Climatic Information
ASHRAE Technical Committee 4.2


What are weather years for energy simulations and how do they differ from other types of weather or climate data?

Short answer
Weather years for energy calculations, such as IWEC, WYEC2, CWEC, TRY_ROW (see Abbreviations), TMY, TMY2, and TMY3 are single years for specific locations comprising of 8760 hourly records of various climatic parameters such as temperature, atmospheric moisture, and insolation. The files are complete with no entries flagged as missing. These single year files do not represent a single year of contiguous measured data but rather are composite years comprising months from different years, selected using statistical criteria (usually the F-S statistic), and modified at the end and beginning of the months to ensure a smooth transition between the non-sequential data. Entries flagged as missing are interpolated. Hourly weather observations, such as those from the NSRDB, represent continuous sequences of measured (or modeled) archived data over a period of record that may contain missing elements. Weather years for energy calculations are derived from such archives.

Long answer
Archival weather data of the type commonly available from local meteorological services generally comprise of hourly records spanning multiple years. Records consist of hourly measurements or modelled values of typical climatic parameters such as temperature, dew point, direct and diffuse solar radiation (beam and diffuse), and wind speed. These data sets, such as NREL’s NSRDB, are generally fully populated with missing or modelled data flagged as such. It is from these data sets that derivative data and data sets are developed, specifically, weather years for energy calculations. Briefly, energy simulations are mainly run to evaluate different scenarios comparing the long-term energy use of the different scenarios, such as different fenestration options or HVAC control strategies. The assumption is that a single year of simulation would represent the typical use over the long-term; 30-years for example. Consequently many energy studies tend to run a single weather year. The years must be fully populated with no missing values so that the simulation tools do not fail upon running. Ideally, the year should represent typical average weather data, and not long-term extremes, but exhibit a range of weather phenomena for the location in question: typical cold conditions, typical hot conditions, yet still giving annual averages that are consistent with the long-term averages for the location in question. So which weather data set to choose? Information on selecting weather data is described in a paper by Crawley [1].

One approach is to select an entire year where the means and standard deviations for the monthly data of that year match the means and standard deviations over a longer period, 10 or more years, a so-called Example Weather Year (EWY) [2] and TRY_US (see Abbreviations). Trying to find such a year however may be difficult and there is a small chance of finding such a year in a 15 to 20-year data set [3].

Another approach is to select typical months and stitch them together to form a typical year. This was, and is, the approach for generating TRY_ROW, TMY, TMY2, TMY3, CWEC, WYEC2, and IWEC data. The method was first developed by Hall et al. [4, 5] and is sometimes referred to as the Sandia method and is now part of an ISO standard (ISO 15927-4) [6].

The simplified procedure is as follows:
For each month in the climate record, calculate the daily means for each index. Indices generally include temperature and solar radiation, and (with lower weights) humidity and wind speed. For each calendar month, determine the CDF of the daily means, sorting the values in rank order.
For all the years in the data set, calculate CDF of the daily means.
Calculate the F-S for each month and select 5 months using a weighted sum of the F-S statistics.Rank the candidate months with respect to the closeness of the month to the long term mean and median.
Use persistence criteria to exclude months with the longest run of temperature, the month with the most runs, and the month with zero runs.
Concatenate the 12 selected months by smoothing the 6 hours on each side of the transition between months to eliminate discontinuities.

This is the basic method. Notice that the year is not a year of actual measured data but rather a year comprising of months from possibly twelve different years, smoothed at the edges. Take the CWEC file for Ottawa Canada, available from the EnergyPlus website [7, 8]. The years of origin for the months comprising the year are given in the table below.

Table: Months of origin for Ottawa Canada CWEC

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1966 1980 1964 1964 1968 1970 1977 1981 1979 1969 1974 1960

The TMY3 method is the currently accepted method for generating energy years for weather calculations in the United States and its territories. The manual for the TMY3 is available from NREL [9]. It should be noted that there has been a wealth of research on the development and application of weather years for energy calculations, on such topics as the effect of the length of period of record. Research on generating TMYs from raw data [10] and on the effect of different weighting factors [11] are among the most recent examples. A search for the exact term “typical meteorological year” yields over 1700 hits in Google Scholar.

Available Energy Weather Years.
A short and non-exhaustive list of energy weathers years in various formats can by found here:  Energy weather years sources

Note : what typical years should be used for, or not.
Typical year weather files are designed to represent a typical year with respect to weather-induced energy loads on a building. Because of that, they are generally appropriate to evaluate the average energy performance of buildings. They are also useful in determining the average production of solar energy systems such as active solar systems or photovoltaic systems. However, they should not be considered for other uses, such as: determining extreme climatic conditions, e.g. design temperatures, as the files represent an 'average' year which may not include extreme conditions;evaluating other kinds of renewable energy systems, such as wind energy systems. The files are typical in terms of solar radiation and dry bulb temperature, not in terms of wind speed;hygrothermal analysis of building envelopes. These files represent “typical” conditions that are not appropriate for design purposes. Also, most of the formats, with the exception of the TMY3 format do not include rainfall (see ASHRAE Research Project 1325-RP “Environmental Weather Loads for Hygrothermal Analysis and Design of Buildings”).

CDF – Cumulative Distribution Function;
CWEC Canadian Weather for Energy Calculations;
F-S – Finkelstein-Schafer statistic; Finkelstein J., M., Schafer, R., E. Improved goodness of fit tests . Biometrika 1971; 58: 641-645;
IWEC – International Weather for Energy Calculations;
NREL – National Renewable Energy Laboratory;
NSRDB – National Solar Radiation Database;
TMY – Typical Meteorological Year;
TRY, TRY_US, TRY_ROW – Test Reference Year; "Test Reference Year" when used in the United States (TRY_US) generally refers to the specific set of 60 TRY historical year weather files for US locations developed by NCDC in the late 70's [12].Therefore TRY_US refers to single contiguous years and are similar to the Example Weather Years in Europe [2]. In the Europe Community and the Rest of the World (ROW) TRY was/is used interchangeably with TMY. The TRY_ROW method of developing the years is the same as TMY years in that months selected rather than single years [13, 14, 15].
WYEC2 - Weather Year for Energy Calculations 2;

Kindly guide us on how we can add weather data for <country/state/county/region> to the ASHRAE Handbook – Fundamentals or ASHRAE Standard 169 – Weather Data for Building Design Standards.

TC 4.2 Climatic Information works continuously to update climate data for existing locations and to expand the coverage of climate locations worldwide. The Committee also attempts to keep current the IWEC (International Weather for Energy Calculations) as well as increasing the number of locations. The Handbook – Fundamentals (HOF) is updated on a four year cycle while Standard 169 is updated on a 5 year cycle, although addenda can be issued on an annual basis. The extent of coverage in the HOF tables is dependent on the availability of multi-year data from the National Climatic Data Center (NCDC) in Asheville NC, from whom TC 4.2 obtains most of its raw climatic data. NCDC houses the World Data Center – and archives all publicly available meteorological data from around the world.

When an international ASHRAE Chapter, for example, finds weather data for their locations absent from the HOF tables, it probably indicates that we were not able to obtain the raw data or data with the sufficient length of record. If in some instances persons or organizations have access to or have knowledge of local sources of climatic data then TC 4.2 is interested in providing technical assistance in processing these data, and reviewing the results with the interested parties. TC 4.2 is well aware of the need for additional weather data in key places of ASHRAE member interest and there is a systematic program in place to accomplish this via the regular update cycles for the HOF and Standard 169.

Before sending a request to TC 4.2 the Committee requests that the following criteria should be met for each proposed location:
Station metadata – station name (eg, city location), latitude, longitude, and elevation at a minimum. Additional metadata such as instrument history, etc, should be provided if available.
Ideally there should be 25 years of data to enable accurate calculation of climate statistics. The absolute minimum below which statistics cannot be calculated is 8 years of data. Data from recent years is preferable to older data.
Hourly data is required by the calculation procedure; however 3-hour data (observations every 3 hours) will work. If data is recorded less often (e.g. every 6 hours, or only twice a day) the calculation will generally fail.
There should be as few missing data records as possible.

The following climatic elements are required to produce a complete HOF table:

Dry bulb temperature.
Some measure of atmospheric moisture; for example, wet-bulb temperature, relative humidity, or dew-point temperature.
Station pressure or sea-level pressure (for psychrometric calculations).
Wind speed and direction.

If there is a large amount of data available please send us data for just ONE typical site to see if there would be enough data to calculate the required design conditions. The format of the data is not critical although comma-delimited ASCII is preferable. With data for one site it should be possible to assess the completeness of data. Whether new stations appear in the current update cycle of the HOF or cycle after the current cycle depends on the timing of the request. Documentation, such as quality control procedures, would also be greatly appreciated. After assessing the data, the availability of resources (for data processing/summarization) will determine if the new stations appear in the next HOF update. For more information please contact the TC Chair.

An example of the type of data required can found below. The file is in ASCII comma-delimited format. Missing values (such as dry bulb temperature for hour 6) are marked with -9999. Dry bulb temperature is expressed in °C, relative humidity in %, station pressure in Pa, wind direction in degrees from North (East = 90°), and wind speed in m/s.

Location: El Arish (Egypt) Lat = 31.08°N, Long = 33.82 °W, Elevation = 32.0 m

References for further reading

[1] Crawley, D., B. "Which Weather Data Should You Use for Energy Simulations of Commercial Buildings?" in ASHRAE Transactions, pp. 498-515, Vol. 104, Pt. 2. Atlanta: ASHRAE. 1998

[2] Hitchin, E. R., Holmes, M. J., Hutt, B. C., Irving, S., Nevrala, D. The CIBS example weather year Building Service Engineering 1983 4: 119-124;

[3] Levermore, G., J., Parkinson, J., B. Analyses and algorithms for new Test Reference Years and Design Summer Years for the UK Building Service Engineering 2006 27: 311-325;

[4] Hall, I., J., Prairie, R., R., Anderson, H., E., Boes, E.C. Generation of a typical meteorological year, Proceedings of the 1978 Annual Meeting Vol. 2.2, American Section of the International Solar Energy Society (1988), pp. 669–671;

[5] NREL, User’s Manual for TMY2s.

[6] ISO, ISO 15927-4 : Hourly data for assessing the annual energy use for heating and cooling,2005;

[7] EnergyPlus Weather Data;

[8] Thevenard, D., J., Brunger, A., P. The development of typical weather years for international locations, Part I: Algorithms. ASHRAE Transactions, 108(2): 376–383. 2002;

[9] Wilcox, S., Marion, W. User's Manual for TMY3 Data Sets, NREL/TP-581-43156. April 2008. Golden, Colorado: National Renewable Energy Laboratory, 2008;;jsessionid=78395F4B35199E4CC4797D0E9AF9F223?purl=/928611-IdkX12/

[10] David, M., Adelard, L., Lauret, P., Garde, F. "A method to generate Typical Meteorological Years from raw hourly climatic databases." Building and Environment 45(7): 1722-1732;

[11] Su, F., Huang, J., Xu, T., Zhang, C. "An evaluation of the effects of various parameter weights on typical meteorological years used for building energy simulation." Building Simulation 2(1): 19-28, 2009;

[12] National Climatic Data Center (NCDC). 1976. Test Reference Year (TRY), Tape Reference Manual, TD-9706, September 1976. Asheville, North Carolina: National Climatic Data Center, U.S. Department of Commerce;

[13]Lund, H. Test Reference Years TRY, Weather data sets for computer simulations of solar energy systems and energy consumption in buildings; Commission of the European Communities, Directorate General XII for Science, Research and Development, 1985.

[14] CIBSE. Current and Future CIBSE Weather Data Combined - all sites

[15] Levermore, G.,J., Doylend, N. North American and European hourly-based weather data and methods for HVAC building energy analyses and design by simulation. ASHRAE Transactions 2002;108(2): 1053-62;