A Process-Oriented Investigation of Subseasonal Drought Forecasting using Dynamical Subseasonal Forecasts and Noah-MP Land Surface Model

The NOAA National Weather Service’s Climate Prediction Center (CPC) releases drought and other hazard outlooks for a range of stakeholders to aid in their situational awareness, operations, planning, and decision making. The development and production of CPC subseasonal drought forecast products, including the Flash Drought Outlook and Monthly Drought Outlook, utilize subseasonal dynamical model forecasts as a key input.

As part of NIDIS’s collaboration with the CPC on Improving NOAA Climate Prediction Center Drought Outlook Products and Services, before applying these subseasonal forecasts for CPC Flash Drought and Monthly Drought Outlook product development, it is imperative to evaluate their performance in predicting U.S. drought through a process-oriented investigation. Meanwhile, with the ongoing transition of National Centers for Environmental Prediction/Environmental Modeling Center (EMC)’s most recent Noah-MP land surface model to CPC, it is desirable to improve subseasonal forecasting of land surface states (e.g., soil moisture) by utilizing the Noah-MP in offline mode with bias-corrected and calibrated subseasonal meteorological forecasts. 

This project component aims to evaluate the performance of subseasonal forecasts in predicting U.S. drought and perform a process-oriented investigation by examining the extent to which these forecasts capture known sources of sub-seasonal drought predictability and their effects on U.S. drought evolvement. This includes incorporating the Noah-MP developed at EMC, a state-of-the-art land surface model, to improve the subseasonal land surface forecasting.

For more information, please contact Amanda Sheffield (amanda.sheffield@noaa.gov).