Quantile regression ensemble for summer temperatures time series and its impact on built environment studies
herrera, M; Eames, ME; Ramallo-Gonzalez, A; et al.Liu, C; Coley, D
Date: 10 July 2016
Publisher
International Environmental Modelling and Software Society
Abstract
Heat waves give rise to order of magnitude higher mortality rates than other
weather-related natural disasters. Unfortunately both the severity and amplitude
of heat waves are predicted to increase worldwide as a consequence of
climate change. Hence, meteorological services have a growing need to identify
such periods in order to ...
Heat waves give rise to order of magnitude higher mortality rates than other
weather-related natural disasters. Unfortunately both the severity and amplitude
of heat waves are predicted to increase worldwide as a consequence of
climate change. Hence, meteorological services have a growing need to identify
such periods in order to set alerts, whilst researchers and industry need representative
future heat waves to study risk. This paper introduces a new locationspecific
mortality risk focused definition of heat waves and a new mathematical
framework for the creation of time series that represents them. It focuses on
identifying periods when temperatures are high during the day and night, as
this coincidence is strongly linked to mortality. The approach is tested using
observed data from Brazil and the UK. Comparisons with previous methods
demonstrate that this new approach represents a major advance that can be
adopted worldwide by governments, researchers and industry.
Engineering
Faculty of Environment, Science and Economy
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