Climate Modeling and Analysis: Difference between revisions
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=== Major conferences ===
* [https://www.ametsoc.org/ '''American Meteorological Society'''] '''(AMS)''' Annual Meeting: A yearly conference organised by the AMS, usually takes place in January, location varies across different states of the USA.
*'''[https://www.agu.org/fall-meeting American Geosciences Union] (AGU)''' Fall Meeting: A yearly conference organised by the AGU, usually takes place in December, location varies across different states of the USA.
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*'''[https://www.egu.eu/ European Geosciences Union] (EGU)''': An organization supporting research in Earth, planetary, and space science in Europe.
*'''[https://www.ipcc.ch/ Intergovernmental Panel on Climate Change] (IPCC)''': A United Nations body that assesses climate change and provides policy-relevant information. IPCC provides Assessment Reports and Special Reports that provide a comprehensive summary of the state-of-the-art developments and findings.
*'''[https://www.ametsoc.org/index.cfm/stac/committees/committee-on-artificial-intelligence-applications-to-environmental-science/ Committee on Artificial Intelligence Applications to Environmental Science]''': A committee of American Meteorological Society on usage of AI and ML for applications in environmental sciences.
== Libraries and Tools ==
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* '''AI2 Climate Modeling''': The [https://github.com/ai2cm ai2cm] climate modelling toolbox provides different Python wrappers to work with climate and weather models provided by the [https://allenai.org/climate-modeling Allen Institute for AI].
* '''[https://cds.climate.copernicus.eu/#!/home Copernicus Climate Data Store]''': The EU Copernicus project provides an [https://cds.climate.copernicus.eu/api-how-to API] and [https://cds.climate.copernicus.eu/cdsapp#!/toolbox Toolbox] to with different free data like raw satellite sensor data.
* '''Meteostat Python Package''': A [https://github.com/meteostat/meteostat-python Python Package] that allows to better access and analyze historical weather and climate data.
* '''XCast''': A Python-based [https://www.frontiersin.org/articles/10.3389/fclim.2022.953262/full climate forecasting toolkit].
== Data ==
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*'''The Coupled Model Intercomparison Project (CMIP)''': A gateway to climate models in use and development, available [https://esgf-node.llnl.gov/projects/cmip5/ here]. CMIP is associated with the Earth System Grid Federation, which also provides data analysis tools and tutorials: https://esgf.llnl.gov/.
*'''[https://www.cesm.ucar.edu/projects/community-projects/MMLEA/ Large
*'''Climate and weather datasets for ML research''' are listed [http://mldata.pangeo.io/ here].
*The Earth and climate science community is also working to create [https://is-geo.org/benchmarks/ benchmark datasets]
*'''[https://cloud.google.com/public-datasets/weather Google Cloud Weather and Climate Datasets]''': Petabyte-scale weather and climate datasets from sources like NOAA’s [https://www.ncdc.noaa.gov/data-access/radar-data/nexrad NEXRAD] and NASA/USGS’s [https://landsat.gsfc.nasa.gov/ Landsat], made available for free as part of Google Cloud’s Public Datasets Program.
*'''[https://earthdata.nasa.gov/ EARTHDATA]''': NASA's gateway to Earth Science data. Data are available at multiple levels of processing.
=== Other Climate Science Datasets ===
*'''Argo float ocean data''': Argo is an international program that collects information from inside the ocean using a fleet of robotic instruments that drift with the ocean currents and move up and down between the surface and a mid-water level. Dataset available [https://argo.ucsd.edu/ here].
== References ==
<references />
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