Data assimilation methods in the Earth sciences

被引:394
作者
Reichle, Rolf H. [1 ,2 ]
机构
[1] NASA, Goddard Space Flight Ctr, Global Modeling & Assimilat Off, Greenbelt, MD 20771 USA
[2] Univ Maryland, Goddard Earth Sci & Technol Ctr, Baltimore, MD 21201 USA
关键词
Data assimilation; Remote sensing; Land surface hydrology; Variational methods; Kalman filter;
D O I
10.1016/j.advwatres.2008.01.001
中图分类号
TV21 [水资源调查与水利规划];
学科分类号
081501 ;
摘要
Although remote sensing data are often plentiful, they do not usually satisfy the users' needs directly. Data assimilation is required to extract information about geophysical fields of interest from the remote sensing observations and to make the data more accessible to users. Remote sensing may provide, for example, measurements of surface soil moisture, snow water equivalent, snow cover, or land surface (skin) temperature. Data assimilation can then be used to estimate variables that are not directly observed from space but are needed for applications, for instance root zone soil moisture or land surface fluxes. The paper provides a brief introduction to modern data assimilation methods in the Earth sciences, their applications, and pertinent research questions. Our general overview is readily accessible to hydrologic remote sensing scientists. Within the general context of Earth science data assimilation, we point to examples of the assimilation of remotely sensed observations in land surface hydrology. (C) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1411 / 1418
页数:8
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