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タイトルIdentifying and Addressing Land Surface Model Deficiencies with Data Assimilation
本文(外部サイト)http://hdl.handle.net/2060/20120016794
著者(英)Zaitchik, Ben; Reichle, Rolf; Kumar, Sujay; Rodell, Matthew; Houborg, Rasmus; Li, Bailing; Beaudoing, Hiroko Kato
著者所属(英)NASA Goddard Space Flight Center
発行日2012-07-10
言語eng
内容記述Land surface models (LSMs) encapsulate our understanding of terrestrial water and energy cycle physics and provide estimates of land surface states and fluxes when and where measurement gaps exist. Gaps in our understanding of the physics are a different issue. Data assimilation can address that issue both directly, through updating of prognostic model variables, or indirectly, when the simulated world conflicts with observation, necessitating adjustment of the model. Here we will focus on the latter case and present several examples, including (1) depth to bedrock adjustment to accommodate assimilated GRACE terrestrial water storage data; (2) steps to prevent immediate melting of assimilated snow cover; (3) irrigation's contribution to evapotranspiration; (4) lessons learned from soil moisture data assimilation; (5) the potential impact of satellite based runoff observation
NASA分類Earth Resources and Remote Sensing
レポートNOGSFC.ABS.6713.2012
権利Copyright, Distribution as joint owner in the copyright


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