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Publications and Documents

Publications and documents of interest on weather data for building simulations.

Published papers

How will future climate impact the design and performance of nearly zero energy buildings (NZEBs)?

D’Agostino D, D Parker, L Epifani, D Crawley, L Lawrie, 2021. “How will future climate impact the design and performance of Nearly Zero Energy Buildings (NZEBs)?,” in Energy, 240 (2022) 122479, November 2021.   https://doi.org/10.1016/j.energy.2021.122479

Abstract: 

Climate change, driven by greenhouse gas emissions, is a growing global concern, threatening worldwide environment, health and economy. Energy needs for buildings are a large source of greenhouse gas emissions. As the energy needs of buildings strongly depends on weather patterns, this paper investigates how climate change may impact building heating and cooling loads, cost-optimal efficiency measures, and renewable energy production. Eight locations (Stockholm, Milan, Vienna, Madrid, Paris, Munich, Lisbon, and Rome) highlight differences among European climates.Weather datasets, commonly used in building energy simulations, are evaluated to see how climatic parameters have changed over recent decades. A future climate change scenario (with uncertainties) is analyzed for the year 2060. Weather files are used to drive building energy simulations for a standard baseline and a (Nearly Zero Energy Building) NZEB residential building whose design is improved using a cost-optimization approach.

The analysis indicates most currently available weather datasets cannot assure reliable results with building simulations. We find the energy balance in European buildings will significantly change under future conditions: heating will decrease by 38%-57%, while cooling will increase by 99%-380% depending on location. In future NZEBs, efficiency measures to reduce cooling needs and overheating will be favored (e.g. roof insulation, window type, solar shading, envelope finishes), illustrating how improving energy efficiency will be more crucial within climate change scenarios. Compared to the baseline, more efficient NZEBs will enable renewable energy to much better cover building needs. There will also be advantages from reducing winter and summer peak demand, particularly when coupled to short-term electrical storage. When solar resource is limited in winter, more airtight, better-insulated NZEBs improve PV self-consumption.

 Assessment of solar radiation data quality in typical meteorological years and its influence on the building performance simulation

Facundo Bre, Rayner Mauricio e Silva Machado, Linda K. Lawrie, Drury B. Crawley, Roberto Lamberts. 2021.  “Assessment of solar radiation data quality in typical meteorological years and its influence on the building performance simulation,” in Energy and Buildings, Vol. 250, 2021, 111251, November 2021.

Abstract: 

Solar radiation along with other weather variables are commonly processed on typical meteorological years (TMYs) to be applied in the design of various energy systems. However, in several regions of the world, solar radiation data usually lacks a suitable and/or representative measurement, which leads to its modeling and prediction to properly fill this information in the databases. Consequently, the accuracy of these models can influence the viability and proper design of such energy systems. Within this context, the present contribution aims to assess the quality of solar radiation data included in the most recent TMY databases with Brazilian data and how that quality can influence the selection of months that create TMYs as well as the building performance simulation (BPS) results. Because two different approaches to generate the solar radiation data are used, we evaluate the global horizontal irradiation data in the two latest versions of recent Brazilian TMY databases against the corresponding satellite-derived ones obtained from the POWER database (NASA). Simultaneously, as another alternative approach, global solar radiation data are calculated for the same studied locations and period through the modeling method used to generate the current version of the International Weather for Energy Calculations (IWEC2), and its performance is also compared against the corresponding reanalysis data (POWER). Finally, a set of case studies applying the local building performance regulations are exhaustively analyzed to quantify the impact of the uncertainty of solar radiation models on BPS results throughout Brazil. The results indicate that the accuracy of solar radiation models can highly influence the resulting TMY configurations. These changes can drive differences up to 40% on the prediction of the ideal annual loads of the residential buildings while, regardless of design performance, differences lower than 10% are found for the commercial case studies in most locations. Conversely, the prediction of peak loads for cooling shows to be more sensitive to the climate data changes in the commercial buildings than in the residential ones.

Extreme weather data in building performance simulation

Gasparella, Andrea, Drury B. Crawley, Giovanni Pernigotto, Alessandro Prada, Linda K. Lawrie. 2021. “Extreme weather data in building performance simulation, in Proceedings of Building Simulation 2021, the 17th IBPSA Conference, pp xx-xx, 2 September 2021.

Abstract: 

This research discusses two different types of extreme weather data for building simulation, the Extreme Reference Years ERYs and the eXtreme Meteorological Years XMYs, with the aim of performing a comparison analysing their impact on the assessment of building energy performance. A dataset of 12 climates is used to generate both typical and extreme weather data, whose properties are examined both in terms of selected reference months and calculated heating and cooling degree-days. Finally, EnergyPlus simulations are run to evaluate the effects of the two alternative types of extreme weather data on the simulation outcomes.

Our climate conditions are already changing – Should we care?

Crawley, Drury B., Linda K. Lawrie. 2021. “Our Climate Conditions Are Already Changing – Should We Care?,” in Building Services Engineering Research and Technology, Vol 42, No. 5, pp. 507-516, September 2021.

Abstract: 

The IPCC and many others predict significant changes to our climates over the rest of this century, including average temperature increases for 2–5 C. However, we can see possible indications of change already – increasing frequency of severe storms and other weather events. However, many of the major
weather data sets used around the world for building energy simulation are more than 15 years old. Does it matter? This paper compares several of the major data sets used in building performance simulation against newer data derived from the past 15 years. Ten of the past 15 years are the hottest on record and this rapidly changing climate already is evident in the temperature record. We use energy simulation to demonstrate how the various data sets impact energy use. In addition, the design conditions for heating and cooling calculations are already seeing slight changes over the past 20 years. Data for 12 locations around the world is used to demonstrate the changing climate that we already see.

Should We Be Using Just Typical Weather Data in Building Performance Simulation?

Crawley, Drury B., Linda K. Lawrie. 2019. “Should We Be Using Just ‘Typical’ Weather Data in Building Performance Simulation?,” in Proceedings of Building Simulation 2019, the 16th IBPSA Conference, pp 4801-4808, 2 September 2019

Abstract: 

Over the past 40 years, organizations worldwide have created weather data sets specifically for use in building energy simulation, usually called typical or reference years. Crawley (1998) showed how a variety of typical data sets compare in terms of impacts on building energy. This study found that TRY-type files (single years) do not represent the period of record well and recommends TMY or other weather data created using similar procedures, such as European test reference years.

Several other studies have concluded that TMY are good enough to represent typical building operation. Yet we need weather that represents a reasonable range of climate conditions that buildings experience. A 2015 study proposed development of eXtreme Meteorological Year (XMY) weather files to represent the range of climate conditions that buildings may experience. An XMY starts with the same period of record as the TMY, but the methodology purposely selects more extreme months.

This paper proposes a new regime for climatic data representation in buildings—an XMY or eXtreme Meteorological Year. We demonstrate how several sets of international typical meteorological data sets compare to the actual period of record that they represent. Then using prototype buildings, we show that the climatic response of the building would be better served by a range of building climatic data, investigating high and low cases of temperature, humidity, solar radiation and wind conditions.

Musings on more than 40 years in building performance simulation

Crawley, Drury. 2019. “Musings on more than 40 years in building performance simulation,” editorial in Building Services Engineering Research and Technology,Vol 40, No. 5, pp. 557-559, September 2019.

Abstract: 

From mainframe computers that filled rooms, an armful of input punched card decks, and 6 inch stack of continuous form "green bar" paper for output to computers the size of a deck of playing cards . . . quite a ride over the last 40 years.

Rethinking the TMY: Is the 'Typical' Meteorological Year Best for Building Performance Simulation

Crawley, Drury B., Linda K. Lawrie. 2015. “Rethinking the TMY: Is the ‘Typical’ Meteorological Year Best for Building Performance Simulation?” in Proceedings of BS 2015: 14th Conference of International Building Performance Simulation Association, pp. 2655-2662, 7-9 December 2015, Hyderabad, India.

Abstract: 

Historically, building simulation users have used a single typical year or a constructed typical meteorological year to represent climatic conditions for a location or region. With advent of increasingly powerful computers, it is no longer necessary to represent climatic conditions with a single year of data. Prior studies have shown that a single year of data often do not well represent the range of climate conditions over a period.

This paper proposes a new regime for climatic data representation in buildings—an XMY or eXtreme Meteorological Year—building on a paper from Building Simulation 1999 that called for a common format for building simulation representation. We demonstrate how several sets of international typical meteorological data sets compare to the actual period of record that they represent. Then using an example prototype building, we show that the climatic response of the building would be better served by a range of building climatic data, investigating high and low cases of temperature, humidity, solar radiation and wind conditions.

Estimating the impacts of climate change and urbanization on building performance

Crawley, Drury B. 2008. “Estimating the Impacts of Climate Change and Urbanization on Building Performance,” Journal of Building Performance Simulation, pp. 91-115, Vol. 1, No. 2 (June).

Abstract: 

Over the past 15 years, much scientific work has been published on the potential human impacts on climates. For their Third Assessment Report in 2001, the United Nations International Programme on Climate Change developed a set of economic development scenarios, which were then run with the four major general circulation models (GCM) to estimate the anthropogenesis-forced climate change. These GCMs produce worldwide grids of predicted monthly temperature, cloud, and precipitation deviations from the period 1961–1990. As this period is the same used for several major typical meteorological year data sets, these typical data sets can be used as a starting point for modifying weather files to represent predicted climate change.

Over the past 50 years, studies of urban heat islands (UHI) or urbanization have provided detailed measurements of the diurnal and seasonal patterns and differences between urban and rural climatic conditions. While heat islands have been shown to be a function of both population and microclimatic and site conditions, they can be generalized into a predictable diurnal and seasonal pattern. Although the scientific literature is full of studies looking at the impact of climate change driven by human activity, there is very little research on the impact of climate change or urban heat islands on building operation and performance across the world.

This article presents the methodology used to create weather files which represent climate change scenarios in 2100 and heat island impacts today. For this study, typical and extreme meteorological weather data were created for 25 locations (20 climate regions) to represent a range of predicted climate change and heat island scenarios for building simulation. Then prototypical small office buildings were created to represent typical, good, and low-energy practices around the world. The simulation results for these prototype buildings provide a snapshot view of the potential impacts of the set of climate scenarios on building performance. This includes location-specific building response, such as fuel swapping as heating and cooling ratios change, impacts on environmental emissions, impacts on equipment use and longevity comfort issues, and how low-energy building design incorporating renewables can significantly mitigate any potential climate variation.

In this article, examples of how heat island and climate change scenarios affect diurnal patterns are presented as well as the annual energy performance impacts for three of the 25 locations. In cold climates, the net change to annual energy use due to climate change will be positive – reducing energy use on the order of 10% or more. For tropical climates, buildings will see an increase in overall energy use due to climate change, with some months increasing by more than 20% from current conditions. Temperate, mid-latitude climates will see the largest change but it will be a swapping from heating to cooling, including a significant reduction of 25% or more in heating energy and up to 15% increase in cooling energy.

Buildings which are built to current standards such as ASHRAE/IESNA Standard 90.1-2004 will still see significant increases in energy demand over the twenty-first century. Low-energy buildings designed to minimize energy use will be the least affected, with impacts in the range of 5–10%. Unless the way buildings are designed, built, and operated changes significantly over the next decades, buildings will see substantial operating cost increases and possible disruptions in an already strained energy supply system.

Creating Weather Files for Climate Change and Urbanization Impacts Analysis

Crawley, Drury B. 2007. “Creating Weather Files for Climate Change and Urbanization Impacts Analysis,” in Proceedings of the Tenth International IBPSA Conference, Building Simulation 2007, pp. 1075-1082, 3-6 September 2007, Beijing, China.

Abstract: 

Over the past 15 years, much scientific work has been published on the potential human impacts on climates. For the Third Assessment Report published by the United Nations International Program on Climate Change in 2001, a series of economic development scenarios were created and four major general circulation models (GCM) were used to estimate the anthropogenesis-forced climate change.

These GCMs produce worldwide grids of predicted monthly temperature, cloud, and precipitation deviations from the period of 1961-1990. As this period is the same used for several major typical meteorological year data sets, these typical data sets can be used as a starting point for modifying weather files to represent predicted climate change. Over the past 50 years, studies of urban heat island (UHI) or urbanization have provided detailed measurements of the diurnal and seasonal patterns and differences between urban and rural climatic conditions. While heat islands have been shown to be a function of both population and microclimatic and site conditions, they can be generalized into a predictable diurnal pattern.

This paper presents the methodology used to create weather files which represent climate change scenarios in 2100 and heat island impacts today and present the typical climatic patterns resulting for 20 climate regions worldwide.

Contrasting the Capabilities of Building Energy Performance Simulation Programs

Crawley, Drury B., Jon W. Hand, Michaël Kummert, Brent T Griffith. 2008. “Contrasting the Capabilities of Building Energy Performance Simulation Programs,” Building and Environment, pp. 661-673, Vol. 43, No. 4 (April).

Abstract: 

For the past 50 ytears, a wide variety of building energy simulation programs have been developed, enhanced, and are in use throughout the building energy community. This report provides an up-to-date comparison of the features and capabilities of twenty major building energy simulation programs: BLAST, BSim, DeST, DOE-2.1E, ECOTECT, Ener-Win, Energy Express, Energy-10, EnergyPlus, eQUEST, ESP-r, IDA, ICE, IES <VE>, HAP, HEED, PowerDomus, SUNREL, Tas, TRACE and TRNSYS. This comparison is based on information provided by the program developers in the following categories: general modeling features; zone loads; building envelope, daylighting and solar; infiltration, ventilation and multizone airflow; renewable energy systems; electrical systems and equipment; HVAC systems; HVAC equipment; environmental emissions; economic evaluation; climate data availability; results reporting; validation; and user interfaces, links to other programs, and availability.

Improving the Weather Information Available to Building Simulation Programs

Drury B. Crawley, Jon W. Hand, Linda K. Lawrie. 1999. “Improving the Weather Information Available to Simulation Programs,” in Proceedings of Building Simulation ’99, Volume II, pp. 529-536, Kyoto, Japan, September 1999. IBPSA.

Abstract: 

Developers of building simulation tools have been continuously improving their programs and adding new capabilities over the last thirty years. Time steps of less than an hour are now common and even necessary to properly simulate the complex interactions of building components and systems. For example, some control issues, such as daylighting, require much shorter time steps of minutes— more traditional hourly time steps have been shown to introduce errors as large as 40% in illumination calculations.
Despite these increased capabilities, many simulation programs are still using the same limited set of hourly climatic/weather data they started with— temperature, humidity, wind speed and cloud cover or solar radiation. This often forces users to find or calculate missing weather data such as illuminance, solar radiation, and ground temperature from other sources or developers to calculate it within their program.
In this paper, we describe a generalized weather data format developed for use with two energy simulation programs. We also compare the new format with previous data sets in use in the US and UK.

Which Weather Data Should You Use for Energy Simulations of Commercial Buildings

Drury B. Crawley. 1998. “Which Weather Data Should You Use for Energy Simulations of Commercial Buildings?” in ASHRAE Transactions, pp. 498-515, Vol. 104, Pt. 2. Atlanta: ASHRAE.

Abstract: 

Users of energy simulation programs have a wide variety of weather data from which to choose–from locally recorded weather data to preselected ‘typical’ years, often a bewildering range of options. In the last five years, several organizations have developed new typical weather data sets including WYEC2, TMY2, CWEC, and CTZ2. Unfortunately, neither how these new data influence energy simulation results nor how they compare to recorded weather data is well documented.
This paper presents results from the DOE-2.1E hourly energy simulation program for a prototype office building as influenced by local measured weather data for multiple years and several weather data sets for eight U.S. locations. We compare the influence of the various weather data sets on simulated annual energy use and costs and annual peak electrical demand, heating load, and cooling load. Statistics for temperature, heating and cooling degree-days, and solar radiation for the different locations and data sets are also presented. Where possible, the author explains the variation relative to the different designs used in developing each data set. The variation inherent in actual weather data and how it influences simulation results is also shown. Finally, based on these results, the question is answered: which weather data should you use?

Documents

EnergyPlus Weather File Format

  • The EPW format in quick data dictionary style along with descriptions of fields.
  • Current format is shown at the document link above and here.