首页|Comparison of Snowfall Variations over China Identified from Different Snowfall/Rainfall Discrimination Methods
Comparison of Snowfall Variations over China Identified from Different Snowfall/Rainfall Discrimination Methods
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国家科技期刊平台
NETL
NSTL
万方数据
维普
Based on the snowfall observations at 836 surface weather stations in China and the Daily Surface Climate Vari-ables of China version 3.0 dataset for 1961–2013, capability of five methods with different objective criteria for identifying wintertime snowfall is evaluated, to provide reference for application of these methods in snowfall/rain-fall discrimination. Methods I,Ⅱ,Ⅲ, IV, and V use the daily average surface air temperature (Ta), wet-bulb temperat-ure (Tw), dynamic threshold Tw, 0-cm ground temperature, and 700–850-hPa thickness, respectively, to identify the snowfall. The results show that the climatological distribution of snowfall can be well produced by Methods I,Ⅱ, and Ⅲ. Method IV underestimates the snowfall days in eastern Tibetan Plateau (ETP), and Method V cannot yield the ac-tual large numbers of snowfall days and amounts. Accordingly, the linear trends of snowfall days estimated from Methods I,Ⅱ, and Ⅲ largely agree with the observations, while a discrepancy is found in the linear trend of snowfall amounts over southeastern China (SEC). For interannual and decadal variations of snowfall, Method V shows the worst performance. It is more reasonable to use Tw to distinguish snowfall from rainfall instead of Ta, 0-cm ground temperature, and 700–850-hPa thickness; and the reference thresholds of Tw in northeastern China (NEC), northwest-ern China (NWC), ETP, and SEC are −1.5, −1.5, −0.4, and −0.3℃, respectively. The above results are beneficial to identifying snowfall in short-term climate prediction.
snowfall/rainfall discrimination methodwintertime snowfallwet-bulb temperature (Tw)thresholdcomparison
Jiangshan LUO、Haishan CHEN、Botao ZHOU
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Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environmental Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters,Nanjing University of Information Science &Technology, Nanjing 210044
School of Atmospheric Sciences, Nanjing University of Information Science &Technology, Nanjing 210044
Supported by the National Key Research and Development Program of Chinaand National Natural Science Foundation of China
国家科技期刊平台
NSTL
万方数据
维普
