Creating state-of-the-art weather files to enable a climate-resilient built environment in the UK

Global warming and net zero transition are the two biggest challenges currently faced by the building industry in the UK. While the net zero transition primarily focuses on the problems of energy efficiency and heat decarbonization, the rise of global temperature imposes a significant threat to the health and wellbeing of occupants and the industry is obliged to make buildings climate-resilient by testing their designs using future weather files. To improve the quality of the current weather files, a new project has been commissioned by CIBSE to revisit the data and the methodology employed for creating future weather files and produce new CIBSE weather files using the latest UK Climate Projections released in 2018 (UKCP18). In this study, we evaluate the newly produced weather files for overheating risk using building simulation. Two different batches of weather files were curated. The first batch was produced primarily using the existing methodology for creating the UKCP09 based weather files, with an adjustment to accommodate new features of the UKCP18 and an improved procedure for morphing the solar radiation data. The second batch was created through an improved morphing process to better emulate the characteristics of distributions of climatic variables. The differences between the existing UKCP09 and new UCKP18 based weather files are compared by evaluating overheating metrics. The new weather files enable robust building performance assessment against future climate conditions under different scenarios and will play an important role in designing climate-resilient buildings and delivering a net zero built environment. Practical applications As the extreme weather events resulting from climate change become more frequent and intense, they pose significant challenges to the resilience of the built environment and severe threats to the health and wellbeing of the occupants. Climate data, which serves as the foundation for climate risk assessment, plays a critical role in helping the building sector to achieve climate resilience through the means of performance assessment and the channel of regulatory compliance. In this study, the revised future weather files created using the latest UKCP18 climate projections are presented and evaluated using building simulation, as part of the weather file testing programme for quality assurance. The revision of the CIBSE weather files according to the latest climate science, i.e. UKCP18, will enable the building industry to quantify overheating risks with more accurate climate assumptions and better inform decision making about risk mitigation and climate adaptation.

The increasing intensity and frequency of extreme weather events resulting from climate change have led to grid outages and other negative consequences. To ensure the resilience of buildings which serve as primary shelters for occupants, resilient strategies are being developed to improve their ability to withstand these extreme events (e.g., building upgrades and renewable energy generators and storage). However, a crucial step towards creating a resilient built environment is accurately estimating building performance during such conditions using historical extreme climate change-induced weather events. To conduct Building Performance Simulation (BPS) in extreme conditions, such as weather events induced by climate change, it is essential to utilize Actual Meteorological Year (AMY) weather files instead of Typical Meteorological Year (TMY) files. AMY files capture the precise climatic conditions during extreme weather events, enabling accurate simulation of such scenarios. These weather files provide valuable data that can be used to assess the vulnerabilities and resilience of buildings to extreme weather events. By analyzing past events and their impacts using BPS tools, we can gain insights into the specific weaknesses and areas that require improvement. This approach applies to both existing buildings needing climate change-resilient retrofits and new building designs that must be compatible with future climatic conditions. Moreover, the intensification and frequency increase of these extreme weather events makes developing adaptation and resilient-building measures imperative. This involves understanding the potential losses that households may experience due to the intensification of extreme events and developing farsighted coping strategies and climate-proof resilient-building initiatives. However, addressing the knowledge gap caused by the absence of an AMY weather file dataset of extreme events is essential. This will allow for accurate BPS during past extreme climate change-induced weather events. To fill this gap, this article introduces a comprehensive .epw format weather file dataset focusing on historical extreme weather events in Canada. This collection encompasses a diverse array of past extreme climate change occurrences in various locations, with potential for future expansion to include additional locations and countries. This dataset enables energy simulations for different types of buildings and considers a diverse range of historical weather conditions, allowing for better estimation of thermal performance.

Comparing micro-scale weather data to building energy consumption in Singapore

Weather files are fundamental for building performance applications such as estimating energy demand or predicting the risk of thermal discomfort. Often such weather files are based on specific locations with limited guidance to which file to use which can lead to non-representative climate conditions for a specific building and potentially under or over engineering of systems. Recently, a new approach to generating representative weather files for building performance using climate zones has been proposed. This work presents a comparative analysis of the two approaches. Results from examining the external climate and an example building simulation reveal substantial differences: heating degree days vary by up to 931° days, cooling degree days by up to 500° days, heating energy demand differs by as much as 60%, and overheating exposure in the bedroom exceeds 26°C for up to 45 h more. Overall, we find significant variations in heating and cooling loads can be expected if unrepresentative climate data is used highlighting the importance of selecting appropriate weather data for building performance simulation. The use of zone-based files provides a more nuanced understanding of climate conditions, improving the reliability of building performance assessments and compliance with overheating standards. Practical application Weather files are fundamental for building performance analysis and supporting design decisions including the prediction of the risk of thermal discomfort. There is a need for these weather files to be kept up to date following the continual warming of the environment to ensure that the performance analysis represents external conditions and ensuring the analysis is fit for purpose. A significant limitation of the current approach is the uncertainty of which weather file should be used for any given location particularly in locations such as the UK. This work provides a framework for the development of climate-zones and representative weather files suitable for supporting the benchmarking of building performance across the climate zone removing ambiguity within the industry for the appropriate selection of weather data.

Weather data plays an important role for energy perfor- mance assessment in the design of buildings and urban environments. Many researches have been carried out to generate and analyse vari- ous weather files for different simulation platforms. However, investi- gations have been lacking in the development of weather files that ac- count for urban heat island (UHI) problems. As a result of global warming and the complexity of the urban environment, the weather file for a modern city cannot be simply based on climate information from 20 years ago. The objective of this research is to demonstrate a method for creating different micro-scale typical meteorological year (TMY) weather files based on different urban texture values. This re- search includes three steps: 1) Recent years weather data is obtained. 2) Considering the UHI impact, a series of new TMY weather files are generated for different micro-scale areas in Singapore based on rele- vant urban texture variables. 3) A comparison of the results shows that there is a big difference between the new and the old TMY. The tem- perature of the new TMY is 1-2°C higher, while the solar radiation is lower than the original TMY data. Hence the new weather files will be more credible than the original TMY for energy performance simula- tion in the design process.

Evaluating the applicability of Typical Meteorological Year under different building designs and climate conditions

<p><b>The purpose of this study was to evaluate the ability of the three different shelter conditions in achieving natural ventilation to improve the indoor thermal comfort level in Kutupalong (KTP) Refugee Camp in Bangladesh. The three shelter conditions were 1) shelter spacing; 2) shelter orientation; and 3) ground sloping conditions. Also, in the absence of favourable conditions, a feasibility study using a wind catcher to improve the wind at occupant level was provided.</b></p> <p>The thermal comfort level defined by the achieved discomfort hours was derived from the adaptive thermal comfort analysis, which included the analysis of adaptive thermal comfort model and weather (humidity and wind) adjustments equations. The adaptive thermal comfort model and the wind adjustment equation used in this study was developed by Humphreys in 1978 and 1970, both of which studies Nicol examined in 2004. Two humidity adjustment equations: ISO7730 and the MacFarlane study were applied and compared. The most favourable conditions for achieving thermal comfort were identified by comparing the current and predicted thermal comfort levels in different conditions.</p> <p>The current level of thermal comfort was achieved by obtaining the comfortable temperature from the adaptive thermal comfort model and adjusted with the humidity data in the weather file. The wind factor was not encountered in this stage because of unavailable data. A +/-2.5oC of the comfortable temperature range was applied to achieve an acceptance level of 80% among shelter occupants. The results showed that the level achieved before and after the consideration of humidity effects were from 16% to 22% (ISO7730) and 26% (MacFarlane) respectively, i.e. the current level of thermal comfort. The MacFarlane study was found to be more sensitive to the effect of humidity on comfort levels.</p> <p>Four cases were derived from different conditions and simulated by CFD analysis with constant wind speed at 6m/s in eight different directions. An OpenFOAM plugin to Grasshopper in Rhino was used as CFD software and was validated with AIJ benchmark test before application. The outcomes of this were compared according to different conditions, and a further CFD analysis was undertaken to achieve the indoor airflow.</p> <p>After developing the links between the wind speed (i.e. 6m/s) with eight different directions, the different conditions and their respective indoor airflow, these were integrated into the weather data of KTP camp. The results showed that the outcomes achieved with or without integration of weather data were almost the same except for shelter orientation: 3m shelter spacing model and single-sided sloping ground was better to achieve higher inward airflow. No preference orientation was found in the case in which real weather data were not considered. But after weather data integration, all orientations except East were preferred, subject to other conditions. The ground sloping conditions (i.e. single-sided sloping ground) might also have potential priority influence in achieving indoor thermal comfort in the KTP camp.</p> <p>The study of the wind catcher was in two parts: CFD simulations to identify the better wind at high level (6m height above ground) when there was low wind at occupant level (1m height above ground); and, the site measurement conducted in KTP camp to demonstrate the capability of the wind catcher in divering the high level wind to occupant level. The positive outcomes of both parts of the wind catcher study indicated that the installation of a wind catcher might able to improve the natural ventilation at occupant level.</p> <p> Throughout the study, the shelter conditions such as shelter spacing, orientation and ground sloping conditions were able to improve natural ventilation to a certain extent and could thus achieve better indoor thermal comfort for occupants in the KTP refugee camp. Without the favour of these conditions, however, installing a wind catcher might able to help in providing the natural ventilation required at occupant level.</p>

Energy consumption reduction under changing climate conditions is a major challenge in buildings design, where excessive energy consumption creates an economic and environmental burden. Improving thermal performance of the buildings through support applying phase change material (PCM) is a promising strategy for reducing building energy consumption under future climate change. Therefore, this study aims to investigate the energy saving potentials in buildings under future climate conditions in the humid and snowy regions in the hot continental and humid subtropical climates of the east Asia (Seoul, Tokyo and Hong Kong) when various PCMs with different phase change temperatures are applied to a lightweight building envelope. Methodology in this work is implemented in two phases: firstly, investigation of energy saving potentials in buildings through inclusion of three types of PCMs with different phase temperatures into the building envelop separately and use weather file in the present (2017); and, secondly, evaluation of the effect of future climate change on the performance of PCMs by analyzing energy saving potentials of PCMs with 2020, 2050 and 2080 weather data. The results show that the inclusion of PCM into the building envelope is a promising strategy to increase the energy performance in buildings during both heating and cooling seasons in Seoul, Tokyo and Hong Kong under future climate conditions. The energy savings achieved by using PCMs in those regions are electricity savings of 4.48–8.21%, 3.81–9.69%, and 1.94–5.15%, and gas savings of 1.65–16.59%, 7.60–61.76%), and 62.07–93.33% in Seoul, Tokyo and Hong Kong, respectively, for the years 2017, 2020, 2050 and 2080. In addition, BioPCM and RUBITHERMPCM are the most efficient for improving thermal performance and saving energy in buildings in the tested regions and years.

diyepw allows for quick and easy generation of a set of EnergyPlus weather (EPW) files for a given location over a given historical period. The user can obtain weather files using an open-source, automated workflow by simply specifying the location of interest using the World Meteorological Organization weather station ID number, and specifying a year or set of years for which to generate EPW files. Building energy modelers can use these auto-generated weather files in building performance simulations to represent the actual observed weather conditions in the location(s) of interest, based on meteorological observations obtained from the National Oceanic and Atmospheric Administration's Integrated Surface Database. Because observed weather data are not available for every meteorological variable specified in the EPW format, diyepw starts with a widely-used set of typical meteorological year (TMY) files, using them as the template to generate new EPW files by substituting in the observed values of selected meteorological variables that are known to affect building energy performance. Its output is a weather file or group of weather files that conform to the data standards associated with the EPW format so they can be used with any building performance simulation software employing EnergyPlus as its simulation engine.

The standardised weather files commonly used for building simulation are compiled from many years of data. Particular to a specific location, these standardised weather files are generally known as Typical Meteorological Years (TMYs). In contrast, Actual Meteorological Years (AMYs) comprise data for a specific site over a defined period of an actual calendar year. The Copernicus Atmosphere Monitoring Service (CAMS) provides freely available satellite-derived radiation data covering Europe, Africa, the Middle East and parts of South America. CAMS data were used as the basis for solar radiation AMYs. For three locations in Europe, multi-year AMYs are used to test the suitability of TMY files as a reliable representation of prevailing sun and sky conditions. Examples are given for London (Gatwick), Rome (Fiumicino) and Stockholm (Arlanda), where, for all three locations, a full decade of AMY data at both 15 min and 1 h time-steps are evaluated alongside four contending standardised TMY files. For all three locations, the decade of AMY data proved to be surprisingly homogeneous, whereas the four TMYs were at variance with each other, and markedly dissimilar to the AMYs. Consequently, the authors propose a reconsideration of the use of TMYs for compliance purposes in particular, and building simulation in general. Given the unexpected findings, and their potentially far-reaching implications, the weather file evaluation is preceded by a detailed validation of CAMS-derived illuminance data against ground measurements taken in the UK. The results of the validation revealed remarkably good agreement between the CAMS-derived and ground measured illuminance data. Practical applications This paper provides compelling evidence that the methods currently used to select solar radiation data for TMYs result in standardised weather files that do not faithfully represent actually occurring conditions over a recent decade. A more reliable method for the evaluation of ‘typical’ annual profiles of solar radiation is described. The findings have relevance for the selection and curation of solar radiation data for all building simulation applications. In addition to supporting the basis of the TMY evaluation, the validation of CAMS-derived illuminance data revealed that CAMS more generally can serve as a valuable – and freely-available – daylight resource for a variety of practical applications. These include the in-situ validation of CBDM metrics and the generation of boundary daylight conditions for light-dosimetry field studies. Or indeed any application where reliable recent data on daylight/solar parameters for specific locations and at high temporal resolution are needed.

Evaluation of current and future hourly weather data intended for building designs: A Philadelphia case study

The choice of weather data is fundamental for assessing building performance in an accurate and representative way. Typical weather files usually apply a statistical approach to select months representative of current climatic conditions, but they do not encompass site-specific characteristics for different locations worldwide. This work analyses the potential of a multi-scale analysis for building performance assessment from different resolutions of weather data, in a comprehensive geographical territory, given the size of Brazil. It presents an overview of weather data and its application on building performance analysis and a general procedure to retrieve and process weather data, and different approaches to compile weather files for building performance assessment. The study also provides an extensive analysis of the Brazilian territory, presenting a climatic profile and trends for the entire territory. The analysis focuses on a climatic and bioclimatic summary, and on building performance simulations for representative cities according to the Brazilian bioclimatic zoning. Then, it compares the records from ERA5-Land and INMET to quantify the differences and present the impact on building performance analysis. The study proposes a new weather file compilation method for Brazil and applies statistical tests to determine whether the new approach delivers better results than the existing TMY methods. The procedure encompasses correlation and sensitivity analysis based on machine learning models to propose a performance-based method. The initial analysis of the Brazilian territory showed predominantly a temperature increase based on the 2008-2022 records, with some locations reaching more than 1 °C. However, the bioclimatic approach based on Givoni’s chart showed that ventilation strategies are still the most effective approach instead of HVAC systems. Following the comparison between high resolution spatial data and weather stations from Brazil, some locations present insufficient years for a multi-year analysis and some municipalities show a significant variation not only of weather data, but also of the building performance results. Finally, the analysis of new weather files for Brazil allowed concluding that creating typical year weather files based on a performance approach delivers the best outcomes, since they are closer to the historical records. Keywords: climate analysis; building performance simulation; weather files; machine learning

Different climate change projections, such as UK Climate Impacts Program (UKCIP02) and 2009 UK Climate projections (UKCP09), have generated a large quantity of data that represent a range of possible future weather scenarios. This article investigates the potential consequences of alternative scenarios for the natural ventilation of non-domestic buildings. The article considers future natural ventilation rates in example buildings, the risk of summer overheating and whether natural ventilation will be a viable thermal control option for future summers. The wind is obviously a key driver of natural ventilation, and a necessary component of building simulation weather files. Problems associated with the generation of wind data from UKCP09 for the natural ventilation analyses are discussed and the influence of differences in weather files on predicted performance considered. These differences are important to the understanding of the consequences for the wider use of UKCP09 derived weather data for building energy evaluation. Practical applications: Weather data are widely used in practice to evaluate the potential and performance of natural ventilation in non-domestic buildings. The predicted differences in future weather data will have direct implications for the design of naturally ventilated buildings, and engineers will need to be aware of the possible implications these climatic differences will create.

Thermal simulations of buildings play a critical role in optimizing energy efficiency, thermal comfort, and heating, ventilation and air conditioning (HVAC) systems design. Accurate weather data is essential for reliable simulations, as local weather and climate have a significant impact on energy requirements for space heating and cooling and thermal comfort. This study conducted a literature review regarding the sources, types, and uncertainties of weather data used for thermal simulations of buildings, including typical meteorological years (TMYs) and extreme weather files under current and future climates. Additionally, this paper evaluates methods for weather data processing, including interpolation, downscaling, and synthetic generation, to improve simulation accuracy. Finally, approaches are proposed for constructing weather files for the future and extreme conditions under a changing climate. This review aims to provide a guide for researchers and practitioners to enhance the reliability of thermal modeling through informed construction, selection, and application of weather data.

Though uncertainties of input variables may have significant implications on building simulations, they are quite often not identified, quantified, or included in building simulations results. This paper considers climatic deterministic, uncertainty, and sensitivity analysis through a series of simulations using the CIBSE UKCIP02 future weather years, CIBSE TM48 for design summer years (DSYs), and the latest CIBSE TM49 DSY future weather data which incorporates the UKCP09 projections to evaluate the variance and the impact of differing London future weather files on indoor operative temperature of a detached dwelling in the United Kingdom using the CIBSE TM52 overheating criteria. The work analyses the variability of comparable weather data set to identify the most influential weather parameters that contribute to thermal comfort implications for these dwellings. The choice of these weather files is to ascertain their differences, as their development is underpinned by different climatic projections. The overall pattern of the variability of the UKCIP02 and UKCP09 Heathrow weather data sets under Monte Carlo sensitivity consideration do not seem to be very different from each other. The deterministic results show that the operative temperatures of the UKCIP02 are slightly higher than those of UKCP09, with the UKCP09 having a narrow range of operative temperatures. The Monte Carlo sensitivity analysis quantified and affirmed the dry bulb and radiant temperatures as the most influential weather parameters that affect thermal comfort on dwellings.