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Transforming existing weather data for worldwide locations to enable energy and building performance simulation under future climates

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Transforming existing weather data for worldwide locations to enable energy and building performance simulation under future climates. / Jentsch, Mark F.; James, Patrick A.B.; Bourikas, Leonidas; Bahaj, AbuBakr S.

In: Renewable Energy, Vol. 55, 07.2013, p. 514 - 524.

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Jentsch, Mark F. ; James, Patrick A.B. ; Bourikas, Leonidas ; Bahaj, AbuBakr S. / Transforming existing weather data for worldwide locations to enable energy and building performance simulation under future climates. In: Renewable Energy. 2013 ; Vol. 55. pp. 514 - 524.

Bibtex

@article{ba6b7d402fe74a4a97ff553bc32526de,
title = "Transforming existing weather data for worldwide locations to enable energy and building performance simulation under future climates",
abstract = "Building performance and solar energy system simulations are typically undertaken with standardised weather files which do not generally consider future climate predictions. This paper investigates the generation of climate change adapted simulation weather data for locations worldwide from readily available data sets. An approach is presented for {\textquoteleft}morphing{\textquoteright} existing EnergyPlus/ESP-r Weather (EPW) data with UK Met Office Hadley Centre general circulation model (GCM) predictions for a {\textquoteleft}medium–high{\textquoteright} emissions scenario (A2). It was found that, for the United Kingdom (UK), the GCM {\textquoteleft}morphed{\textquoteright} data shows a smoothing effect relative to data generated from the corresponding regional climate model (RCM) outputs. This is confirmed by building performance simulations of a naturally ventilated UK office building which highlight a consistent temperature distribution profile between GCM and RCM {\textquoteleft}morphed{\textquoteright} data, yet with a shift in the distribution. It is demonstrated that, until more detailed RCM data becomes available globally, {\textquoteleft}morphing{\textquoteright} with GCM data can be considered as a viable interim approach to generating climate change adapted weather data.",
keywords = "Climate change, Simulation weather data, Weather data morphing, Weather data generation tool",
author = "Jentsch, {Mark F.} and James, {Patrick A.B.} and Leonidas Bourikas and Bahaj, {AbuBakr S.}",
year = "2013",
month = jul
doi = "https://doi.org/10.1016/j.renene.2012.12.049",
language = "English",
volume = "55",
pages = "514 -- 524",
journal = "Renewable Energy",
issn = "0960-1481",
publisher = "Elsevier BV",

}

RIS

TY - JOUR

T1 - Transforming existing weather data for worldwide locations to enable energy and building performance simulation under future climates

AU - Jentsch, Mark F.

AU - James, Patrick A.B.

AU - Bourikas, Leonidas

AU - Bahaj, AbuBakr S.

PY - 2013/7

Y1 - 2013/7

N2 - Building performance and solar energy system simulations are typically undertaken with standardised weather files which do not generally consider future climate predictions. This paper investigates the generation of climate change adapted simulation weather data for locations worldwide from readily available data sets. An approach is presented for ‘morphing’ existing EnergyPlus/ESP-r Weather (EPW) data with UK Met Office Hadley Centre general circulation model (GCM) predictions for a ‘medium–high’ emissions scenario (A2). It was found that, for the United Kingdom (UK), the GCM ‘morphed’ data shows a smoothing effect relative to data generated from the corresponding regional climate model (RCM) outputs. This is confirmed by building performance simulations of a naturally ventilated UK office building which highlight a consistent temperature distribution profile between GCM and RCM ‘morphed’ data, yet with a shift in the distribution. It is demonstrated that, until more detailed RCM data becomes available globally, ‘morphing’ with GCM data can be considered as a viable interim approach to generating climate change adapted weather data.

AB - Building performance and solar energy system simulations are typically undertaken with standardised weather files which do not generally consider future climate predictions. This paper investigates the generation of climate change adapted simulation weather data for locations worldwide from readily available data sets. An approach is presented for ‘morphing’ existing EnergyPlus/ESP-r Weather (EPW) data with UK Met Office Hadley Centre general circulation model (GCM) predictions for a ‘medium–high’ emissions scenario (A2). It was found that, for the United Kingdom (UK), the GCM ‘morphed’ data shows a smoothing effect relative to data generated from the corresponding regional climate model (RCM) outputs. This is confirmed by building performance simulations of a naturally ventilated UK office building which highlight a consistent temperature distribution profile between GCM and RCM ‘morphed’ data, yet with a shift in the distribution. It is demonstrated that, until more detailed RCM data becomes available globally, ‘morphing’ with GCM data can be considered as a viable interim approach to generating climate change adapted weather data.

KW - Climate change

KW - Simulation weather data

KW - Weather data morphing

KW - Weather data generation tool

U2 - https://doi.org/10.1016/j.renene.2012.12.049

DO - https://doi.org/10.1016/j.renene.2012.12.049

M3 - Journal article

VL - 55

SP - 514

EP - 524

JO - Renewable Energy

JF - Renewable Energy

SN - 0960-1481

ER -