2.5.1 Introduction
Climate affects building energy use in most buildings. There are two main types of climates, macroclimate and microclimate. For a particular location, environmental factors (i.e., elevation, land forms, soil types, vegetation, man-made structures) can change from climate to climate. Many procedures were previously used to classify these various climates into categories. This research focuses on those climate categories developed for building energy conservation designs. In the U.S., the National Oceanic and Atmospheric Administration (NOAA, 1980, and 1986) has collected and published extensive climatic weather data. These data have been used to develop several climatic data sets in different formats (i.e., TMY2, TRY2, WYEC2, CWEC, CTZ2, IWEC). These weather data sets are commonly used for energy simulation programs and therefore were reviewed in this research.
2.5.2 Climate Classifications
In the United States, many energy conservation design guidelines, standards and energy codes have been developed based on climate. Victor Olgyay classified climate into four categories: cool, temperate, hot-arid, and hot-humid (Olgyay, 1963). His classification system was based on the Köppen study (Köppen, 1924; Köppen and Geiger, 1930). In 1949, The American Institute of Architects (AIA) developed the House Beautiful Climate Control Project, which divided the U.S. into 15 regions and presented comprehensive climatic information for each representative city (Watson, 1993).
In 1978, the AIA Research Corporation developed 13 Regional Guidelines for Building Passive Energy Conserving Homes. The guidelines were based on heating and cooling needs, solar availability when temperatures ranged from 50-60°F, and the effect of diurnal temperature swings and humidity (Watson, 1993). Lechner (1991), using climatic information from the study conducted by the AIA, divided the U. S. climate into 17 regions. He proposed design guidelines and graphical climatic data for each region.
Briggs et al. (2003a; 2003b) developed a new climate classification system for building energy codes, standards, energy analysis, and design guidelines. This new climate classification was based on the widely accepted classification systems of world climates (Köppen and Geiger, 1930), and was meant to improve the implementation of building energy codes and standards. In order to accomplish this, Briggs et al. used a “hierarchical cluster analysis”, which is a distance metric that represents the degree of similarity or dissimilarity between observations in a data set (Briggs et al., 2003a; 2003b), to classify the climate into 17 new climate zones (see Table 2.3 and Figure 2.12). These new climate classifications were considered in this research.
ASHRAE Standards 90.1 (ASHRAE, 2004b) and the International Energy Conservation Code (IECC) (ICC, 2006) both use four different methods for specifying climate-dependent requirements. In many situations, the climatic data needed to determine the requirements is not included in the standards or the code documents. The ASHRAE energy standards and the IECC were both considered for this research.
2.5.3 Representative Weather Data
There are two main categories of hourly weather data used in energy simulations: 1) actual year data and 2) typical year data. The actual hourly observations data are available from many sources, which include the U.S. National Climatic Data Center (NCDC, 1976, 1981, and 1993) and the Solar and Meteorological Surface Observational Network (SAMSON) (NCDC, 1993). A number of weather data sets for energy simulations (i.e. TRY, TMY, TMY2, WYEC, WYEC2, BIN, IWEC, etc.) have been developed by several groups for different purposes, which include the NCDC, Sandia
Table 2.3 Climate zone definitions for new classification (Briggs et al. 2003b, p.124).
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Figure 2.12 Map of the United States showing the proposed new climate zone assignments under the new classifications (Briggs et al. 2003b, p.125). Copyright © 2003 by ASHRAE (Reprinted with permission).
National Laboratory, ASHRAE, and the National Renewable Energy Laboratory (NREL). In 1976, the NCDC developed the Test Reference Year (TRY) weather data sets for use in energy simulations (NCDC, 1976). TRY weather data are from actual historic years. These years were selected by eliminating any year that had months with extreme conditions until only one suitable year remained. That year contained dry-bulb, wet-bulb, and dewpoint temperatures, wind speed and wind direction, relative humidity, barometric pressure, cloud cover and type, and a place holder for solar radiation, but no measured solar data (Huang et al., 1996).
To deal with the limitations of the TRY weather tape’s lack of solar data, the NCDC and the Sandia National Laboratory developed a new data set, the Typical Meteorological Year (TMY), for 234 U.S. locations (NCDC, 1981). In 1995, NREL updated the TMY data set to TMY2 (Marion and Urban, 1995). The new TMY2 data utilized the Solar and Meteorological Surface Observational Network (SAMSON), which includes the published weather and the solar data from the National Solar Radiation Data Base (NSRDB) from 1961-1990, which was compiled by the NREL (NSRDB; 1992, 1995) and NCDC (1993).
In 1983, ASHRAE developed the Weather Year for Energy Calculations (WYEC) (Crow, 1983), which also included solar data. WYEC weather data was designated to represent more typical weather patterns than would occur in a single annual or monthly weather data set. ASHRAE sponsored research to update the solar insolation models (Perez et al., 1992) and worked with the NREL to update the WYEC data set (Stoffel, 1995). The new format is known as WYEC2. In 2001, ASHRAE developed a new typical meteorological year hourly weather data set, the International Weather for Energy Calculations (IWEC), for 227 locations outside the USA and Canada (ASHRAE, 2002). IWEC data were derived from up to 18 years of DATSAV3 hourly weather data originally archived at the NCDC. Solar radiation was calculated from cloud cover using a model calibrated on a station-by-station basis with measured solar radiation data collected from the World Radiation Data Center (ICSU, 1996).
Several studies have highlighted shortcomings in current weather files, including: Kusuda and Achenbach, 1965; Huang and Crawley, 1996; Crawley, 1998; and Haberl et al., 1995. Kusuda and Achenbach explained how to calculate ground temperatures, an item that is missing from most weather data sets. Huang and Crawley recommended that energy simulation users avoid using TRY and use TMY2 or WYEC2 weather files, which have more appropriate long-term weather data (Huang and Crawley, 1996, p.4.188; and Crawley, 1998). Haberl et al. compared measured weather data versus TMY weather data in the DOE-2 simulation. Their study showed that the measured data contains dryer conditions, lower temperatures, and less wind speed than appeared in the TMY weather data. Therefore, in this study, the TMY2 weather data was used with the DOE-2 program for all but one of the selected sites and ground temperatures are calculated with the Kusuda and Achenbach algorithms inside the DOE-2 program.