Enhancing Seasonal Drought Prediction Capabilities for the US and the Globe Using the National Multi-Model Ensemble

As articulated in the National Integrated Drought Information System implementation plan (NIDIS; NOAA 2007), decision-makers in drought-sensitive sectors would gain substantial utility from enhanced and objectively derived drought outlooks which allow stakeholders to test a variety of scenarios across different time scales to guide their decision-making. One of the two adopted strategies for the enhancement of seasonal drought outlooks under the NIDIS plan is the prediction of widely-used, meteorologically based drought indicators, and common goals of both the climate test bed program (CTB) and NIDIS is to enhance skill of seasonal drought forecasts via multi-model ensemble techniques. The new National Multi-Model Ensemble (NMME) brings an important new tool to this effort. And given its global coverage, the NMME further allows for the development and test bedding of a prototype global drought prediction system, a core component of a global drought early warning system (GDEWS) recently endorsed by the World Climate Research Program (WCRP).

Here we propose to build on probabilistic seasonal drought prediction capabilities recently developed by members of the research team by incorporating NMME forecasts into that framework. The overall goal of the project is to enhance current seasonal drought prediction efforts over the US while also developing a prototype drought prediction system for the globe. The work will blend observed drought conditions with the dynamical model precipitation (and temperature) forecasts to predict multiple “drought” indicators. The focus will be on generating objectively derived probabilities of future drought conditions (i.e., drought indicator values) given the current drought state at lead times of 1 to 8 months. Web-based tools will be developed for the interactive display of drought forecast information as well as historical drought conditions. The overall strategy is envisioned to be an intermediate complexity approach that can easily transition to near real time operations to support the NIDIS Drought Early Warning system.

This proposal responds to the MAPP program priority area 1: “Advance intra-seasonal to decadal climate prediction” while tied to priority area 2: “Develop an experimental National Multi model ensemble climate prediction system.” Specifically, the proposed research will contribute to the priority area 1 objectives to “assess optimal prediction methodologies for specific applications” and “achieve an improved understanding of the impact of initializing select components of the Earth system for climate prediction at a particular timescale.” Products from this proposal will contribute to the CPC drought briefing and the NMME drought indicator predictions will provide drought forecasters a valuable tool for their operational monthly and seasonal Drought Outlook. The work also relates to the NOAA Next-Generation Strategic Plan (NGSP) by addressing its objective for “improved scientific understanding of the changing climate system and its impacts”, which includes a new generation of climate predictions and increased confidence in assessing and anticipating climate impacts. It also provides necessary information for addressing the NGSP objective of “mitigation and adaptation choices supported by sustained, reliable, and timely climate services” by which national, state, local, and tribal governments and water resource managers are better able to prepare for, adapt, and respond to drought and flooding and can more confidently manage water resources.