<p>Drought is a natural climate extreme phenomenon that presents great challenges in forecasting and monitoring for water management purposes. Previous studies have examined the use of Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage anomalies to measure the amount of water <q>missing</q> from a drought-affected region, and other studies have attempted statistical approaches to drought recovery forecasting based on joint probabilities of precipitation and soil moisture. The goal of this study is to combine GRACE data with historical precipitation observations to quantify the amount of precipitation required to achieve normal storage conditions in order to estimate a likely drought recovery time. First, linear relationships between terrestrial water storage anomaly (TWSA) and cumulative precipitation anomaly are established across a range of conditions. Then, historical precipitation data are statistically modeled to develop simplistic precipitation forecast skill. Three different precipitation scenarios are simulated by using a standard deviation in climatology. Precipitation scenarios are convolved with precipitation deficit estimates to calculate best-estimate of a drought recovery period. The results show that in the regions of strong seasonal amplitude (like monsoon belt) drought continues even with the above-normal precipitation until its wet season. Historical GRACE-observed drought recovery period is used to validate the approach. Estimated drought for an example month demonstrated 80% similar recovery period as observed by the GRACE.</p>