{"id":"openalex:W3105945687","kind":"article","title":"Using Machine Learning to Parameterize Moist Convection: Potential for Modeling of Climate, Climate Change, and Extreme Events","authors":["Paul Ambrose O'Gorman","J. G. Dwyer"],"author_count":2,"year":2018,"published":"2018-01-01","venue":"DSpace@MIT (Massachusetts Institute of Technology)","cited_by":374,"doi":null,"arxiv_id":null,"nct_id":null,"source_url":"https://hdl.handle.net/1721.1/132185.2","archive_url":"https://space-kitty.com/papers/openalex:W3105945687","updated":null,"pmid":null,"pmcid":null,"openalex_id":"W3105945687","pdf_url":"https://dspace.mit.edu/bitstream/1721.1/132185.2/4/2018MS001351.pdf","abstract":null,"abstract_license":null,"license":"cc-by-nc-nd","is_open_access":true,"retracted":false,"peer_reviewed":null,"categories":["Meteorological Phenomena and Simulations"],"details":null,"provenance":"openalex","attribution":"Metadata and citation counts: OpenAlex (CC0).","topics":[{"slug":"ai-weather-climate","name":"AI Weather & Climate Modeling","domain_slug":"energy"}],"cited_in_dossiers":[]}