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1 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.

2 Haque, A.; Shampa; Akter, M.; Hussain, Md. M.; Rahman, Md. R.; Salehin, M.; Rahman, M. 2024. An integrated risk-based early warning system to increase community resilience against disaster. Progress in Disaster Science, 21:100310. [doi: https://doi.org/10.1016/j.pdisas.2023.100310]

Disaster risk reduction ; Flood forecasting ; Communities ; Resilience ; Early warning systems ; Model ; Sustainable Development Goals ; Vulnerability ; Villages ; Indicators ; River water ; Water levels / Bangladesh / Kurigram

(Location: IWMI HQ Call no: e-copy only Record No: H052633)

https://www.sciencedirect.com/science/article/pii/S2590061723000376/pdfft?md5=40313c2dfaa230bcc2d53032aa35f8bf&pid=1-s2.0-S2590061723000376-main.pdf
https://vlibrary.iwmi.org/pdf/H052633.pdf

(9.74 MB) (9.74 MB)

The need to integrate Early Warning System (EWS) with Disaster Risk Reduction (DRR) has long been recognized in several global forums. In the year 2006, the United Nations International Strategy for Disaster Reduction (UNISDR) proposed an Integrated Risk-based EWS (IR-EWS) by integrating four elements: (1) Monitoring and warning service; (2) Risk knowledge; (3) Dissemination and communication; and (4) Response capability. Nearly after two decades of the UNISDR proposal, our study finds that there are still gaps in making IR-EWS operational. Our study also finds that works on conceptualizing integration of resilience against disaster with EWS as part of DRR (in line with SDG-13) has not yet been started. Against this backdrop, in this study we developed an IR-EWS for flood termed as Dynamic Flood Risk Model (DFRM) which contains: (1) simple risk-based warning numbers which are easily understandable and communicable to the community, with risk considered as a proxy for resilience; and (2) capital-based action plans in relation to community capital to reduce disaster risk and increase community resilience against disaster. The DFRM is applied in two flood-prone districts in Bangladesh and found to be acceptable to the community with reasonable accuracy. The model is the customized version of flood for generic IR-EWS. This study can be considered as the first attempt of the next generation IR-EWS where risk is represented by simple warning numbers and where EWS (as part of DRR) can be applied to increase the resilience.