{"id":1231,"date":"2023-07-03T02:53:41","date_gmt":"2023-07-03T01:53:41","guid":{"rendered":"https:\/\/research.reading.ac.uk\/s2s-summit2023\/?page_id=1231"},"modified":"2023-07-03T02:53:41","modified_gmt":"2023-07-03T01:53:41","slug":"abstract259","status":"publish","type":"page","link":"https:\/\/research.reading.ac.uk\/s2s-summit2023\/programme\/abstract259\/","title":{"rendered":"Abstract 259"},"content":{"rendered":"

[vc_row][vc_column][vc_column_text]Abstract ID:<\/strong> 259<\/p>\n

An Emergent Constraint to Improve the Representation of Biosphere-Atmosphere Feedbacks in Earth System Models<\/h2>\n

Lead Author:<\/strong> Julia Green
\nUniversity of Arizona, United States of America
\n<\/span><\/p>\n

Keywords:<\/strong> biosphere-atmosphere feedbacks, emergent constraint, seasonal forecasting, surface temperatures, vegetation<\/p>\n

Abstract:<\/strong> Biosphere-atmosphere feedbacks operate on subseasonal to seasonal timescales. Therefore, accurately representing vegetation processes and their interactions with the atmosphere in models is essential to improving subseasonal to seasonal forecasts. One related process, the response of vegetation canopy conductance (gc) to changes in moisture availability (\u03b3_gc^m) is a major source of uncertainty in weather and climate projections. Representing \u03b3_gc^m accurately in Earth System Models (ESMs) is particularly problematic because no regional scale gc observations exist with which to evaluate it. Here, we overcome this challenge by deriving an emergent constraint on \u03b3_gc^m across ESMs from Phase 6 of the Coupled Model Intercomparison Project (CMIP6). We leverage an ensemble of satellite, reanalysis and station-based estimates of surface temperatures, which are physically and statistically linked to \u03b3_gc^m due to the local cooling effect of gc from transpiration. We find that models systemically underestimate \u03b3_gc^m by ~50%, particularly in semi-arid grasslands, croplands, and savannas. Based on the mediating effect of gc on carbon, water and energy fluxes through land-atmosphere interactions, the underestimation of modeled \u03b3_gc^m in these regions contributes to biases in these three fluxes. Our results provide a novel benchmark to improve model representation of vegetation dynamics and biosphere-atmosphere feedbacks in these regions, thus improving forecasting ability under future climate change scenarios.<\/p>\n

Co-authors:
\n<\/strong>Yao Zhang (Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China)
\nXiangzhong Luo (Department of Geography, National University of Singapore, Singapore; Center for Nature-based Climate Solutions, National University of Singapore, Singapore)
\nTrevor F. Keenan (Department of Environmental Science, Policy, and Management, University of California Berkeley, Berkeley, California, USA; Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA)[\/vc_column_text][vc_separator][\/vc_column][\/vc_row][vc_row][vc_column width=”1\/6″][vc_single_image image=”344″ img_size=”full” onclick=”custom_link” link=”http:\/\/s2sprediction.net\/”][\/vc_column][vc_column width=”1\/6″][vc_single_image image=”345″ img_size=”full” onclick=”custom_link” link=”https:\/\/public.wmo.int\/en”][\/vc_column][vc_column width=”1\/6″][vc_single_image image=”346″ img_size=”full” onclick=”custom_link” link=”https:\/\/community.wmo.int\/activity-areas\/wwrp”][\/vc_column][vc_column width=”1\/6″][vc_single_image image=”347″ img_size=”full” onclick=”custom_link” link=”https:\/\/www.wcrp-climate.org\/”][\/vc_column][vc_column width=”1\/6″][vc_single_image image=”348″ img_size=”full”][\/vc_column][vc_column width=”1\/6″][vc_single_image image=”349″ img_size=”full” onclick=”custom_link” link=”https:\/\/www.reading.ac.uk\/”][\/vc_column][\/vc_row]<\/p>\n","protected":false},"excerpt":{"rendered":"

[vc_row][vc_column][vc_column_text]Abstract ID: 259 An Emergent Constraint to Improve the Representation of Biosphere-Atmosphere Feedbacks in Earth System Models Lead Author: Julia Green University of Arizona, United States of America Keywords: biosphere-atmosphere…Read More ><\/a><\/p>\n","protected":false},"author":145,"featured_media":0,"parent":528,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"__cvm_playback_settings":[],"__cvm_video_id":"","footnotes":""},"coauthors":[13],"class_list":["post-1231","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"\nAbstract 259 - WWRP\/WCRP S2S Summit 2023<\/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:\/\/research.reading.ac.uk\/s2s-summit2023\/programme\/abstract259\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Abstract 259 - 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