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Many regions in Africa and the Middle East are vulnerable to drought and to water and food insecurity, motivating agency efforts such as the U.S. Agency for International Development's (USAID) Famine Early Warning Systems Network (FEWS NET) to provide early warning of drought events in the region. Each year these warnings guide life-saving assistance that reaches millions of people. A new NASA multimodel, remote sensing-based hydrological forecasting and analysis system, NHyFAS, has been developed to support such efforts by improving the FEWS NET's current early warning capabilities. NHyFAS derives its skill from two sources: (i) accurate initial conditions, as produced by an offline land modeling system through the application and/or assimilation of various satellite data (precipitation, soil moisture, and terrestrial water storage), and (ii) meteorological forcing data during the forecast period as produced by a state-of-the-art ocean-land-atmosphere forecast system. The land modeling framework used is the Land Information System (LIS), which employs a suite of land surface models, allowing multimodel ensembles and multiple data assimilation strategies to better estimate land surface conditions. An evaluation of NHyFAS shows that its 1-5-month hindcasts successfully capture known historic drought events, and it has improved skill over benchmark-type hindcasts. The system also benefits from strong collaboration with end-user partners in Africa and the Middle East, who provide insights on strategies to formulate and communicate early warning indicators to water and food security communities. The additional lead time provided by this system will increase the speed, accuracy, and efficacy of humanitarian disaster relief, helping to save lives and livelihoods. [ABSTRACT FROM AUTHOR]

The Famine Early Warning Systems Network (FEWS NET) team provides food insecurity outlooks for several developing countries in Africa, central Asia, and Central America. This study describes development of a new global reference evapotranspiration (ET0) seasonal reforecast and skill evaluation with a particular emphasis on the potential use of this dataset by FEWS NET to support food insecurity early warning. The ET0 reforecasts span the 1982-2009 period and are calculated following the American Society for Civil Engineers formulation of the Penman-Monteith method driven by seasonal climate forecasts of monthly mean temperature, humidity, wind speed, and solar radiation from the National Centers for Environmental Prediction CFSv2 model and the National Aeronautics and Space Administration GEOS-5 model. The skill evaluation, using deterministic and probabilistic scores, focuses on the December-February (DJF), March-May (MAM), June-August (JJA), and September-November seasons. The results indicate that ET0 forecasts are a promising tool for early warning of drought and food insecurity. Globally, the regions where forecasts are most skillful (correlation > 0.35 at leads of 2 months) include the western United States, northern parts of South America, parts of the Sahel region, and southern Africa. The FEWS NET regions where forecasts are most skillful (correlation > 0.35 at lead 3) include northern sub-Saharan Africa (DJF; dry season), Central America (DJF; dry season), parts of East Africa (JJA; wet season), southern Africa (JJA; dry season), and central Asia (MAM; wet season). A case study over parts of East Africa for the JJA season shows that ET0 forecasts in combination with the precipitation forecasts would have provided early warning of recent severe drought events (e.g., in 2002, 2004, 2009) that contributed to substantial food insecurity in the region. [ABSTRACT FROM AUTHOR]