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http://www.ep.liu.se/ecp/057/v...
Conference object
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https://doi.org/10.3384/ecp110...
Conference object . 2011 . Peer-reviewed
Data sources: Crossref
Renewable Energy
Article . 2014 . Peer-reviewed
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Simple Statistical Model for Complex Probabilistic Climate Projections: Overheating Risk and Extreme Events

Authors: Gavin J. Gibson; Sandhya Patidar; Phillip Frank Gower Banfill; David Jenkins;

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

Abstract

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).

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
15
Top 10%
Average
Average