A Bayesian quantile regression framework for modeling trends in air temperature: The case for Greece

A Bayesian quantile regression framework for modeling trends in air temperature: The case for Greece | 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 A Bayesian quantile regression framework for modeling trends in air temperature: The case for Greece Athanassios Argiriou, Anna Mamara, Georgios Tsiotas This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4956757/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 17 Dec, 2024 Read the published version in Theoretical and Applied Climatology → Version 1 posted 11 You are reading this latest preprint version Abstract This study investigates the trend dynamics of some extreme air temperature bounds estimated via quantile models. In practice, we investigate the dynamics of the 5% lower, the median and the 95% upper quantile measures of the minimum and maximum temperature in various regions of Greece. For this purpose, we propose some semi-parametric quantile trend models. Our estimation is based on a Bayesian early-rejection Markov chain Monte Carlo algorithm. The climatic data used, are the mean monthly homogenized minimum and maximum air temperatures observed at several meteorological stations of the Hellenic Meteorological Service located in Greece for the 1960-2010 period. Results based on several margins of datas' distribution, reveal the strongest and the weakest inter-annual quantile trends for both temperature extremes. The results are very significant since they show the existence of time-trend heterogeneities in temperature extremes under alternative types of quantiles, time periods, geographical zones and seasons. Quantile analysis Bayesian trend analysis Air temperature trends Homogenized data Climate change Greece Full Text Additional Declarations No competing interests reported. Supplementary Files manuscript.tsiotas.airtemp.quant.appendix.2024.pdf Cite Share Download PDF Status: Published Journal Publication published 17 Dec, 2024 Read the published version in Theoretical and Applied Climatology → Version 1 posted Editorial decision: Revision requested 10 Oct, 2024 Reviews received at journal 09 Oct, 2024 Reviews received at journal 22 Sep, 2024 Reviews received at journal 16 Sep, 2024 Reviewers agreed at journal 02 Sep, 2024 Reviewers agreed at journal 02 Sep, 2024 Reviewers agreed at journal 02 Sep, 2024 Reviewers invited by journal 24 Aug, 2024 Editor assigned by journal 22 Aug, 2024 Submission checks completed at journal 22 Aug, 2024 First submitted to journal 22 Aug, 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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