Climate models optimised for East Africa say 2100 will be much hotter

Researchers optimised existing computer-based climate models for East Africa to better predict how temperatures might increase by 2100. This information will help regional authorities plan for and adapt to climate change effects, like food shortages or natural disasters.

Average temperatures are rising due to global warming, causing more extreme weather events like droughts and floods, which in turn spreads disease and disrupts farming. Such unpredictable events make it challenging to plan and adapt to climate change, so researchers are working on models to better predict climate change.

In this study, researchers wanted to identify existing climate models that best predict changes in East Africa, specifically over the years 2021 to 2100. The researchers fed temperature recordings from Kenya, Uganda, Tanzania, Burundi, and Rwanda into 13 existing computer-based climate models. The temperature recordings spanned the years 1970 to 2014. 

They combined the 5 models that were the most accurate on other data from East Africa. They used this combined model to predict how the climate in East Africa will change over time until 2100. They made predictions for two different scenarios: one where no new policies are implemented to slow climate change, and the other where policies moderately slow it.

The researchers predicted that the average temperature in East Africa will increase slowly from 2021 to 2049, by 1 degree Celsius. But, they expected the temperature to increase faster from 2080 to 2100, by 2.4 to 4.4 degrees Celsius. They also predicted that the average temperature will increase almost 3 times more quickly if no policies are introduced to slow climate change, compared to policies that might moderately slow climate change.

These findings identified the best existing climate models for East Africa, and the most accurate average temperature predictions for the region as of 2021. This information will help future researchers improve climate models and predictions tailored to this area.

The researchers suggest starting with improving the ability of the models to predict extreme weather events, like droughts and floods. They also say the accuracy of the models over complex terrain like mountains or lakes should be improved.

This study was done by researchers from Uganda, Rwanda, Morocco, and China.

Abstract

This study evaluates the historical mean surface temperature (hereafter T2m) and examines how T2m changes over East Africa (EA) in the 21st century using CMIP6 models. An evaluation was conducted based on mean state, trends, and statistical metrics (Bias, Correlation Coefficient, Root Mean Square Difference, and Taylor skill score). For future projections over EA, five best performing CMIP6 models (based on their performance ranking in historical mean temperature simulations) under the shared socioeconomic pathways SSP2-4.5 and SSP5-8.5 scenarios were employed. The historical simulations reveal an overestimation of the mean annual T2m cycle over the study region with fewer models depicting underestimations. Further, CMIP6 models reproduce the spatial and temporal trends within the observed range proximity. Overall, the best performing models are as follows: FGOALS-g3, HadGEM-GC31-LL, MPI-ESM2-LR, CNRM-CM6-1, and IPSL-CM6A-LR. During the three-time slice under consideration, the Multi Model Ensemble (MME) project many changes during the late period (2080 – 2100) with expected mean changes at 2.4 °C for SSP2-4.5 and 4.4 °C for the SSP5-8.5 scenario. The magnitude of change based on Sen’s slope estimator and Mann-Kendall test reveal significant increasing tendencies with projections of 0.24°C decade-1 (0.65°C decade-1) under SSP2-4.5 (SSP5-8.5) scenarios. The findings from this study illustrate higher warming in the latest model outputs of CMIP6 relative to its predecessor, despite identical instantaneous radiative forcing.

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