TY - JOUR
T1 - Tackling resolution mismatch of precipitation extremes from gridded GCMs and site-scale observations
T2 - Implication to assessment and future projection
AU - LI, Jianfeng
AU - Gan, Thian Yew
AU - Chen, Yongqin David
AU - Gu, Xihui
AU - Hu, Zengyun
AU - Zhou, Qiming
AU - Lai, Yangchen
N1 - Funding Information:
This work was substantially supported by research grants from the Research Grants Council of the Hong Kong Special Administrative Region , China (No. HKBU12303517 , No. HKBU12302518 , and No. CUHK441313 ). Observed daily precipitation and temperature are available at the National Meteorological Information Center for the China Meteorological Administration at http://www.cma.gov.cn/2011qxfw/2011qsjgx/ . We acknowledge the World Climate Research Programme's Working Group on Coupled Modeling which is responsible for CMIP5. We thank the climate modeling groups for developing and making their CMIP5 GCM outputs available. Detailed information of the data can be obtained by contacting to the corresponding author at [email protected]
Funding Information:
This work was substantially supported by research grants from the Research Grants Council of the Hong Kong Special Administrative Region, China (No. HKBU12303517, No. HKBU12302518, and No. CUHK441313). Observed daily precipitation and temperature are available at the National Meteorological Information Center for the China Meteorological Administration at http://www.cma.gov.cn/2011qxfw/2011qsjgx/. We acknowledge the World Climate Research Programme's Working Group on Coupled Modeling which is responsible for CMIP5. We thank the climate modeling groups for developing and making their CMIP5 GCM outputs available. Detailed information of the data can be obtained by contacting to the corresponding author at [email protected]
PY - 2020/7/15
Y1 - 2020/7/15
N2 - The resolution mismatch between GCMs and in-situ gauge observations is an issue that has to be addressed for assessments and projections of precipitation extremes. The impacts of using different strategies to address this issue on GCM assessments and projections are evaluated in this study. The differences of precipitation extremes derived from GCMs at the original gridded resolutions and site-scale observations can be mostly explained by resolution mismatch. As the spatial and temporal “discontinuous” nature of precipitation, consecutive dry days (precipitation intensity) estimated from GCM data over a grid are likely to be shorter (smaller) than in-situ observations. By interpolating GCMs and observations to a common resolution, areal differences are moderately reduced, but spatial correlations between GCMs and observations may not be necessarily improved. By statistically downscaling the GCM-derived precipitation extremes, the indices agree better with the in-situ observations substantially. Using interpolation or downscaling to resolve resolution mismatch in GCMs may result in contradictory projected changes in extremes. Downscaled precipitation extremes generally change in greater magnitude than interpolated extremes in the projections.
AB - The resolution mismatch between GCMs and in-situ gauge observations is an issue that has to be addressed for assessments and projections of precipitation extremes. The impacts of using different strategies to address this issue on GCM assessments and projections are evaluated in this study. The differences of precipitation extremes derived from GCMs at the original gridded resolutions and site-scale observations can be mostly explained by resolution mismatch. As the spatial and temporal “discontinuous” nature of precipitation, consecutive dry days (precipitation intensity) estimated from GCM data over a grid are likely to be shorter (smaller) than in-situ observations. By interpolating GCMs and observations to a common resolution, areal differences are moderately reduced, but spatial correlations between GCMs and observations may not be necessarily improved. By statistically downscaling the GCM-derived precipitation extremes, the indices agree better with the in-situ observations substantially. Using interpolation or downscaling to resolve resolution mismatch in GCMs may result in contradictory projected changes in extremes. Downscaled precipitation extremes generally change in greater magnitude than interpolated extremes in the projections.
UR - http://www.scopus.com/inward/record.url?scp=85079608553&partnerID=8YFLogxK
U2 - 10.1016/j.atmosres.2020.104908
DO - 10.1016/j.atmosres.2020.104908
M3 - Journal article
AN - SCOPUS:85079608553
SN - 0169-8095
VL - 239
JO - Atmospheric Research
JF - Atmospheric Research
M1 - 104908
ER -