Climate Modeling and Analysis: Difference between revisions
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[[File:Climate_prediction.png|alt=|right|148x148px|The main avenues through which machine learning can support climate science, as described in <ref>{{Cite journal|title=Tackling Climate Change with Machine Learning|url=https://arxiv.org/pdf/1906.05433.pdf#page=63&zoom=100,109,256}}</ref>.]]
The first global warming prediction was made in 1896, when Arrhenius estimated that burning fossil fuels could eventually release enough CO2 to warm the Earth by 5°C. The fundamental physics underlying those calculations has not changed, but our predictions have become far more detailed and precise. The predominant predictive tools are climate models, known as General Circulation Models (GCMs) or Earth System Models (ESMs). These models inform local and national government decisions<ref>{{Cite book|url=https://www.ipcc.ch/sr15/|title=Global warming of 1.5C. An IPCC special report on the impacts of global warming of 1.5C above
pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the
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Assessment Report of the Intergovernmental Panel on Climate Change|date=2014}}</ref><ref>{{Cite book|url=https://www.ipcc.ch/report/ar5/wg3/|title=Climate Change 2014: Synthesis Report. Contribution of Working Groups I, II and III to the Fifth
Assessment Report of the Intergovernmental Panel on Climate Change|author=IPCC|date=2014}}</ref>), help people calculate their climate risks (see [[Policy, Markets, and Decision Science]] and [[Climate Change Adaptation]]) and allow us to estimate the potential impacts of [[solar geoengineering]].
Recent trends have created opportunities for ML to advance the state-of-the-art in climate prediction. First, new and cheaper satellites are creating petabytes of climate observation data<ref>{{Cite web|url=https://earth.esa.int/eogateway/}}</ref><ref>{{Cite web|url=earthdata.nasa.gov}}</ref>. Second, massive climate modeling projects are generating petabytes of simulated climate data<ref>{{Cite web|url=cmip.llnl.gov}}</ref>. Third, climate forecasts are computationally expensive<ref>{{Cite journal|title=Position paper on high performance computing needs in Earth system prediction|last=Carman|first=T|coauthors=T Clune, F Giraldo, M Govett, B Gross, A Kamrathe, T Lee, D McCarren, J Michalakes, S Sandgathe,
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