A National Oceanic and Atmospheric Administration’s National Environmental Satellite, Data, and Information Service (NOAA-NESDIS) and Earth Prediction Innovation Center (EPIC) led effort delivers near-real-time, and high-resolution soil moisture products to support Earth System modeling applications worldwide.
Acknowledgements: Yin, Jifu; University of Maryland, ESSIC; Zhan, Xiwu; NOAA; Liu, Jicheng; University of Maryland College Park; Kim, Jong; NOAA; Jeon, Chan-Hoo; NOAA; Petro, Gillian; NOAA
NOAA NESDIS has advanced global soil moisture monitoring through the development and operational production of the Soil Moisture Operational Products System (SMOPS), a blended satellite-based dataset that integrates observations from multiple microwave sensors to support numerical weather prediction, hydrological forecasting, and atmospheric research research. Led by Zhan, Yin and collaborators, this work addresses long-standing limitations in soil moisture coverage, consistency, and latency by delivering near-real-time, weather data record, and high-resolution products for operational and scientific use. In parallel, this effort supports the research-to-operations (R2O) pipeline within the Unified Forecast System (UFS), where SMOPS products are increasingly evaluated and integrated through the UFS Land Data Assimilation (Land-DA) framework to improve land surface initial conditions and coupled forecast performance.
The objective of SMOPS is to serve as a one-stop, operational system that blends soil moisture observations from multiple passive and active microwave satellite missions into consistent, high-quality products. The system is designed to support both near-real-time operational forecasting and long-term weather applications while minimizing latency, reducing inter-sensor biases, and improving spatial coverage—capabilities that are especially critical for assimilation into advanced land data assimilation systems such as the UFS Land-DA.
SMOPS provides substantial value to NOAA operations and the broader scientific community by delivering blended soil moisture products that outperform individual satellite datasets in spatial coverage and data availability. Assimilation studies show that incorporating SMOPS into land surface and numerical weather prediction models improves simulations of soil moisture, soil temperature, and surface energy fluxes.
Within the UFS Land Data Assimilation (Land-DA) system, SMOPS products are assimilated using advanced data assimilation techniques (e.g., ensemble-based or hybrid methods) that optimally merge satellite-derived soil moisture with model background states. This process improves the initialization of land surface states, including root-zone soil moisture, which is not directly observable but critically influences evapotranspiration and boundary layer evolution. By correcting biases and propagating surface moisture information vertically through model soil layers, Land-DA enhances the representation of land–atmosphere coupling. These improvements translate into better forecasts of near-surface temperature, humidity, planetary boundary layer development, and ultimately precipitation. Additionally, Land-DA leverages SMOPS’ multi-sensor blending to provide more spatially complete and temporally consistent updates, reducing data gaps and improving forecast stability across cycles.
By supporting both real-time forecasting and research, SMOPS strengthens NOAA’s ability to predict droughts, floods, and other high-impact environmental events, benefiting water managers, forecasters, researchers, and decision-makers.
Future SMOPS enhancements will incorporate observations from new satellite missions, including AMSR3 on GOSAT-GW and soil moisture products from the NASA–ISRO NISAR mission. These additions are expected to further improve spatial resolution, coverage, and product robustness. Development of the 1-km SMOPShr product is ongoing, with public release planned to support high-resolution hydrological modeling and operational applications, including next-generation Land-DA capabilities within UFS.
Through sustained investment and innovation, NOAA-NESDIS has established SMOPS as a robust, operational soil moisture monitoring system that bridges near-real-time forecasting needs and long-term research. By blending multi-sensor satellite observations into consistent, accessible products, SMOPS enhances NOAA’s capacity to understand and predict critical land–atmosphere processes now and into the future.
