Powerpoint talk presented by Dr. Clay Blankenship, Universities Space Research Association (USRA)/NASA Short-Term Prediction Research and Transition (SPoRT)
Soil moisture is a critical variable for agriculture and for predicting fire risk, and monitoring drought and water resources. As an influence on runoff from precipitation, it has a major effect on stream flow and flooding. Meteorologically, it influences the division between latent and sensible heating from solar radiation at the surface; hence it is an important initial condition for numerical weather models and for predicting diurnal heating, convective initiation, and precipitation. This talk includes an overview of land surface modeling with the NASA Land Information System. Some examples of using LIS to monitor or predict floods, fire risk, and drought are presented, along with potential applications for Alaska.
The assimilation of soil moisture retrievals from the NASA Soil Moisture Active-Passive (SMAP) satellite is also described. SMAP retrievals are shown to improve the soil moisture in two cases where the forcing data was deficient. In general, correlations with ground measurements were improved in the Eastern US. Additionally, results are shown from a modeling experiment assessing the impact of SMAP assimilation on a numerical weather forecast. Forecasts from parallel Weather Research and Forecasting (WRF) simulations illustrate the potential for SMAP assimilation to improve the prediction of precipitation. A case study of a significant squall line over the Great Lakes region in July 2016 is presented, in which SMAP assimilation improved the timing and structure of the precipitation, based on changes in Convective Available Potential Energy (CAPE).