A Digital Twin for Climate Extremes Using Artificial Intelligence

A novel approach and methodology is developed to detect and characterize the changes in climate extreme events using Artificial Intelligence. These machine learning techniques, especially neural networks, can process large climate simulation ensembles better than traditional statistical methods. They therefore better assess uncertainties associated with the various projected IPCC (Intergovernmental Panel on Climate Change) scenarios and climate assessments, in a Digital Twin environment. The tool will enable end users to perform on-demand what-if scenarios in order to better evaluate the impact of climate change on several real-world applications in specific regions to better adapt and prepare the society.