Hi all,
Thank you for your part in making our first Forecasting and Prediction WG meeting on ML for modelling and prediction such a success!
Here are the presentations from the day that we have received permission to share:
Getting Started
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Getting started with Machine Learning - Sanaa Hobeichi (269.2 KB download)
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Key developments in ML for weather and climate modelling in the last ~18 months - Catherine de Burgh-Day (11.6 MB download)
Applications of ML
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Siteboost: Gradient Boosted Decision Trees for Site Optimised Forecasts - Tennessee Leeuwenburg (1.8 MB download)
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Random Forests for identifying predictors of flash droughts. - Pallavi Goswami (10.0 MB download)
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Dynamic Bayesian networks for evaluation of Granger causal relationships in climate models - Terry O’Kane (5.1 MB download)
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Harnessing the Potential of Remote Sensing and Machine Learning for Improving Bushfire Fuels Data - Abolfazl Abdollahi (11.6 MB download)
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A framework for embedding ML physics into climate models - Steve Sherwood (5.1 MB download)
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A deep learning model for forecasting global monthly mean sea surface temperature anomalies using CNN (Unet-LSTM) and transformers (TUnet) - John Taylor (11.9 MB download)
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Cutting the cost of downscaling using Machine Learning - Sanaa Hobeichi (5.1 MB download)
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ML Big and small - what hardware and software do you need? - Tennessee Leeuwenburg (7.4 MB download)