Improving estimated soil moisture fields through assimilation of AMSR-E soil moisture retrievals with an ensemble Kalman filter and a mass conservation constraint

Hydrology and Earth System Sciences

Volumn 16, Issue 1, 2012, Pages 105-119

  Li, B ^a,b   Toll, D ^b   Zhan, X ^c   Cosgrove, B ^d  

^a UNIVERSITY OF MARYLAND   (United States)

^b NASA GODDARD SPACE FLIGHT CENTER   (United States)

^c OFFICE OF RESEARCH AND APPLICATIONS   (United States)

^d NOAA EARTH SYSTEM RESEARCH LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADVANCED MICROWAVE SCANNING RADIOMETER; ASSIMILATION ALGORITHMS; DATA ASSIMILATION TECHNIQUES; ENSEMBLE KALMAN FILTER; GOVERNING EQUATIONS; INPUT PARAMETER; LAND SURFACE MODELS; MASS BALANCE; MASS CONSERVATION; MODEL ESTIMATES; MODEL PHYSICS; MOISTURE FIELD; NEAR-SURFACE; OKLAHOMA; PRE-PROCESSING; ROOT ZONE; SOIL LAYER; SOIL MOISTURE RETRIEVALS; SURFACE OBSERVATION; WATER BUDGET;

COMPUTER SIMULATION; DATA PROCESSING; ESTIMATION; KALMAN FILTERS; MICROWAVE FILTERS; SOIL MOISTURE;

GEOLOGIC MODELS;

AMSR-E; DATA ASSIMILATION; ERROR ANALYSIS; KALMAN FILTER; MOISTURE CONTENT; RHIZOSPHERE; SOIL MOISTURE; SOIL PROFILE; WATER BUDGET;

LITTLE WASHITA BASIN; OKLAHOMA [UNITED STATES]; UNITED STATES;

EID: 84862908327     PISSN: 10275606     EISSN: 16077938     Source Type: Journal    
DOI: 10.5194/hess-16-105-2012     Document Type: Article

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