The Seasonality and Physical Drivers of Long Duration Heat Extremes in Eritrea using AM4 and ERA5

This study investigates the seasonality and physical drivers of long-duration heat extremes in Eritrea, focusing on insights from both ERA5 reanalysis data and the GFDL AM4 model. We explore heatwaves during the wet (JJAS) and dry (FMAM) seasons, aiming to identify the key atmospheric patterns that drive these extreme events. Using a heatwave tracking algorithm, we zero in on the 30 longest heatwaves based on 90th percentile temperature anomalies, followed by detailed compositing analyses.

Our study finds that during the wet season, Rossby waves play a significant role, contributing to the formation of high-pressure systems that intensify heat extremes. However, in the dry season, the signal is less clear, with noticeable differences between ERA5 data and AM4 model outputs. The warming scenarios (SSP5-8.5) indicate that future heatwaves could become more intense and longer-lasting, largely due to greater soil moisture depletion and reduced evaporative cooling.

These findings point to the need for better model simulations, particularly for the dry season. Future work could involve refining the calculation methods, exploring additional metrics like heat index or wet bulb temperature, and integrating coupled ocean simulations to better understand the dynamics at play. This research is crucial for improving our understanding of heatwave behavior in an understudied region like Eritrea, with significant implications for public health, agriculture, and ecosystems.