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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Hydrology and Remote Sensing Laboratory » Research » Publications at this Location » Publication #404525
Research Project: From Field to Watershed: Enhancing Water Quality and Management in Agroecosystems through Remote Sensing, Ground Measurements, and Integrative Modeling

Location: Hydrology and Remote Sensing Laboratory

Title: IMERG precipitation improves the SMAP level-4 soil moisture product

Author
item REICHLE, R. - National Aeronautics And Space Administration (NASA)
item LIU, Q. - National Aeronautics And Space Administration (NASA)
item ARDIZZONE, J. - National Aeronautics And Space Administration (NASA)
item Crow, Wade
item DE LANNOY, G. - Ku Leuven
item KIMBALL, J. - University Of Montana
item KOSTER, R. - National Aeronautics And Space Administration (NASA)

Submitted to: Journal of Hydrometeorology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/18/2023
Publication Date: 10/4/2023
Citation: Reichle, R., Liu, Q., Ardizzone, J., Crow, W.T., De Lannoy, G., Kimball, J., Koster, R. 2023. IMERG precipitation improves the SMAP level-4 soil moisture product. Journal of Hydrometeorology. 24, 1699-1723. https://doi.org/10.1175/JHM-D-23-0063.1.
DOI: https://doi.org/10.1175/JHM-D-23-0063.1

Interpretive Summary: Tracking soil moisture availability is critical for monitoring agricultural drought. The current state of the art for such tracking is the NASA Soil Moisture Active Passive (SMAP) Level-4 Soil Moisture (L4_SM) data product that merges satellite observations and observation-based precipitation data into a numerical model of land surface water and energy balance processes to generate global, 9-km resolution, 3-hourly soil moisture estimates. This paper demonstrates that a recent SMAP L4_SM update using satellite- and gauge-based precipitation inputs from a new global precipitation product improves the temporal precision of SMAP L4_SM estimates - particularly in otherwise poorly instrumented regions of South America, Africa, Australia, and East Asia. This new update is currently being assessed by the USDA Foreign Agricultural Service as a means for improving the global monitoring of agricultural drought.

Technical Abstract: The NASA Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides global, 9-km resolution, 3-hourly surface and root-zone soil moisture from April 2015 to present with a mean latency of 2.5 days from the time of observation. The L4_SM algorithm assimilates SMAP L-band (1.4 GHz) brightness temperature (Tb) observations into the NASA Catchment land surface model as the model is driven with observation-based precipitation. This paper describes and evaluates the use of satellite- and gauge-based precipitation from the NASA Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (IMERG) mission in the L4_SM algorithm beginning with L4_SM Version 6. Specifically, IMERG is used in two ways: (i) The L4_SM precipitation reference climatology is based on IMERG-Final (Version 06B) data, replacing the Global Precipitation Climatology Project version 2.2 data used in previous L4_SM versions, and (ii) the precipitation forcing outside of North America and the high latitudes is corrected to match the daily totals from IMERG, replacing the gauge-only, daily product or uncorrected weather analysis precipitation used there in earlier L4_SM versions. The IMERG precipitation inputs result in improvement of the anomaly time series correlation coefficient of L4_SM surface soil moisture by 0.03 in the global average and by up to ~0.3 in parts of South America, Africa, Australia, and East Asia, where the quality of the gauge-only precipitation product used in earlier L4_SM versions was poor. The improvements are also manifested in smaller Tb observation-minus-forecast (O-F) residuals, with the O-F time series standard deviation reduced from 5.5 K in L4_SM Version 5 to 5.1 K in Version 6.