{"id":756,"date":"2023-07-02T18:47:06","date_gmt":"2023-07-02T17:47:06","guid":{"rendered":"https:\/\/research.reading.ac.uk\/s2s-summit2023\/?page_id=756"},"modified":"2023-07-02T18:48:26","modified_gmt":"2023-07-02T17:48:26","slug":"abstract044","status":"publish","type":"page","link":"https:\/\/research.reading.ac.uk\/s2s-summit2023\/programme\/abstract044\/","title":{"rendered":"Abstract 044"},"content":{"rendered":"

[vc_row][vc_column][vc_column_text]Abstract ID:<\/strong> 044<\/p>\n

Multi-model Assessment of the Sub-seasonal Predictive Skill for the Year-round Atlantic-European Weather Regimes<\/h2>\n

Lead Author:<\/strong> Marisol Osman
\nKarlsruhe Institute of Technology, Germany
\n<\/span><\/p>\n

Keywords:<\/strong> North Atlantic Oscillation, Blocking<\/p>\n

Abstract:<\/strong> The prediction skill of sub-seasonal forecast models is evaluated for seven year-round weather regimes in the Atlantic-European region. Re-forecasts based on models from three prediction centers (the European Centre for Medium-Range Weather Forecasts, the National Center for Environmental Prediction and the UK Met Office) for the 2000-2015 period are considered and compared against weather regimes obtained from ERA Interim reanalysis over the same period. We first focus on the assessment of skill, placing emphasis on the differences in the performance for each weather regime depending on the time of the year. Then, we consider the year-to-year evolution of skill and the role of interannual variability of the atmosphere in this skill. Finally, we study the changes in skill of weather regimes in the models analyzed with respect to previous model versions.
\nResults show that predicting weather regimes using a life-cycle criteria adds value over using a simple weather regime definition or the full 500-hPa geopotential height field over the regime domain. The ECMWF model shows the highest skill for most of the weather regimes and seasons, followed closely by the NCEP model. The average regime skill horizon is 3 days longer for ECMWF and NCEP models than for the UKMO model, mainly due to the differences in skill in winter. Greenland Blocking tends to have the longest year-round skill horizon for the three models driven by their performance in winter. On the other hand, the skill is lowest for the European Blocking regime for the three models, followed by Scandinavian Blocking. Furthermore, models struggle to forecast random flow situations in comparison to weather regimes. Related to this, the analysis of the daily variability of skill reveals that there is a predictability gap between winter and summer and the transitional seasons that can be partly linked to the daily variability of no regime events. In addition, the interannual variability of wintertime skill is associated with the anomalous occurrence of no regime: the winters with fewer no regime days have higher skill. Finally, we find that the skill has improved in ECMWF and NCEP models with newer versions. For the NCEP model this improvement leads to an extension of the skill by around 4 days. This study represents the first systematic multi-model assessment of the seven year-round weather regimes with different state-of-the-art sub-seasonal models and represents a contribution towards a more objective assessment of the evolution of weather regimes for days to weeks ahead for a better forecast guidance.<\/p>\n

Co-authors:
\n<\/strong>Christian M. Grams (Institute of Meteorology and Climate Research (IMK-TRO), Department of Tropospheric Research, Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany)
\nRemo Beerli (Axpo Solutions AG, Baden, Switzerland)[\/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: 044 Multi-model Assessment of the Sub-seasonal Predictive Skill for the Year-round Atlantic-European Weather Regimes Lead Author: Marisol Osman Karlsruhe Institute of Technology, Germany Keywords: North Atlantic Oscillation, Blocking…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-756","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"\nAbstract 044 - 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\/abstract044\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Abstract 044 - 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