{"id":830218,"date":"2022-03-28T08:25:24","date_gmt":"2022-03-28T15:25:24","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=830218"},"modified":"2022-03-28T08:25:24","modified_gmt":"2022-03-28T15:25:24","slug":"quantifying-causal-pathways-of-teleconnections","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/quantifying-causal-pathways-of-teleconnections\/","title":{"rendered":"Quantifying Causal Pathways of Teleconnections"},"content":{"rendered":"
Teleconnections are sources of predictability for regional weather and climate, but the relative contributions of different teleconnections to regional anomalies are usually not understood. While physical knowledge about the involved mechanisms is often available, how to quantify a particular causal pathway from data are usually unclear. Here, we argue for adopting a causal inference-based framework in the statistical analysis of teleconnections to overcome this challenge. A causal approach requires explicitly including expert knowledge in the statistical analysis, which allows one to draw quantitative conclusions. We illustrate some of the key concepts of this theory with concrete examples of well-known atmospheric teleconnections. We further discuss the particular challenges and advantages these imply for climate science and argue that a systematic causal approach to statistical inference should become standard practice in the study of teleconnections.<\/p>\n","protected":false},"excerpt":{"rendered":"
Teleconnections are sources of predictability for regional weather and climate, but the relative contributions of different teleconnections to regional anomalies are usually not understood. While physical knowledge about the involved mechanisms is often available, how to quantify a particular causal pathway from data are usually unclear. Here, we argue for adopting a causal inference-based framework […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[198583],"msr-publication-type":[193715],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-830218","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-ecology-environment","msr-locale-en_us"],"msr_publishername":"","msr_edition":"","msr_affiliation":"","msr_published_date":"2021-12-1","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"Bulletin of the American Meteorological Society","msr_volume":"102","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"12","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"url","viewUrl":"false","id":"false","title":"https:\/\/journals.ametsoc.org\/view\/journals\/bams\/102\/12\/BAMS-D-20-0117.1.xml","label_id":"243109","label":0}],"msr_related_uploader":"","msr_attachments":[],"msr-author-ordering":[{"type":"text","value":"Marlene Kretschmer","user_id":0,"rest_url":false},{"type":"text","value":"Samantha V. Adams","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Alberto Arribas Herranz","user_id":41275,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Alberto Arribas Herranz"},{"type":"text","value":"Rachel Prudden","user_id":0,"rest_url":false},{"type":"text","value":"Niall Robinson","user_id":0,"rest_url":false},{"type":"text","value":"Elena Saggioro","user_id":0,"rest_url":false},{"type":"text","value":"Theodore G. Shepherd","user_id":0,"rest_url":false}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[847351,768895],"msr_project":[809614],"publication":[],"video":[],"download":[],"msr_publication_type":"article","related_content":{"projects":[{"ID":809614,"post_title":"Sustainability Science Team","post_name":"sustainability-science-team","post_type":"msr-project","post_date":"2022-03-28 10:57:06","post_modified":"2023-06-28 11:54:15","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/sustainability-science-team\/","post_excerpt":"Building a\u202fmore environmentally sustainable\u202ffuture \u201cWe have a growing team of\u202fsustainability scientists working with\u202fresearchers, businesses, governments,\u202fand non-profit organizations around the\u202fworld to help Microsoft, its customers\u202fand partners, and the world to build a\u202fmore environmentally sustainable\u202ffuture.\u201d The Sustainability Science Team, part of our Corporate Environmental Sustainability area, ensures that Microsoft\u2019s sustainability strategy and programs are informed by the best available science by working with researchers inside and outside Microsoft. 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