@article{HeidenreichBuchnerWalzetal.2021, author = {Heidenreich, Anna and Buchner, Martin and Walz, Ariane and Thieken, Annegret}, title = {How to deal with heat stress at an open-air event?}, series = {Weather, climate \& society / American Meteorological Society}, volume = {13}, journal = {Weather, climate \& society / American Meteorological Society}, number = {4}, publisher = {American Meteorological Soc.}, address = {Boston}, issn = {1948-8327}, doi = {10.1175/WCAS-D-21-0027.1}, pages = {989 -- 1002}, year = {2021}, abstract = {Heat waves are increasingly common in many countries across the globe, and also in Germany, where this study is set. Heat poses severe health risks, especially for vulnerable groups such as the elderly and children. This case study explores visitors' behavior and perceptions during six weekends in the summer of 2018 at a 6-month open-air horticultural show. Data from a face-to-face survey (n = 306) and behavioral observations ( n = 2750) were examined by using correlation analyses, ANOVA, and multiple regression analyses. Differences in weather perception, risk awareness, adaptive behavior, and activity level were observed between rainy days (maximum daily temperature, 25 degrees C), warmsummer days (25 degrees-30 degrees C), and hot days (>30 degrees C). Respondents reported a high level of heat risk awareness, butmost (90\%) were unaware of actual heat warnings. During hot days, more adaptive measures were reported and observed. Older respondents reported taking the highest number of adaptive measures. We observed the highest level of adaptation in children, but they also showed the highest activity level. From our results we discuss how to facilitate individual adaptation to heat stress at open-air events by taking the heterogeneity of visitors into account. To mitigate negative health outcomes for citizens in the future, we argue for tailored risk communication aimed at vulnerable groups.
SIGNIFICANCE STATEMENT: People around the world are facing higher average temperatures. While higher temperatures make open-air events a popular leisure time activity in summer, heat waves are a threat to health and life. Since there is not much research on how visitors of such events perceive different weather conditions-especially hot temperatures-we explored this in our case study in southern Germany at an open-air horticultural show in the summer of 2018. We discovered deficits both in people's awareness of current heat risk and the heat adaptation they carry out themselves. Future research should further investigate risk perception and adaptation behavior of private individuals, whereas event organizers and authorities need to continually focus on risk communication and facilitate individual adaptation of their visitors.}, language = {en} } @misc{SamprognaMohorThiekenKorup2021, author = {Samprogna Mohor, Guilherme and Thieken, Annegret and Korup, Oliver}, title = {Residential flood loss estimated from Bayesian multilevel models}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, issn = {1866-8372}, doi = {10.25932/publishup-51774}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-517743}, pages = {1599 -- 1614}, year = {2021}, abstract = {Models for the predictions of monetary losses from floods mainly blend data deemed to represent a single flood type and region. Moreover, these approaches largely ignore indicators of preparedness and how predictors may vary between regions and events, challenging the transferability of flood loss models. We use a flood loss database of 1812 German flood-affected households to explore how Bayesian multilevel models can estimate normalised flood damage stratified by event, region, or flood process type. Multilevel models acknowledge natural groups in the data and allow each group to learn from others. We obtain posterior estimates that differ between flood types, with credibly varying influences of water depth, contamination, duration, implementation of property-level precautionary measures, insurance, and previous flood experience; these influences overlap across most events or regions, however. We infer that the underlying damaging processes of distinct flood types deserve further attention. Each reported flood loss and affected region involved mixed flood types, likely explaining the uncertainty in the coefficients. Our results emphasise the need to consider flood types as an important step towards applying flood loss models elsewhere. We argue that failing to do so may unduly generalise the model and systematically bias loss estimations from empirical data.}, language = {en} } @article{SamprognaMohorThiekenKorup2021, author = {Samprogna Mohor, Guilherme and Thieken, Annegret and Korup, Oliver}, title = {Residential flood loss estimated from Bayesian multilevel models}, series = {Natural Hazards and Earth System Sciences}, volume = {21}, journal = {Natural Hazards and Earth System Sciences}, publisher = {European Geophysical Society}, address = {Katlenburg-Lindau}, issn = {2195-9269}, doi = {10.5194/nhess-21-1599-2021}, pages = {1599 -- 1614}, year = {2021}, abstract = {Models for the predictions of monetary losses from floods mainly blend data deemed to represent a single flood type and region. Moreover, these approaches largely ignore indicators of preparedness and how predictors may vary between regions and events, challenging the transferability of flood loss models. We use a flood loss database of 1812 German flood-affected households to explore how Bayesian multilevel models can estimate normalised flood damage stratified by event, region, or flood process type. Multilevel models acknowledge natural groups in the data and allow each group to learn from others. We obtain posterior estimates that differ between flood types, with credibly varying influences of water depth, contamination, duration, implementation of property-level precautionary measures, insurance, and previous flood experience; these influences overlap across most events or regions, however. We infer that the underlying damaging processes of distinct flood types deserve further attention. Each reported flood loss and affected region involved mixed flood types, likely explaining the uncertainty in the coefficients. Our results emphasise the need to consider flood types as an important step towards applying flood loss models elsewhere. We argue that failing to do so may unduly generalise the model and systematically bias loss estimations from empirical data.}, language = {en} }