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1 Arsenault, K. R.; Shukla, S.; Hazra, A.; Getirana, A.; McNally, A.; Kumar, S. V.; Koster, R. D.; Peters-Lidard, C. D.; Zaitchik, B. F.; Badr, H.; Jung, H. C.; Narapusetty, B.; Navari, M.; Wang, S.; Mocko, D. M.; Funk, C.; Harrison, L.; Husak, G. J.; Adoum, A.; Galu, G.; Magadzire, T.; Roningen, J.; Shaw, M.; Eylander, J.; Bergaoui, K.; McDonnell, Rachael A.; Verdin, J. P. 2020. The NASA hydrological forecast system for food and water security applications. Bulletin of the American Meteorological Society (BAMS), 101(7):E1007-E1025. [doi: https://doi.org/10.1175/BAMS-D-18-0264.1]

Hydrology ; Forecasting ; Early warning systems ; Food security ; Water security ; Drought ; Flooding ; Precipitation ; Groundwater ; Water storage ; Soil water content ; Stream flow ; Monitoring ; Land area ; Meteorological factors ; Satellite observation ; Modelling / Africa / Middle East

(Location: IWMI HQ Call no: e-copy only Record No: H049803)

https://journals.ametsoc.org/bams/article-pdf/101/7/E1007/4981535/bamsd180264.pdf
https://vlibrary.iwmi.org/pdf/H049803.pdf

(8.47 MB) (8.47 MB)

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.

2 de Perez, E. C.; Harrison, L.; Berse, K.; Easton-Calabria, E.; Marunye, J.; Marake, M.; Murshed, S. B.; Shampa; Zauisomue, E.-H. 2022. Adapting to climate change through anticipatory action: the potential use of weather-based early warnings. Weather and Climate Extremes, 38:100508. [doi: https://doi.org/10.1016/j.wace.2022.100508]

Climate change adaptation ; Weather forecasting ; Early warning systems ; Vulnerability ; Disasters ; Precipitation ; Policies ; Rain ; Models

(Location: IWMI HQ Call no: e-copy only Record No: H051562)

https://www.sciencedirect.com/science/article/pii/S2212094722000871/pdfft?md5=50d4d199c5f1c35a2908c2150ebe5348&pid=1-s2.0-S2212094722000871-main.pdf
https://vlibrary.iwmi.org/pdf/H051562.pdf

(2.16 MB) (2.16 MB)

As a crucially-needed adaptation to climate change, the United Nations plans to expand Early Warning Systems (EWS) for extreme weather to cover everyone on Earth. Given the growing interest in this climate change adaptation solution, we assess how well weather early warnings perform for extreme events in different parts of the world. First, we carry out a forecast verification for weather forecasts from the National Oceanic and Atmospheric Administration (NOAA) for 95th percentile extreme heat and extreme precipitation globally at 0.5° resolution, with three days of lead time. We present the results alongside similar verification results from ECMWF forecasts and a CHIRPS-GEFS forecast, to identify regions of the world with consistent forecast skill. We then overlay the skill of these short-term weather forecasts on top of climate change projections for the increasing frequency of the extreme events themselves. Based on these results, we offer policy implications for EWS investments in different regions. We find that in much of the tropics, weather forecasts have relatively poor skill in forecasting extreme temperature and precipitation events, calling for further investments in predictability. In the extra-tropics, most extreme heat and extreme precipitation events can be correctly forecasted, with better results for multi-day events and shorter lead-times. While there is room to improve predictability, end-to-end investments in EWS in these regions can focus on the use of existing skillful forecasts. Finally, most of the world's land area is projected to see an increase in the magnitude of extreme heat and precipitation events with climate change, and EWS investments in these regions should prepare for unprecedented extremes and changing vulnerabilities. These results provide a foundation for localized research on EWS in different parts of the world as well as evidence for policy and donors on how best to invest in EWS in different regions.