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LEO Soil Moisture Observations Support Better NOAA Weather and Water Forecasts

July 22, 2026
Soil moisture plays a critical role in weather prediction, drought and flood forecasting, agricultural monitoring and water resource planning.
Feature Story | Office of Low Earth Orbit Observations

Soil moisture plays a critical role in weather prediction, drought and flood forecasting, agricultural monitoring and water resource planning. The amount of water stored in the soil influences how rainfall moves through the environment, determining whether it soaks into the ground or flows across the surface as runoff. This, in turn, impacts streamflow, groundwater recharge and the likelihood of flooding.

Soil moisture also regulates the exchange of heat and moisture between the land surface and atmosphere, influencing temperature, humidity and the potential for precipitation. As a result, accurate soil moisture observations are essential for improving weather forecasts, monitoring water availability and supporting hazard prediction and response.

Aerial view of severe flooding and mud damage in a town, showing submerged areas, brown rushing water, roads, buildings, and surrounding trees.

Flooding in western North Carolina following Hurricane Helene in September 2024. Days of heavy rainfall before Helene's arrival saturated soils across the region, leaving little capacity to absorb additional water. As Helene delivered extreme rainfall, much of the water rapidly flowed across the land surface rather than infiltrating into the ground, contributing to historic flooding, widespread landslides and extensive damage to communities and infrastructure. Credit: U.S. Army National Guard/Sgt. 1st Class Leticia Samuels, CC BY-ND 2.0.

NOAA’s weather and water models rely on soil moisture information to more realistically represent land-atmosphere interactions. Although ground-based measurements are highly accurate, they are limited to specific locations, leading to data gaps and an incomplete picture of soil moisture at regional and global scales.Satellites help fill these gaps by providing continuous observations across vast areas, including remote regions where ground-based monitoring is sparse or unavailable. Most satellite-based soil moisture measurements come from microwave sensors on board low Earth orbit (LEO) satellites. Because water changes how soil absorbs, emits and reflects microwave energy, these sensors can detect those differences and estimate how much moisture is present in the soil.

Numerous LEO microwave sensors measure soil moisture, each with unique strengths and limitations in terms of coverage and measurement capabilities. While these observations complement each other, using them independently can also lead to gaps and inconsistencies. Combining observations from the various sensors helps compensate for individual sensor limitations, resulting in a more complete and accurate depiction of global soil moisture conditions.

NOAA's Soil Moisture Operational Product System (SMOPS), developed by the NOAA/NESDIS Center for Satellite Applications and Research (STAR), was created to address this challenge. Operational since 2013, SMOPS merges soil moisture retrievals from multiple LEO microwave sensors into a single, consistent product that serves as a centralized source of soil moisture observations. Produced in near real-time at 25-kilometer resolution, SMOPS provides timely data to forecast and analysis systems used by NOAA’s Environmental Modeling CenterNational Weather Service and National Water Center.

Global daily soil moisture for June 1–21, 2026, from the near real-time 25-kilometer SMOPS Soil Moisture product. Values represent volumetric soil moisture (volume water/volume soil) in the upper 1–5 centimeters of soil, indicating the fraction of soil volume occupied by water. Credit: NOAA/NESDIS STAR.

Global daily soil moisture for June 1–21, 2026, from the near real-time 25-kilometer SMOPS Soil Moisture product. Values represent volumetric soil moisture (volume water/volume soil) in the upper 1–5 centimeters of soil, indicating the fraction of soil volume occupied by water. Credit: NOAA/NESDIS STAR.

With support from the NOAA/NESDIS Office of LEO Observations, a 1-kilometer resolution version of SMOPS was developed to extend these capabilities to higher-resolution hydrologic applications. This product provides soil moisture data for the National Water Model, which requires finer-scale information to better represent localized hydrological processes that influence runoff and streamflow. Developed using a machine learning approach, the 1-kilometer product offers much finer spatial detail than the 25-kilometer version, capturing details that are not visible in the coarser resolution product.

A comparison between the 25-kilometer (top) and the 1-kilometer (bottom) SMOPS products shows the improvement in detail with the higher resolution product. Credit: NOAA/NESDIS STAR/Dr. Xiwu Zhan.

A comparison between the 25-kilometer (top) and the 1-kilometer (bottom) SMOPS products shows the improvement in detail with the higher resolution product. Credit: NOAA/NESDIS STAR/Dr. Xiwu Zhan. 

SMOPS products support a wide range of operational and research activities across NOAA. They are used for model verification, calibration, validation and data assimilation, helping to improve the accuracy of NOAA’s weather and water prediction systems. Beyond modeling applications, observations from SMOPS also support critical decision-making during floods, droughts, and other severe weather events, helping reduce impacts on communities while supporting key sectors of the national economy, including agriculture, transportation and commerce.

The 2025 LEO Science Digest cover features a colorful map globe of Earth showing dry air temperatures, with NOAA and NASA logos at the top.

Learn more about SMOPS in Feature 7 of the 2025 LEO Science DigestEnhancing Weather, Water, and Hazard Forecasts With Blended LEO Soil Moisture Observations. Published each January, the Digest highlights real-world applications of LEO satellite observations, showcasing how they enhance weather forecasting, support disaster response and benefit the U.S. economy.