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Title: Potential Soil Moisture Products from the Aquarius Radiometer and Scatterometer Using an Observing System Simulation Experiment

Using an observing system simulation experiment (OSSE), we investigate the potential soil moisture retrieval capability of the National Aeronautics and Space Administration (NASA) Aquarius radiometer (L-band 1.413 GHz) and scatterometer (L-band, 1.260 GHz). We estimate potential errors in soil moisture retrievals and identify the sources that could cause those errors. The OSSE system includes (i) a land surface model in the NASA Land Information System, (ii) a radiative transfer and backscatter model, (iii) a realistic orbital sampling model, and (iv) an inverse soil moisture retrieval model. We execute the OSSE over a 1000 2200 km2 region in the central United States, including the Red and Arkansas river basins. Spatial distributions of soil moisture retrieved from the radiometer and scatterometer are close to the synthetic truth. High root mean square errors (RMSEs) of radiometer retrievals are found over the heavily vegetated regions, while large RMSEs of scatterometer retrievals are scattered over the entire domain. The temporal variations of soil moisture are realistically captured over a sparely vegetated region with correlations 0.98 and 0.63, and RMSEs 1.28% and 8.23% vol/vol for radiometer and scatterometer, respectively. Over the densely vegetated region, soil moisture exhibits larger temporal variation than the truth, leading to correlationmore » 0.70 and 0.67, respectively, and RMSEs 9.49% and 6.09% vol/vol respectively. The domain-averaged correlations and RMSEs suggest that radiometer is more accurate than scatterometer in retrieving soil moisture. The analysis also demonstrates that the accuracy of the retrieved soil moisture is affected by vegetation coverage and spatial aggregation.« less
Authors:
 [1] ;  [2] ;  [2] ;  [3] ;  [4] ;  [5] ;  [6] ;  [7]
  1. I.M. Systems Group at NOAA/NCEP/EMC
  2. George Mason University
  3. ORNL
  4. Western Kentucky University, Bowling Green
  5. Ghent University, Belgium
  6. NOAA/NESDIS Center for Satellite Applications and Research
  7. Mississippi State University (MSU)
Publication Date:
OSTI Identifier:
1157092
DOE Contract Number:
DE-AC05-00OR22725
Resource Type:
Journal Article
Resource Relation:
Journal Name: Geoscientific Instrumentation, Methods and Data Systems; Journal Volume: 2; Journal Issue: 1
Research Org:
Oak Ridge National Laboratory (ORNL); Oak Ridge Leadership Computing Facility (OLCF)
Sponsoring Org:
SC USDOE - Office of Science (SC)
Country of Publication:
United States
Language:
English
Subject:
satellite remote sensing; soil moisture retrieval; land surface hydrology; climate; observing systems simulation experiment