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Intro
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Climate Data Science: A tour
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Context Climate is what you expect
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PART 1 continued Climate models
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Earth Climate System
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Climate as a dynamical system
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How is this model computed?
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Observations
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North American Rainfall
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Multi-resolution representation
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Estimated field and prediction errors
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Ensembles
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Combining models and data
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Detection and Attribution
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Results for temperature trends
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Inference on signals
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Climate model output
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Pattern scaling
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Individual patterns
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Does this work?
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The model as data NCAR CESM
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Graphical analysis test case
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Summary Data Science challenges for the Earth System
Description:
Explore climate data science in this comprehensive lecture by Professor Doug Nychka, Director of the Institute for Mathematics Applied to Geosciences at the US National Center for Atmospheric Research. Delve into the complexities of climate modeling, Earth observation, and data analysis techniques used to understand our rapidly changing planet. Learn about the advancements in climate and weather models, the growth of Earth observation satellites, and the challenges of processing vast amounts of environmental data. Discover how new tools in data sciences are being applied to address critical questions related to climate and the environment. Gain insights into topics such as climate dynamics, multi-resolution representation, ensemble modeling, detection and attribution of climate signals, and pattern scaling. Understand the data science challenges facing Earth System research and the importance of combining models and observational data to improve our understanding of climate processes.

Climate Data Science: A Tour - Professor Doug Nychka, National Center for Atmospheric Research

Alan Turing Institute
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