A Process-Oriented Investigation of Sub-seasonal Drought Forecasting Using Dynamical Sub-seasonal Forecasts and Noah-MP Land Surface Model

Each month, the National Weather Service issues monthly and seasonal U.S. drought outlooks. These forecasts support drought decision-making and situational awareness for national, regional, and state governments and other stakeholders. 

Computer forecasts for two to four weeks ahead are essential to creating U.S. drought outlooks. Before National Weather Service forecasters could develop new probabilistic outlooks, they had to evaluate how well these forecast inputs performed in predicting drought across the U.S. 

The research team evaluated how well these forecasts predicted U.S. drought by examining the extent to which these forecasts capture known sources of sub-seasonal drought predictability, and their effects on U.S. drought evolution. The team also incorporated the Noah-MP—a state-of-the-art land surface model developed at the National Weather Service’s Environmental Modeling Center—to improve the sub-seasonal land surface forecasting. 

This work is part of a broader NIDIS-supported research effort to  improve NOAA National Weather Service drought outlooks. For more information, please contact Amanda Sheffield (amanda.sheffield@noaa.gov).