Leveraging AI for climate adaptation: A new era for resilience
Adaptation is rapidly emerging as a critical pathway to safeguard communities and ecosystems from the impacts of climate variability which creates unpredictable challenges that are hard to plan for. Climate change adaptation has lagged because it involves managing many interconnected factors and the solutions are often not risk-informed for local measures.
AI offers new possibilities to address this critical gap. It can manage complex risk analyses, even in data-scarce areas, and serve as a crucial tool to link intricate global climate analyses with local adaptation measures.
AI: The game-changer for navigating complex risk analysis
AI's power lies in its ability to process and predict impacts from vast amounts of data quickly and accurately. The World Meteorological Organization highlights that AI is bringing new innovations to earth system prediction, enhancing the accuracy and speed of weather forecasts. Google and Microsoft are using AI to enhance flood forecasting, wildfire tracking and human health. Many of these models often outperform traditional forecasting techniques, but are yet to be operationalized for developing countries.
At ESCAP, therefore, initiatives like the Asia Pacific Risk and Resilience Portal (Figure 1) are leveraging predictive AI to improve multi-hazard-multi-criteria risk modeling by using open-source datasets on climate, hazards, socioeconomic factors and the environment to pinpoint vulnerable locations in developing countries. In Bhutan, where mountainous terrain and limited data pose significant challenges, disaster management policymakers were trained with the Portal's risk analytics to develop impact scenarios for climate-sensitive sectors. Similarly, for small island developing states like the Maldives, the Portal supported preparation for mid- and long-term impacts of sea level rise and other coastal hazards. AI-powered tools are critical for these countries, where data scarcity has traditionally hindered accurate climate and disaster analysis and planning.
The next frontier for AI: Bridging the gap between global climate risk and local adaptation
Transformative adaptation must be localized. While AI-powered risk analysis has progressed, tailored adaptation lags behind. AI excels in risk analysis and vulnerability assessment, but the challenge is connecting global climate risks with local geographical and socioeconomic factors to guide localized adaptation strategies.
Recent advancements demonstrate the potential of AI in this area. AI-powered apps like Farmer.Chat aid farmers in rural India by providing agricultural content, including farmer-generated resilience practice videos, in local languages. BrainBox AI helps building owners reduce energy costs by predicting temperatures using historical data.
At ESCAP, a prototype of the AI-powered adaptation tool Climawise (Figure 2) won the 2023 ESCAP innovation award and seed funding. This tool, to be housed under the Risk and Resilience Portal, first uses models powered by machine learning to create a global database of adaptation solutions linked to the specific climate risks they address. Then, using natural language processing, the tool sifts through the solutions to identify relevant adaptation measures for a specific location. The data is displayed on an interactive map that connects local geophysical and social risk factors with successful global adaptation case studies. Policymakers can identify and adapt these strategies to fit their local needs, facilitating effective and context-specific climate adaptation, contributing to national adaptation plans and achieving climate related SDGs.
The path forward: Embracing AI for a resilient future
As AI continues to advance, its role in climate adaptation will only grow more vital. While ensuring data privacy and security are paramount, including the use of personal and sensitive data in AI models, the vision of a comprehensive analysis-to-adaptation pathway holds real promise in climate proofing the Asia-Pacific region and advancing progress towards disaster and climate-related Sustainable Development Goals. Realizing the full potential of AI will require sustained investment, international collaboration and commitment to open data sharing. By embracing the full potential of AI, we can navigate the complexities of climate adaptation with foresight, paving the way for a resilient and sustainable future.