The impact of NASA SMAP soil moisture data assimilation on Great Plains low-level jet wind forecasts

Abstract:

Demonstrating the added-value of SMAP soil moisture data assimilation (SMAP DA) to weather forecasts, especially over the data-rich U.S., has constituted a major challenge to the SMAP Science Team. On time- and area-averaged bases, forecast improvements attributable to SMAP DA are significant but only marginal. A more fitting measure of SMAP DA’s value is its efficacy during societally-impactful Great Plains low-level jet events characterized by extreme precipitation and winds. In this study, we simulate 75 Great Plains low-level jets both with- and without EnKF SMAP DA using the NASA-Unified Weather Research and Forecasting model. Then, with the aid of a jet mapping algorithm and dynamical jet classification, we quantify wind speed differences between the DA and no-DA simulations along the jet axis and between strong- and weakly synoptically coupled jets. The largest differences in 850-hPa wind speed are observed at the jet core and exit regions. At the jet exit, the impact of SMAP DA varies significantly between strong and weakly coupled jets: weakly coupled jets tend to be enhanced whereas strongly coupled jets tend to be suppressed. Overall, SMAP DA’s impact on wind forecasts is greatest during weakly coupled jet events, which we explore further.