Modelling Extremal Temperatures using Extreme Value Theory: A case for Namibia

Modelling Extremal Temperatures using Extreme Value Theory: A case for Namibia | 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 Modelling Extremal Temperatures using Extreme Value Theory: A case for Namibia Samuel M Nuugulu, Markus Mandume This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6177853/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Temperature extremes (commonly referred to as cold spell and heat waves) are regarded as the most significant climate events and have been extensively studied over the last several decades. The heat waves and drought during the summer of 2017 in Namibia sent shock waves to the energy industry, farming and water resources infrastructures and health system in terms of system vulnerability and management. This paper focuses on modeling of extreme temperatures using Extreme Value Theory (EVT). The aim is to explore the frequency of occurrences of extremely low and extremely high temperatures. The dataset consists of 27900 daily maximum temperatures from 1990 to 2019 collected from the Namibia Meteorological services. Block maxima (BM) approach is used to fit the Generalized Extreme Value Distribution (GEVD) while the Peak Over Threshold approach is employed to fit the Generalized Pareto Distribution (GPD) model which analyzes the upper and lower tails of the distribution of the data. The Maximum Likelihood Estimation (MLE) technique is used to estimate the parameters in two distributions. The model’s goodness of fit is assessed graphically means, such as probability plots, quantile-quantile plots and mean excess plots as well using some empirical goodness-of-fit tests. Results indicate that, the models under consideration provide overall good fits for the data Subject Classifications: 68Txx, 68Pxx, 68Nxx. Climate Analysis and Modeling Applied Statistics Applied Mathematics Extreme Value theory (EVT) Block Maxima (BM) Extreme Temperature (EV) Generalized Extreme Value Distribution Generalized Pareto Distribution (GPD) Maximum Likelihood Estimation (MLE) Peak Over threshold (POT) Namibia Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted 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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