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JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 112, D09108, doi:10.1029/2006JD008033, 2007

Comparison and assimilation of global soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) and the Scanning Multichannel Microwave Radiometer (SMMR)

Rolf H. Reichle

Goddard Earth Sciences and Technology Center, University of Maryland Baltimore County, Baltimore, Maryland, USA
Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA


Randal D. Koster

Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA


Ping Liu

Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
Science Applications International Corporation, Beltsville, Maryland, USA.


Sarith P. P. Mahanama

Goddard Earth Sciences and Technology Center, University of Maryland Baltimore County, Baltimore, Maryland, USA
Global Modeling and Assimilation Office, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA


Eni G. Njoku

Jet Propulsion Laboratory, Pasadena, California, USA


Manfred Owe

Hydrological Sciences Branch, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA


Abstract

Two data sets of satellite surface soil moisture retrievals are first compared and then assimilated into the NASA Catchment land surface model. The first satellite data set is derived from 4 years of X-band (10.7 GHz) passive microwave brightness temperature observations by the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), and the second is from 9 years of C-band (6.6 GHz) brightness temperature observations by the Scanning Multichannel Microwave Radiometer (SMMR). Despite the similarity in the satellite instruments, the retrieved soil moisture data exhibit very large differences in their multiyear means and temporal variability, primarily because they are computed with different retrieval algorithms. The satellite retrievals are also compared to a soil moisture product generated by the NASA Catchment land surface model when driven with surface meteorological data derived from observations. The climatologies of both satellite data sets are different from those of the model products. Prior to assimilation of the satellite retrievals into the land model, satellite-model biases are removed by scaling the satellite retrievals into the land model's climatology through matching of the respective cumulative distribution functions. Validation against in situ data shows that for both data sets the soil moisture fields from the assimilation are superior to either satellite data or model data alone. A global analysis of the innovations (defined as the difference between the observations and the corresponding model values prior to the assimilation update) reveals how changes in model and observations error parameters may enhance filter performance in future experiments.

Received 18 September 2006; accepted 13 December 2006; published 8 May 2007.

Keywords: soil moisture; data assimilation; retrievals.

Index Terms: 3315 Atmospheric Processes: Data assimilation; 1866 Hydrology: Soil moisture; 1855 Hydrology: Remote sensing (1640); 1843 Hydrology: Land/atmosphere interactions (1218, 1631, 3322); 1833 Hydrology: Hydroclimatology.

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Citation: Reichle, R. H., R. D. Koster, P. Liu, S. P. P. Mahanama, E. G. Njoku, and M. Owe (2007), Comparison and assimilation of global soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) and the Scanning Multichannel Microwave Radiometer (SMMR), J. Geophys. Res., 112, D09108, doi:10.1029/2006JD008033.