Overview of Drought Task Force Research Objectives
3) Improving Drought Prediction
Improved drought prediction is the key to developing a useful drought early warning system. Central to this effort is improving the prediction of precipitation on intraseasonal to seasonal and longer time scales. The usefulness of improved precipitation forecasts (especially necessary in the warm season) will depend on the extent to which predictable signals in soil moisture and stream flow emerge. Currently, the accuracy of hydrological forecasts extending out one or two months is a result of the hydrological system's memory of the initial conditions (e.g., soil moisture, snow). Little additional improvement is gained from forecasts of precipitation, with the exception of precipitation patterns influenced by the occasional strong ENSO event. Studying the three designated Northern American drought cases can help illuminate the influence of initial hydrological conditions and precipitation forecasts on regional heterogeneity of drought. The extent to which these improvements lead to useful and actionable information in the variables and at the spatial scales of importance to users will be assessed.
The task force applies a wide array of tools towards the goal of improving drought prediction including coupled climate models, very high-resolution atmospheric and land models, hydrological models, and various data sets for initializing and validating the model results. Accordingly, various individual research projects will address the challenges described above from different perspectives. The Task Force Test Bed will play a coordinating role.
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