Tailored Forecasts Can Predict Extreme Climate Informing Proactive Interventions in East Africa

Author:

Funk Chris1ORCID,Harrison Laura1,Segele Zewdu2,Rosenstock Todd3ORCID,Steward Peter3,Anderson C. Leigh4,Coughlan de Perez Erin56,Maxwell Daniel7ORCID,Endris Hussen Seid2,Koch Eunice2,Artan Guleid2,Teshome Fetene8,Aura Stella Maris9,Galu Gideon1,Korecha Diriba1,Anderson Weston10,Hoell Andrew11ORCID,Damerau Kerstin12ORCID,Williams Emily1ORCID,Ghosh Aniruddha3,Ramirez‐Villegas Julian313,Hughes David14

Affiliation:

1. Climate Hazards Center University of California, Santa Barbara Santa Barbara CA USA

2. IGAD Climate Prediction and Applications Center Ngong Kenya

3. Alliance of Biodiversity International and the International Center for Tropical Agriculture (Biodiversity – CIAT) Nairobi Kenya

4. Marc Lindenberg Professor for Humanitarian Action International Development and Global Citizenship University of Washington Seattle WA USA

5. Friedman School of Nutrition Tufts University Boston MA USA

6. Red Cross Red Crescent Climate Centre The Hague The Netherlands

7. Feinstein International Center, Friedman School of Nutrition Science and Policy Tufts University Boston MA USA

8. Ethiopian National Meteorological Agency Addis Ababa Ethiopia

9. Kenya Meteorological Department Nairobi Kenya

10. NASA GSFC FEWS NET Science Team Greenbelt MD USA

11. NOAA Physical Sciences Laboratory Boulder CO USA

12. Department of Global Development Cornell University Ithaca NY USA

13. Plant Production Systems Group Wageningen University & Research Wageningen The Netherlands

14. USAID Innovation Lab on Current and Emerging Threats to Crops Pennsylvania State University State College PA USA

Abstract

AbstractThis commentary discusses new advances in the predictability of east African rains and highlights the potential for improved early warning systems (EWS), humanitarian relief efforts, and agricultural decision‐making. Following an unprecedented sequence of five droughts, 23 million east Africans faced starvation in 2022, requiring >$2 billion in aid. Here, we update climate attribution studies showing that these droughts resulted from an interaction of climate change and La Niña. Then we describe, for the first time, how attribution‐based insights can be combined with the latest dynamical models to predict droughts at 8‐month lead‐times. We then discuss behavioral and social barriers to forecast use, and review literature examining how EWS might (or might not) enhance agro‐pastoral advisories and humanitarian interventions. Finally, in reference to the new World Meteorological Organization “Early Warning for All” Executive Action Plan, we conclude with a set of recommendations supporting actionable and authoritative climate services. Trust, urgency, and accuracy can help overcome barriers created by limited funding, uncertain tradeoffs, and inertia. Understanding how climate change is producing predictable climate extremes now, investing in African‐led EWS, and building better links between EWS and agricultural development efforts can support long‐term adaptation, reducing chronic needs for billions of dollars in reactive assistance. In Africa and beyond, climate change brings increasingly extreme sea surface temperature (SST) gradients. Using climate models, we can often see these extremes coming. Prediction, therefore, offers opportunities for proactive risk management and improved advisory services, if we can create effective societal linkages via cross‐silo collaborations.

Funder

Bureau for Economic Growth, Education, and Environment, United States Agency for International Development

Publisher

American Geophysical Union (AGU)

Subject

Earth and Planetary Sciences (miscellaneous),General Environmental Science

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