Imprints of Soil Moisture Memory on Predictability and T2M Bias in SubX Subseasonal Forecasts

Analyses of both observational and simulated soil moisture data identify 1-2 months as a typical time scale for the memory associated with root zone soil moisture anomalies. Through an in-depth analysis of the subseasonal forecasts produced for the SubX project by a state-of-the-art S2S forecast system (the NASA GMAO S2S forecast system), we examine an important facet of this soil moisture memory on predictability and prediction. As a result of the strongly nonlinear relationship between soil moisture and ET, the nearsurface air temperature (T2M) forecast bias (relative to independent observations) differs depending on the character of the local initial soil moisture -a negative precipitation bias in the forecast system has a larger impact on T2M forecast bias when the initial soil moisture is dry as opposed to wet. Such results provide a pathway for improving the estimation of error in subseasonal T2M forecasts.