Ashrae Code 2005

4784 (RP-1273)

The Calculation of Climatic Design Conditions in the 2005 ASHRA E Handbook-Fundamentals

Didier J. Thevenard, PhD, PEng Member ASHRAE

ABSTRACT

ASHRAE Research project 1273-RP recalculated and expanded the tables of climatic design conditions in the ASHRAE Handbook-Fundamentals. These tables provide values of dry-bulb, wet-bulb, and dew-point temperature, enthalpy, and wind speed at various frequencies of occurrence over annual and monthlyperiods and for some of these, mean coincident values of other variables of interest. Compared to the previous edition of the Handbook, the new tables include additional elements and are calculated for a much greater number of stations over a longerperiod of record. This paper explains the procedure used to compute the design conditions, the data sources used, the techniques employed to screen out erroneous data, and the completeness criteria required by the calculation. It also provides a summary of the stations included in the 2005 Handbook and a brief description of how the new values compare to thosepublishedin the 2001 edition. Finally, thepaperprovides an overview of the capability of the Weather Data Viewer, a companion CD-ROM that gives full access to the frequency information used to compile the tables of climatic design conditions.

INTRODUCTION

In support of HVAC design and sizing calculations found throughout its Handbooks (ASHRAE 2001-2004) ASHRAE provides, in a separate chapter of Fundamentals, tables of climatic conditions for many locations in the United States, Canada, and around the world. These tables include values such as dry-bulb temperature, dew-point temperature, wet- bulb temperature, wind speed and wind direction at various

Robert G. Humphries, PhD Associate Member ASHRAE

frequencies of occurrence over a long-term period, corresponding mean coincident values of some other parameters, and statistics on some extremes. Some tables provide yearly statistics; others provide statistics on a monthly basis. ASHRAE also sells a CD-ROM called the Weather Data Viewer (ASHRAE 2000) that can be used to display actual design values, joint frequency tables, or summary statistics for dry-bulb, dew-point, and wet-bulb temperature, as well as enthalpy and wind speed.

In response to the needs expressed by its members and the HVAC community, ASHRAE-sponsored research project 1273-RP aimed at

updating the tables in the ASHRAE Handbook-Funda- mentals to include data for recent years; expanding the number of geographical locations, both in North America and in other countries; including a number of new climatic elements in the tables; expanding monthly percentile tables to include locations outside the United States; developing a CD-ROM with the entire full-resolution joint frequency information used to compile the design information, and updating the Weather Data Viewer.

This paper details how the new tables included in chapter 28 of the 2005 ASHRAE Handbook-Fundamentals (ASHRAE 2005) were developed. The paper details the principles of the calculation method, describes the data sources used, and provides a summary of the information contained in the tables.

Didier J. Thevenard is president of Numerical Logics Inc., Vancouver, BC, Canada. Robert G. Humphries is manager of the Air Quality Modeling and Assessment Group of Levelton Engineering Ltd., Richmond, BC, Canada.

02005 ASHRAE. 457 Copyright ASHRAE Provided by IHS under license with ASHRAE

Not for ResaleNo reproduction or networking permitted without license from IHS

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PRINCIPL€§ SF CALCULATION METHOD

Simple Design Conditions

Annual simple climatic design conditions included in the 2005 Fundamentals are listed below, with conditions new to the 2005 edition marked with an asterisk:

99.6% and 99% heating dry-bulb temperature 0.4%, 1%, and 2% cooling dry-bulb temperature 0.4%, 1%, and 2% evaporation wet-bulb temperature 0.4%, 1%, and 2% dehumidification dew-point temperature and the corresponding humidity ratio "99.6% and *99% humidification dew-point temperature and the corresponding humidity ratio *0.4%, * 1%, and *2% enthalpy

The Handbook also includes the following monthly design conditions:

0.4% and 1% wind speed for the coldest month 0.4%, 1%, and 2% dry-bulb temperature for all months 0.4%, 1%, and 2% wet-bulb temperature for all months

The 99.6% and 99% humidification dew-point temperatures are used for cold season humidification applications. Enthalpy design conditions are used for calculating cooling loads caused by infiltration and ventilation into buildings. It should also he noted that monthly design conditions werc available only for selected US stations in the 2001 Handbook and are provided for all stations in the 2005 edition. The monthly design conditions provide additional information when seasonal variations in solar geometry and intensity, building or facility occupancy, or building use patterns require consideration. In particular, these values can be used when determining air-conditioning loads during periods of maximum solar radiation.

The x% simple design condition is the condition that is exceeded, on average, x% of the time frame under consideration. For example, the 1% annual design dry-bulb temperature is the temperature that is exceeded on average 1 % of the year, or 87.6 hours per year. The 0.4% monthly design wind speed for January corresponds to a wind speed exceeded 0.4% of the time in a typical January month, or roughly three hours during the month.

In the previous edition ofthe Handbook (ASHRAE 2001) the calculation of simple design conditions was performed using joint frequency matrices; for example, the 0.4% dry- bulb design condition was calculated by totaling rows in the (dry-bulb, dew-point) joint frequency matrix. This method runs the risk, as will be seen later, that dry-bulb temperatures are not taken into account for those hours where the dew-point temperature is missing. The method chosen for the 2005 edition was to usefrequency vectors, i.e., calculate the distribution functions for individual variables.

To calculate simple design conditions for a given variable, long-term hourly data are required. As will be explained later,

up to 30 years of data were used. The data are then grouped by bins of equal width. The following bin widths were used for Canadian and international locations:

1 kJkg for enthalpy

0.5"C for dry-bulb, dew-point, and wet-bulb temperatures

1 m / s for wind speed

For US stations, the preference was to convert the data back to I-P units (since most were originally recorded in that system of units) and use I-P bin sizes:

0.5 Bhdlb for enthalpy 1 "F for dry-bulb, dew-point, and wet-bulb temperatures

2 mph for wind speed

These values are identical to those used in the 2001 edition. They provide enough resolution while keeping the number of bins relatively low,

The frequency vector is defined by counting the number of values in each bin. A cumulative sum of the frequency vector, starting from its lowest value, followed by a division by the total number of values, provides the cumulative distribution function of the variable. Finally, a lookup of the function enables the determination of the design conditions that are exceeded a given percentage of the time.

The procedure will he illustrated with the calculation of the 2% dry-bulb temperature for Atlanta, GA, USA (WMO id: 722 190). Dry-bulb temperature values are sorted by bins 1°F (or 0.56"C) wide, leading to the frequency vector shown in Figure 1. Each value of the frequency vector counts all dry-bulb temperatures TDB satisfiing

Dry bulb temperature ("C)

10 15 20 25 30 35 40 1,600 T----, -___

1 O00 . r 0 a 800 r -

600 -

400.

50 59 68 77 86 95 104

Dry bulb temperature ("F)

Figure 1 Dry-bulb temperature frequency distribution in August for Atlanta, GA.

458 ASHRAE Transactions: Research Copyright ASHRAE Provided by IHS under license with ASHRAE


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where CE represents the center of bin k and A T D B the bin width. The cumulative distribution function (CDF) is calculated by summing all bins below a certain level and dividing by the total of all bins:

i

Care should be taken in interpreting the meaning of C D d B . It represents the probability that the dry-bulb temperature TDB is less than the upper limit of the bin, that is,

ATDB CO$, = PITDB i CE+ - 2 '

The CDF is shown in Figure 2. The 2% dry-bulb temperature is found simply by looking up, on the graph of Figure 2, the dry-bulb temperature corresponding to a CDF of 0.98, or in this case, 923°F (333°C).

Coincident Design Conditions

In addition to the simple design conditions described above, the Handbook provides yearly mean coincident conditions for a number of variables (conditions new to the 2005 edition are marked with an asterisk):

mean wind speed and prevailing wind direction coincident with the 99.6% and 0.4% yearly dry-bulb temperatures; mean wet-bulb temperature coincident with the 0.4%, 1 %, and 2% yearly cooling dry-bulb temperatures; mean dry-bulb temperature coincident with the 0.4%, 1%, and 2% yearly evaporation wet-bulb temperatures; mean dry-bulb temperature coincident with the 0.4%, 1%, and 2% yearly dehumidification dew-point temperatures; *mean dry-bulb temperature coincident with the 99.6% and 99% yearly humidification dew-point temperatures; mean dry-bulb temperature coincident with the 0.4%, 1%, and 2% yearly enthalpies;

as well as the following monthly mean conditions:

mean dry-bulb temperature coincident with the 0.4% and 1 % wind speeds, for the coldest month; mean wet-bulb temperature coincident with the 0.4%, 1%, and 2% dry-bulb temperatures, for all months; mean dry-bulb temperature coincident with the 0.4%, 1%, and 2% wet-bulb temperatures, for all months.

The calculation of mean coincident conditions requires double binning of the data into what is called a joint frequency matrix. For example, to calculate the mean wet-bulb temperature coincident with a given design dry-bulb temperature, one uses a (dry-bulb temperature, wet-bulb temperature) joint frequency matrix. Bin widths ATDE and A T W B are chosen for

Dry bulb temperatura ("C) 10 15 20 25 30 35 40

50 59 68 77 86 95 104

Dry bulb temperature ("F)

Figure 2 Dry-bulb temperature cumulative distribution function in August for Atlanta, GA.

dry-bulb and wet-bulb temperatures, respectively, and element 0, k) of the joint frequency matrix FDB,wB counts the hours during which both of the following conditions are met:

ATDE I TDB < YDB + - %E 2 2

ATWE '*WB 2 5 TwE< - 2

(4)

(5)

where ?iE is the center bin value of dry-bulb bin j , and TkwE is the center bin value of wet-bulb temperature bin k.

the mean coincident wet-bulb temperature TkwB,DB can be calculated by simply doing an average of the wet-bulb center-bin temperatures weighted by the values of the corresponding row of the frequency matrix. In mathematical terms:

For each dry-bulb temperature center-bin value

.i

The mean coincident wet-bulb temperature can be calculated for every dry-bulb center-bin value, leading to a function such as the one represented in Figure 3. It is then possible to interpolate the function to calculate the mean coincident wet- bulb temperature for any dry-bulb temperature, for example, to calculate the mean wet-bulb temperature coincident with the 2% dry-bulb temperature calculated in the previous section. This is illustrated again in Figure 3; the 2% dry-bulb temperature being 923°F (33.8"C), the mean coincident wet- bulb has a value of 749°F (233°C).

If the weighted averages had been calculated with dry- bulb temperatures over the rows of the matrix, rather than its columns, the results would have been the mean dry-bulb temperatures coincident with wet-bulb temperatures.

ASHRAE Transactions: Research 459 Copyright ASHRAE Provided by IHS under license with ASHRAE


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ory bulb temperatura PC) 10 15 20 25 30

50 50 59 68 77 ea

Dry bulb temperature ('F)

35

92 8 'F 33 8 'C .-

u 14 a

12 2

10 95 104

Figure 3 Mean wet-bulb temperature coincident with dry- bulb temperature in August for Atlanta, GA.

Similar procedures can, of course, be used to calculate other mean coincident conditions. The only slightly different case is that of prevailing wind direction coincident with dry- bulb temperature. It is calculated by searching the maximum cell in a row of the (dry-bulb temperature, wind direction) matrix. Instead of performing a linear interpolation, the value nearest to the considered design dry-bulb value is used.

The bin widths used to calculate the mean coincident conditions need not be the same as those used to calculate the simple conditions. Paradoxically, the use of smaller bins often makes the calculation of coincident design conditions less correct, the reason being that larger bins provide a natural smoothing of the mean coincident function, particularly near the extremes (see Thevenard et al. 2004). The following bin widths were used in the joint frequency matrices for Canadian and international locations:

1 kJkg for enthalpy

10" for wind direction

1°C for dry-bulb, dew-point, and wet-bulb temperatures

1 mís for wind speed

For US stations the bin widths were:

2°F for dry-bulb, dew-point, and wet-bulb temperatures 0.5 Btu/lb for enthalpy 2 mph for wind speed 10" for wind direction

The case of the 2°F bins for US stations requires special attention. A difficulty arises from the fact that many ofthe dry- bulb and dew-point temperatures were recorded as whole Fahrenheit values. When using 2°F bins, this leads to the bins not being properly centered. For example, the bin centered around 40°F is expected to hold all values in the interval [39OF, 4 1 "FI; but because whole Fahrenheit values are used, it really

contains only 39°F and 40"F, so practically it is centered around 39.5"F, not 40°F. A careless use of such 2°F bins results in systematic shifts in the calculation of coincident design values, compared to the values that would be obtained with 1 "F bins. The temperature bins were therefore shifted by OSOF, i.e., the bins are centered around 60.5"F, 62.5"F, 64.5"F, etc., instead of 60°F, 62"F, 64"F, etc.

Other Design Conditions

Other design conditions included in the Handbook include coldest and hottest month, mean and standard deviation of extreme annual temperature, monthly mean daily temperature range, and extreme maximum wet-bulb temperature, as explained below (conditions new to the 2005 edition are marked with an asterisk).

*Coldest and Hottest Months. The coldest and hottest months are calculated simply as the month with the lowest or highest average dry-bulb temperature. They may be used, for example, as input to the ASHRAE clear sky model for gener- ation of solar data consistent with the annual heating and cooling design conditions.

Mean and Standard Deviation of Extreme Annual Dry-Bulb Temperature. The mean TDB,max and the standard deviation of the maximum annual dry-bulb temperature are calculated as

N

(7) i = I 1 f ('DB,mana TDB,max) 2

(8) - - i = l ODB,max

where N is the number of years for which the maximum annual dry-bulb temperature can be calculated, and is the maximum annual dry-bulb temperature for year i. A similar formula is used for the mean and standard deviation of the minimum annual dry-bulb temperature.

*Monthly Mean Daily Dry-Bulb Temperature Range. The daily dry-bulb temperature range is the difference between the maximum and minimum temperature for the day. The monthly mean daily dry-bulb temperature range is simply calculated as the average of the daily values over the days in that month over all the years.

*Extreme Maximum Wet-Bulb Temperature. This is simply the largest value of wet-bulb temperature over the period ofrecord. This value is the most extreme condition ever expected for evaporative processes such as cooling towers. For most locations, it is significantly higher than the 0.4% wet- bulb temperature and should be used only for design of critical applications where an occasional short-duration capacity shortfall is not acceptable.



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DATA SOURCES

Weather Data Sets

As mentioned previously, the calculation of the design conditions requires hourly weather data. Whenever possible, the data covered the period 1972-2001, except for most international locations where it spanned 1982-2001. Three sources of data were used.

For many US stations, data from the Solar and Meteoro- logical Surface Observation Network (SAMSON) files were used (NCDC 1993). It should be noted that although the SAMSONfilescovertheperiod 1961-1990, datapriorto 1972 were not used (except for a couple of stations that had too few data in the 1972-2001 period). On the other hand, and whenever possible, the SAMSON data were supplemented by the Integrated Surface Hourly (ISH) weather data files obtained from the National Climatic Data Center (NCDC 2003) for the period 1991-2001 in order to cover the whole period 1972- 2001.

Many Canadian data came from the Canadian Weather Energy and Engineering Data Sets (CWEEDS) files obtained from Environment Canada (2002). Only data from the 1972- 2001 period were used (a handful of stations had too few data in the 1972-2001 period and for these, data from the 1961- 1990 period were used, as was done in the 2001 edition of the Handbook).

Finally, for international locations and some US and Canadian locations, the ISH weather data files were used. At most the files contain data from 1982 to 2001, but the amount of data varies widely from one site to the other.

Data Screening

Experience showed that data issued from the sets above, despite having gone through quality procedures at their national weather services or NCDC, still contain a fair number of obviously erroneous values. Two examples are a temperature stuck at +37.8"C (+100"F) for most of the month of Janu- ary for an Alaskan station, or a one-hour temperature spike from +6"C to +50"C (+43"F to +122"F) for an Italian station. As long as there are few of these outliers, they have little influence on the shape of the cumulative distribution curves (see "Principles of Calculation Method" above) and, therefore, on the calculation of extreme percentiles such as the 0.4% cooling dry bulb. They do, however, have a strong influence on the calculation of extremes, such as the mean and standard deviation of extreme annual dry bulb, the hottest month dry-bulb temperature range, or the extreme maximum wet bulb, and for that reason need to be eliminated.

A combination of techniques is used to identifj outliers. First, ranges of acceptable values are defined. For example, dry-bulb temperatures are normally within the [-50, 501°C range ([-58, 122]"F), so values outside that range are set to missing. These bounds are appropriate for most stations and eliminate some obviously erroneous data. However, this technique is applied with caution since there are some stations

that do experience temperatures outside that [-50, 501°C range, such as Kuwait Intl, KWT (405820). For stations with very high or very low temperatures (which we defined mathematically as having a 99.6% heating dry-bulb temperature less than -44°C [-47"F] or a 0.4% cooling dry bulb greater than 44°C [ 1 1 1 "FI), the temperature check was disabled. Similar checks are applied to dew-point temperature, sea level pressure, wind speed, and wind direction.

A second technique uses high-pass digital filters to catch spikes in temperature or pressure (not wind since it is highly variable). The detection thresholds were chosen by trial and error, guided by physical considerations. For one-hour spikes, the detection thresholds correspond roughly to a rate of change of 15°C (27°F) per hour for dry-bulb and dew- point tcrnperature and 600 Pa (0.087 psia) per hour for station pressure. For three-hour spikes, the detection thresholds correspond roughly to a rate of change of 22°C (39.6"F) per three hours for dry-bulb and dew-point temperatures and 800 Pa (0.12 psia) per three hours for station pressure.

A third technique checks for large numbers of empty consecutive bins separating two non-empty bins. This technique is applied on the raw temperature data (before any interpolation takes place) on a monthly basis. The presence of such gaps in the distribution is a fairly sure indicator of outliers. The maximum gap between two non-empty bins was set to 10°C (1 8°F). It may happen that the temperature varies by more than that amount within the course of an hour, but the reasoning is that such events would not be unique and, therefore, would not likely leave a large gap in the frequency distribution.

Finally, consistency between dry-bulb temperature and dew-point temperature is asserted. Together, all these methods reduce considerably the amount of erroneous data and do have an influence on the calculated design conditions. For example, for Pt. Piedras Blanca, CA, USA (723900) the 0.4% dry-bulb temperature was calculated as 41.7"C (107°F) without elimination of outliers; the actual value after elimination of outliers is 26.0"C (783°F).

Data Interpolation

The weather data sets used for the calculations often contain missing values, either isolated records or because some stations record data only every third hour. Gaps up to six hours are filled by linear interpolation in order to provide a time series as complete as possible (see "Completeness Crite- ria" below). Dry-bulb temperature, station pressure, and humidity ratio were interpolated. However, wind speed and wind direction were not due to their more stochastic and some- what unpredictable nature. Dew-point temperature was calculated from interpolated values of dry-bulb temperature and humidity ratio.

Some stations in the ISH data set also provide data that are not recorded at the top of the hour. When data at the exact hour were missing, they were replaced by data up to half an hour before or after, when available.



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Finally psychrometric quantities such as wetibulb temperature or enthalpy are not contained in the weather data sets. They were calculated from dry-bulb temperature, dew- point temperature. and station pressure using psychrometric formulae contained in the 2001 Handbook (ASHRAE 2001).

Region

1 - Africa

2 - Asia

Completeness Criteria The data set had to be complete enough so that the design

conditions were statistically meaningful. Following recom- mendations from ASHRAE research project 890-RP (Colher et al. 1998), whole months are accepted in the analysis, or rejected from it, based on the following criteria (note: all criteria below are evaluated after linear interpolation):

Number of Stations Number of Stations (2005 edition) (2001 edition)

163 56

1366 257

At least 85% of the dry-bulb temperature values (ajler linear interpolation) for the month are present. The difference between the number of daytime (from 9 a.m. to 8 p.m. included) and nighttime (from 9 p.m. to 8 a.m. included) dry-bulb temperature values for the month is no more than 60. A station can be processed if there are at least 8 valid month data sets for each of the 12 months for the period of record (i.e., there must be 8 valid Januaries, 8 valid Februaries, etc.). These criteria are almost identical to what was used for

~

4 - North and Central America

5 - South-West Pacific

the calculation of design conditions for the 2001 Handbook and are appropriate for dry-bulb temperature. However, they are insufficient to screen other variables because they don’t address the fact that dry-bulb temperature may be present but a large number of dew-point temperature, wind speed, or wind direction values may be missing. For these, additional criteria must be met: 1. Dew-point temperature. wet-bulb temperature, and

enthalpy statistics: the number of valid data has to exceed 85% of the number of records with dry-bulb temperature. Mnd speed and wind direction statistics: the number of valid data has to exceed (85/3)% the number ofrecords with dry-bulb temperature. The (1/3) factor is to account for the fact that wind speed and direction are not interpolated, and, therefore, for those stations that record data only every third hour, there would be three times fewer wind speed and wind

2.

1094 655

274 52

direction data as there would be interpolated dry-bulb temperature data. If these criteria are not met, the corresponding entries

appear as ‘“/A” in the Handbook tables. For mean and standard deviation of yearly minimum and

maximum dry-bulb temperatures, these additional criteria must be met: 1. The minimum and maximum dry-bulb temperatures for a

given year may be calculated only if at least 85% of the dry- bulb temperature values (after linear interpolation) are present. This makes sure that the statistics are not calculated for years that are too incomplete. The minimum and maximum have to be calculated for at least eight years for the calculation of the mean and standard deviation to take place. If these conditions are not met, the mean and standard

deviation of yearly minimum and maximum dry-bulb temperatures appear as “N/A” in the Handbook tables.

Finally, for the monthly mean daily dry-bulb temperature range: 1. The dry-bulb temperature range for any given day may be

calculated only if there is no missing dry-bulb temperature for that day.

2.

RESULTS

6 - Europe

7 - Antarctica

Total

Stations Processed Over 17,000 weather stations were processed. Of these,

about 4,400 were complete enough to be included in the Hand- book, This represents a significant increase over the 2001 edition, which contained about 1,460 sites. An unforhinate consequence is that it was not possible to include ail stations in the printed edition of the Handbook. It was therefore decided that the Handbook would only contain sample station data for one station (chosen as Atlanta, GA, to be in harmony with other sample calculations throughout the Handbook), the rest being available in electronic form in the CD version of the Handbook.

The breakdown of stations by region is provided in Table 1, along with a count of stations in the 200 1 edition of the

1381 379

17 O

4422 1464

Table I. Geographical Distribution of the Stations

13 - South America I 127 I 65 I



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Figure 4 Map of stations with design conditions in the 2005 Handbook.

Handbook. North and Central America, Europe, and Asia have the bulk of the stations, with Africa and South America trailing far behind. There are 753 stations in the USA and 307 in Canada (vs. 510 and 133 in the 2001 edition). Figure 4 shows a map of all the stations; additional maps can be found on the Weather Data Viewer CD-ROM (see later).

Quality Control

All efforts were made to ensure that the calculated design conditions are as reliable as possible. Several quality control procedures were employed during the course of the project, such as data screening (see previous section), code reviews, and use of revision control software. Final checks after the processing was complete included the use of contour plots and consistency checks. Contour plots were used to identify values that were substantially different from those of neighboring stations. These were then manually examined and, if the cause of the difference proved to be erroneous data, the station was eliminated. In the example shown in Figure 5, the 0.4% dry- bulb temperatures for Galena, AK, USA, and for Chamber- lain, SD, USA, look suspicious. A closer look at the data reveals a probable mix-up of SI and I-P units, so these two stations were eliminated from the Handbook. Consistency checks, plotting one design condition against the design condition for the same variable but at different levels, for example, the 0.4% against the 1% dry-bulb temperatures, also revealed a few abnormalities. Such cases were rather excep- tional (see Thevenard et al. [2004]). In all, fewer than 20 stations were eliminated in the final quality check.

Comparison with 2001 Values

Almost all the stations in the 2001 Handbook were included in the 2005 edition, which was to be expected since the data sources used were, in particular for international locations, a superset of those used previously. However, some stations were dropped because not enough data were available in the period of record (1972-200 1) used for the calculation. A few stations were also eliminated due to quality concerns. In total, only six stations from the 200 1 Handbook have no equiv- alent within 20 km in the 2005 edition.

About 170 stations from the 2001 Handbook have incomplete design conditions in the 2005 edition. As indicated in the “Completeness Criteria” section, this is due to the fact that some variables other than dry-bulb temperature were not present in sufficient number. The method used in 2001 did not check for the completeness of dew-point temperature, wind direction, or wind speed and calculated the corresponding design conditions even when the data were not statistically sufficient.

Most 2005 design conditions compare well to their 2001 counterpart for the majority of stations. Figure 6 shows such a comparison for the 2% cooling dry-bulb temperature. Thev- enard et al. (2004) contains element-by-element statistics of the differences between the two editions. The more noticeable differences occur for the following elements:

9 The 99.6% and 99% heating dry-bulb temperature- Figure 7 shows that some 2005 values tend to be lower than 2001 values in cold climates. This can be traced to the fact that 2001 values were calculated from the (dry-



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4 ? #

- .

Figure 5 Contour map of 0.4% dry-bulb temperature.

2% cooling dry bulb temperature ( T I , 2001 Handbook

O 10 20 30 40 50 122+-- -_.-- - -_i-- -

I 50

32 50 68 86 104 1 22 2%cooling dry bulb temperature (OF), 2001 Handbook

Figure 6 Comparison of 2% cooling dry-bulb temperature in the 2001 and 2005 Handbooks.

99.6% heating dry bulb temperature (OC), 2001 Handbook

60 -50 -40 -30 -20 -10 O 10 20 30

r -y----- ~ - - -

-76 58 -40 -22 -4 14 32 50 68 86 99.6% heatlng dry bulb temperature (OF), 2001 Handbook

Figure 7 Comparison of 99.6% heating dry-bulb temperature in the 2001 and 2005 Handbooks.



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bulb temperature, dew-point temperature) frequency matrix. Dew-point temperature is often missing when the dry temperature is very low; as a consequence, some low dry-bulb temperatures were not taken into account in the 2001 calculation. The 2005 values are Calculated from the frequency vector for dry-bulb temperature alone, which corrects the problem. Prevailing wind direction coincident with 99.6% dry- bulb temperature for coldest month-This can change significantly for some stations because they may have more than one prevailing wind direction and a change in the period of record may lead to picking one rather than the other. Mean and standard deviation of annual minimum and maximum temperatures-In the 2001 edition there was no check of the completeness of a year before it was included in the calculation of these values. As well, many outliers eliminated by the 2005 procedure were left in 2001, which was skewing the values. As a consequence, the 2005 mean annual extreme temperatures tend to be less extreme than their 2001 counterparts, and the standard deviations tend to be lower, as illustrated in Figure 8.

Weather Data Viewer

In addition to the tables published in the SI and I-P editions of Fundamentals, Research Project 1273 also produced a new version of the Weather Data Viewer. WDView 3.0 enables one to view the frequency vectors and joint frequency matrices for all stations and all elements listed in the Handbook. The viewer uses Microsoft Excel as a front-end, and one is able one to display the tables in numeric form or plot the frequency distribution, the cumulative distribution frequency, and the mean coincident functions. It also provides additional information, such as the time zone and daylight savings time of the stations and the months and years that were used for the calculation of design conditions for each station. The Weather Data Viewer CD-ROM is available as a separate product from ASHRAE.

CONCLUSIONS

Project 1273-RP has produced new tables of climatic design conditions for the 2005 ASHRAE Handbook-Funda- mentals. Compared with the previous edition, these new tables are characterized by an increased number of stations, the addition of a number of design conditions, and the expansion of monthly tables of design conditions to all stations. The calculation method for simple design conditions was slightly modi- fied and uses frequency vectors of individual variables. Coincident design conditions are calculated with the use of joint frequency matrices, as was done in the past. For most US and Canadian stations, data for the period 1972-2001 were used; for other stations, the 1982-2001 period was used.

Standard deviation of annual minimum dry bulb Wmperature f'C), 2001 Handbook

O 2 4 6 8 1 0 1 2 1 4

O 3 6 7 2 108 144 18 216 252 288 324 36

Standard deviation of annual minimum dry bulb temperature (OF),

2001 Handbook

Figure 8 Comparison of standard deviation of annual minimum dry-bulb temperature in the 2001 and 2005 editions of the Handbook.

Extensive checks were performed on the data to ensure that most outliers are eliminated from the analysis.

Design conditions were calculated for over 4,400 stations worldwide, including close to 1,100 in North and Central America and almost 1,400 each in Europe and Asia. The new design conditions usually compare well with the 2001 values. It is our hope that these design conditions will be useful to engineers involved in the design and sizing of HVAC systems and will provide valuable information in support of other chapters in the ASHRAE Handbook-Fundamentals.

ACKNOWLEDGMENTS

The work reported in this paper was sponsored by ASHRAE research project 1273-RP. The authors would like to thank M. Jeffrey Lundgren, M.Sc., for his work on the project and the members of the project monitoring subcommittee of T.C. 4.2 for their useful feedback and comments.

REFERENCES

ASHRAE. 2000. Weather Data I lmer, version 2.1. Atlanta: American Socieîy of Heating, Refrigerating and Air- conditioning Engineers, Inc.

ASHRAE. 2001. 2001 ASHRAE Handbook-Fundamen- tals. Atlanta: American Society of Heating, Refrigerat- ing and Air-conditioning Engineers, Inc.

ASHRAE. 2001 -2004. 2001 ASHRAE Handbook-Funda- mentals, 2002 ASHRAE Handbook-Refrigeration, 2003 ASHRAE Handbook-HVAC Applications, 2004 ASHRAE Handbook-HVAC Systems and Equipment. Atlanta: American Society of Heating, Refrigerating and Air-conditioning Engineers, Inc.



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ASHRAE. 2005. 2005 ASHRAE Handbook-Fundamen- tals. Atlanta: American Society of Heating, Refrigerat- ing and Air-conditioning Engineers, Inc.

Colher, D.G., R.S. Gates, H. Zhang, T. Burks, and K.T. Priddy. 1998. Final Report for Updating the Tables of Design Weather Conditions in the ASHRAE Hand- book-Fundamentals (890-RP). Atlanta: American Society of Heating, Refngerating and Air-conditioning Engineers, Inc.

Environment Canada. 2002. Canadian Weather Energy and Engineering Datu Sets (CWEEDS). Downsview, ON, Canada: Environment Canada.

NCDC. 1993. SoZar and Meteorological Surface Observa- tional Network (SAMSON), 3-vol. CD-ROM. Asheville, NC: National Climatic Data Center.

NCDC. 2003. Data Set 3505 (DSI-3505), Integrated Surface Hourly Data. Asheville, NC: National Climatic Data Center.

Thevenard, D., J. Lundgren, and R. Humphries. 2004. Updating the Climatic Design Conditions in the ASHRAE Handbook of Fundamentals (2005 Edition), 1273-RP Final Report. Atlanta: American Society of Heating, Refrigerating and Air-conditioning Engineers, Inc.



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