Conference article

Simple Statistical Model for Complex Probabilistic Climate Projections: Overheating Risk and Extreme Events

Sandhya Patidar
Maxwell Institute for Mathematical Sciences , School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, UK

David Jenkins
Urban Energy Research Group, School of Built Environment, UK

Phil Banfill
Urban Energy Research Group, School of Built Environment, UK

Gavin Gibson
Maxwell Institute for Mathematical Sciences , School of Mathematical and Computer Sciences, Heriot-Watt University, Edinburgh, UK

Download articlehttp://dx.doi.org/10.3384/ecp11057596

Published in: World Renewable Energy Congress - Sweden; 8-13 May; 2011; Linköping; Sweden

Linköping Electronic Conference Proceedings 57:4, p. 596-603

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Published: 2011-11-03

ISBN: 978-91-7393-070-3

ISSN: 1650-3686 (print), 1650-3740 (online)

Abstract

Climate change could substantially impact the performance of the buildings in providing thermal comfort to occupants. Recently launched UK climate projections (UKCP09); clearly indicate that all areas of the UK will get warmer in future with the possibility of more frequent and severe extreme events; such as heat waves. This study; as part of the Low Carbon Futures (LCF) Project; explores the consequent risk of overheating and the vulnerability of a building to extreme events. A simple statistical model proposed by the LCF project elsewhere has been employed to emulate the outputs of the dynamic building simulator (ESP-r) which cannot feasibly be used itself with thousands of available probabilistic climate database. Impact of climate change on the daily external and internal temperature profiles has been illustrated by means of 3D plots over the entire overheating period (May - October) and over 3000 equally probable future climates. Frequency of extreme heat events in changing climate and its impact on overheating issues for a virtual case study domestic house has been analyzed. Results are presented relative to a baseline climate (1961-1990) for three future timelines (2030s; 2050s; and 2080s) and three emission scenarios (Low; Medium; and High).

Keywords

Probabilistic climate projections; Building and Adaptation; Overheating

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