A Collaborative and Interdisciplinary Approach to Addressing Societal Needs Related to Severe Weather Forecasting in East Africa

Lake Victoria Basin is home to more than 40 million people in East Africa, with more than 5 million people living along the coastlines and small islands of Lake Victoria. The population benefits from a prosperous fishing industry and agriculture but also faces the risks of living in a global hotspot for convective activity. The basin is experiencing some of the world’s fastest population growth, and climate change projections suggest an increase in extreme events and thunderstorm intensification, increasing societal exposure to natural hazards in the region. Despite the evidence of high-impact weather affecting this region of the world, it is estimated that only 40% of the population of Africa has access to Early Warning advisory systems and less than 4% of funded research on climate change is focused on this continent. Studying, understanding, and building research to operations (R2O) pathways is a challenging task in Africa, partially due to the lack of sustainable observational systems to monitor and forecast weather. However, several past and current initiatives and programs are currently playing a major role in advancing knowledge and capacity-building in Africa.

The Climate Risk and Early Warning System/Severe Weather Forecasting Project – Eastern Africa- Training Workshop on Severe Weather and Impact-based Forecast and Warning Services was held in Kigali, Rwanda, on June 12-23, 2023. During the workshop, a collaborative activity to leverage background knowledge on nowcasting was conducted with forecasters from the region to understand the needs and challenges for severe weather forecasting in East Africa. The initial activity led to extended conversations with the different teams and the proposal of a more in-depth study, conducting interviews to understand, research, observation and modeling capacities, risk communication, and office operations. In this work, we present our preliminary findings of this ongoing research and long learning process, which we hope will lead to more meaningful research and collaborations.