胡光成等:Comparison of MOD16 and LSA-SAF MSG evapotranspiration products over Europe for 2011
被阅读 1705 次
2015-03-06
Comparison of MOD16 and LSA-SAF MSG evapotranspiration products over Europe for 2011
作者:Hu, GC (Hu, Guangcheng)[ 1 ] ; Jia, L (Jia, Li)[ 1 ] ; Menenti, M (Menenti, Massimo)[ 2 ]
REMOTE SENSING OF ENVIRONMENT
卷: 156  页: 510-526
DOI: 10.1016/j.rse.2014.10.017
出版年: JAN 2015
 
摘要
Terrestrial actual evapotranspiration (ETa) is an important component of the terrestrial water cycle. Currently there are two operational ETa products using moderate spatial resolution remote sensing data at continental and global scales, i.e. MOD16 and LSA-SAF MSG ETa These two products are based on different parameterizations and forcing data, with the spatial and temporal resolutions of 1-km/8-day and 5-km/daily for MOD16 and LSA-SAF MSG ETa respectively. We compared the MOD16 ETa and LSA-SAF MSG ETa products and evaluated them against in-situ measurements at 15 ground sites with biome types ranging from croplands, grasslands, shrublands, savannas, to forests over Europe for 2011. The intercomparison results at local scale demonstrate that LSA-SAF MSG ETa is closer to eddy covariance (EC) measurements than MOD16 ETa product, with larger correlation coefficient Rest-obs, smaller root mean square error RMSEest-obs and bias of LSA-SAF MSG vs. EC at most of the 15 flux sites. Spatial distributions of the RMOD16-MSG and RMSEMOD16-MSG between MOD16 and LSA-SAF MSG ETa for 2011 show that both ETa data products are consistent over most of Europe, except for some semi-arid regions where the water availability is the main limiting factor of land surface evapotranspiration. LSA-SAF MSG ETa is shown to have a more adequate response to the forest fire. Our study contributes to assess the quality and uncertainty of each product, which can be beneficial for improving ETa algorithm and product quality. (C) 2014 Elsevier Inc. All rights reserved.
 
通讯作者地址: Jia, L (通讯作者)
Inst Remote Sensing & Digital Earth, CAS Olympic Pk,20 Da Tun Rd,POBox 9718, Beijing 100101, Peoples R China.
地址:
[ 1 ] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China
[ 2 ] Delft Univ Technol, Delft, Netherlands