Journal
GEOPHYSICAL RESEARCH LETTERS
Volume 41, Issue 20, Pages 7159-7166Publisher
AMER GEOPHYSICAL UNION
DOI: 10.1002/2014GL060659
Keywords
SMOPS soil moisture product; quality control; data assimilation; green vegetation fraction
Categories
Funding
- NOAA JPSS Proving Ground and Risk Reduction Program
- Graduate Education Innovation Project in Jiangsu Province [CXZZ12_0499]
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A global Soil Moisture Operational Product System (SMOPS) has been developed to process satellite soil moisture observational data at the NOAA National Environmental Satellite, Data, and Information Service for improving numerical weather prediction (NWP) models at the NOAA National Weather Service (NWS). A few studies have shown the benefits of assimilating satellite soil moisture data in land surface models (LSMs), which are the components of most NWP models. In this study, synthetic experiments are conducted to determine how soil moisture data quality control may impact the benefit of their assimilation into LSMs. It is found that using green vegetation fraction to quality control the SMOPS soil moisture product may significantly increase the benefit of assimilating it into Noah LSM in terms of increasing the agreement of Noah LSM surface and root zone soil moisture simulations with the corresponding in situ measurements. The quality control procedures and parameters are suggested for the assimilation of SMOPS data into NWS NWP models.
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