Paper Info
Title
Development of a Snow Depth Estimation Algorithm over China for the FY-3D/MWRI.
Abstract
Launched on 15 November 2017, China's FengYun-3D (FY-3D) has taken over prime operational weather service from the aging FengYun-3B (FY-3B). Rather than directly implementing an FY-3B operational snow depth retrieval algorithm on FY-3D, we investigated this and four other well-known snow depth algorithms with respect to regional uncertainties in China. Applicable to various passive microwave sensors, these four snow depth algorithms are the Environmental and Ecological Science Data Centre of Western China (WESTDC) algorithm, the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) algorithm, the Chang algorithm, and the Foster algorithm. Among these algorithms, validation results indicate that FY-3B and WESTDC perform better than the others. However, these two algorithms often result in considerable underestimation for deep snowpack (greater than 20 cm), while the other three persistently overestimate snow depth, probably because of their poor representation of snowpack characteristics in China. To overcome the retrieval errors that occur under deep snowpack conditions without sacrificing performance under relatively thin snowpack conditions, we developed an empirical snow depth retrieval algorithm suite for the FY-3D satellite. Independent evaluation using weather station observations in 2014 and 2015 demonstrates that the FY-3D snow depth algorithm's root mean square error (RMSE) and bias are 6.6 cm and 0.2 cm, respectively, and it has advantages over other similar algorithms.
Year
DOI
Venue
2019
10.3390/rs11080977
REMOTE SENSING
Keywords
Field
DocType
snow depth,FY-3D,MWRI,regional algorithms,China
Remote sensing,China,Geology,Snow
Journal
Volume
Issue
ISSN
11
8
2072-4292
Citations 
PageRank 
References 
0
0.34
0
Authors
6
Name
Order
Citations
PageRank
Jianwei Yang15812.73
Lingmei Jiang210834.89
Shengli Wu3219.34
Gongxue Wang402.37
Jian Wang517973.08
Xiaojing Liu652.77