Future Weather Scenarios Research Articles

Impact of future climate scenarios on thermal performance and resilience of building façades: Canadian climate case study

Buildings in urban areas are responsible for a significant share of GHG emissions that directly contribute to climate change. Nevertheless, the built environment is vulnerable to the changing climate. Particularly, the unpredictable weather threatens the performance of building components, durability of building materials, and indoor environmental comfort. In this study, the impact of future climate on thermal performance of building façades in the Canadian climate is investigated using simulation analysis. To account for different climate conditions, three future weather scenarios pertaining to global temperature rise of 0.5 °C, 1.5 °C, and 2.5 °C were compared with historical weather data. Both hourly and Typical Meteorological Year (TMY) weather data were studied. The results, including thermal transmittance, heat flux, moisture content, and façade temperature were compared. This comparison could show the applicability of using averaged TMY data compared to the large hourly dataset. The results show a pattern of change in the façade's thermal and hygrothermal performance as temperature, relative humidity and solar radiation norms change in both seasons. The comparison between the TMY and the Yearly data showed an underestimation of heat transfer within the façade when the TMY data is used. The historical TMY data results showed the inadequacy of this weather file for climate impact assessments of facades in both summer and winter. The approach used in this study can be repeated for different climate conditions, acting as a tool to design façades and predict their performance in face of a changing climate.

Climate change mitigation and adaptation in Spanish office stock through cool roofs

In a context of climate change, the cooling period of buildings is increasing every year in Mediterranean countries. This will become a relevant issue when existing buildings are retrofitted. Cool roofs have a passive cooling effect on a building and can contribute to decreasing the annual cooling demand. In office buildings, thermal comfort has a considerable influence on workers’ performance. In these buildings cooling energy demands tend to be high due to the high internal thermal loads. This paper describes annual energy simulations of Spanish office stock to evaluate the potential energy savings of cool roofs within the context of building retrofitting. The energy demand and thermal comfort of representative office buildings is compared before and after the application of a cool roof coating, in the present time and in the year 2050, for all climate areas of Spain, under the most optimistic and most pessimistic future weather scenarios. Results showed that the cooling energy demand of Spanish office stock can be potentially reduced by 25 % when a cool roof is applied, and the annual energy demand for heating and cooling can be cut by 6 %, 11 % and 12 % in the present, the optimistic future scenario and the pessimistic future scenario, respectively.

Evaluating Thermal Comfort and Overheating Risks in A Social Housing Prototype: As Built Versus Retrofit Scenarios

Climate change has highlighted the importance of thermal comfort and its health-related outcomes, particularly for the most vulnerable members of society living in social housing. Due to their vulnerable living conditions, low-income people are more exposed to negative outcomes of overheating and cold indoor temperatures in buildings. Previous studies suggest that there is a significant risk of overheating in retrofitted buildings both for the current and future weather scenarios. The UK government has introduced new building regulations to assess and limit the risk of overheating in new buildings; however, there is still a need to assess and improve conditions for existing and retrofitted properties. This study aims to evaluate the effect of retrofit strategies on thermal comfort and the risk of overheating in social housing under current and future climatic conditions. A typical case study building was simulated in DesignBuilder to assess thermal comfort conditions for upgraded building fabric to Part L of the UK building regulations and Passive House standards. The summer results were analyzed according to CIBSE TM59 while the Predicted Mean Vote index (PMV) was used for winter analysis. Findings revealed that the south-facing bedrooms are most exposed to overheating. Risk of overheating significantly increased for the future weather scenarios by up to 10 times while winter thermal comfort improved for the retrofitted scenarios.

Marine heatwaves alter competition between the cultured macroalga Gracilariopsis lemaneiformis and the harmful bloom alga Skeletonema costatum

Seaweed cultivation can inhibit the occurrence of red tides. However, how seaweed aquaculture interactions with harmful algal blooms will be affected by the increasing occurrence and intensity of marine heatwaves (MHWs) is unknown. In this study, we run both monoculture and coculture systems to investigate the effects of a simulated heatwave on the competition of the economically important macroalga Gracilariopsis lemaneiformis against the harmful bloom diatom Skeletonema costatum. Coculture with G. lemaneiformis led to a growth decrease in S. costatum. Growth and photosynthetic activity (Fv/Fm) of G. lemaneiformis was greatly reduced by the heatwave treatment, and did not recover even after one week. Growth and photosynthetic activity of S. costatum was also reduced by the heatwave in coculture, but returned to normal during the recovery period. S. costatum also responded to the stressful environment by forming aggregates. Metabolomic analysis suggests that the negative effects on S. costatum were related to an allelochemical release from G. lemaneiformis. These findings show that MHWs may enhance the competitive advantages of S. costatum against G. lemaneiformis, leading to more severe harmful algal blooms in future extreme weather scenarios.

Decarbonising well-insulated buildings in a warming climate: The case of adaptive thermal comfort with geothermal space heating

Buildings contribute to 40% of global energy demand and are responsible for a third of CO2 emissions. Strategies to decarbonise buildings are, therefore, crucial for reaching the net-zero emissions targets by most of the countries in the world. This study investigates the feasibility of decarbonising well-insulated buildings with current and future weather scenarios by applying adaptive thermal comfort strategy in combination with a closed-loop deep geothermal system. An office building has been chosen as a case study because of the comprehensive sensor system installed in the building which allows for detailed data extraction and analysis. The results show that the building’s heating and cooling demand can be reduced by 51% using an adaptive thermal comfort approach, while this decreases to 45% in 2080 under a warming climate. Combined with this adaptive approach, geothermal energy can satisfy 50% of building heating demand at present when combined with intermittent storage scenarios, while 5 deep borehole heat exchangers (DBHEs) would be required to meet all the heating demand directly. In conclusion, this study shows that using a DBHE and adaptive thermal comfort approach to well-insulated buildings presents an innovative and low-cost opportunity for buildings to significantly lower building thermal demand and carbon emissions.

Climate-resilient building energy efficiency retrofit: Evaluating climate change impacts on residential buildings

Buildings have the potential to mitigate climate change effects by integrating energy-efficient solutions. Building resilient design strategies based on forthcoming weather predictions offers an effective means of adaptation. The study focuses on the impact of climate change on residential buildings in Istanbul and Izmir, two Turkish cities with distinctive climate characteristics. By creating future weather scenarios and conducting dynamic simulations, buildings’ and improvement measures’ performance under RCP 4.5 and RCP 8.5 climate scenarios and short- and long-term periods are evaluated. The findings reveal varying degrees of climate change impact on the two regions, with decreased heating degree days (HDDs) and increased cooling degree days (CDDs). Notably, the RCP 8.5 scenario projects significant temperature increases, with a rise of 4.3 °C in Istanbul and 5 °C in Izmir, leading to profound consequences for buildings. The CDD can be doubled in July and reach 292 in Izmir and quadrupled, reaching 158 in Istanbul. Without retrofit, in a well-naturally ventilated building, primary heating energy consumption can be decreased by 36–41 %, while primary cooling energy consumption tripled in both cities. With the aid of improvements, a ∼ 5–6 °C decrease was observed in the highest temperature predictions in naturally ventilated spaces in summer in Istanbul, while a ∼ 4–5 °C decrease was observed in Izmir.

Enhancing the smart readiness of buildings: Combining Collective intelligence and Reinforcement learning in Building Energy Management

This research introduces a novel Energy Management approach, named CIRLEM, aiming to enhance the smartness of buildings by focusing on technical systems operations, environmental variations, and occupants' needs. Deployed in a simulated environment using Building Performance Simulation and Python integration, the study evaluates CIRLEM's performance under future extreme cold weather scenarios, employing a set of representative climate data. The pilot case, two building blocks in Sweden, undergoes assessment for energy demand, peak power, and thermal comfort. Results indicate that CIRLEM, particularly when driven by demand and price signals, effectively reduces energy demand and costs, demonstrating strong adaptability to extreme weather conditions. Thermal comfort is maintained regarding the temperature limits and variations. Ongoing developments attempt to refine the reward function and signal generation for thermal comfort enhancement and real-world implementation.

A Systematic Review of Climate Change Implications on Building Energy Consumption: Impacts and Adaptation Measures in Hot Urban Desert Climates

The climate change–built environment nexus is complex and intertwined. Recognizing the rising air temperatures and solar radiations owing to climate-induced global warming, it is critical to manage the increased building energy and cooling loads in the Middle East Gulf states’ hot desert climates (Bwh). One of the top climate priorities is to promote climate resilience by reducing risks and enhancing adaptation options. This study aims to systematically review the existing literature to document building energy performances in and the associated adaptation measures of the Middle East Gulf states, regarding the implications of climate change. It is accomplished by answering the following questions: ‘How well do we understand the effects of climate change on building energy use in hot urban deserts?’ and ‘What are the most appropriate adaptation strategies to reduce energy use in hot urban deserts?’. Using the Preferred Reporting Items for Systematic review and Meta-Analysis protocols (PRISMA), 17 studies on the influence of present and future weather scenarios on building performance are examined, considering variations in typology, methods, and input variables. Finally, the paper identifies the preferred methods and input variables for modelling building energy performance under predicted climatic changes. Passive design considerations are considered highly effective in mitigating and adapting to climate change implications. Thermal insulation and efficient window glazing are identified as the best-performing strategies, while the use of solar Photovoltaic (PV) is considered efficient in meeting the primary energy demands. The study’s findings can assist planners and designers in projecting future climatic influences on the energy usage of existing buildings.

Extending the IFC-Based bim2sim Framework to Improve the Accessibility of Thermal Comfort Analysis Considering Future Climate Scenarios

Future weather scenarios significantly affect indoor thermal comfort, influencing people’s well-being and productivity at work. Thus, future weather scenarios should be considered in the design phase to improve a building’s climate change resilience for new constructions as well as renovations in building stock. As thermal comfort is highly influenced by internal and external thermal loads resulting from weather conditions and building usage, only a dynamic building performance simulation (BPS) can predict the boundary conditions for a thermal comfort analysis during the design stage. As the model setup for a BPS requires detailed information about building geometry, materials, and usage, recent research activities have tried to derive the required simulation models from the open BIM (Building Information Modeling) Standard IFC (Industry Foundation Classes). However, even if IFC data are available, they are often faulty or incomplete. We propose a template-based enrichment of the BPS models that assists with imputing missing data based on archetypal usage of thermal zones. These templates are available for standardized enrichment of BPS models but do not include the required parameters for thermal comfort analysis. This study presents an approach for IFC-based thermal comfort analysis and a set of zone-usage-based templates to enrich thermal comfort input parameters.

Inclusive urban building energy modeling through socioeconomic data: A persona-based case study for an underrepresented community

Urban Building Energy Modeling provides a way to simulate energy use at the scale of a neighborhood or city, rather than the typical simulation of a single building. This can be a powerful tool to reduce current energy usage and to guide future planning efforts. This switch in scales is crucial in reducing energy use and planning more sustainable and resilient cities. Critical work is being done to utilize and improve urban building energy modeling. However, current workflows and tools do not account for the socioeconomic factors of study areas. This paper identifies the impacts of socioeconomic factors and establishes a framework that can be used to gather the data required to run accurate urban building energy modeling studies that consider the urban context. A case study utilizing the Urban Modeling Interface Rhino plugin to simulate the energy use of 110 single-family residential structures in the Grove Park neighborhood of Atlanta, Georgia demonstrates the framework. The results of the study analyze current energy use patterns, compare underserved neighborhood-specific archetype definitions to default residential archetype templates, and investigate the neighborhood's performance under future weather scenarios. The study shows that within a single neighborhood the Energy Use Intensity can vary by up to 92 kWh/m2 based on building envelope condition and occupancy patterns. Default archetype inputs can dramatically underestimate or overestimate the energy use of households in a low resource community. Urban energy models must account for demographic and socioeconomic factors to create an accurate model that reflects lived experiences.

Climate Change Impact on Energy Poverty and Energy Efficiency in the Public Housing Building Stock of Bari, Italy

The public housing stock across the European Union is generally constituted of old buildings (built prior to 1980) with high energy demand and indoor thermal comfort issues, which could be exacerbated by climate change. The aim of this paper was to quantify the impact of climate change on the energy demand of the public housing building stock. A neighbourhood located in Bari (south Italy) is considered as representative of a common construction typology of late 1970s in Italy. Energy models were created and calibrated with real-time data collected from utilities’ bills. The results showed a medium to strong correlation between age and energy consumption (r = 0.358), but no evident correlation between the number of tenants and energy consumption, although a significantly low energy consumption was found in apartments occupied by more than five tenants. An energy penalty of about 7 kWh/m2 of heating energy consumption for every 10 years of increase in the average age of tenants was calculated. Moreover, the impact of future weather scenarios on energy consumptions was analysed and an average annual energy penalty of 0.3 kWh/m2 was found.

High-resolution impact assessment of climate change on building energy performance considering extreme weather events and microclimate – Investigating variations in indoor thermal comfort and degree-days

• Exploiting a high-resolution building energy model of two residential blocks in Sweden. • Considering 13 future weather scenarios besides typical and extreme conditions. • Impacts of microclimate emerge significantly during nighttime and warm seasons. • Climate change can considerably reduce indoor thermal comfort. • Peak cooling loads increase by 210% and 290% at the middle and end of the century. • Cooling systems are essential to maintain thermal comfort in the future. Climate change and urbanization are two major challenges when planning for sustainable energy transition in cities. The common approach for energy demand estimation is using only typical meso-scale weather data in building energy models (BEMs), which underestimates the impacts of extreme climate and microclimate variations. To quantify the impacts of such underestimation on assessing the future energy performance of buildings, this study simulates a high spatiotemporal resolution BEM for two representative residential buildings located in a 600 × 600 m2 urban area in Southeast Sweden while accounting for both climate change and microclimate. Future climate data are synthesized using 13 future climate scenarios over 2010-2099, divided into three 30-year periods, and microclimate data are generated considering the urban morphology of the area. It is revealed that microclimate can cause 17% rise in cooling degree-day (CDD) and 7% reduction in heating degree-day (HDD) on average compared to mesoclimate. Considering typical weather conditions, CDD increases by 45% and HDD decreases by 8% from one 30-year period to another. Differences can become much larger during extreme weather conditions. For example, CDD can increase by 500% in an extreme warm July compared to a typical one. Results also indicate that annual cooling demand becomes four and five times bigger than 2010-2039 in 2040-2069 and 2070-2099, respectively. The daily peak cooling load can increase up to 25% in an extreme warm day when accounting for microclimate. In the absence of cooling systems during extreme warm days, the indoor temperature stays above 26°C continuously over a week and reaches above 29.2°C. Moreover, the annual overheating hours can increase up to 140% in the future. These all indicate that not accounting for influencing climate variations can result in maladaptation or insufficient adaptation of urban areas to climate change.

The Impact of Climate Change on a University Campus’ Energy Use: Use of Machine Learning and Building Characteristics

Global warming is expected to increase 1.5 °C between 2030 and 2052. This may lead to an increase in building energy consumption. With the changing climate, university campuses need to prepare to mitigate risks with building energy forecasting models. Although many scholars have developed buildings energy models (BEMs), only a few have focused on the interpretation of the meaning of BEM, including climate change and its impacts. Additionally, despite several review papers on BEMs, there is no comprehensive guideline indicating which variables are appropriate to use to explain building energy consumption. This study developed building energy prediction models by using statistical analysis: multivariate regression models, multiple linear regression (MLR) models, and relative importance analysis. The outputs are electricity (ELC) and steam (STM) consumption. The independent variables used as inputs are building characteristics, temporal variables, and meteorological variables. Results showed that categorizing the campus buildings by building type is critical, and the equipment power density is the most important factor for ELC consumption, while the heating degree is the most critical factor for STM consumption. The laboratory building type is the most STM-consumed building type, so it needs to be monitored closely. The prediction models give an insight into which building factors remain essential and applicable to campus building policy and campus action plans. Increasing STM is to raise awareness of the severity of climate change through future weather scenarios.

Warm winters challenge the cultivation of temperate species in South America\u2014a spatial analysis of chill accumulation

Winter chill accumulation plays a crucial role in determining the moment of bud burst in temperate fruit and nut trees, and insufficient chill can greatly limit yield potentials. To assess future cultivation options for such species in South America, we estimated winter chill through a spatial analysis. We used historical data (1980–2017) from 158 weather stations to calibrate a weather generator and produce temperature data for 10 historical and 60 future scenarios. We computed Safe Winter Chill (SWC, corresponding to the 10th quantile of a chill distribution) for the period 1980–2017 and for all historical and future weather scenarios and developed a framework to interpolate SWC for the continent using the Kriging method. To improve the interpolation, we applied a 3D correction model based on two co-variables (means of daily temperature extremes in July). Our results suggest important chill declines in southern Brazil and central Chile. By 2050 under the global warming scenario RCP4.5 (Representative Concentration Pathway), absolute SWC in these regions may reach a median of 18.7 and 39.6 Chill Portions (CP), respectively. Projections are most alarming for a strong global warming scenario (RCP8.5). In southern South America, adequate SWC levels of about 60 CP may be expected even under the RCP8.5 scenario. Our results highlight the need for climate change adaptation measures to secure temperate fruit production in important growing regions of South America. The procedure we developed may help farmers and practitioners across South America estimate future SWC to adapt their orchards to future challenges.

Energy performance assessment of passive buildings in future climatic scenarios: the case of study of the childcare centre in Putignano (Bari, Italy)

The building sector is a primary target for GreenHouse Gas emissions mitigation efforts, as it accounts for 36% of final energy use. The most effective mitigation strategies include the energy retrofit of the existing building stock. Among existing buildings, particular attention should be paid to school buildings, which are among the most diffuse public buildings in Europe, most of them built decades ago, with a resulting high potential in terms of refurbishment effectiveness. Moreover, schools cover a social function and require high levels of indoor environmental quality. In this field, the research activity is intense, but retrofit strategies are still conceived considering historical weather data, which could not represent correctly present and future climate patterns, reducing the retrofit effectiveness. In this work, an energy retrofit to “Passivhaus standard” of a childcare centre located in the Mediterranean area is analysed through dynamic simulations. A post-retrofit building model is simulated using Typical Meteorological Year (TMY) and compared with the ones simulated in future weather scenarios, created using the morphing method. The analyses aim to assess if the technical solutions currently adopted on the basis of the TMY will lead to acceptable energy performance in future decades. Furthermore, a sensitivity analysis of different design solutions is performed, aiming to assess their effectiveness in future weather conditions.

Improving building thermal performance through an integration of Passivhaus envelope and shading in a tropical climate

Due to the success of the energy-efficient Passivhaus building envelope and its principles in regulating indoor thermal comfort in European climates, the potential implementation of it in other climates has been subjected to much attention in recent years. In this work, we adopted the hypothesis that slightly higher U-values of walls and floors than Passivhaus suggestion could be sufficient to achieve Passivhaus targets in the tropical context if the synergistic effects between shading and building envelope design were considered in a naturally ventilated condition.Firstly, thermal comfort thresholds were reviewed to establish the boundaries in the tropical context, choosing Myanmar as a case study. Secondly, Passivhaus steady-state calculation for shading design was compared with other dynamic simulation programs to inform the next step. The impacts of other parameters, which were excluded in Passihvuas’s PHPP calculation, were then investigated. Finally, thirty shading scenarios for ten different building envelopes were analysed in free-running modes using typical and future weather scenarios. The results showed that the hypothesis was true and 3.6% of annual overheating hours were reduced by coupling Passivhaus building envelope, thermal mass and shading devices, and also overall extremes of temperature were reduced by more than 2.4 K on the hottest day.

Performance assessment of dual-mode evaporative cooler for futuristic climatic scenarios considering climate change effect

Climate change is expected to have a significant impact on device usability in different regions. Hence, it is necessary to study its impact on the performance of evaporative cooling, which is an alternative cooling technology to reduce increasing energy demand and carbon footprint. This study focuses on exploring the usefulness of the dual-mode evaporative cooler for future weather scenarios. An experimental prototype of a dual-mode evaporative cooler is developed and tested to validate the simulation model. The exponential smoothing method is used to forecast the temperature and humidity for four Indian cities (Varanasi, Delhi, Jodhpur, and Mumbai) of different climatic zones (composite, hot-dry and hot-humid). The six-month average temperature of Delhi and Mumbai city will increase by 0.48 °C and 0.62 °C, respectively. The dew point effectiveness, cooling capacity, and COP in both modes of the dual-mode evaporative cooler are investigated for all four cities. The suitability of the modes of the dual-mode evaporative cooler is predicted based on the thermal comfort conditions for present and future scenarios using a psychometric chart. The present study reveals the usefulness of the dual-mode cooler in future (for example, 2030) scenarios for composite and hot-dry climatic conditions.

Multi-objective building design optimization considering the effects of long-term climate change

Building performance is heavily influenced by weather conditions. Though the climate is changing vastly, few building performance optimizations (BPO) consider global warming over the life expectancy of the buildings. This paper develops a novel multi-objective BPO framework by the using simulation-based surrogate models under the future weather conditions that are determined by morphing the typical meteorological year (TMY) data. This framework is adopted to optimize a typical classroom in a hot and humid area under the future weather scenarios of representative concentration pathways (RCP) 4.5 and 8.5. The energy, thermal comfort and daylighting performances with and without considering the climate changes in the optimizations are compared and their notable differences are discussed. Under future climate, the optimization considering the future climate change improves the building performances significantly compared to the optimization without any climate change considerations (i.e., using the historical TMY). Especially, the winter discomfort hours in RCP4.5 and 8.5 decrease by 7.4% and 13.3%, respectively, when such future climate changes are considered in the BPOs, compared to the BPOs using the historical TMY data. The results show that BPO without considering climate change effects may cause non-negligible uncertainties. The proposed method can effectively improve the building performance in a changing climate.

Analysing the future energy performance of residential buildings in the most populated Italian climatic zone: A study of climate change impacts

There is growing concern that global warming will change the building’s performance pattern in the future. This paper investigates the effects of climate changes on the heating and cooling energy demand, the overall energy performance and the overheating risk of typical residential buildings (existing and refurbished) in the biggest city of the most populated Italian climatic zone, Milan. The widely used morphing methodology was adapted for creating future weather data for different scenarios. Energy performance analysis was carried out using dynamic simulation for the near term (2021–2040) and the long term (2081–2099) periods. The results show decreases in heating energy demand up to 30.9%, intense increases in cooling energy demand, up to 255.1% and significant increases of overheating risk up to 155%. In addition, the effect of refurbishment on each parameter is also analysed and reported. The research demonstrates that climate change causes a paradigm shift in the building energy performance, while the magnitude of climate change impact is not equal for different building types, time periods, insulation levels, and future weather scenarios. Therefore, climate change must be considered for future energy performance assessment of buildings.

Predicting the impact of climate change in Srepok river basin by LARS-WG model with CMIP5 scenarios

Global warming has significantly challenged the natural environment and livelihood conditions. Understanding potential future changes of climate variables, such as temperature and precipitation, is critical for water resource management in this region. This study proposed an approach to applying LARS-WG model in CMIP5 scenarios, 9 monitoring stations with 25-year series of dately data used for calibration and validation, which were the input data of the model. Combining data from 5 outputs of general periodic model (GCMs) for the periods 2021–2020, 2041–2060, and 2061– 2080, the results showed that the CMIP5 scenarios could be used successfully in the LARS-WG model and the model worked well under the climatic conditions of the Srepok river basin (Central Highlands of Vietnam). Comparing future weather scenarios with current weather data showed that warmer transitions and reduced rainfall would be generally in the future. Future temperature and precipitation trends showed an increase in both the magnitude and frequency of extreme events. So the affects of climate change are enormous on the management of related projects. Water resources need to be considered a lot in the local decision-making.