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CausalEarth aims to enhance understanding of climate variability by developing new statistical methods for causal inference. The project focuses on the interdependencies of climate modes, improving the evaluation of climate models through advanced machine learning techniques.
CausalEarth is an interdisciplinary project, aiming to improve our understanding of the interdependencies between major drivers (modes) of climate variability by developing novel statistical causal inference methods for both observations and model data.
Disentangling the interdependencies of the major modes, such as El Nino Southern Oscillation and the North Atlantic Oscillation, is key to understand regional climate, and essential for process-based climate model evaluation.
The modes' interdepe…
UNIVERSITAET POTSDAM
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