Computer simulations rely on a variety of datasets when assessing the effects of climate on building performance. These data, and the models they power, provide an important basis for planning, design, and cost analysis. Below I describe some of the major types of climate datasets used in energy and hygrothermal modeling.
Datasets described here, including EWY, TRY-US, TRY-ROW, TMY, TMY2, TMY3, IWEC, WYEC2, CWEC, and AMY represent weather years, which are typically single year compilations for specific locations. Each year is compiled from 8,760 hourly records for the desired data elements (e.g. temperature, dew point, direct and diffuse solar radiation, wind speed, wind direction, liquid precipitation, etc.). There are three general approaches to selecting weather years. The first approach selects a contiguous year where the monthly means and standard deviations for that year match the means and standard deviations for a longer period of record – often 15 to 30 years. Examples of this approach include EWY and TRY-US. The second approach involves creating composite years using representative months from different years. Examples of this approach include TRY-ROW, TMY, TMY2, TMY3, CWEC, WYEC2, and IWEC. These first two approaches were devised for the specific purpose of energy simulations that compare long-term energy use under varied test scenarios. Data selection therefore emphasized ‘typical’ years that are representative of these longer-term durations (e.g. 30 years). The third approach includes Actual Meteorological Years (AMYs), which represent hourly weather data from a single contiguous year that is not necessarily representative of a greater span of time. This approach is favored when examining atypical or extreme years.
Energy Vs Hygrothermal Data
There exists a dichotomy in the evolution of datasets for energy and hygrothermal modeling. Where energy modeling has favored ‘typical’ weather years for the purpose of long-term energy use, hygrothermal modeling has favored ‘typical severe’ years. This is not to say that datasets used by one pursuit are excluded from use by the other. Hygrothermal modeling software can accept a wide variety of file types typically used in energy modeling (e.g. TMY3). Often the limiting parameter for robust hygrothermal analysis is whether the dataset includes rain data. With the exception of the TMY3 format, most datasets designed for energy simulation do not include quantitative rainfall data. Conversely, energy modeling places much greater emphasis on the type and quality of solar radiation data.
TRY (TRY-US) – Test Reference Years
The TRY datasets were first created in 1976 by NOAA’s National Climatic Data Center. They entail hourly data from 60 locations in the United States. The data include dry bulb temperature, wet bulb temperature, dew point temperature, wind direction, wind speed, barometric pressure, relative humidity, cloud cover, and cloud type. Absent in the TRY format is information on solar radiation, which was generally estimated from cloud cover and cloud type for a specific location. It is important to understand that although TRY files contain measured meteorological information for specific locations, they represent a single year from the 1948-1975 period of record. The representative year was obtained by eliminating years that contained months having high and low temperature means. This process continued until a single reference year remained. The elimination of extremes resulted in datasets that were significantly more moderate than other contiguous years for the period of record. The TRY data therefore represent a poor choice when evaluating atypical or extreme conditions. The original TRY datasets also lacked precipitation data, which limits their use when considering the effects of rain loads.
EWY – Example Weather Years
Example Weather Year datasets in the UK were also developed in the 1970s using methodologies similar to those used for TRY-US. These data were compiled using a representative contiguous year from a 20-year period of record. Although EWY datasets are still used, newer methodologies developed by the Chartered Institution of Building Services Engineers (CIBSE) created the Test Reference Year using a TMY-like composite year from a 23-year period (1983-2005).
TRY (TRY-ROW) – Test Reference Years
TRY datasets created in Europe and other parts of the world employed methods and data elements similar to those used in TMY datasets. Therefore, TRY-US and TRY-ROW are not interchangeable.
TMY – Typical Meteorological Year
TMY represents a refinement in the TRY methodology. The fist TMY datasets were created in 1981 from a collaboration between NCDC and the U.S. Department of Energy. These datasets expanded on TRY by including horizontal and direct normal insolation data measured from 26 U.S. locations for the period of 1952 to 1975. An additional 206 locations were derived from estimates using cloud cover and cloud type. The typical year was obtained in a similar manner as the TRY format; however, the data represent individual months rather than an entire contiguous year. In other words, the datasets represent an amalgam or months from different years from the entire 23 year period of record. The data were selected based on statistical analysis of monthly composites for eleven weather variables. Those monthly composites that were closest to the distribution for the entire period were selected. Like the TRY method, the data selection process resulted in data that were more in keeping with the long-term distribution (i.e. ‘typical’); thus they are more reflective of moderate years, not atypical years or extremes.
A new TMY dataset was created as TMY2 in 1990. Improvements from the original TMY format included refinements in weighted averages and a revised period of record (1961-1990).
In 2005, the DOE introduced TMY3 files. This format included greater emphasis on solar radiation data as well as the inclusion of precipitation data. TMY3 files include data for approximately 2,500 locations primarily in the United States and Europe. The TMY3 method is the currently accepted approach for generating energy years for weather calculations in the United States and its territories.
WYEC – Weather Year for Energy Calculations
In 1983, ASHRAE created WYEC datasets as another means for simulating ‘typical’ weather patterns. This database was built on the TRY format utilizing solar data that was either measured or estimated from cloud cover and type. The original WYEC files included data for 51 North American locations (46 locations in the United States and 5 in Canada).
The WYEC format was updated in 1992 utilizing the monthly weighted average approach used by the TMY data. WYEC2 included 77 North American locations. As with the TMY datasets, WYEC and WYEC2 files were developed specifically for use with building energy simulation programs. Both file types (WYEC and WYEC2) lack precipitation data.
CWEC – Canadian Weather for Energy Calculations
The CWEC datasets represent typical year data based on the WYEC2/TMY methodologies.
IWEC – International Weather Year for Energy Calculation
ASHRAE released IWEC weather files in 2000. These datasets contain ‘typical’ weather data based on the TMY format intended for use with building energy simulation programs. The IWEC format utilizes 18 years of hourly data by the National Climatic Data Center for 227 locations outside the USA and Canada. Information on solar radiation is estimated on an hourly basis from earth-sun geometry and hourly weather elements such as cloud cover and type. IWEC files lack quantitative rain data but, they do include rain intensity indicators such as ‘light’, ‘moderate’, and ‘heavy’ which can provide the basis for semi-quantitative estimates. Still, IWEC files should not be relied upon for robust hourly precipitation data.
Version 2 of IWEC or IWEC2 represents ASHRAE’s current weather format. The data are derived from meteorological reports from over 3,000 international locations. IWEC utilizes data archived in the Integrated Surface Hourly (ISH) database maintained by the NCDC. For these selected locations, the ISH database contains weather observations on average at least four times per day of wind speed and direction, sky cover, visibility, ceiling height, dry-bulb temperature, dew-point temperature, atmospheric pressure, liquid precipitation, and present weather for at least 12 years of record up to 25 years.
The original IWEC files and the newer IWEC2 format used models that estimate solar radiation data from cloud cover, change in dry-bulb temperature over the past three hours, relative humidity, and wind speed.
AMY – Actual Meteorological Year
As the title implies, AMY files represent actual hourly contiguous datasets for a given location and time. Commercially-available AMY files are often placed in TMY file format, but AMY files may be generated from data sources as standard text files or even HTML. The most comprehensive data source is the Integrated Surface Hourly database maintained by the NCDC. Because the NCDC archived data is widely available and free, users may create their own database specific to their individual needs. The advantage of AMY datasets is their flexibility and customization; however, when creating customized datasets the user may be challenged by significant data gaps and a healthy dose of tedium. Still, AMY files are the way to go when seeking customized datasets that account for actual observed conditions and climate extremes.
EPW – EnergyPlus
The EPW file format is utilized by EnergyPlus, the energy modeling software developed by the U.S. Department of Energy. EPW files represent a type of weather file, not a weather dataset. The EPW file is the default format for DOE’s library of weather files for over 2,100 locations – including 1,042 locations in the United States, 71 locations in Canada, and 1,000 locations in 100 other countries throughout the world. The EPW files were compiled from TMY, TMY2, TMY3, and other international datasets.
MDRY – Moisture Design Reference Years
In 2011, ASHRAE 1325-RP developed Environmental Weather Loads for Hygrothermal Analysis and Design of Buildings with the purpose of developing representative weather year data for moisture design calculations. This undertaking created a methodology to determine Moisture Design Reference Years (MDRY) from hourly climate records for 100 locations in the United States and 7 locations in Canada. The current data include a collection of three ‘worst’ years for each location. The three years were selected from two weather datasets: 1961-1990 SAMSON dataset and the 1953-1993 CWEED dataset. Future updates will include data from NCDC’s 1990-2005 dataset. The equation-based method uses average weather parameters for a north facing wall and predicts an estimate for a damage function called RHT-index. The study also compared the predicted damage function to simulated hygrothermal performance with 30-year measured hourly data on a north-facing framed wall assembly having an OSB moisture loading component. The most widely used hygrothermal datasets have employed warm and cold hygrothermal years selected from the 10th percentile of the warmest and coolest years from 30-year measured hourly data (e.g. WUFI’s cold year/warm year). The newer MDRY datasets offer weather years that are, in some cases, more severe. ASHRAE 1325 recommends the third highest damage function, which corresponds to the 10th percentile for a 30-year dataset and a severity event that is expected to occur once in every 10 years.
Synthetic Weather Data
Commercially available software, such as Meteonorm, can generate weather data from monthly climate averages. For example, Meteonorm creates hourly data using measured 30-year datasets for 7,400 locations. The source of Meteonorm’s data include the Global Energy Balance Archive (GEBA), the World Meteorological Organization (WMO/OMM) Climatological Normals 1961–1990, and the Swiss database compiled by MeteoSwiss. Among the strengths of Meteonorm’s process is its ability to interpolate data for locations between reporting weather stations. Although Meteonorm provides precipitation data, the synthetically derived rain data may be unreliable when simulating driving rain events for hygrothermal modeling.
In general, synthetic data may be well-suited for a wide variety of building simulations, however, there are limitations to their reliability. It is important to note that synthetic datasets rely heavily on interpolation between weather stations and then generation of hourly data. In contrast, datasets such as TMY use hourly measurements extracted from months that are closet to average conditions to form a typical year dataset. Thus, synthetic data may have an advantage in generating data for any location, the generated data may or may not offer high reliability. Synthetic data are similar to TMY and IWEC datasets in representing ‘typical’ or normal conditions, not extremes.
Reading and Conversion of Weather Files & Datasets
Energy modeling software packages have varying capabilities for reading the growing array of file types and datasets. File conversion software is also available to facilitate exchange into proprietary applications, common spreadsheet formats, or generic text formats such as ASCII and CSV. It should be noted that TMY, TMY2, and TMY3 datasets are not interchangeable due to variations in the collected data elements. File conversion is necessary for most software packages.
Hygrothermal modeling software such as WUFI and hygRIC supply a database of world weather files as well as updates for ASHRAE 1325 datasets (WDRY). In addition to its standard .WET file format, WUFI can also accept weather data in the following formats:
- TRY–Test Reference Year datasets
- DAT – German National Meteorological Service
- IWC – International Weather Year for Energy Calculation (IWEC)
- WAC – WUFI ASCII climate format
- WBC – WUFI binary climate file
- EPW – EnergyPlus file
The developers of WUFI had the foresight to include a file conversion tool that converts Excel spreadsheets into the ASCII-based WAC format. This offers a fairly straigtforward approach for importing various types of weather data. Tutorials for creating WAC files can be found here.
U.S. Department of Energy: EnergyPlus Weather Data Sources: Link
U.S. Department of Energy: Weather Files for Simulations: Link
WUFI: Creating *.WAC Weather Files: Link
Effect of Selected Weather Year for Hygrothermal Analyses: Link
A Fresh Look at Weather Impact on Peak Electricity Demand and Energy Use of Buildings Using 30-Year Actual Weather Data: Link
The University of Exeter: Weather Files for Current and Future Climate: Link
Does It Matter Which Weather Data You Use in Energy Simulations? ACEEE 1996 Summer Study on Energy Efficiency in Buildings, 25-31 August 1996, Asilomar Conference Center, Pacific Grove, California: Link