周旺等:Estimating High Resolution Daily Air Temperature Based on Remote Sensing Products and Climate Reanalysis Datasets over Glacierized Basins: A Case Study in the Langtang Valley, Nepal
被阅读 527 次
2017-12-11
Estimating High Resolution Daily Air Temperature Based on Remote Sensing Products and Climate Reanalysis Datasets over Glacierized Basins: A Case Study in the Langtang Valley, Nepal 
作者:Zhou, W (Zhou, Wang)[ 1,2 ] ; Peng, B (Peng, Bin)[ 3,4 ] ; Shi, JC (Shi, Jiancheng)[ 1 ] ; Wang, TX (Wang, Tianxing)[ 1 ] ; Dhital, YP (Dhital, Yam Prasad)[ 5,6 ] ; Yao, RZ (Yao, Ruzhen)[ 1,2 ] ; Yu, YC (Yu, Yuechi)[ 1,2 ] ; Lei, ZT (Lei, Zhongteng)[ 1,7 ] ; Zhao, R (Zhao, Rui)[ 1,8 ]  
REMOTE SENSING 
卷: 9 
期: 9 
文献号: 959 
DOI: 10.3390/rs9090959 
出版年: SEP 2017 
 
摘要
Near surface air temperature (Ta) is one of the key input parameters in land surface models and hydrological models as it affects most biogeophysical and biogeochemical processes of the earth surface system. For distributed hydrological modeling over glacierized basins, obtaining high resolution Ta forcing is one of the major challenges. In this study, we proposed a new high resolution daily Ta estimation scheme under both clear and cloudy sky conditions through integrating the moderate-resolution imaging spectroradiometer (MODIS) land surface temperature (LST) and China Meteorological Administration (CMA) land data assimilation system (CLDAS) reanalyzed daily Ta. Spatio-temporal continuous MODIS LST was reconstructed through the data interpolating empirical orthogonal functions (DINEOF) method. Multi-variable regression models were developed at CLDAS scale and then used to estimate Ta at MODIS scale. The new Ta estimation scheme was tested over the Langtang Valley, Nepal as a demonstrating case study. Observations from two automatic weather stations at Kyanging and Yala located in the Langtang Valley from 2012 to 2014 were used to validate the accuracy of Ta estimation. The RMSEs are 2.05, 1.88, and 3.63 K, and the biases are 0.42, -0.68 and -2.86 K for daily maximum, mean and minimum Ta, respectively, at the Kyanging station. At the Yala station, the RMSE values are 4.53, 2.68 and 2.36 K, and biases are 4.03, 1.96 and -0.35 K for the estimated daily maximum, mean and minimum Ta, respectively. Moreover, the proposed scheme can produce reasonable spatial distribution pattern of Ta at the Langtang Valley. Our results show the proposed Ta estimation scheme is promising for integration with distributed hydrological model for glacier melting simulation over glacierized basins.
 
通讯作者地址: Shi, JC (通讯作者)
 Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China.
通讯作者地址: Peng, B (通讯作者)
 Univ Illinois, Natl Ctr Supercomp Applicat, Urbana, IL 61801 USA.
通讯作者地址: Peng, B (通讯作者)
 Univ Illinois, Dept Nat Resources & Environm Sci, Urbana, IL 61801 USA.
地址:  
 [ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
 [ 2 ] Univ Chinese Acad Sci, Beijing 100049, Peoples R China
 [ 3 ] Univ Illinois, Natl Ctr Supercomp Applicat, Urbana, IL 61801 USA
 [ 4 ] Univ Illinois, Dept Nat Resources & Environm Sci, Urbana, IL 61801 USA
 [ 5 ] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
 [ 6 ] Kathmandu Univ, Sch Sci, Dhulikhel 45200, Nepal 
 [ 7 ] Shandong Univ Sci & Technol, Coll Geomat, Qingdao 266000, Peoples R China
 [ 8 ] Jilin Univ, Coll Geoexplorat Sci & Technol, Changchun 130000, Jilin, Peoples R China