A novel approach to validate satellite soil moisture retrievals using precipitation data

A novel approach is proposed that attempts to validate passive microwave soil moisture retrievals using precipitation data (applied over India). It is based on the concept that the expectation of precipitation conditioned on soil moisture follows a sigmoidal convex‐concave‐shaped curve, the characte...

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Bibliographic Details
Published in:Journal of geophysical research. Atmospheres 2016-10, Vol.121 (19), p.11,516-11,535
Main Authors: Karthikeyan, L., Kumar, D. Nagesh
Format: Article
Language:English
Subjects:
Colleges & universities
copula
Data integration
Elevation
Geophysics
Hydrologic data
Impact analysis
Land cover
Land use
Microwave radiometers
Moisture
mutual information
Precipitation
Precipitation (meteorology)
Precipitation data
Probability density function
Probability density functions
Probability theory
Radiometers
Rainfall
Retrieval
satellite
Satellite soil moisture estimates
Satellites
Soil
Soil conditions
Soil moisture
Strategy
validation
Water resources
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Summary:A novel approach is proposed that attempts to validate passive microwave soil moisture retrievals using precipitation data (applied over India). It is based on the concept that the expectation of precipitation conditioned on soil moisture follows a sigmoidal convex‐concave‐shaped curve, the characteristic of which was recently shown to be represented by mutual information estimated between soil moisture and precipitation. On this basis, with an emphasis over distribution‐free nonparametric computations, a new measure called Copula‐Kernel Density Estimator based Mutual Information (CKDEMI) is introduced. The validation approach is generic in nature and utilizes CKDEMI in tandem with a couple of proposed bootstrap strategies, to check accuracy of any two soil moisture products (here Advanced Microwave Scanning Radiometer–EOS sensor's Vrije Universiteit Amsterdam‐NASA (VUAN) and University of Montana (MONT) products) using precipitation (India Meteorological Department) data. The proposed technique yields a “best choice soil moisture product” map which contains locations where any one of the two/none of the two/both the products have produced accurate retrievals. The results indicated that in general, VUA‐NASA product has performed well over University of Montana's product for India. The best choice soil moisture map is then integrated with land use land cover and elevation information using a novel probability density function‐based procedure to gain insight on conditions under which each of the products has performed well. Finally, the impact of using a different precipitation (Asian Precipitation‐Highly‐Resolved Observational Data Integration Towards Evaluation of Water Resources) data set over the best choice soil moisture product map is also analyzed. The proposed methodology assists researchers and practitioners in selecting the appropriate soil moisture product for various assimilation strategies at both basin and continental scales. Key Points A novel approach is introduced to validate satellite soil moisture retrievals using rainfall data VUA‐NASA product in general performed well compared to University of Montana's product over India Results are integrated with LULC and elevation data; impact of reference rainfall data is analyzed
ISSN:2169-897X
2169-8996
DOI:10.1002/2016JD024829