Disseminating Critical Climate Information
Disseminating Critical Climate Information

AI warns of imminent 3°C temperature rise in Africa 

Artificial intelligence (AI)-powered climate research has revealed that parts of Africa could face drastic temperature rises, surpassing critical warming thresholds much earlier than previously estimated. 

The findings emphasise the need for swift adaptation strategies to protect vulnerable ecosystems and communities.

A team of climate scientists—Elizabeth Barnes from Colorado State University, Noah Diffenbaugh from Stanford University, and Sonia Seneviratne from ETH-Zurich—utilised AI to analyse data from 10 global climate models. 

Their research, published in Environmental Research Letters by IOP Publishing, predicts that most land regions globally will exceed the 1.5°C warming limit by 2040. 

AFRICAN HOTSPOTS AT RISK

Sub-Saharan Africa has emerged as one of the most vulnerable regions. The study projects that temperatures in parts of this region could surpass the 1.5°C threshold before 2040 and potentially exceed 3.0°C by 2060. 

These findings suggest a significantly faster-warming trajectory than previous estimates, amplifying existing vulnerabilities tied to water scarcity, food insecurity, and desertification.

Key areas at risk include the Sahel, the Horn of Africa, and parts of Southern Africa, where prolonged droughts and heatwaves have already disrupted agricultural productivity and access to clean water.

Regions including South Asia, the Mediterranean, and Central Europe are also expected to reach these thresholds faster, compounding risks for vulnerable ecosystems and communities.

AI-ENHANCED CLIMATE MODELING

The research utilised cutting-edge AI techniques, specifically transfer learning, to refine predictions by integrating knowledge from multiple climate models and observational data. This approach provided a clearer picture of localised impacts, highlighting Africa’s heightened vulnerability to global warming.

Elizabeth Barnes said the research underscores the “importance of incorporating innovative AI techniques like transfer learning into climate modelling to potentially improve and constrain regional forecasts”.

According to the researcher, this approach would provide actionable insights for policymakers, scientists, and communities worldwide.

Noah Diffenbaugh, co-author and professor at Stanford University, emphasised the importance of examining not just global temperature trends but also localised and regional changes.

He noted that pinpointing when specific areas might cross warming thresholds enables better predictions of societal and ecological impacts, facilitating timely adaptation measures.

“The challenge is that regional climate change can be more uncertain, both because the climate system is inherently more noisy at smaller spatial scales and because processes in the atmosphere, ocean, and land surface create uncertainty about exactly how a given region will respond to global-scale warming.”

KEY PROJECTIONS

  • 34 regions globally are likely to exceed 1.5°C of warming by 2040.
  • 31 of these 34 regions are expected to reach 2°C by 2040.
  • 26 regions could surpass 3°C by 2060, with several African zones among them.

For Africa, this research underscores the urgency of integrating AI-driven models into national climate adaptation plans. 

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