Soil moisture is a critical variable and influences the climate system through modification of energy and moisture fluxes of the boundary layer. This in turn affects temperature, humidity and precipitation. In addition, soil moisture is used as an indicator for agricultural drought and recent studies have determined soil moisture as a key indicator of, and possible early warning for, flash drought in the United States. Due to its significance, accurate soil moisture information is critical for subseasonal-to-seasonal climate prediction as well as forecasting extreme events at those timescales.
Recent initiatives, such as the National Coordinated Soil Moisture Monitoring Network effort, have increased the spatial coverage and quality of soil moisture monitoring infrastructure across the contiguous United States. This effort has laid the foundation for a high-resolution, real-time gridded soil moisture product available at nationalsoilmoisture.com that leverages data from in situ networks, satellite platforms, and land surface models. An important precursor to this development is a comprehensive, national-scale assessment of in situ soil moisture data. Since in situ soil moisture observations are vital for a comprehensive soil moisture monitoring infrastructure, evaluation of the United States’ current in situ soil moisture monitoring infrastructure can provide a means toward more informed satellite and model calibration and validation.
In a new study, published in the Journal of Hydrometeorology, authors Trent Ford, Steven Quiring, Chen Zhao, Zachary T. Leasor, and Christian Landry employed a triple collocation approach to evaluate the fidelity of in situ soil moisture observations from over 1,200 stations across the contiguous United States. The goal of this research is to determine the monitoring stations that are best suited for: (1) inclusion in national-scale soil moisture datasets, (2) deriving in-situ-informed gridded soil moisture products, and (3) validating and benchmarking satellite and model soil moisture data.
It was found that 90% of the 1,233 stations evaluated exhibited high spatial consistency with satellite remote sensing and land surface model soil moisture datasets. In addition, in situ error did not significantly vary by climate, soil type, or sensor technology, but instead, the stations with high error were affected by land cover and station factors that are more difficult to identify. This study was funded by NIDIS in partnership with the MAPP program.
The National Integrated Drought Information System (NIDIS) program was authorized by Congress in 2006 (Public Law 109-430) with an interagency mandate to coordinate and integrate drought research, building upon existing federal, tribal, state, and local partnerships in support of creating a national drought early warning information system. For more information, please visit https://www.drought.gov/drought/.
The Modeling, Analysis, Predictions, and Projections (MAPP) Program is a competitive research program in NOAA Research’s Climate Program Office. MAPP’s mission is to enhance the Nation’s and NOAA’s capability to understand, predict, and project variability and long-term changes in Earth’s system and mitigate human and economic impacts. To achieve its mission, MAPP supports foundational research, transition of research to applications, and engagement across other parts of NOAA, among partner agencies, and with the external research community. MAPP plays a crucial role in enabling national preparedness for extreme events like drought and longer-term climate changes. For more information, please visit www.cpo.noaa.gov/MAPP.