DOI: 10.5194/hess-19-4831-2015
Scopus记录号: 2-s2.0-84951740141
论文题名: The impact of near-surface soil moisture assimilation at subseasonal, seasonal, and inter-annual timescales
作者: Draper C ; , Reichle R
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2015
卷: 19, 期: 12 起始页码: 4831
结束页码: 4844
语种: 英语
Scopus关键词: Catchments
; Errors
; Mean square error
; Moisture
; Runoff
; Soil moisture
; Soils
; Systematic errors
; Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E)
; Data assimilation
; In-situ observations
; Land surface modeling
; Model representation
; Root zone soil moistures
; Soil moisture dynamics
; Soil moisture retrievals
; Soil surveys
; AMSR-E
; catchment
; data assimilation
; drought stress
; EOS
; in situ measurement
; land surface
; rhizosphere
; seasonal variation
; soil moisture
; timescale
; watershed
; United States
英文摘要: A 9 year record of Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) soil moisture retrievals are assimilated into the Catchment land surface model at four locations in the US. The assimilation is evaluated using the unbiased mean square error (ubMSE) relative to watershed-scale in situ observations, with the ubMSE separated into contributions from the subseasonal (SMshort), mean seasonal (SMseas), and inter-annual (SMlong) soil moisture dynamics. For near-surface soil moisture, the average ubMSE for Catchment without assimilation was (1.8 × 10-3 m3 m-3)2, of which 19 % was in SMlong, 26 % in SMseas, and 55 % in SMshort. The AMSR-E assimilation significantly reduced the total ubMSE at every site, with an average reduction of 33 %. Of this ubMSE reduction, 37 % occurred in SMlong, 24 % in SMseas, and 38 % in SMshort. For root-zone soil moisture, in situ observations were available at one site only, and the near-surface and root-zone results were very similar at this site. These results suggest that, in addition to the well-reported improvements in SMshort, assimilating a sufficiently long soil moisture data record can also improve the model representation of important long-term events, such as droughts. The improved agreement between the modeled and in situ SMseas is harder to interpret, given that mean seasonal cycle errors are systematic, and systematic errors are not typically targeted by (bias-blind) data assimilation. Finally, the use of 1-year subsets of the AMSR-E and Catchment soil moisture for estimating the observation-bias correction (rescaling) parameters is investigated. It is concluded that when only 1 year of data are available, the associated uncertainty in the rescaling parameters should not greatly reduce the average benefit gained from data assimilation, although locally and in extreme years there is a risk of increased errors. © Author(s) 2015. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78366
Appears in Collections: 气候变化事实与影响
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作者单位: NASA GSFC, Global Modeling and Assimilation Office, Greenbelt, MD, United States; Universities Space Research Association, Columbia, MD, United States
Recommended Citation:
Draper C,, Reichle R. The impact of near-surface soil moisture assimilation at subseasonal, seasonal, and inter-annual timescales[J]. Hydrology and Earth System Sciences,2015-01-01,19(12)