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HOME > Outreach > Meetings > 33rd Annual Climate Diagnostics & Prediction Workshop > Abstracts

Predicting Present and Future Drought


Abstract Author: Lifeng Luo, Justin Sheffield, Haibin Li and Eric F Wood

Abstract Title: A Global Drought Monitoring and Forecasting Capability

Abstract: An experimental real time drought monitoring and seasonal forecasting system developed for the USA is being extended globally, firstly to Africa. The system supports a number of activities that include improved information for water management and food security as well as the evaluation of remote sensing retrievals of water cycle variables, including soil moisture and evapotranspiration. The system comprises three parts: a 1.0 degree baseline 50-yr retrospective simulation with the VIC model that forms a drought climatology, driven by a new forcing dataset that combines reanalysis with a suite of observational datasets; a real time monitoring component that updates hydrologic fields daily; and a forecast component that currently makes seasonal forecasts on a monthly basis using ensemble (probabilistic) forecast techniques with lead times up to 6 months. High resolution hydrologic fields are generated from land surface model simulations and are used to characterize agricultural and hydrologic drought severity. The soil moisture data derived from the baseline simulation are shown to be capable of representing large scale historical droughts in terms of climatology and trends. Current efforts are focused on bringing the simulations up to real time to link in with the forecast system. The current forecast system uses the seasonal forecast from the NCEP Climate Forecast System (CFS). 60-member ensemble forecasts of precipitation and temperature from CFS are bias corrected and downscaled to 1 degree via a Bayesian merging technique. The long-term climatology, derived from the baseline simulation, serves as a reference for the real time monitoring and forecasts, by removing the difference between model climatology and actual observations. Seasonal hindcasts of soil moisture and other variables are being assessed for their skill in replicating historical data, which is highly dependent on the skill of the precipitation and temperature forecasts. Improved forecast skill can be obtained by adding information derived from observed teleconnections and improved downscaling methods. The forecast system is designed to have such flexibility that other climate forecast products and hydrologic models can be incorporated in the future and there is potential to extend to global monitoring.

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