Future Weather Files Research Articles

Evaluating UKCP18-Based weather files for overheating assessment using building simulation: A case study for a flat in london

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.

Impact of climate change on the heating and cooling load components of an archetypical residential room in major Indian cities

Residential heating and cooling (H/C) accounts for ∼7 % of India's electricity consumption. A warming climate will increase residential cooling requirements while heating needs will decrease — an alarming consequence for India, which has predominantly cooling requirements. Thus, to reduce the Indian building sector's energy and carbon footprint, it is essential to assess the impact of climate change on future H/C needs and develop energy-efficiency solutions.This research evaluated the effect of climate change on the H/C energy needs of an archetypical residential room in India by conducting energy simulations for current and future climates. We developed future weather files for eight major Indian cities, covering all climate zones of the country, using predictions from multiple general circulation climate models under two different representative concentration pathways (RCPs): RCP4.5 and RCP8.5. We also developed a novel approach to quantify the H/C load components (walls, windows, infiltration, etc.) for identifying building elements to target for improving energy efficiency.The ensemble median of climate model projections showed that the room's cooling energy demand would increase by 20–179 % by the 2090s compared to the 1990s, depending on the room's orientation, city, and emission scenario. Walls and windows account for over 63 % of the current and future cooling needs and should be the prime targets for energy-efficiency measures. In contrast to rising cooling needs, the room's heating energy demand will decrease by 34–100 % by the 2090s. External walls contribute to over 67 % of the heating needs; thus, insulating them could effectively reduce the heating demand.

Comparison of future weather files for Brazilian cities

Comparison of future weather files for Brazilian cities

Development of a hybrid timber and aluminum based unitized façade system resilient to the future weather conditions in Europe via monitoring campaigns and computational models

The StaticusCare project aims to develop a hybrid timber and aluminum unitized façade system (HUF) equipped with a predictive maintenance system (PMS) for Nordic climates, which will be based on the digital twin concept and fed by an Internet-of-Things system. The use of timber in the structure elements of the façade system aims to reduce the typical system's CO2 footprint by 70–75 %, and the non-renewable energy consumption by 53–56 %. Nonetheless, ensuring that this novel system is durable in the Nordic current and future climate conditions is necessary. For this purpose, the HUF system will be installed in a two-floor building, monitored by a multi-sensor campaign, and replicated computationally to assess the energy use and indoor environmental quality, as well as the hygrothermal performance of the building elements for contemporary climate and under various climate change scenarios. The maintenance of the buildings with the façade system installed will be based on a PMS that is backed by an open-source python heat, air, and moisture transport (HAM) software. This one-dimensional software will be validated using a commercial one. To analyze specific problems, such as air infiltration and moisture entrapment, a two-dimensional HAM model will also be developed. In addition, building energy simulations will be performed to test several parameters affecting the indoor climate quality and energy use. Finally, the current outdoor weather files for the HAM simulations will be built based on multi-year datasets following the ISO 15927-4 methodology and the Perez model, whilst the future weather files will be based on multi-year datasets following the same methodology for two future scenarios. This multi-step methodology will allow to thoroughly test and design the HUF façade system whilst minimizing the risk, e.g., mold growth, for current and future conditions.

Multi-scenario Extreme Weather Simulator application to heat waves: Ko’olauloa community resilience hub

Heat waves are increasing in severity, duration, and frequency. The Multi-Scenario Extreme Weather Simulator (MEWS) models this using historical data, climate model outputs, and heat wave multipliers. In this study, MEWS is applied for planning of a community resilience hub in Hau’ula, Hawaii. The hub will have normal operations and resilience operations modes. Both these modes were modeled using EnergyPlus. The resilience operations mode includes cutting off air conditioning for many spaces to decrease power requirements during emergencies. Results were simulated for 300 future weather files generated by MEWS for 2020, 2040, 2060, and 2080. Shared socioeconomic pathways 2–4.5, 3–7.0 and 5–8.5 were used. The resilience operations mode results show two to six times increase of hours of exceedance beyond 32.2 °C from present conditions, depending on climate scenario and future year. The resulting decrease in thermal resilience enables an average decrease of energy use intensity of 26% with little sensitivity to climate change. The decreased thermal resilience predicted in the future is undesirable, but was not severe enough to require a more energy-intensive resilience mode. Instead, planning is needed to assure vulnerable individuals are given prioritized access to air-conditioned parts of the hub if worst-case heat waves occur.

Investigation of urban heat island and climate change and their combined impact on building cooling demand in the hot and humid climate of Qatar

Urban Heat Island (UHI) and climate change are two critical factors affecting the energy demand of buildings. However, the previous literature often overlooked the concurrent impacts of these factors, which leads to an erroneous estimation of the current and future energy demand of buildings. To address this issue, this paper investigates the UHI and climate change and their combined impacts on the current and future cooling demands of high-rise residential buildings in the hot and humid climate of Qatar. The impacts of UHI and climate change on the climatic conditions of the Marina district of Lusail City, Qatar, are evaluated using Urban Weather Generator (UWG) and World Weather Generator (WWG) tools, respectively, for 2050 and 2080. A total of eight weather sources, two for 2020 and six for 2050 and 2080, are compared to the weather data collected from the established local weather stations in the city. Two important methods are adopted to elaborate on the combined impact of the UHI and climate change on building cooling demand. In the first method (M1), the future weather file obtained from the Open Weather Map (OM) is processed by UWG for the UHI impact analysis and then by WWG for the climate change impact analysis, while in the second method (M2), the future weather file is first processed by WWG, followed by UWG. According to the results, for the hot and humid climate of Qatar, the cooling energy consumption of the high-rise residential building increases by 19% and 33.5% for 2050 and 2080, respectively, by the first method, and by 20% and 34.4% for 2050 and 2080, respectively by the second method. Both methods yield fairly similar results on the combined impact of UHI and climate change on building cooling demand in hot and humid climates. The findings of this study highlight the importance and necessity of considering UHI and climate change impact in building energy simulations to estimate the present and future energy demand of buildings accurately.

Building Adaptation Measures Using Future Climate Scenarios—A Scoping Review of Uncertainty Treatment and Communication

The global climate is changing. Predicting the impacts this will have on buildings is the first step in the process of finding suitable building adaptation measures. Future climate adaptation of buildings and infrastructure is a growing field of research, relying on both socio-economical and meteorological research for input values to the simulation models. Models producing hourly future weather data rely on global climate models which are based on emission scenarios made from assumptions of future political, social, and economic developments. Accounting for the uncertainties from these underlying models as much as possible, and communicating the uncertainties in the results, is obviously paramount for reliable conclusions from the building simulation models. This paper is a scoping review, investigating how 132 studies treat and communicate the string of uncertainties from underlying models connected to future weather file generation in the scientific literature on building adaptation research. The findings suggest that climate-model-induced uncertainties are often under-communicated, due to either insufficient analysis or neglect. The studies that included the most comprehensive analyses of the uncertainties frequently concluded that treatment of these is important for the reliability of the results, and neglecting this could lead to misleading conclusions.

Climate change impacts on heating and cooling energy demand in residential building units. Application in the city of Thessaloniki, Greece

The present study aims to evaluate the effect of climate change on the heating and cooling energy needs of a residential building unit, located in the city of Thessaloniki, Greece. Future weather files have been generated using both statistical and dynamical downscaling methods. In the first case, the Meteonorm weather generator was used to generate a future weather file, while for the dynamic downscaling approach, the Hadley Regional Model 3 (HRM3), coupled with Hadley Climate Model 3 was employed. The generated future weather datasets have been then used as an input parameter in the dynamic energy performance simulations of the residential building unit with Energy Plus. For all examined weather datasets, the simulation results show a decrease of the heating energy use, an effect that is strongly counterbalanced by the rise of the cooling energy demand.

The Importance of Moisture Transport Properties of Wall Finishings on the Hygrothermal Performance of Masonry Walls for Current and Future Climates

A render is the first protective layer of exterior walls against the outdoor climate, which, due to its constitution, aims to gradually slow down the liquid moisture penetration to prevent it from reaching the wall inner layers. Due to the future expected changes in the outdoor climate, today’s exterior mortar might not be adequately designed to protect these walls. This paper aims to analyse the influence of mortars on the hygrothermal performance of solid brick walls under current and future climates. The study includes four types of assemblies and three types of mortars, and it was carried out for Lisbon and three other climates by using a computational simulation tool. Finally, the moisture gains and respective reach due to the future wind-driven rain (WDR) spells were assessed by means of using future weather files for Lisbon’s climate. It was shown that the solid brick layer is influenced differently depending on the characteristics of the mortar layers and outdoor conditions. In terms of WDR spells, aside from the precipitation and the spell period, the distribution of the WDR events within the spell also conditions the dryness of the assembly. The depth that the outdoor moisture was able to reach varies between 94 and 200 mm.

A Comparative Case Study of Certified and Non-Certified Green Buildings and Their Response to Climate Change

Green buildings (GBs) employ a wide range of passive and active energy-saving strategies to improve buildings’ energy performance. The suitability and performance of some of these strategies depend on outdoor climate conditions and may change over time due to global warming. Therefore, a GB may not retain its performance in the future. To address this issue and explore how much GB performance may be affected by climate change, this research aims to (1) evaluate the energy performance and thermal comfort of a GB and non-GB under present climate conditions; (2) predict the impact of climate change on these buildings, and (3) evaluate the climate resilience of a GB as opposed to a non-GB. To this end, a university GB and non-GB are simulated using DesignBuilder and calibrated with measured data. Future weather files based on Representative Concentration Pathways (RCPs) are used to predict climate conditions in the 2050s and 2090s. A comparison between the GB and non-GB revealed that the GB would save 15.1% and up to 21.9% of site energy under present and future climate conditions, respectively. It was also found that the thermal comfort level in the GB will remain significantly higher than in the non-GB in the future. The overheating issue in non-GBs will deteriorate in the future, with an increase of nearly 70% by the 2090s. The GB produces approximately 15% and up to 22% fewer GHG emissions than the non-GB under present and future climate conditions (RCP 8.5), respectively.

Future weather generator for building performance research: An open-source morphing tool and an application

Mathematical morphing of historical weather data to match the projected climate change scenario is a commonly used method to generate future weather files for building energy simulation. It is known for preserving the local weather characteristics, which is particularly important when designing or analyzing high-performance buildings. Researchers may use one of the available morphing tools. Unfortunately, current tools use future climate data from outdated climate models with lesser accuracy, coarser spatial resolution, and fewer climate scenarios than recent models. In addition, these tools are closed, preventing others from adding corrections, updating, and developing them further. This paper presents an open-source, cross-platform, and state-of-the-art morphing tool that generates future hourly weather data for the whole building performance simulation. The novel tool is applied to a real-case office building in Coimbra, Portugal. In the SSP5-8.5 scenario, simulations show thermal energy needs and electricity use will reduce by 60% in 2050 and 77% in 2080 for heating and will increase by 67% in 2050 and 121% in 2080 for cooling. As a result, the building's global electricity consumption will increase by 24% in 2050 and by 53% in 2080. The study is extended to other locations in Europe, concluding that the total HVAC energy needs will remain constant or even decrease in heating-dominated climates, mainly due to the significant drop in the heating demand in the future.

The Vatic Weather File Generator (VWFG v1.0.0)

To combat climate change caused by cities, it is necessary to perform urban physics modeling to assess mitigation solutions suitable for future climates. A challenge is availability of reliable future weather files for investigation of future climate scenarios. This research aims to develop the Vatic Weather File Generator (VWFG) using the statistical downscaling approach to fill this gap. VWFG is novel by using a history of weather files over multiple years to downscale future climate model data utilizing (1) quantile–quantile bias corrections, (2) record matching by the Finkelstein–Schafer method, and (3) shifting–stretching corrections. This implementation of VWFG uses the CanRCM4 climate model (1980–2100) and the ERA5 reanalysis data product as weather files (1980–2020) for two Representative Concentration Pathway (RCP) scenarios. VWFG outputs are consistent with findings in other studies. Further, to investigate the performance of VWFG for a case in Toronto, Canada, the Vertical City Weather Generator (VCWG) is forced by VWFG to predict the building sensible heating and cooling energy demands for a two-story single-family residential house. It is found that the building sensible heating demand is reduced over time (∼ 15%–30% for RCP 4.5–8.5 W m−2) and the building sensible cooling demand is increased over time (∼ 20%–50% for RCP 4.5–8.5 W m−2). The amount of change is greater for RCP 8.5 than RCP 4.5 W m−2. VWFG is a simple, practical, and widely applicable tool for urban physics simulations of future climates, particularly in cases where reliable forcing data is lacking otherwise.

Review of future weather data for building simulations available in Japan and confirmation of its characteristics

Buildings use a large amount of energy, depending on the climate. To design buildings with high energy and thermal performance in the future, it is necessary to use weather data that reflect future climatic information. Some future weather files for building simulations have been developed. However, these datasets are based on different predictions, and each future weather file has a different creation process. Such methodological differences may lead to differences in predicting the energy and thermal performance of buildings. Understanding the characteristics of each data type is necessary for its appropriate use. However, limited information is available for properly utilizing future weather data for building simulations. This study aims to provide information on the characteristics of future weather data for better utilization. After thoroughly reviewing the existing data and creation methods, we propose a framework for understanding future weather data based on their creative process. We collected five types of future weather datasets available in Japan and compared their characteristics. One of these datasets is the future weather dataset based on climate information provided by the National Institute for Environmental Studies (NIES). We confirmed the degree of variation in each weather element and predicted cooling/heating demand using future weather data available in Japan.

Resiliency comparison of radiant cooling systems and all- air systems

Radiant systems have been proven to be an energy-efficient and resource-effective heating and cooling solution for buildings. A key feature of a thermally active building system (TABS), one type of a radiant cooling system, is its ability to activate and control the thermal mass of the building structure. The advantage of this feature is the peak load shifting effect by the thermal mass, which leads to energy saving compared to a conventional system, e.g., an all-air system. This feature of the radiant cooling system could be particularly beneficial under a heat wave and power outage event. Dynamic building simulations were carried out to quantify the resilience of TABS to heat waves and power outages. An all-air system (i.e., airconditioning) was used as the reference cooling system. The simulations were carried out using EnergyPlus. Future weather files (typical meteorological years and years with heat waves) developed in IEA EBC Annex 80 were used for the simulations. In both HVAC systems. Simulation results for future weather data resulted in a decrease in heating demand and an increase in cooling demand.

Development of the Indian Future Weather File Generator Based on Representative Concentration Pathways

India’s fossil-fuel-based energy dependency is up to 68%, with the commercial and residential sectors contributing to the rise of building energy demand, energy use, and greenhouse gas emissions. Several studies have shown that the increasing building energy demand is associated with increased space-cooling ownership and building footprint. The energy demand is predicted to grow further with the conditions of global warming and the phenomenon of urban heat islands. Building designers have been using state-of-the-art transient simulation tools to evaluate energy-efficient envelopes with present-day weather files that are generated with historical weather datasets for any specific location. Designing buildings with historical climatic conditions makes the buildings vulnerable to the predicted climate change impacts. In this paper, a weather file generator was developed to generate Indian future weather files using a geo-filtering-based spatial technique, as well as the temporal downscaling and machine learning (ML)-based bias correction approach proposed by Belcher et al. The future weather files of the three representative concentration pathways of 2.6, 4.5, and 8.5 could be generated for the years 2030, 2050, 2070, 2090, and 2100. Currently, the outputs of the second-generation Canadian Earth System Model are being used to create future weather files that will aid architects, urban designers, and planners in developing a built environment that is resilient to climate change. The novelty lies in using observed historical data from present-day weather files on the typical meteorological year for testing and training ML models. The typical meteorological weather files are composed of the concatenation of the monthly weather datasets from different years, which are referred to for testing and training ML models for bias correction.

Future performance evaluation of PCM integrated buildings under changing climate

The high energy consumption and associated carbon emissions due to the heating and cooling of buildings create a heavy environmental burden. One of the cost-efficient solutions to reduce the heating and cooling demands is to incorporate phase change materials (PCMs) in the building components, increasing the thermal mass of the building and providing latent heat thermal storage. However, the rising temperatures over the years will alter the effectiveness of PCM in building envelopes. In this study, four cities in Turkey with different climatic characteristics were selected. For each city, future weather files representing the climatic conditions of 2050 and 2080 were generated from the current weather data using CCWorldWeatherGen. A typical office building that utilizes gypsum wallboards was modeled with EnergyPlus as a reference case. Alternative energy models were generated by modifying the wallboard compositions (PCM melting temperature: 19-27°C). The building’s annual heating and cooling energy demands were calculated for each city, year, and wallboard alternative. Generated data were analyzed to evaluate the future efficiency of the wallboards with the changing climate over the years in order to maximize the long-term performance gains from PCM incorporating wallboards. The results showed that the selection of the optimum PCM melting temperature of a location should not only depend on thermo-physical and layer properties of the PCM wallboard as the optimum melting temperature of the PCM is subject to change with rising temperatures. The impact of climate change should be considered to fully evaluate the long-term performance of the PCM wallboard in terms of energy use and CO2 emissions.

Data-driven, long-term prediction of building performance under climate change: Building energy demand and BIPV energy generation analysis across Turkey

This research presents a methodological framework for lifetime energy demand and PV energy generation predictions for a given building considering the CC impacts through multivariate regression models. As a case study, a hypothetical office building in Turkey was selected. An existing linear morphing methodology was utilized to generate future weather files for all 81 cities in Turkey. For each year and city, corresponding weather metrics were calculated, and heating/cooling demand and PV energy generation values were computed through building energy simulations. Obtained data were used to develop two sets of multivariate regression models: (i) models to predict future weather metrics and (ii) models to predict future energy demand and generation. These models allowed lifetime energy demand and generation analysis (including associated GWP and cost) of the building considering CC impacts using only the current weather metrics of its location. For a lifetime of 60 years, considering CC impacts yielded substantially higher cooling (averaging at +0.5 MWh/m2 in the warmest region) and lower heating loads (averaging at −0.4 MWh/m2 in the coldest region). For Turkey, the carbon intensity and the unit cost of cooling are much higher than those of heating. Therefore, the shift from heating to cooling has significant consequences in lifetime GWP and cost values (averaging +212 kg CO2-eq/m2 and +27 $/m2, respectively, for the warmest region), emphasizing the importance of the decarbonization of the energy sector. The impact of CC on PV energy generation was limited (all-city average of +0.02 MWh/m2 for the building lifetime). Our regression-based approach can be further expanded to include not only various building parameters and types, but also supply-demand matching potentials.

Creation and application of future typical weather files in the evaluation of indoor overheating in free-floating buildings

Expected Global warming and heatwaves coupled with the urban heat island effect (UHI) can overheat indoor environments of free-floating buildings in temperate climate regions. Overheating assessment requires practitioners to use appropriate climate data and suitable measurement indices. The aim of this article is first, to propose a practical approach to generate yearly and typical ready-to-use future typical weather datasets (FTWY) using high-resolution Regional Climate Model (RCM) data from Coordinated Regional Climate Downscaling Experiment (CORDEX), and second, investigate the potential of FTWYs in the assessment of indoor overheating, considering UHI effect.To achieve these objectives, three dynamically downscaled (DDS) FTWYs generated from RCMs (IPSL-SMHI, CNRM-ALADIN, MPI-REMO) were compared with one statistically downscaled (ESD) FTWY from Meteonorm, and observed heatwave weather data of 2003. Comparative analysis was performed in two stages: comparison of monthly statistical distribution of climate variables, and analysis of heatwave presence. Urban weather generator (UWG) was used to project UHI effect on two weather files for two buildings, and three overheating measurement indices were used to exploit results. Comparative analysis of weather files show that temperature in a FTWY in the medium future (2040–2070) is likely not as intense as the heatwave of 2003 for Nantes. Results also confirm that it is better to use two weather files, and at least two overheating indices to obtain reliable outputs. This study also revealed that indoor overheating is not limited to densely built areas where impact of UHI is highest; buildings located in sparsely built neighbourhoods are also at risk.

Multistage Optimization toward a Nearly Net Zero Energy Building Due to Climate Change

Climate change is one of the major problems of the planet. The atmosphere is overloaded with carbon dioxide caused by fossil fuels that are burned for energy. Almost 40 percent of the total energy worldwide is used by the building sector, which comes from non-renewable sources and contributes up to 30% of annual greenhouse gas emissions globally. The building sector in Iran accounts for 33.8% of Iran’s total energy usage. Within the building sector, the energy consumption of Iranian educational buildings is 2.5 times higher than educational buildings in developed countries. One of the most effective ways of reducing global energy consumption and greenhouse gas emissions is retrofitting existing buildings. This study aims to investigate whether a particular energy-optimized design under the present climate conditions would respond effectively to future climate change. This can help designers make a better decision on an optimal model, which can remain optimal over the years based on climate change. For methodological purposes, multistage optimization was used to retrofit an existing educational building. Specifically, the non-dominated sorting genetic algorithm (NSGA-II) was chosen to minimize the cooling and heating load, as well as consider investment costs for present and future weather files, using the jEPlus tool. Furthermore, the TOPSIS method was used to identify the best set of retrofit measures. For this purpose, a four-story educational building in Tehran was modeled on Design Builder software v7.0.0.116 as a case study to provide a better understanding for researchers of how to effectively retrofit a building to achieve a nearly zero energy building considering climate change. The results show that the optimized solution for the present weather file does not remain the optimized solution in 2080. Moreover, it is shown that to have an optimized building in regard to future weather files, the model should be designed for the future weather conditions. This study shows that if the building becomes optimized using the present weather file the total energy consumption will be reduced by 65.14% and 86.18% if using the future weather file. These two figures are obtained by implementing active and passive measures and show the priority of using the future weather file for designers. Using PV panels also, this building is capable of becoming a nearly net zero building, which would produce about 90% of its own energy demands.

Selecting extreme weather file to assess overheating in residential building

Climate change is great challenge for current and newly built buildings. Nowadays, TMY weather file can be easily generated following the IPCC scenarios. Nevertheless, since these data are extrapolated with stochastic model from monthly mean values, they do not show a real pattern and do not include extreme events like heatwaves. In order to get more representative data, we propose in this work a methodology to select real measured files from a large database in light of heatwaves and climate change. This methodology is applied to the city of Lyon, for which 26 years of weather data are available. Three measured weather files projected for the time periods 2020, 2050 and 2080 are selected. These files are used in building thermal simulation of residential building with low or high thermal inertia. Summer overheating is analysed through two different comfort indicators: adaptative comfort and Givoni chart. Results indicates that summer overheating risk is obviously increased with future weather files. When compared to usual TMY files, this risk is also enhanced by using weather file including extreme events like heatwaves. Last, we note that discomfort is mainly encountered during this extreme events.