Statistical downscaling of hourly and daily climate scenarios for various meteorological variables in South-central Canada

被引:0
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作者
C. S. Cheng
G. Li
Q. Li
H. Auld
机构
[1] Meteorological Service of Canada (MSC) Branch-Ontario,Adaptation and Impacts Research Division
[2] Environment Canada,undefined
[3] MSC Branch,undefined
[4] Environment Canada,undefined
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关键词
Weather Variable; Statistical Downscaling; Total Cloud Cover; Weather Element; Compare Data Distribution;
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摘要
A regression-based methodology was used to downscale hourly and daily station-scale meteorological variables from outputs of large-scale general circulation models (GCMs). Meteorological variables include air temperature, dew point, and west–east and south–north wind velocities at the surface and three upper atmospheric levels (925, 850, and 500 hPa), as well as mean sea-level air pressure and total cloud cover. Different regression methods were used to construct downscaling transfer functions for different weather variables. Multiple stepwise regression analysis was used for all weather variables, except total cloud cover. Cumulative logit regression was employed for analysis of cloud cover, since cloud cover is an ordered categorical data format. For both regression procedures, to avoid multicollinearity between explanatory variables, principal components analysis was used to convert inter-correlated weather variables into uncorrelated principal components that were used as predictors. The results demonstrated that the downscaling method was able to capture the relationship between the premises and the response; for example, most hourly downscaling transfer functions could explain over 95% of the total variance for several variables (e.g. surface air temperature, dew point, and air pressure). Downscaling transfer functions were validated using a cross-validation scheme, and it was concluded that the functions for all weather variables used in the study are reliable. Performance of the downscaling method was also evaluated by comparing data distributions and extreme weather characteristics of downscaled GCM historical runs and observations during the period 1961–2000. The results showed that data distributions of downscaled GCM historical runs for all weather variables are significantly similar to those of observations. In addition, extreme characteristics of the downscaled meteorological variables (e.g. temperature, dew point, air pressure, and total cloud cover) were examined.
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页码:129 / 147
页数:18
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  • [1] Statistical downscaling of hourly and daily climate scenarios for various meteorological variables in South-central Canada
    Cheng, C. S.
    Li, G.
    Li, Q.
    Auld, H.
    [J]. THEORETICAL AND APPLIED CLIMATOLOGY, 2008, 91 (1-4) : 129 - 147
  • [2] Nonparametric statistical temporal downscaling of daily precipitation to hourly precipitation and implications for climate change scenarios
    Lee, Taesam
    Jeong, Changsam
    [J]. JOURNAL OF HYDROLOGY, 2014, 510 : 182 - 196
  • [3] Simulating streamflow response to climate scenarios in central Canada using a simple statistical downscaling method
    Choi, Woonsup
    Rasmussen, Peter F.
    Moore, Adam R.
    Kim, Sung Joon
    [J]. CLIMATE RESEARCH, 2009, 40 (01) : 89 - 102
  • [4] Statistical downscaling of daily climate variables for climate change impact assessment over New South Wales, Australia
    De Li Liu
    Heping Zuo
    [J]. Climatic Change, 2012, 115 : 629 - 666
  • [5] Sub-daily Statistical Downscaling of Meteorological Variables Using Neural Networks
    Kumar, Jitendra
    Brooks, Bjorn-Gustaf J.
    Thornton, Peter E.
    Dietze, Michael C.
    [J]. PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE, ICCS 2012, 2012, 9 : 887 - 896
  • [6] Statistical downscaling of daily climate variables for climate change impact assessment over New South Wales, Australia
    Liu, De Li
    Zuo, Heping
    [J]. CLIMATIC CHANGE, 2012, 115 (3-4) : 629 - 666
  • [7] An asynchronous regional regression model for statistical downscaling of daily climate variables
    Stoner, Anne M. K.
    Hayhoe, Katharine
    Yang, Xiaohui
    Wuebbles, Donald J.
    [J]. INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2013, 33 (11) : 2473 - 2494
  • [8] Possible impacts of climate change on freezing rain in south-central Canada using downscaled future climate scenarios
    Cheng, C. S.
    Auld, H.
    Li, G.
    Klaassen, J.
    Li, Q.
    [J]. NATURAL HAZARDS AND EARTH SYSTEM SCIENCES, 2007, 7 (01) : 71 - 87
  • [9] Statistical downscaling of temperatures under climate change scenarios for Thames river basin, Canada
    Goyal, Manish Kumar
    Burn, Donald H.
    Ojha, C. S. P.
    [J]. INTERNATIONAL JOURNAL OF GLOBAL WARMING, 2012, 4 (01) : 13 - 30
  • [10] Spatial downscaling of climate variables using three statistical methods in Central Iran
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    Mostafa Tarkesh
    Mehdi Bassiri
    [J]. Journal of Mountain Science, 2018, 15 : 606 - 617