Satellite estimates and subpixel variability of rainfall in a semi-arid grassland |
| |
| Authors: | Yong Chen Jing Duan Junling An Huizhi Liu Ulrich G?rsdorf Franz H.Berger |
| |
| Affiliation: | 1. State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China;2. State Key Laboratory of Severe Weather & Key Laboratory for Cloud Physics of China Meteorological Administration, Chinese Academy of Meteorological Sciences, Beijing, China;3. Meteorologisches Observatorium Lindenberg/Richard Aβmann Observatory, Deutscher Wetterdienst, Lindenberg, Germany |
| |
| Abstract: | ![]()
Uncertainties in satellite rainfall estimation may derive from both the local rainfall characteristics and its subpixel variability.To study this issue,Micro Rain Radars and a rain gauge network were deployed within a 9-km satel-lite pixel in the semi-arid Xilingol grassland of China in summer 2009.The authors characterized the subpixel variability with the coefficient of variation(CV)and evaluated the satellite rainfall estimation for this semi-arid area.The results showed that rainfall events with a high CV were mostly convective with a small amount of rain-fall.Spatially inhomogeneous rainfall was most likely to occur at the edges of small clouds producing rain.The performance of the TRMM(Tropical Rainfall Measuring Mission)3B42V7 product for daily rainfall was better than that of the CMORPH(Climate Prediction Center morphing technique)and PERSIANN(Precipitation Estima-tion from Remotely Sensed Information Using Artificial Neural Networks)products,although the TRMM product tended to overestimate rainfall in a lake area of the semi-arid grassland. |
| |
| Keywords: | Satellite rainfall estimation Rainfall variability Micro Rain Radar TRMM |
| 本文献已被 万方数据 ScienceDirect 等数据库收录！ |
|
