the decrease in HDD will outbalance the increase in CDD in the
    21st century over most of Europe. Thus the related energy demand (expressed as Energy
    Degree-days, EDD) is expected to decrease. If, however, population projections over the
    21st century are included in the calculations, it is shown that despite the persisting
    warming, EDD will increase over northern Europe, the Baltic countries, Great Britain,
    Ireland, Benelux, the Alps, Spain, and Cyprus, resulting in an overall increase in EDD
    over Europe.},
  year = {2018},
  langid = {english}
}


@article{lauret_solar_2022,
  title = {Solar Forecasts Based on the Clear Sky Index or the Clearness Index: Which Is
    Better?},
  author = {Lauret, Philippe and Alonso-Suárez, Rodrigo and Le Gal La Salle, Josselin and
    David, Mathieu},
  journal = {Solar},
  volume = {2},
  year = {2022},
  number = {4},
  pages = {432--444},
  url = {https://www.mdpi.com/2673-9941/2/4/26},
  issn = {2673-9941},
  doi = {10.3390/solar2040026}
}


@book{Deza2016,
  author = {Deza, Michel Marie and Deza, Elena},
  publisher = {Springer Berlin Heidelberg},
  title = {Encyclopedia of Distances},
  year = {2016},
  isbn = {9783662528440},
  doi = {10.1007/978-3-662-52844-0}
}


@article{li2021,
  title = {Optimality of antecedent precipitation index and its application},
  author = {Li, Xungui and Wei, Yining and Li, Fang},
  journal = {Journal of Hydrology},
  volume = {595},
  pages = {126027},
  year = {2021},
  publisher = {Elsevier}
}


@article{schroter2015,
  title = {What made the June 2013 flood in Germany an exceptional event? A
    hydro-meteorological evaluation},
  author = {Schr{\"o}ter, Kai and Kunz, Michael and Elmer, Florian and M{\"u}hr, Bernhard
    and Merz, Bruno},
  journal = {Hydrology and Earth System Sciences},
  volume = {19},
  number = {1},
  pages = {309--327},
  year = {2015},
  publisher = {Copernicus Publications G{\"o}ttingen, Germany}
}


@article{dai_snowfall_2008,
  title = {Temperature and pressure dependence of the rain-snow phase transition over land
    and ocean},
  volume = {35},
  copyright = {Copyright 2008 by the American Geophysical Union.},
  issn = {1944-8007},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2008GL033295},
  doi = {10.1029/2008GL033295},
  language = {en},
  number = {12},
  urldate = {2025-07-09},
  journal = {Geophysical Research Letters},
  author = {Dai, Aiguo},
  year = {2008},
  note = {\_eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2008GL033295},
  keywords = {precipitation, phase transition, snow frequency}
}


@article{buck_new_1981,
  title = {New {Equations} for {Computing} {Vapor} {Pressure} and {Enhancement} {Factor}},
  volume = {20},
  issn = {1520-0450},
  url = {    https://journals.ametsoc.org/view/journals/apme/20/12/1520-0450_1981_020_1527_nefcvp_2_0_co_2.xml},
  doi = {10.1175/1520-0450(1981)020<1527:NEFCVP>2.0.CO;2},
  language = {EN},
  number = {12},
  urldate = {2025-07-07},
  journal = {Journal of Applied Meteorology and Climatology},
  author = {Buck, Arden L.},
  month = {dec},
  year = {1981},
  note = {Publisher: American Meteorological Society Section: Journal of Applied
    Meteorology and Climatology},
  pages = {1527--1532}
}


@article{alduchov_improved_1996,
  title = {Improved {Magnus} {Form} {Approximation} of {Saturation} {Vapor} {Pressure}},
  volume = {35},
  issn = {1520-0450, 0894-8763},
  url = {    https://journals.ametsoc.org/view/journals/apme/35/4/1520-0450_1996_035_0601_imfaos_2_0_co_2.xml},
  doi = {10.1175/1520-0450(1996)035<0601:IMFAOS>2.0.CO;2},
  language = {EN},
  number = {4},
  urldate = {2025-07-07},
  journal = {Journal of Applied Meteorology and Climatology},
  author = {Alduchov, Oleg A. and Eskridge, Robert E.},
  month = {apr},
  year = {1996},
  note = {Publisher: American Meteorological Society Section: Journal of Applied
    Meteorology and Climatology},
  pages = {601--609}
}


@incollection{ecwmf_physical_2016,
  edition = {Cy43r1},
  title = {{PART} {IV}: {Physical} {Processes}},
  author = {ECMWF},
  language = {en},
  booktitle = {{IFS} {Documentation}},
  publisher = {ECMWF},
  year = {2016},
  url = {    https://www.ecmwf.int/sites/default/files/elibrary/2016/17117-part-iv-physical-processes.pdf}
}


@article{alonso_gonzalez_2022,
  title = {Combined influence of maximum accumulation and melt rates on the duration of the
    seasonal snowpack over temperate mountains},
  journal = {Journal of Hydrology},
  volume = {608},
  pages = {127574},
  year = {2022},
  issn = {0022-1694},
  doi = {https://doi.org/10.1016/j.jhydrol.2022.127574},
  url = {https://www.sciencedirect.com/science/article/pii/S0022169422001494},
  author = {Esteban Alonso-González and Jesús Revuelto and Steven R. Fassnacht and Juan
    {Ignacio López-Moreno}},
  abstract = {The duration of the seasonal snowpack determines numerous aspects of the
    water cycle, ecology and the economy in cold and mountainous regions, and is a balance
    between the magnitude of accumulated snow and the rate of melt. The contribution of
    each component has not been well quantified under contrasting topography and
    climatological conditions although this may provide useful insights into how snow cover
    duration could respond to climate change. Here, we examined the contribution of the
    annual peak snow water equivalent (SWE) and the seasonal melt rate to define the
    duration of the snowpack over temperate mountains, using snow data for mountain areas
    with different climatological characteristics across the Iberian Peninsula. We used a
    daily snowpack database for the period 1980--2014 over Iberia to derive the seasonal
    peak SWE, melt rate and season snow cover duration. The influence of peak SWE and melt
    rates on seasonal snow cover duration was estimated using a stepwise linear model
    approach. The stepwise linear models showed high R-adjusted values (average R-adjusted
    = 0.7), without any clear dependence on the elevation or geographical location. In
    general, the peak SWE influenced the snow cover duration over all of the mountain areas
    analysed to a greater extent than the melt rates (89.1\%, 89.2\%, 81.6\%, 93.2\% and
    95.5\% in the areas for the Cantabrian, Central, Iberian, Pyrenees and Sierra Nevada
    mountain ranges, respectively). At these colder sites, the melt season occurs mostly in
    the spring and tends to occur very fast. In contrast, the areas where the melt rates
    dominated snow cover duration were located systematically at lower elevations, due to
    the high interannual variability in the occurrence of annual peak SWE (in winter or
    early spring), yielding highly variable melt rates. However, in colder sites the melt
    season occurs mostly in spring and it is very fast in most of the years. The results
    highlight the control that the seasonal precipitation patterns, in combination with
    temperature, exert on the seasonal snow cover duration by influencing the peak SWE and
    suggest a future increased importance of melt rates as temperatures increase. Despite
    the high climatological variability of the Iberian mountain ranges, the results showed
    a consistent behaviour along the different mountain ranges, indicating that the methods
    and results may be transferrable to other temperate mountain areas of the world.}
}


@article{sauquet_2025,
  AUTHOR = {Sauquet, E. and Evin, G. and Siauve, S. and Aissat, R. and Arnaud, P. and
    B\'erel, M. and Bonneau, J. and Branger, F. and Caballero, Y. and Coll\'eoni, F. and
    Ducharne, A. and Gailhard, J. and Habets, F. and Hendrickx, F. and H\'eraut, L. and
    Hingray, B. and Huang, P. and Jaouen, T. and Jeantet, A. and Lanini, S. and Le Lay, M.
    and Magand, C. and Mimeau, L. and Monteil, C. and Munier, S. and Perrin, C. and
    Robelin, O. and Rousset, F. and Soubeyroux, J.-M. and Strohmenger, L. and Thirel, G.
    and Tocquer, F. and Tramblay, Y. and Vergnes, J.-P. and Vidal, J.-P.},
  TITLE = {A large transient multi-scenario multi-model ensemble of future streamflow and
    groundwater projections in France},
  JOURNAL = {EGUsphere},
  VOLUME = {2025},
  YEAR = {2025},
  PAGES = {1--41},
  URL = {https://egusphere.copernicus.org/preprints/2025/egusphere-2025-1788/},
  DOI = {10.5194/egusphere-2025-1788}
}


@article{burn_2010,
  author = {Burn, Donald H. and Sharif, Mohammed and Zhang, Kan},
  title = {Detection of trends in hydrological extremes for Canadian watersheds},
  journal = {Hydrological Processes},
  volume = {24},
  number = {13},
  pages = {1781-1790},
  keywords = {flood analysis, low flow events, climate change, trend analysis, Canada},
  doi = {https://doi.org/10.1002/hyp.7625},
  url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/hyp.7625},
  eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/hyp.7625},
  abstract = {Abstract The potential impacts of climate change can alter the risk to
    critical infrastructure resulting from changes to the frequency and magnitude of
    extreme events. As well, the natural environment is affected by the hydrologic regime,
    and changes in high flows or low flows can have negative impacts on ecosystems. This
    article examines the detection of trends in extreme hydrological events, both high and
    low flow events, for streamflow gauging stations in Canada. The trend analysis involves
    the application of the Mann–Kendall non-parametric test. A bootstrap resampling process
    has been used to determine the field significance of the trend results. A total of 68
    gauging stations having a nominal record length of at least 50 years are analysed for
    two analysis periods of 50 and 40 years. The database of Canadian rivers investigated
    represents a diversity of hydrological conditions encompassing different extreme flow
    generating processes and reflects a national scale analysis of trends. The results
    reveal more trends than would be expected to occur by chance for most of the measures
    of extreme flow characteristics. Annual and spring maximum flows show decreasing trends
    in flow magnitude and decreasing trends in event timing (earlier events). Low flow
    magnitudes exhibit both decreasing and increasing trends. Copyright © 2010 John Wiley
    \& Sons, Ltd.},
  year = {2010}
}


@article{zomer_2022,
  title = {Version 3 of the global aridity index and potential evapotranspiration database},
  author = {Zomer, Robert J and Xu, Jianchu and Trabucco, Antonio},
  journal = {Scientific Data},
  volume = {9},
  number = {1},
  pages = {409},
  year = {2022},
  publisher = {Nature Publishing Group UK London}
}


@article{knoben_2024,
  title = {Setting expectations for hydrologic model performance with an ensemble of simple
    benchmarks},
  author = {Knoben, Wouter JM},
  journal = {Hydrological Processes},
  volume = {38},
  number = {10},
  pages = {e15288},
  year = {2024},
  publisher = {Wiley Online Library}
}


@article{singh_2019,
  title = {Towards baseflow index characterisation at national scale in New Zealand},
  journal = {Journal of Hydrology},
  volume = {568},
  pages = {646-657},
  year = {2019},
  issn = {0022-1694},
  doi = {https://doi.org/10.1016/j.jhydrol.2018.11.025},
  url = {https://www.sciencedirect.com/science/article/pii/S0022169418308801},
  author = {Shailesh Kumar Singh and Markus Pahlow and Doug J. Booker and Ude Shankar and
    Alejandro Chamorro},
  keywords = {Baseflow, Quickflow, Prediction, BFI, Random forests technique},
  abstract = {Streamflow is typically divided into two components for hydrograph
    separation, quickflow and baseflow. Baseflow is the portion of streamflow that contains
    groundwater flow and flow from other delayed sources and is of key importance for river
    basin ecology and water resources planning and management. The BaseFlow Index (BFI) is
    defined as the ratio of long-term mean baseflow to total streamflow. Knowledge of the
    BFI is not directly available for ungauged catchments and hence for most of the
    terrestrial land surface. In this study, the BFI was determined for all river reaches
    in New Zealand. First a recursive digital filtering technique was applied to separate
    baseflow from total streamflow for 482 gauged sites across New Zealand, whereby an
    individual filter parameter was determined for each catchment. Based on the baseflow
    and total streamflow data the long-term BFI for each gauged site was determined, as
    well as seasonal values of BFI. BFI varies between 0.20 and 0.96 with an average of
    0.53, which indicates that 53% of long-term streamflow in New Zealand is likely to
    originate from groundwater discharge and other delayed sources. Long-term BFI values
    for all river reaches that comprise the New Zealand river network were predicted using
    the random forest technique. Furthermore, the winter to summer BFI for all river
    reaches in New Zealand were also determined. Distinct spatial patterns of the BFI were
    identified. While the spatial distribution and the magnitude of the BFI was determined
    by a combination of factors, certain patterns can be attributed to geological
    formations in New Zealand, namely the volcanic plateau region and the Southern Alps.
    While the dataset determined in this work can support work specifically pertaining to
    water resources planning and management in New Zealand, in particular water supply,
    stream ecology and pollution risk, the methodology devised to calculate the BFI for
    gauged sites and to predict the BFI for ungauged sites is applicable to any region
    around the world.}
}


@article{jaffres_2021,
  title = {Hydrological characteristics of Australia: relationship between surface flow,
    climate and intrinsic catchment properties},
  journal = {Journal of Hydrology},
  volume = {603},
  pages = {126911},
  year = {2021},
  issn = {0022-1694},
  doi = {https://doi.org/10.1016/j.jhydrol.2021.126911},
  url = {https://www.sciencedirect.com/science/article/pii/S0022169421009616},
  author = {Jasmine B.D. Jaffrés and Ben Cuff and Chris Cuff and Iain Faichney and Matthew
    Knott and Cecily Rasmussen},
  keywords = {Climate variability, Non-perennial streams, Surface hydrology, Topography,
    Soil field capacity, Water infiltration},
  abstract = {Streamflow and baseflow dynamics are driven by complex, interconnected
    catchment properties. A national study was conducted to assess the relationship between
    surface flow, climate and intrinsic catchment attributes in Australia. Subcatchments
    were delineated based on Horton's 5th stream order and were characterised by
    identifying parameters that influence streamflow and flood behaviour. Because
    observational datasets like rainfall and streamflow commonly have a non-normal
    distribution, the method of L-moments was applied to several time series. Surface
    hydrology and baseflow patterns were represented by twenty indices, which were
    statistically summarised via principal component (PC) analysis, yielding six PCs. Forty
    catchment descriptors from the themes of climate, topography, surface condition and
    hydrogeology were used to investigate their link with runoff patterns. Among these is
    the land surface value, a newly defined index incorporating soil properties and land
    use to estimate the capacity for water infiltration. All metrics were explored via
    correlation and regression analysis against the surface hydrology PCs and their
    influence on runoff discussed. The predictive skill of the regression models is
    improved when non-perennial waterways are excluded. Although rainfall characteristics
    dominate streamflow behaviour, topographical and surface conditions also greatly impact
    on runoff, especially during low-flow periods.}
}