Investigating the Predictability of Terrestrial Water Storage at Subseasonal to Seasonal Scale to support drought and food insecurity early warning in Data-Sparse Regions

Earth System Science Interdisciplinary Center, University of Maryland

Terrestrial Water Storage (TWS) integrates information from various important sources of moisture, each with distinct temporal and spatial dynamics, including groundwater, soil moisture, and surface water storage. TWS anomalies, hence, can serve as an indicator of drought, and are being used operationally, such as by the U.S. Drought Monitor. TWS can be simulated by land surface models and observed from satellites like GRACE/GRACE-FO, providing extensive spatial and temporal coverage in near-real time, which is particularly attractive in data-sparse regions that are also food insecurity hot spots. FLDAS (Famine Early Warning Systems Network Land Data Assimilation System)-Forecasts provide TWS forecasts at the subseasonal to seasonal scale (S2S). While past research has found the TWS forecasts to be a skillful predictor of Leaf Area Index (used as a surrogate of vegetative productivity) at 3 months lead time, further research is needed to facilitate operational application of TWS forecasts in supporting food insecurity early warning. This presentation summarizes recent research that (i) evaluates the skill of TWS forecasts from the FLDAS-forecasts system relative to GRACE/GRACE-FO observations and highlights the inter-model differences that lead to differences in TWS forecasts, (ii) investigates the role that each of the TWS components plays in the predictability of TWS at the S2S scale, and highlights the role of rootzone soil moisture in TWS predictability. Together, these analyses provide insights into both the promise and limitations of producing S2S forecasts of TWS using either land surface models or statistical models. We focus our analysis on data-sparse, food-insecure regions in Africa where data limitations are widespread and any improvement in forecast skill can be translated into improved early warnings of agricultural drought.