Analysis of probabilistic climate projections: heat wave, overheating and adaptation

Research output: Contribution to journalArticle

Abstract

Climate change could substantially impact on the performance of buildings in providing thermal comfort to
occupants. The recently launched UK climate projections (UKCP09) suggest that all areas of the UK will become
warmer in the 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 if directly used with the numerous
replicated climates available from a probabilistic climate database could be practically challenging. For complex
probabilistic climate datasets, we demonstrate the efficiency of the statistical tool in performing a systematic analysis
of various aspects of heat waves including: frequency of extreme heat events in changing climate; its impact on
overheating issues and effects of specific adaptation techniques applied to offset predicted overheating. We consider
a domestic building as a virtual case study. 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).
Original languageEnglish
Pages (from-to)65-77
JournalJournal of Building Performance Simulation
Volume6
Issue number1
Early online date9 May 2012
DOIs
Publication statusPublished - 2013

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climate
extreme event
carbon
simulator
heat wave
analysis
vulnerability
climate change
project

Keywords

  • probabilistic climate projections
  • heat wave
  • overheating
  • adaptation

Cite this

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title = "Analysis of probabilistic climate projections: heat wave, overheating and adaptation",
abstract = "Climate change could substantially impact on the performance of buildings in providing thermal comfort tooccupants. The recently launched UK climate projections (UKCP09) suggest that all areas of the UK will becomewarmer in the 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 ofa building to extreme events. A simple statistical model proposed by the LCF project elsewhere has been employedto emulate the outputs of the dynamic building simulator (ESP-r), which if directly used with the numerousreplicated climates available from a probabilistic climate database could be practically challenging. For complexprobabilistic climate datasets, we demonstrate the efficiency of the statistical tool in performing a systematic analysisof various aspects of heat waves including: frequency of extreme heat events in changing climate; its impact onoverheating issues and effects of specific adaptation techniques applied to offset predicted overheating. We considera domestic building as a virtual case study. Results are presented relative to a baseline climate (1961–1990) for threefuture timelines (2030s, 2050s and 2080s) and three emission scenarios (Low, Medium and High).",
keywords = "probabilistic climate projections, heat wave, overheating, adaptation",
author = "S. Patidar and David Jenkins and G.J. Gibson and P.F.G. Banfill",
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AU - Patidar, S.

AU - Jenkins, David

AU - Gibson, G.J.

AU - Banfill, P.F.G.

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N2 - Climate change could substantially impact on the performance of buildings in providing thermal comfort tooccupants. The recently launched UK climate projections (UKCP09) suggest that all areas of the UK will becomewarmer in the 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 ofa building to extreme events. A simple statistical model proposed by the LCF project elsewhere has been employedto emulate the outputs of the dynamic building simulator (ESP-r), which if directly used with the numerousreplicated climates available from a probabilistic climate database could be practically challenging. For complexprobabilistic climate datasets, we demonstrate the efficiency of the statistical tool in performing a systematic analysisof various aspects of heat waves including: frequency of extreme heat events in changing climate; its impact onoverheating issues and effects of specific adaptation techniques applied to offset predicted overheating. We considera domestic building as a virtual case study. Results are presented relative to a baseline climate (1961–1990) for threefuture timelines (2030s, 2050s and 2080s) and three emission scenarios (Low, Medium and High).

AB - Climate change could substantially impact on the performance of buildings in providing thermal comfort tooccupants. The recently launched UK climate projections (UKCP09) suggest that all areas of the UK will becomewarmer in the 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 ofa building to extreme events. A simple statistical model proposed by the LCF project elsewhere has been employedto emulate the outputs of the dynamic building simulator (ESP-r), which if directly used with the numerousreplicated climates available from a probabilistic climate database could be practically challenging. For complexprobabilistic climate datasets, we demonstrate the efficiency of the statistical tool in performing a systematic analysisof various aspects of heat waves including: frequency of extreme heat events in changing climate; its impact onoverheating issues and effects of specific adaptation techniques applied to offset predicted overheating. We considera domestic building as a virtual case study. Results are presented relative to a baseline climate (1961–1990) for threefuture timelines (2030s, 2050s and 2080s) and three emission scenarios (Low, Medium and High).

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