Creating Extreme Weather Time Series through a Quantile Regression Ensemble
Ramallo-Gonz alez, A
Environmental Modelling and Software
© 2018 Elsevier Ltd. All rights reserved.
Reason for embargo
Under embargo until 21 March 2019 in compliance with publisher policy.
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
This research has been performed in the project COLBE on The creation of localized current and future weather for the built environment, EPSRC [grant code EP/K002724/1]. Ramallo-Gonz´alez would like to acknowledge Fundaci´on S´eneca-Agencia de Ciencia y Tecnolog´ıa de la Regi´on de Murcia, CARM.
This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.
Published online 21 March 2018.