Neural network based estimates of the climate impact on mortality in Germany-application to storyline climate simulations

Neural network based estimates of the climate impact on mortality in Germany-application to storyline climate simulations | 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 Article Neural network based estimates of the climate impact on mortality in Germany-application to storyline climate simulations Reyko Schachtschneider, Jan Saynisch-Wagner, Antonio Sánchez-Benitez, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3758347/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Oct, 2024 Read the published version in Scientific Reports → Version 1 posted 12 You are reading this latest preprint version Abstract The aim of this work is the prediction of heat-related mortality for Germany under future, i.e. hotter, climate conditions. The prediction is made based on 2m temperature data from climate storyline simulations using machine learning techniques. We use an echo state network for linking the outputs of storyline climate simulations to the target data. The target data are all-cause mortality rates of Germany for all ages. The network is trained with present day climate model outputs. Model outputs of future, i.e. 2K and 4K warmer, storylines are used to predict mortality rates under such climatic conditions. We find that we can train an echo state network with recent temperature data and mortality and make plausible predictions about expected developments of mortality in Germany based on future climate storylines. The trained network can successfully predict mortality rates for future climate conditions. We find increased mortality during the summer months which is attributed to the presence of more severe heat waves. The mortality decrease found during winter can be explained milder winters leading to fewer deaths caused by respiratory diseases. However, mortality in winter is largely influenced by other factors such as influenza waves or vaccination rate and explainability due to temperature is limited. Earth and environmental sciences/Climate sciences/Climate change/Climate change impacts Health sciences/Risk factors Full Text Additional Declarations No competing interests reported. Supplementary Files mainnatsr.tex scenic.bib Cite Share Download PDF Status: Published Journal Publication published 30 Oct, 2024 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 15 Jul, 2024 Reviews received at journal 30 Jun, 2024 Reviewers agreed at journal 23 May, 2024 Reviewers agreed at journal 20 Apr, 2024 Reviews received at journal 05 Feb, 2024 Reviewers agreed at journal 02 Feb, 2024 Reviewers agreed at journal 31 Jan, 2024 Reviewers invited by journal 18 Jan, 2024 Editor assigned by journal 10 Jan, 2024 Editor invited by journal 10 Jan, 2024 Submission checks completed at journal 10 Jan, 2024 First submitted to journal 15 Dec, 2023 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-3758347","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":266520377,"identity":"1f9aafda-2f6d-402c-b6f1-6161bd9fe54e","order_by":0,"name":"Reyko Schachtschneider","email":"data:image/png;base64,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","orcid":"","institution":"Helmholtz Centre Potsdam - 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