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Kenny, Ian and Kbaier, Dhouha (2024). Adaptive Machine Learning: Pioneering Climate Modelling for a Sustainable Future. Climate Perspectives, Winter 2023/24.
URL: https://issuu.com/binarycarbon/docs/climate_perspe...
Plain Language Summary
By developing a model that adapts dynamically to smaller datasets, we aim not only to enhance climate predictions but also to inspire positive changes in policy, decision making and behaviour for climate adaptation. The output of the model takes the form of probabilities as to an event occurring. However, the accuracy of these probabilities are a significant improvement over the current method of forecasting. This allows for better planning of future resource need in the short to medium-term: we are currently working on a five year adaptive cycle.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)
