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Climate Modeling and Analysis: Difference between revisions

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=== Uniting data, ML, and climate science ===
*'''Data for climate models''': Assimilation of diverse sources can improve climate models, and machine learning can transform raw sensor output into more relevant derived data. Well-curated benchmark datasets have the potential to advance several geoscience problems.
* Data for climate models
*'''Accelerating climate models''': Physical constraints are key ingredients for cloud, aerosol, ice sheet, and sea level models. Traditional solutions to these physics-based models are computationally expensive, but machine learning components can help alleviate the most problematic bottlenecks.
* Accelerating climate models
*'''Working with climate models''': It is possible to streamline existing climate models, pruning them down to key relationships simplifying computation with ensembles.
* Working with climate models
=== Forecasting extreme events ===
* Storm tracking: While climate models can forecast long-term changes in the climate system, separate systems are required to detect specific extreme weather phenomena, like cyclones, atmospheric rivers, and tornadoes.
* Storm tracking
* Local forecasts: Machine learning can be used to refine what are otherwise coarse-grained forecasts. These high-resolution forecasts can guide improvements in system robustness and resilience.
* Local forecasts
== Background Readings ==
*'''Introduction to climate dynamics and climate modeling (2010)'''<ref>{{Cite book|title=Climate system dynamics and modeling|last=Goosse|first=Hugues|date=2015|publisher=Cambridge University Press|isbn=978-1-107-08389-9|location=New York, NY}}</ref>: A technical treatment of the climate system, energy balance, climate modeling, and climate perturbations. Available [http://www.climate.be/textbook/contents.html here].
*'''Principles of Planetary Climate (2010)'''<ref>{{Cite book|url=https://www.worldcat.org/title/mediawiki/oclc/601113992|title=Principles of planetary climate|last=Pierrehumbert|first=Raymond T.|date=2010|publisher=Cambridge University Press|isbn=978-0-521-86556-2|location=Cambridge ; New York|oclc=601113992}}</ref>: An introduction to the physics of climate, with examples in python.
=== Other ===
*'''An Introduction to Climate Modeling (2014)'''<ref>{{Cite web|url=https://www.youtube.com/watch?v=XGi2a0tNjOo&feature=youtu.be|title=5.1 Introduction to Climate Modeling - YouTube|website=www.youtube.com|access-date=2020-09-24}}</ref>: A video lesson from Climate Literacy's Youtube channel. Available [https://www.youtube.com/watch?v=XGi2a0tNjOo&feature=youtu.be here].
*'''Oxford Research Encyclopedia of Climate Science'''<ref>{{Cite web|url=https://oxfordre.com/climatescience/climatescience/|title=Oxford Research Encyclopedia of Climate Science|website=Oxford Research Encyclopedia of Climate Science|language=en|access-date=2020-11-19}}</ref>: A collection of articles on the climate systems, impacts of climate change, and the methods used in climate science.
== Online Courses and Course Materials ==
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