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Matthew E. Eames

Researcher at University of Exeter

Publications -  45
Citations -  1899

Matthew E. Eames is an academic researcher from University of Exeter. The author has contributed to research in topics: Iterative reconstruction & Climate change. The author has an hindex of 19, co-authored 45 publications receiving 1659 citations.

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A comparison of structural and behavioural adaptations to future proofing buildings against higher temperatures

TL;DR: It is found that an alteration to how a building is used is as equally important as common structural adaptations, and that the risk of choosing what turns out to be an incorrect climate change projection can be dealt with by seeing non-structural adaptations as a way of nullifying this risk.
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Assessing the risk of climate change for buildings:A comparison between multi-year and probabilistic reference year simulations

TL;DR: In this paper, the UK Climate Projections (UKCP09) were used to model the internal conditions and energy use of a building with all 3000 example years produced by the UKCP09 weather generator in an attempt to study the full range of response and risk.
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Estimation of the urban heat island for UK climate change projections

TL;DR: In this article, a simple methodology has been developed to calculate the urban heat island (UHI) from a set of gridded temperature data; the UHI may then be added to climate model projections and weather data files.
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A comparison of future weather created from morphed observed weather and created by a weather generator

TL;DR: In this paper, the use of UKCP09 climate change anomalies within the morphing procedure gave an unrealistic representation of future temperatures both mathematically and physically, limiting its use. But the potential to use both products to investigate the effects of climate change is clear.
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Comparison of multi-year and reference year building simulations

TL;DR: It is found that while the reference years allow rapid thermal modelling of building designs they are not always representative of the average energy use exposed by modelling with many weather years and can give a misleading representation of the risk of overheating (DSY).