{"id":87864,"date":"2026-08-19T10:56:10","date_gmt":"2026-08-19T09:56:10","guid":{"rendered":"https:\/\/www.lse.ac.uk\/granthaminstitute\/?post_type=publication&#038;p=87864"},"modified":"2026-08-25T08:56:36","modified_gmt":"2026-08-25T07:56:36","slug":"bridging-the-weather-and-climate-divide-with-artificial-intelligence","status":"publish","type":"publication","link":"https:\/\/www.lse.ac.uk\/granthaminstitute\/publication\/bridging-the-weather-and-climate-divide-with-artificial-intelligence\/","title":{"rendered":"Bridging the weather and climate divide with artificial intelligence"},"content":{"rendered":"<!DOCTYPE html PUBLIC \"-\/\/W3C\/\/DTD HTML 4.0 Transitional\/\/EN\" \"http:\/\/www.w3.org\/TR\/REC-html40\/loose.dtd\">\n<?xml encoding=\"UTF-8\"><h3 class=\"wp-block-heading\">Journal<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\"><em>Nature Communications<\/em>, Vol. 17, Article 8578 (2026)<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Authors<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Camps-Valls G, Carrassi A, de Melo Vir&iacute;ssimo F*, Debeire K, Fern&aacute;ndez-Torres M, Hess P, Heuer H, Mankovich N, Montero D, Rodrigo-Bonet E, Serva F, Sitokonstantinou V, White A, Cohrs K, Wider J, Reimers C, Bountos NI, Papoutsis I, Gentine P, Eyring V<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><em>*The starred author is a contributor from the Grantham Research Institute<\/em><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Weather and climate shape every aspect of our lives, yet for decades they have been studied as separate worlds &ndash; one concerned with what happens tomorrow, the other with what awaits us over the coming decades. This long-standing divide has slowed progress in both fields. Here, we argue that artificial intelligence (AI) is helping to dissolve the boundary between them. By learning directly from vast streams of Earth observations, AI is starting to predict both tomorrow&rsquo;s storm and next century&rsquo;s climate within a single, unified framework. We show how this convergence is already underway, why weather and climate science have much to gain from each other, and what still stands in the way &ndash; from trust, transparency, and fairness to the energy cost of computation and the risk of widening global inequalities. Realizing this vision will demand not only better algorithms but a new culture of collaboration across scientific communities, operational centers, fields and disciplines. Done well, a unified, AI-driven Earth science could deliver faster, more reliable, and more actionable predictions &ndash; helping societies anticipate and adapt to a rapidly warming planet.<br><\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>DOI:<\/strong> 10.1038\/s41467-026-75787-y<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n","protected":false},"excerpt":{"rendered":"<!DOCTYPE html PUBLIC \"-\/\/W3C\/\/DTD HTML 4.0 Transitional\/\/EN\" \"http:\/\/www.w3.org\/TR\/REC-html40\/loose.dtd\">\n<?xml encoding=\"UTF-8\"><p>By learning directly from vast streams of Earth observations, AI is starting to predict both tomorrow&rsquo;s storm and next century&rsquo;s climate within a single, unified framework. The authors of this paper show how this convergence is already underway, why weather and climate science have much to gain from each other, and what still stands in the way&mdash;from trust, transparency, and fairness to the energy cost of computation and the risk of widening global inequalities.<\/p>\n\n","protected":false},"author":80,"featured_media":0,"template":"","tags":[],"publication-type":[436],"topic_area":[],"class_list":["post-87864","publication","type-publication","status-publish","hentry","publication-type-research-articles"],"acf":{"exclude_from_sync":{"ref_value":"field_560538b0e7350","value":"0","type":false,"post_type":""},"show_translations_widget":{"ref_value":"field_6203d588c41e8","value":"0","type":false,"post_type":""},"downloads":{"ref_value":"field_52f16cc1a80f2","value":false,"type":"repeater","post_type":""},"rss_newsletter":{"ref_value":"field_54f5c2c1544d8","value":"","type":false,"post_type":""},"profile_link":{"ref_value":"field_52f164b5189e9","value":["francisco-de-melo-virissimo"],"type":"relationship","post_type":"profile"},"article_link":{"ref_value":"field_52eee3c7f0586","value":"https:\/\/www.nature.com\/articles\/s41467-026-75787-y","type":false,"post_type":""},"article_link_title":{"ref_value":"field_5322399d89d42","value":"External link to article","type":false,"post_type":""},"spotlight":{"ref_value":"field_52f80896506d3","value":"","type":false,"post_type":""}},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Bridging the weather and climate divide with artificial intelligence - Grantham Research Institute on climate change and the environment<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.lse.ac.uk\/granthaminstitute\/publication\/bridging-the-weather-and-climate-divide-with-artificial-intelligence\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Bridging the weather and climate divide with artificial intelligence - Grantham Research Institute on climate change and the environment\" \/>\n<meta property=\"og:description\" content=\"By learning directly from vast streams of Earth observations, AI is starting to predict both tomorrow\u2019s storm and next century\u2019s climate within a single, unified framework. 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