Daily snow water equivalent product with SMMR, SSM/I and SSMIS from 1980 to 2020 over China

被引:26
作者
Jiang, Lingmei [1 ,2 ]
Yang, Jianwei [1 ,2 ]
Zhang, Cheng [1 ,2 ]
Wu, Shengli [3 ]
Li, Zhen [4 ]
Dai, Liyun [5 ]
Li, Xiaofeng [6 ]
Qiu, Yubao [4 ]
机构
[1] Beijing Normal Univ, State Key Lab Remote Sensing Sci, Beijing, Peoples R China
[2] Beijing Normal Univ, Aerosp Informat Res Inst, Chinese Acad Sci, Fac Geog Sci,State Key Lab Remote Sensing Sci, Beijing, Peoples R China
[3] China Meteorol Adm, Natl Satellite Meteorol Ctr, Beijing, Peoples R China
[4] Chinese Acad Sci, Aerosp Informat Res Inst, Key Lab Digital Earth Sci, Beijing, Peoples R China
[5] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Key Lab Remote Sensing Gansu Prov, Heihe Remote Sensing Expt Res Stn, Lanzhou, Peoples R China
[6] Chinese Acad Sci, Northeast Inst Geog & Agroecol, Changchun, Peoples R China
基金
中国国家自然科学基金;
关键词
Snow water equivalent; daily; 1980-2020; passive microwave remote sensing; China; REMOTE-SENSING DATA; ALGORITHM; MASS;
D O I
10.1080/20964471.2022.2032998
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The reliable knowledge of seasonal snow volume and its trend is very important to understand Earth's climate system. Thus, a long-time snow water equivalent (SWE) dataset is necessary. This work presents a daily SWE product of 1980-2020 with a linear unmixing method through passive microwave data including SMMR, SSM/I and SSMIS over China after cross-calibration and bias-correction. The unbiased root-mean-square error of snow depth is about 5-7 cm, corresponding to 10-15 mm for SWE, when compared with stations measurements and field snow course data. The spatial patterns and trends of SWE over China present significant regional differences. The overall slope trend presented an insignificant decreasing pattern during 1980-2020 over China; however, there is an obvious fluctuation, i.e. a significant decrease trend during the period 1980-1990, an upward trend from 2005 to 2009, a significant downward trend from 2009 to 2018. The increase of SWE occurred in the Northeast Plain, with an increase trend of 0.2 mm per year. Whereas in the Hengduan Mountains, it presented a downward trend of SWE, up to -0.3 mm per year. In the North Xinjiang, SWE has an increasing trend in the Junggar Basin, while it shows a decreasing trend in the Tianshan and Altai Mountains.
引用
收藏
页码:420 / 434
页数:15
相关论文
共 32 条
[1]   Estimating snow-cover trends from space [J].
Bormann, Kat J. ;
Brown, Ross D. ;
Derksen, Chris ;
Painter, Thomas H. .
NATURE CLIMATE CHANGE, 2018, 8 (11) :923-927
[2]  
Chang AT C., 1987, ANN GLACIOL, V9, P39, DOI DOI 10.3189/S0260305500200736
[3]  
[车涛 Che Tao], 2019, [中国科学院院刊, Bulletin of the Chinese Academy of Sciences], V34, P1247
[4]   Snow depth derived from passive microwave remote-sensing data in China [J].
Che, Tao ;
Li, Xin ;
Jin, Rui ;
Armstrong, Richard ;
Zhang, Tingjun .
ANNALS OF GLACIOLOGY, VOL 49, 2008, 2008, 49 :145-+
[5]   Inter-Calibrating SMMR, SSM/I and SSMI/S Data to Improve the Consistency of Snow-Depth Products in China [J].
Dai, Liyun ;
Che, Tao ;
Ding, Yongjian .
REMOTE SENSING, 2015, 7 (06) :7212-7230
[6]   Evaluation of passive microwave snow water equivalent retrievals across the boreal forest/tundra transition of western Canada [J].
Derksen, C ;
Walker, A ;
Goodison, B .
REMOTE SENSING OF ENVIRONMENT, 2005, 96 (3-4) :315-327
[7]   Comparison of snow mass estimates from prototype passive microwave snow algorithm, a revised algorithm and a snow depth climatology [J].
Foster, JL ;
Chang, ATC ;
Hall, DK .
REMOTE SENSING OF ENVIRONMENT, 1997, 62 (02) :132-142
[8]   Spatiotemporal dynamics of snow cover based on multi-source remote sensing data in China [J].
Huang, Xiaodong ;
Deng, Jie ;
Ma, Xiaofang ;
Wang, Yunlong ;
Feng, Qisheng ;
Hao, Xiaohua ;
Liang, Tiangang .
CRYOSPHERE, 2016, 10 (05) :2453-2463
[9]   Improvement of snow depth retrieval for FY3B-MWRI in China [J].
Jiang LingMei ;
Wang Pei ;
Zhang LiXin ;
Yang Hu ;
Yang JunTao .
SCIENCE CHINA-EARTH SCIENCES, 2014, 57 (06) :1278-1292
[10]  
Kelly R.E. J., 2009, J. Remote Sens. Soc. Japan, V29, P307, DOI [DOI 10.11440/RSSJ.29.307, 10.11440/rssj.29.307]