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Benefit of Modeling the Observation Error in a Data Assimilation Framework Using Vegetation Information Obtained From Passive Based Microwave DataA primary operational goal of the United States Department of Agriculture (USDA) is to improve foreign market access for U.S. agricultural products. A large fraction of this crop condition assessment is based on satellite imagery and ground data analysis. The baseline soil moisture estimates that are currently used for this analysis are based on output from the modified Palmer two-layer soil moisture model, updated to assimilate near-real time observations derived from the Soil Moisture Ocean Salinity (SMOS) satellite. The current data assimilation system is based on a 1-D Ensemble Kalman Filter approach, where the observation error is modeled as a function of vegetation density. This allows for offsetting errors in the soil moisture retrievals. The observation error is currently adjusted using Normalized Difference Vegetation Index (NDVI) climatology. In this paper we explore the possibility of utilizing microwave-based vegetation optical depth instead.
Document ID
20170007837
Acquisition Source
Goddard Space Flight Center
Document Type
Conference Paper
Authors
Bolten, John D.
(NASA Goddard Space Flight Center Greenbelt, MD United States)
Mladenova, Iliana E.
(Maryland Univ. College Park, MD, United States)
Crow, Wade
(Department of Agriculture Beltsville, MD, United States)
De Jeu, Richard
(Transmissivity B.V. Noordwijk, Netherlands)
Date Acquired
August 18, 2017
Publication Date
November 3, 2016
Publication Information
Publication: IEEEXplore
Publisher: IEEE
e-ISSN: 2153-7003
Subject Category
Earth Resources And Remote Sensing
Meteorology And Climatology
Report/Patent Number
GSFC-E-DAA-TN45519
Meeting Information
Meeting: IEEE International Geoscience and Remote Sensing Symposium (IGARSS) 2016
Location: Beijing
Country: China
Start Date: July 10, 2016
End Date: July 15, 2016
Sponsors: Institute of Electrical and Electronics Engineers
Funding Number(s)
CONTRACT_GRANT: NNX17AE79A
Distribution Limits
Public
Copyright
Other
Keywords
Vegetation
microwave
remote sensing

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