Neural network based estimates of the climate impact on mortality in Germany: application to storyline climate simulations
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...
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Nature Portfolio
2024-10-01
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| Series: | Scientific Reports |
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| Online Access: | https://doi.org/10.1038/s41598-024-77398-3 |
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| author | R. Schachtschneider J. Saynisch-Wagner A. Sánchez-Benítez M. Thomas |
| author_facet | R. Schachtschneider J. Saynisch-Wagner A. Sánchez-Benítez M. Thomas |
| author_sort | R. Schachtschneider |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-7a2d78b1ba2e427ebfd57d4809694516 |
| institution | OA Journals |
| issn | 2045-2322 |
| language | English |
| publishDate | 2024-10-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-7a2d78b1ba2e427ebfd57d48096945162025-08-20T02:16:59ZengNature PortfolioScientific Reports2045-23222024-10-011411910.1038/s41598-024-77398-3Neural network based estimates of the climate impact on mortality in Germany: application to storyline climate simulationsR. Schachtschneider0J. Saynisch-Wagner1A. Sánchez-Benítez2M. Thomas3Helmholtz Centre Potsdam GFZ German Research Centre for GeosciencesHelmholtz Centre Potsdam GFZ German Research Centre for GeosciencesAlfred Wegener Institute, Helmholtz Centre for Polar and Marine ResearchHelmholtz Centre Potsdam GFZ German Research Centre for GeosciencesAbstract 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.https://doi.org/10.1038/s41598-024-77398-3Climate changeMachine learningMortality predictionHuman healthStoryline simulations |
| spellingShingle | R. Schachtschneider J. Saynisch-Wagner A. Sánchez-Benítez M. Thomas Neural network based estimates of the climate impact on mortality in Germany: application to storyline climate simulations Scientific Reports Climate change Machine learning Mortality prediction Human health Storyline simulations |
| title | Neural network based estimates of the climate impact on mortality in Germany: application to storyline climate simulations |
| title_full | Neural network based estimates of the climate impact on mortality in Germany: application to storyline climate simulations |
| title_fullStr | Neural network based estimates of the climate impact on mortality in Germany: application to storyline climate simulations |
| title_full_unstemmed | Neural network based estimates of the climate impact on mortality in Germany: application to storyline climate simulations |
| title_short | Neural network based estimates of the climate impact on mortality in Germany: application to storyline climate simulations |
| title_sort | neural network based estimates of the climate impact on mortality in germany application to storyline climate simulations |
| topic | Climate change Machine learning Mortality prediction Human health Storyline simulations |
| url | https://doi.org/10.1038/s41598-024-77398-3 |
| work_keys_str_mv | AT rschachtschneider neuralnetworkbasedestimatesoftheclimateimpactonmortalityingermanyapplicationtostorylineclimatesimulations AT jsaynischwagner neuralnetworkbasedestimatesoftheclimateimpactonmortalityingermanyapplicationtostorylineclimatesimulations AT asanchezbenitez neuralnetworkbasedestimatesoftheclimateimpactonmortalityingermanyapplicationtostorylineclimatesimulations AT mthomas neuralnetworkbasedestimatesoftheclimateimpactonmortalityingermanyapplicationtostorylineclimatesimulations |