The impact of vertical model levels on the prediction of MJO teleconnections. Part 2: The stratospheric pathway in the UFS global coupled model

The impact of vertical model levels on the prediction of MJO teleconnections. Part 2: The stratospheric pathway in the UFS global coupled model | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The impact of vertical model levels on the prediction of MJO teleconnections. Part 2: The stratospheric pathway in the UFS global coupled model Chaim Garfinkel, Zheng Wu, Priyanka Yadav, Zachary Lawrence, Daniela Domeisen, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3922041/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Dec, 2024 Read the published version in Climate Dynamics → Version 1 posted 5 You are reading this latest preprint version Abstract This study continues the evaluation of the prediction of MJO teleconnections in two versions of the NOAA Unified Forecast System (UFS): prototype 5 (UFS5) and prototype 6 (UFS6). The key difference between the two prototypes is in the number of vertical layers (127 in UFS6 vs. 64 in UFS5) and model top (80 km in UFS6 vs. 54 km in UFS5), and the role of this increased resolution for the stratospheric pathway of MJO teleconnections is explored. The higher resolution prototype (UFS6) suffers from larger biases in its representation of tropospheric stationary waves, though both simulate a reasonable flux of wave activity entering the stratosphere. The stratospheric polar vortex in both is over-sensitive to incoming wave activity, however both simulate a reasonable downward propagation of vortex anomalies within the stratosphere and down to the troposphere. The net effect is that both simulate the stratospheric pathway of the MJO better than has been documented for any forecasting system. This allows them to predict, e.g., near-surface temperature over Eurasia with some skill on subseasonal timescales (week 3 to 5). However this success could be the result of ``two wrongs making a right", and as individual biases are fixed, skill could temporarily be reduced. Overall, the two prototypes show similar performance in simulating the stratospheric route, suggesting that in the UFS, the increase in model vertical resolution has limited impact on the prediction of MJO teleconnections via the stratosphere. Madden Julian Oscillation subseasonal predictability stratosphere-troposphere coupling Full Text Cite Share Download PDF Status: Published Journal Publication published 13 Dec, 2024 Read the published version in Climate Dynamics → Version 1 posted Editorial decision: Major Revision 26 Jul, 2024 Reviewers agreed at journal 18 Feb, 2024 Reviewers invited by journal 06 Feb, 2024 Editor assigned by journal 02 Feb, 2024 First submitted to journal 01 Feb, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3922041","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":271661828,"identity":"e6ed1e83-7cca-4927-9be9-2d672c2b12da","order_by":0,"name":"Chaim 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