Evaluating Hydrostatic vs. Non-Hydrostatic Dynamics in RegCM5: A 50-Year Simulation of Near-Surface Wind Speed over the Yellow River Basin | 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 Evaluating Hydrostatic vs. Non-Hydrostatic Dynamics in RegCM5: A 50-Year Simulation of Near-Surface Wind Speed over the Yellow River Basin Yimeng Jiao, Jiayin Deng, Qingjie Li, Na Zhao, TiangXiang Yue, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8801849/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 5 You are reading this latest preprint version Abstract Accurate simulation of near-surface wind speeds over complex terrain is essential for wind energy assessment, ecological conservation, and hydro-climatic change studies. This study presents a 50-year (1971–2020) evaluation of the RegCM5 regional climate model over the Yellow River Basin, China. Three dynamical configurations are systematically compared: the traditional hydrostatic core (Model 1), the MM5-like non-hydrostatic core (Model 2), and the newly introduced Moloch non-hydrostatic core (Model 3). Driven by ERA5 reanalysis at a 25-km resolution, the simulations are validated against high-density observations (CN05.1). Results indicate that while all configurations capture the spatial climatology, they exhibit a systematic positive wind speed bias (+ 1.3 to + 2.8 m s⁻¹), particularly in the rugged Upper Reaches due to sub-grid topographic smoothing.. However, Model 3 (Moloch) consistently outperforms the other configurations, achieving the lowest bias magnitude and the highest distributional fidelity (Perkins Skill Score). Regarding long-term trends, all models reproduce the interannual variability driven by large-scale circulation but fail to capture the magnitude of the observed "terrestrial stilling", highlighting a critical need to incorporate time-varying land use forcing in future multi-decadal experiments. Crucially, the study reveals a decisive disparity in computational efficiency. While the traditional non-hydrostatic core (Model 2) is computationally expensive due to strict CFL stability constraints (dt = 25 s), the Moloch core (Model 3) maintains numerical stability with a significantly larger time step (dt = 200 s). This capability results in a 58% reduction in total runtime compared to Model 2 and a 17% reduction compared to the hydrostatic baseline, without compromising physical accuracy. Consequently, the Moloch core emerges as the optimal configuration for long-term regional climate downscaling over complex terrains, effectively bridging the gap between high physical fidelity and numerical efficiency. RegCM5 Dynamical Cores Wind Speed Yellow River Basin Computational Efficiency Moloch Full Text Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Major Revision 25 Mar, 2026 Reviewers agreed at journal 23 Feb, 2026 Reviewers invited by journal 23 Feb, 2026 Editor assigned by journal 22 Feb, 2026 First submitted to journal 14 Feb, 2026 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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-8801849","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":595784381,"identity":"19fbed7a-d008-49df-a33a-d1476f5894a3","order_by":0,"name":"Yimeng 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