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Journal articles on the topic 'Future weather file'

Author: Grafiati

Published: 14 March 2023

Last updated: 31 July 2025

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1

Manapragada, Naga Venkata Sai Kumar, Anoop Kumar Shukla, Gloria Pignatta, et al. "Development of the Indian Future Weather File Generator Based on Representative Concentration Pathways." Sustainability 14, no. 22 (2022): 15191. http://dx.doi.org/10.3390/su142215191.

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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

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Lauzet, N., T. Colinart, M. Musy, and K. Lapray. "Selecting extreme weather file to assess overheating in residential building." Journal of Physics: Conference Series 2069, no. 1 (2021): 012231. http://dx.doi.org/10.1088/1742-6596/2069/1/012231.

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Abstract 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 a

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Aram, Kimiya, Roohollah Taherkhani, and Agnė Šimelytė. "Multistage Optimization toward a Nearly Net Zero Energy Building Due to Climate Change." Energies 15, no. 3 (2022): 983. http://dx.doi.org/10.3390/en15030983.

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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 eff

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P.Tootkaboni, Mamak, Ilaria Ballarini, Michele Zinzi, and Vincenzo Corrado. "A Comparative Analysis of Different Future Weather Data for Building Energy Performance Simulation." Climate 9, no. 2 (2021): 37. http://dx.doi.org/10.3390/cli9020037.

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The building energy performance pattern is predicted to be shifted in the future due to climate change. To analyze this phenomenon, there is an urgent need for reliable and robust future weather datasets. Several ways for estimating future climate projection and creating weather files exist. This paper attempts to comparatively analyze three tools for generating future weather datasets based on statistical downscaling (WeatherShift, Meteonorm, and CCWorldWeatherGen) with one based on dynamical downscaling (a future-typical meteorological year, created using a high-quality reginal climate model

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Arima, Yusuke, Kunihiko Fujiwara, Yasuhiko Azegami, Hajime Iseda, Akihito Ozaki, and Younhee Choi. "Review of future weather data for building simulations available in Japan and confirmation of its characteristics." E3S Web of Conferences 396 (2023): 05014. http://dx.doi.org/10.1051/e3sconf/202339605014.

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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 f

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Tsoka, S., and K. Velikou. "Climate change impacts on heating and cooling energy demand in residential building units. Application in the city of Thessaloniki, Greece." IOP Conference Series: Earth and Environmental Science 1196, no. 1 (2023): 012021. http://dx.doi.org/10.1088/1755-1315/1196/1/012021.

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Abstract 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

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Yassaghi, Hamed, Patrick L. Gurian, and Simi Hoque. "Propagating downscaled future weather file uncertainties into building energy use." Applied Energy 278 (November 2020): 115655. http://dx.doi.org/10.1016/j.apenergy.2020.115655.

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Demanuele, C., A. Mavrogianni, M. Davies, M. Kolokotroni, and I. Rajapaksha. "Using localised weather files to assess overheating in naturally ventilated offices within London's urban heat island." Building Services Engineering Research and Technology 33, no. 4 (2011): 351–69. http://dx.doi.org/10.1177/0143624411416064.

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Urban environments typically experience increased average air temperatures compared to surrounding rural areas – a phenomenon referred to as the Urban Heat Island (UHI). The impact of the UHI on comfort in naturally ventilated buildings is the main focus of this article. The overheating risk in urban buildings is likely to be exacerbated in the future as a result of the combined effect of the UHI and climate change. In the design of such buildings in London, the usual current practice is to view the use of one generic weather file as being adequate to represent external temperatures. However,

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Fiorito, Francesco, Giandomenico Vurro, Francesco Carlucci, et al. "Adaptation of Users to Future Climate Conditions in Naturally Ventilated Historic Buildings: Effects on Indoor Comfort." Energies 15, no. 14 (2022): 4984. http://dx.doi.org/10.3390/en15144984.

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User behaviour can significantly affect indoor thermal comfort conditions, as well as energy consumption, especially in existing buildings with high thermal masses where natural cross ventilation is the main strategy to reduce cooling loads. The aims of this paper were: (i) to compare how behavioural changes evaluated by means of rule-based and stochastic models lead to changes in indoor thermal comfort levels, and (ii) to define the patterns of indoor thermal comfort in historic residential buildings in future scenarios. To this end, a historic building located in Molfetta (Southern Italy) wa

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Ciancio, Virgilio, Serena Falasca, Iacopo Golasi, et al. "Resilience of a Building to Future Climate Conditions in Three European Cities." Energies 12, no. 23 (2019): 4506. http://dx.doi.org/10.3390/en12234506.

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Building energy need simulations are usually performed using input files that contain information about the averaged weather data based on historical patterns. Therefore, the simulations performed are not able to provide information about possible future scenarios due to climate change. In this work, future trends of building energy demands due to the climate change across Europe were studied by comparing three time steps (present, 2050, and -2080) in three different European cities, characterized by different Köppen-Geiger climatic classes. A residential building with modern architectural fea

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Watkins, R., GJ Levermore, and JB Parkinson. "Constructing a future weather file for use in building simulation using UKCP09 projections." Building Services Engineering Research and Technology 32, no. 3 (2011): 293–99. http://dx.doi.org/10.1177/0143624410396661.

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Hutchison, Keith D., Barbara D. Iisager, Sudhakar Dipu, Xiaoyan Jiang, Johannes Quaas, and Randy Markwardt. "A Methodology for Verifying Cloud Forecasts with VIIRS Imagery and Derived Cloud Products—A WRF Case Study." Atmosphere 10, no. 9 (2019): 521. http://dx.doi.org/10.3390/atmos10090521.

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A methodology is presented to evaluate the accuracy of cloud cover fraction (CCf) forecasts generated by numerical weather prediction (NWP) and climate models. It is demonstrated with a case study consisting of simulations from the Weather Research and Forecasting (WRF) model. In this study, since the WRF CCf forecasts were initialized with reanalysis fields from the North American Mesoscale (NAM) Forecast System, the characteristics of the NAM CCf products were also evaluated. The procedures relied extensively upon manually-generated, binary cloud masks created from VIIRS (Visible Infrared Im

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Passos Filho, José Aderson Araújo, Bruno de Payva y. Raviolo, Natasha Catunda, Nayana Helena Barbosa de Castro, Karoline Cordeiro de Andrade, and Daniel Ribeiro Cardoso. "Synthesizing test Reference Year files from known climate patterns of nearby cities." PARC Pesquisa em Arquitetura e Construção 10 (December 29, 2019): e019030. http://dx.doi.org/10.20396/parc.v10i0.8653706.

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The importance of an architecture adapted to its climatic context is often debated. In order to avoid future unexpected environmental behavior or failure of a building during its use, building simulation tools are used in the design and require complete and consistent weather data. However, such data are not always available for the locations where buildings are simulated, and the use of data from neighboring cities becomes usual. There are, though, several uncertainties involved in the behavior of environmental variables when the climate of large urban centers is attributed to nearby localiti

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Sommer, Philipp S., and Jed O. Kaplan. "A globally calibrated scheme for generating daily meteorology from monthly statistics: Global-WGEN (GWGEN) v1.0." Geoscientific Model Development 10, no. 10 (2017): 3771–91. http://dx.doi.org/10.5194/gmd-10-3771-2017.

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Abstract. While a wide range of Earth system processes occur at daily and even subdaily timescales, many global vegetation and other terrestrial dynamics models historically used monthly meteorological forcing both to reduce computational demand and because global datasets were lacking. Recently, dynamic land surface modeling has moved towards resolving daily and subdaily processes, and global datasets containing daily and subdaily meteorology have become available. These meteorological datasets, however, cover only the instrumental era of the last approximately 120 years at best, are subject

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Pouriya, Jafarpur, and Berardi Umberto. "Building energy demand within a climate change perspective: The need for future weather file." IOP Conference Series: Materials Science and Engineering 609 (October 23, 2019): 072037. http://dx.doi.org/10.1088/1757-899x/609/7/072037.

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Gaarder, Jørn Emil, Hans Olav Hygen, Rolf André Bohne, and Tore Kvande. "Building Adaptation Measures Using Future Climate Scenarios—A Scoping Review of Uncertainty Treatment and Communication." Buildings 13, no. 6 (2023): 1460. http://dx.doi.org/10.3390/buildings13061460.

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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 underl

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Dannenberg, Valentin, Robert Schüler, and Achill Schürmann. "A Data Processing Framework for Polar Performance Diagrams." Applied Sciences 12, no. 6 (2022): 3085. http://dx.doi.org/10.3390/app12063085.

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Polar performance diagrams are commonly used to predict the performance of a sailing vessel under given wind conditions. They are, in particular, an essential part of robotic sailing vessels and a basis for weather routing algorithms. In this paper we introduce a new framework for scientific work with such diagrams, which we make available as an open source Python package. It contains a model for the creation of polar performance diagrams from measurement data and supports different representations of polar performance diagrams for different tasks. The framework also includes several methods f

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Yassaghi, Hamed, and Simi Hoque. "Impact Assessment in the Process of Propagating Climate Change Uncertainties into Building Energy Use." Energies 14, no. 2 (2021): 367. http://dx.doi.org/10.3390/en14020367.

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Buildings are subject to significant stresses due to climate change and design strategies for climate resilient buildings are rife with uncertainties which could make interpreting energy use distributions difficult and questionable. This study intends to enhance a robust and credible estimate of the uncertainties and interpretations of building energy performance under climate change. A four-step climate uncertainty propagation approach which propagates downscaled future weather file uncertainties into building energy use is examined. The four-step approach integrates dynamic building simulati

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Yassaghi, Hamed, and Simi Hoque. "Impact Assessment in the Process of Propagating Climate Change Uncertainties into Building Energy Use." Energies 14, no. 2 (2021): 367. http://dx.doi.org/10.3390/en14020367.

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Buildings are subject to significant stresses due to climate change and design strategies for climate resilient buildings are rife with uncertainties which could make interpreting energy use distributions difficult and questionable. This study intends to enhance a robust and credible estimate of the uncertainties and interpretations of building energy performance under climate change. A four-step climate uncertainty propagation approach which propagates downscaled future weather file uncertainties into building energy use is examined. The four-step approach integrates dynamic building simulati

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Chatterjee, Sumana. "Role of ChatGPT to Predict Trend of Special Weather during Nor ’wester Season." International Journal of Education, Modern Management, Applied Science & Social Science 07, no. 02(II) (2025): 15–20. https://doi.org/10.62823/ijemmasss/7.2(ii).7512.

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This paper is based on data analysis by python programming language code provided by ChatGPT executed on google collaborator platform, model used as neural network, to understand the trend of special weather phenomena for the period March to May, to check the occurrence of special weather event like lightning, thunderstorm, rain, drizzle, squall, during this period, called as Nor ‘wester season and also as pre-monsoon period. Analysis has been done with data starting from the historical period since 1969, as recorded from observation for the station Alipore (42807) and thus with the help of th

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Bodarya, Kishan, and Vinayak Kaushal. "Thermoenergetic Performance of Phase Change Materials in Building Envelopes Under Future Climate Scenario." Applied Sciences 15, no. 3 (2025): 1562. https://doi.org/10.3390/app15031562.

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This study evaluates the thermal and energy performance of building envelopes incorporating phase change materials (PCM) compared with traditional resistive thermal insulation, considering future climate scenarios. Using EnergyPlus simulations, the study analyzes a medium office building with varying envelope compositions in two distinct Brazilian climates—Curitiba and Rio de Janeiro—representing bioclimatic zones 1 and 8, respectively. The PCM used, SP24E, aligns with the HVAC system setpoints, and climate projections for 2050 and 2080 are integrated using the Climate Change World Weather Fil

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Schinder, Aaron M., Shannon R. Young, Bryan J. Steward, et al. "Deterministic Global 3D Fractal Cloud Model for Synthetic Scene Generation." Remote Sensing 16, no. 9 (2024): 1622. http://dx.doi.org/10.3390/rs16091622.

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This paper describes the creation of a fast, deterministic, 3D fractal cloud renderer for the AFIT Sensor and Scene Emulation Tool (ASSET). The renderer generates 3D clouds by ray marching through a volume and sampling the level-set of a fractal function. The fractal function is distorted by a displacement map, which is generated using horizontal wind data from a Global Forecast System (GFS) weather file. The vertical windspeed and relative humidity are used to mask the creation of clouds to match realistic large-scale weather patterns over the Earth. Small-scale detail is provided by the frac

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Wallace, Carlington W., Dennis C. Flanagan, and Bernard A. Engel. "Quantifying the Effects of Future Climate Conditions on Runoff, Sediment, and Chemical Losses at Different Watershed Sizes." Transactions of the ASABE 60, no. 3 (2017): 915–29. http://dx.doi.org/10.13031/trans.12094.

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Abstract. Quantifying the effects of climate change on watershed hydrology and agricultural chemical losses is imperative when developing appropriate management practices for agricultural watersheds. Agricultural management practices are often assessed at the watershed scale; therefore, understanding the influence of climate change at different watershed sizes can provide insight into the effectiveness of watershed management strategies. In this study, the Soil and Water Assessment Tool (SWAT) and downscaled weather data generated using the MarkSim weather file generator were used to evaluate

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Pandit, Sameer, and Nawraj Bhattarai. "Impact of Rise in Atmosphere Temperature on an Official Building’s Energy Consumption in Kathmandu." Journal of the Institute of Engineering 13, no. 1 (2018): 102–7. http://dx.doi.org/10.3126/jie.v13i1.20354.

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The objective of this research is to study the impact of rise in atmospheric temperature, in buildings energy consumption in the future. An existing Typical Meteorological Year (TMY) weather file of time span 1973-1996 composed of weather data by Solar and Wind Energy Resource Assessment (SWERA) project is assumed as the baseline climate in this study. Monthly average temperature of future years in business as usual scenario predicted by Meteonorm is downscaled to hourly temperature data using downscaling method, morphing. This showed that annual average air temperature of the atmosphere will

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Risner, Jamie, and Anna Sutherland. "Static grid carbon factors – Can we do better?" Building Services Engineering Research and Technology 42, no. 3 (2021): 257–77. http://dx.doi.org/10.1177/0143624421991964.

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The average carbon intensity (gCO2e/kWh) of electricity provided by the UK National Grid is decreasing and becoming more time variable. This paper reviews the impact on energy calculations of using various levels of data resolution (half hourly, daily, monthly and annual) and of moving to region specific data. This analysis is in two parts, one focused on the potential impact on Part L assessments and the other on reported carbon emissions for existing buildings. Analysis demonstrated that an increase in calculated emissions of up to 12% is possible when using an emissions calculation methodol

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Fajilla, Gianmarco, Emiliano Borri, Marilena De Simone, Luisa F. Cabeza, and Luís Bragança. "Effect of Climate Change and Occupant Behaviour on the Environmental Impact of the Heating and Cooling Systems of a Real Apartment. A Parametric Study through Life Cycle Assessment." Energies 14, no. 24 (2021): 8356. http://dx.doi.org/10.3390/en14248356.

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Climate change has a strong influence on the energy consumption of buildings, affecting both the heating and cooling demand in the actual and future scenario. In this paper, a life cycle assessment (LCA) was performed to evaluate the influence of both the occupant behaviour and the climate change on the environmental impact of the heating and cooling systems of an apartment located in southern Italy. The analysis was conducted using IPCC GWP and ReCiPe indicators as well as the Ecoinvent database. The influence of occupant behaviour was included in the analysis considering different usage prof

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Qasim, Osama A., Mohammed Y. Alhayani, and Mohammed S. Noori. "Deep Learning-based Weather Prediction: A Focused Case Study on Mosul City, Iraq." Asian Journal of Research in Computer Science 18, no. 4 (2025): 176–86. https://doi.org/10.9734/ajrcos/2025/v18i4614.

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Background: Despite technological advancements, accurate weather forecasting remains a complex and challenging task. This looks at climate forecasts in Mosul City, Iraq, using a deep getting-to-know-you model that uses Long Short-Term Memory (LSTM) networks. More than a century's worth of historical weather records, including temperature, humidity, and precipitation, was used to teach and validate the model. The results demonstrate the effectiveness of LSTM in enhancing the dependability of climate forecasting, with an accuracy charge of above 88%. This takes a look at offers a strong basis fo

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Fürtön, Balázs, Dóra Szagri, and Balázs Nagy. "The Effect of European Climate Change on Indoor Thermal Comfort and Overheating in a Public Building Designed with a Passive Approach." Atmosphere 13, no. 12 (2022): 2052. http://dx.doi.org/10.3390/atmos13122052.

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Dynamic building energy performance modeling is becoming increasingly important in the architectural, engineering, and construction (AEC) industry because of the sector’s significant environmental impact. For such analysis, a climate file representing a typical meteorological year (TMY) is needed, including hourly values for the most important weather-related parameters. However, TMY shows little resemblance to the future of the particular location where a building has been used for decades. Therefore, using predicted future climates during building design is unfortunately rarely practiced, po

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Horton, Pascal. "AtmoSwing: Analog Technique Model for Statistical Weather forecastING and downscalING (v2.1.0)." Geoscientific Model Development 12, no. 7 (2019): 2915–40. http://dx.doi.org/10.5194/gmd-12-2915-2019.

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Abstract. Analog methods (AMs) use synoptic-scale predictors to search in the past for similar days to a target day in order to infer the predictand of interest, such as daily precipitation. They can rely on outputs of numerical weather prediction (NWP) models in the context of operational forecasting or outputs of climate models in the context of climate impact studies. AMs require low computing capacity and have demonstrated useful potential for application in several contexts. AtmoSwing is open-source software written in C++ that implements AMs in a flexible way so that different variants c

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Ariza Flores, Victor Andre, and Rachel Salvador. "Adaptive Risk Management in Road Construction: Oyon-Ambo Highway Insights, El Niño 2019 Case Study." E3S Web of Conferences 497 (2024): 02020. http://dx.doi.org/10.1051/e3sconf/202449702020.

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This research provides an in-depth analysis of the challenges faced during the construction of the Oyon-Ambo highway in Peru, particularly during the extreme rainfall events associated with the 2019 El Niño phenomenon. Situated in the high Andean area of the Pasco region, this rigid pavement road project encountered significant disruptions due to the extraordinary weather conditions. The adjacent Chaupihuaranga River experienced increased flow rates, causing extensive damage to the road and necessitating substantial modifications to the engineering plans. Focusing on 14 critical sectors identi

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Bouvier, Clément, Daan van den Broek, Madeleine Ekblom, and Victoria A. Sinclair. "Analytical and adaptable initial conditions for dry and moist baroclinic waves in the global hydrostatic model OpenIFS (CY43R3)." Geoscientific Model Development 17, no. 7 (2024): 2961–86. http://dx.doi.org/10.5194/gmd-17-2961-2024.

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Abstract. This article presents a description of an analytical, stable, and flexible initial background state for both dry and moist baroclinic wave simulation on an aquaplanet in order to test the dynamical core of numerical weather prediction models and study the dynamics and evolution of extratropical cyclones. The initial background state is derived from an analytical zonal wind speed field, or jet structure, and the hydrostatic primitive equations for moist adiabatic and frictionless flow in spherical coordinates. A baroclinic wave can develop if a perturbation is added to the zonal wind

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Shantala, Devi Patil, Satheesh Sreedevi, S. M. Seema, and Mothish Chowdary R. "Linear Regression Based Demand Forecast Model in Electric Vehicles -LRDF." International Journal of Human Computations and Intelligence 2, no. 2 (2023): 82–93. https://doi.org/10.5281/zenodo.7900508.

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Machine learning is an Artificial Intelligence (AI) software application that uses algorithms to analyze data, make inferences from that data, and then use what they've learned to create well-informed conclusions. Machine learning cannot process characters or strings; in order to process them, we must transform them to numerics. Otherwise, there will be exceptions or mistakes of some kind. After pre-processing, which removes the null or empty data from the original dataset, machine learning algorithms can predict or forecast future events using the provided dataset. Machine learning is now

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Pollak, Cheryl L. ""Hurricane" Sandy." Texas A&M Journal of Property Law 5, no. 2 (2018): 157–92. http://dx.doi.org/10.37419/jpl.v5.i2.3.

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On the evening of October 29, 2012, “Hurricane” Sandy made land- fall on the New York coastline, battering the land with strong winds, torrential rain, and record-breaking storm surges. Homes and commercial structures were destroyed; roads and tunnels were flooded; and more than 23,000 people sought refuge in temporary shelters, with many others facing weeks without power and electricity. At the time, Sandy was heralded as one of the costliest hurricanes in the his- tory of the United States; the second costliest hurricane only to Katrina, which hit New Orleans in 2005. Unfortunately, recent e

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Medojevic, Milana, Milovan Medojevic, and Villar Díaz. "Simulation-based design of solar photovoltaic energy generation system for manufacturing support." Thermal Science, no. 00 (2020): 161. http://dx.doi.org/10.2298/tsci190719161m.

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Having in mind that energy is being regarded as indispensable to the socio-economic progress of developing and developed nations, where the main objective implies replacement and reduction of a major portion of the fossil fuels utilization, implementation of renewable energy technologies where natural phenomena are transformed into beneficial types of energy are becoming more and more appreciated and needed. Among renewable energy resources we know today, solar energy is the most beneficial, relatively limitless, effective, and dependable. Having this in mind, the aim of this paper is primaril

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Wesdhi Pandhu Putra, Maulidiah Rahmawati, and Dyah Ratnaningsih. "Analisis Penyebab Terjadinya Incident Process Berthing pada Tongkang BG. RMN 3316 Milik PT. Kartika Samudra Adijaya di Jetty PLTU Batang." Trending: Jurnal Manajemen dan Ekonomi 2, no. 4 (2024): 318–29. http://dx.doi.org/10.30640/trending.v2i4.3194.

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A ship accident is an unwanted event that can cause material losses or casualties. In this case, the party who feels aggrieved can file a lawsuit to get compensation for the losses suffered. It is undeniable that ship accidents often occur due to various reasons ranging from human error, technical factors, force majeur factors and several other factors. This research aims to find out what are the causes of berthing incidents and to find out the efforts made by ship owners after incidents that occurred at the jetty. In this thesis, a qualitative descriptive method is used with a fishbone diagra

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Herrera, Manuel, Sukumar Natarajan, David A. Coley, et al. "A review of current and future weather data for building simulation." Building Services Engineering Research and Technology 38, no. 5 (2017): 602–27. http://dx.doi.org/10.1177/0143624417705937.

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This article provides the first comprehensive assessment of methods for the creation of weather variables for use in building simulation. We undertake a critical analysis of the fundamental issues and limitations of each methodology and discusses new challenges, such as how to deal with uncertainty, the urban heat island, climate change and extreme events. Proposals for the next generation of weather files for building simulation are made based on this analysis. A seven-point list of requirements for weather files is introduced and the state-of-the-art compared to this via a mapping exercise.

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Machard, Anaïs, Christian Inard, Jean-Marie Alessandrini, Charles Pelé, and Jacques Ribéron. "A Methodology for Assembling Future Weather Files Including Heatwaves for Building Thermal Simulations from the European Coordinated Regional Downscaling Experiment (EURO-CORDEX) Climate Data." Energies 13, no. 13 (2020): 3424. http://dx.doi.org/10.3390/en13133424.

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With increasing mean and extreme temperatures due to climate change, it becomes necessary to use—not only future typical conditions—but future heatwaves in building thermal simulations as well. Future typical weather files are widespread, but few researchers have put together methodologies to reproduce future extreme conditions. Furthermore, climate uncertainties need to be considered and it is often difficult due to the lack of data accessibility. In this article, we propose a methodology to re-assemble future weather files—ready-to-use for building simulations—using data from the European Co

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Gavidia-Calderón, Mario Eduardo, Sergio Ibarra-Espinosa, Youngseob Kim, Yang Zhang, and Maria de Fatima Andrade. "Simulation of O<sub>3</sub> and NO<sub><i>x</i></sub> in São Paulo street urban canyons with VEIN (v0.2.2) and MUNICH (v1.0)." Geoscientific Model Development 14, no. 6 (2021): 3251–68. http://dx.doi.org/10.5194/gmd-14-3251-2021.

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Abstract. We evaluate the performance of the Model of Urban Network of Intersecting Canyons and Highways (MUNICH) in simulating ozone (O3) and nitrogen oxides (NOx) concentrations within the urban street canyons in the São Paulo metropolitan area (SPMA). The MUNICH simulations are performed inside the Pinheiros neighborhood (a residential area) and Paulista Avenue (an economic hub), which are representative urban canyons in the SPMA. Both zones have air quality stations maintained by the São Paulo Environmental Agency (CETESB), providing data (both pollutant concentrations and meteorological)

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Zekry, Omnya Saleh, Ahmed Ahmed Fekry, and Reham El Dessuky Hamed. "Artificial Neural Network to Predict Curvature Light Shelf Design Related Daylighting Optimization on Office Spaces." Journal of Daylighting 11, no. 2 (2024): 334–48. http://dx.doi.org/10.15627/jd.2024.23.

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Energy Optimization in building design field now has been revolutionized due to AI and machine learning applications. Leveraging daylight to reduce artificial lighting consumption holds promise for significant energy savings, yet the nonlinear nature of daylight patterns poses challenges in prediction and optimization. This study proposes a novel approach to automated light shelf design using machine learning algorithms, specifically artificial neural networks (ANNs) such as recurrent neural networks (RNN) by long short term memory (LSTM), to accelerate daylighting simulation and optimization

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Liu, C., W. Chung, F. Cecinati, S. Natarajan, and D. Coley. "Current and future test reference years at a 5 km resolution." Building Services Engineering Research and Technology 41, no. 4 (2019): 389–413. http://dx.doi.org/10.1177/0143624419880629.

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Frequently, the computer modelling of the natural and human-made environment requires localised weather files. Traditionally, the weather files are based on the observed weather at a small number of locations (14 for the UK). Unfortunately, both the climate and the weather are known to be highly variable across the landscape, so the small number of locations has the potential to cause large errors. With respect to buildings, this results in incorrect estimates of the annual energy use (sometimes by a factor of 2), or of overheating risk. Here we use a validated weather generator running on a 5

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Vaz, Igor Catão Martins, Marina Ribeiro Viana, and Enedir Ghisi. "Comparison of future weather files for Brazilian cities." E3S Web of Conferences 546 (2024): 01017. http://dx.doi.org/10.1051/e3sconf/202454601017.

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There is an increasing interest from academia, government, and private companies in future weather generation to predict new climate realities and prepare our assets for resilience and adaptability. In the built environment, practitioners have evolved by building simulation weather files with new tools to implement updated climate change predictions. Thus, this paper focuses on testing and understanding Brazilian climate change using the tool Future Weather Generator. Simulations under different Shared Socioeconomic Pathways were carried out, and future climate variables were discussed. This p

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Arango-Díaz, Lucas, Maria Alejandra Garavito-Posada, Juan Sebastian Calle-Medina, Adriana Marcela Murcia-Cardona, Olga Lucia Montoya-Flórez, and Sebastián Pinto-Quintero. "Suficiencia lumínica de ambientes interiores en escenarios de cambio climático." Revista Hábitat Sustentable 12, no. 2 (2022): 40–51. http://dx.doi.org/10.22320/07190700.2022.12.02.03.

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The bioclimatic performance of buildings under climate change scenarios has been extensively studied from a thermo-energy perspective but hardly studied at all from the perspective of indoor daylight sufficiency. This shortcoming is related to the invariability of radiation data in the available weather files of future scenarios. This research proposes identifying the impacts that the variability of radiation data in weather files of future scenarios would have on daylight sufficiency in indoor spaces. The methodology includes the adaptation of available weather files and the running of daylig

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Ren, Zhengen. "A Literature Review on the Use of Weather Data for Building Thermal Simulations." Energies 18, no. 14 (2025): 3653. https://doi.org/10.3390/en18143653.

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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

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Andresen, Inger, Matthias Haase, and Anne Grete Hestnes. "The Development of Future Weather Data Files for Norway." International Journal of Climate Change: Impacts and Responses 2, no. 3 (2011): 1–24. http://dx.doi.org/10.18848/1835-7156/cgp/v02i03/37327.

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Cox, Rimante A., Martin Drews, Carsten Rode, and Susanne Balslev Nielsen. "Simple future weather files for estimating heating and cooling demand." Building and Environment 83 (January 2015): 104–14. http://dx.doi.org/10.1016/j.buildenv.2014.04.006.

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Alecssandrei, Nicole A. Loyola, L. Petalver Mckinley, Kenji A. Trentado Mark, and Jocelyn B. Bernardino Engr. "DESIGN AND DEVELOPMENT OF A MICRO-COMPUTER BASED VEHICLE DASHBOARD CAMERA USING SYNCTHING APPLICATION." International Journal of Engineering Research and Reviews 11, no. 3 (2023): 10–20. https://doi.org/10.5281/zenodo.8177283.

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<strong>Abstract:</strong> The automotive industry's growing population has raised concerns about road congestion and traffic accidents. To tackle these challenges, the Internet-of-Things (IoT) paradigm has regained attention in the tech market, accompanied by advancements in modern wireless telecommunications. However, companies like Thinkware and Blackvue rely on cloud storage for driving purposes, necessitating manual file downloading and fast internet access (Costa, 2019). In this research study, it aims to build and develop a microcomputer based vehicle dashboard camera system that in

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Kolokotroni, Maria, May Zune, Petra Gratton, Thet Paing Tun, Ilia Christantoni, and Dimitra Tsakanika. "Impact of the Urban Environment on the Thermal Performance and Environmental Quality of Residential Buildings: A Case Study in Athens." Energies 18, no. 8 (2025): 2062. https://doi.org/10.3390/en18082062.

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This paper examines the impact of the urban context on the energy performance of a residential building in Athens. Current and future weather files were modified to consider the urban heat island, the overshadowing of adjacent buildings, and the modification of wind speed due to the effects of urban canyons. Dynamic thermal simulations were carried out using the modified weather files. The results indicate that there was a change in heating and cooling demand in comparison to using typical weather files; heating was reduced, but cooling was increased with a total increase in energy demand. The

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Gupta, A., A. Thounaojam, and P. Vaidya. "Enhancing building resilience: the role of future weather data in building design." FARU Journal 11, no. 2 (2024): 115–23. https://doi.org/10.4038/faruj.v11i2.328.

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With climate change driving unprecedented shifts in global weather patterns, the need to future-proof building designs has become critical. Current design practices predominantly rely on simulations and analysis that use Typical Meteorological Year (TMY) files, which are based on historical weather data and may not reflect future climatic conditions. This could result in buildings that may not be able to adapt to long-term climate change. Our study examines whether the use of future weather data in design analysis points to different strategies and is necessary to successfully predict building

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Eames, M., T. Kershaw, and D. Coley. "The appropriate spatial resolution of future weather files for building simulation." Journal of Building Performance Simulation 5, no. 6 (2012): 347–58. http://dx.doi.org/10.1080/19401493.2011.608133.

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Alhindawi, Ibrahim, and Carlos Jimenez-Bescos. "Assessing the Performance Gap of Climate Change on Buildings Design Analytical Stages Using Future Weather Projections." Environmental and Climate Technologies 24, no. 3 (2020): 119–34. http://dx.doi.org/10.2478/rtuect-2020-0091.

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AbstractWith the higher pace of climate change, temperatures are rising each year, resulting in various effects on the thermal status of buildings. This paper takes the opportunity of analysing different scenarios of greenhouse gas (GHG) emissions using hourly weather data of future projections by implementing EPW weather files on EnergyPlus software dynamic simulations, coupled with architectural science methods of climate analysis, to test the effect of high and medium-high emission scenarios for the 2050s and 2080s future timelines on thermal comfort range, passive zones potential, and heat

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