Machine learning for predicting climate risk: toward a digital twin for extreme events

date:

Wednesday, Jun 1, 2022

Time:

1:50 pm

Track:

Summary:

Climate change is increasing the frequency and severity of extreme weather events. In order to quantify the impacts of climate on financial systems, improved climate models are needed with much higher spatial resolution than is currently possible. Moreover the models must be able to accurately quantify uncertainty in the frequency and severity of impacts under different climate forcing scenarios. Terrafuse AI is developing deep learning-based climate models trained on large Earth observation and simulation data sets, deployed on cloud computing infrastructure. With this approach our aim is to develop a “digital twin” of the climate system and its societal impacts so that appropriate adaptation and resilience strategies can be developed.

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