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Developing a Heatwave Early Warning System for Sweden: Evaluating Sensitivity of Different Epidemiological Modelling Approaches to Forecast Temperatures
SMHI, Research Department, Air quality.ORCID iD: 0000-0002-2757-2864
2015 (English)In: International Journal of Environmental Research and Public Health, ISSN 1661-7827, E-ISSN 1660-4601, Vol. 12, no 1, p. 254-267Article in journal (Refereed) Published
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Abstract [en]

Over the last two decades a number of heatwaves have brought the need for heatwave early warning systems (HEWS) to the attention of many European governments. The HEWS in Europe are operating under the assumption that there is a high correlation between observed and forecasted temperatures. We investigated the sensitivity of different temperature mortality relationships when using forecast temperatures. We modelled mortality in Stockholm using observed temperatures and made predictions using forecast temperatures from the European Centre for Medium-range Weather Forecasts to assess the sensitivity. We found that the forecast will alter the expected future risk differently for different temperature mortality relationships. The more complex models seemed more sensitive to inaccurate forecasts. Despite the difference between models, there was a high agreement between models when identifying risk-days. We find that considerations of the accuracy in temperature forecasts should be part of the design of a HEWS. Currently operating HEWS do evaluate their predictive performance; this information should also be part of the evaluation of the epidemiological models that are the foundation in the HEWS. The most accurate description of the relationship between high temperature and mortality might not be the most suitable or practical when incorporated into a HEWS.

Place, publisher, year, edition, pages
2015. Vol. 12, no 1, p. 254-267
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Environmental Sciences
Research subject
Environment
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URN: urn:nbn:se:smhi:diva-2017DOI: 10.3390/ijerph120100254ISI: 000348403300014PubMedID: 25546283OAI: oai:DiVA.org:smhi-2017DiVA, id: diva2:917272
Available from: 2016-04-06 Created: 2016-03-03 Last updated: 2017-11-30

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Langner, Joakim

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