Abstract:
Water resources throughout High Mountain Asia (HMA) are dependent on the balance of precipitation, evaporation, runoff, glaciers, permafrost, and soil moisture. The complexities of these relationships and the regional topography make the prediction of these variables challenging. Yet, HMA land surface hydrologic conditions can impact, through teleconnections, global weather and climate patterns. Thus, it is plausible that the accurate representation of HMA soil moisture conditions has the potential to enhance Subseasonal to Seasonal (S2S) prediction skill of global climate conditions. Here, we evaluate HMA soil moisture and associated climate variables from the Goddard Earth Observing System Subseasonal-to-Seasonal Forecasting System (GEOS-S2S) at different lead times (1-month to 3-month forecasts). We use the NASA Soil Moisture Active-Passive (SMAP) level 4 soil moisture product as the reference to evaluate the model prediction skill. The results from this assessment can be used to improve the forecasting of soil moisture in the HMA region. Such improvements can help downstream water resources and natural hazards management, and can give hope of better capturing the relationship with teleconnections and thus weather patterns throughout the globe.