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).
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 language | English |
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Pages (from-to) | 65-77 |
Journal | Journal of Building Performance Simulation |
Volume | 6 |
Issue number | 1 |
Early online date | 9 May 2012 |
DOIs | |
Publication status | Published - 2013 |
Keywords
- probabilistic climate projections
- heat wave
- overheating
- adaptation