Appendix C — Division B

Climatic and Seismic Information for Building Design in Canada

Introduction
The great diversity of climate in change beginBritish Columbiachange end has a considerable effect on the performance of buildings; consequently, building design must reflect this diversity. This Appendix briefly describes how climatic design values are computed and provides recommended design data for a number of cities, towns, and lesser populated locations. Through the use of such data, appropriate allowances can be made for climate variations in different localities of change beginBritish Columbiachange end and the change beginBritish Columbiachange end Building Code can be applied change beginregionallychange end.
The climatic design data provided in this Appendix are based on weather observations collected by the Atmospheric Environment Service, Environment Canada. The climatic design data have been researched and analyzed by Environment Canada, and appear at the end of this Appendix in Table C-2., Design Data for Selected Locations in change beginBritish Columbiachange end.
As it is not practical to list values for all municipalities in change beginBritish Columbiachange end, recommended climatic design values for locations not listed can be obtained by contacting the Atmospheric Environment Service, Environment Canada, 4905 Dufferin Street, Downsview, Ontario M3H 5T4, (416) 739-4365. It should be noted, however, that these recommended values may differ from the legal requirements set by change beginlocal governmentchange end building authorities.
The information on seismic hazard in spectral format has been provided by the Geological Survey of Canada of Natural Resources Canada. Information for municipalities not listed may be obtained through the Natural Resources Canada Web site at www.EarthquakesCanada.ca, or by writing to the Geological Survey of Canada at 7 Observatory Crescent, Ottawa, Ontario K1A 0Y3, or at P.O. Box 6000, Sidney, B.C. V8L 4B2.

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General
The choice of climatic elements tabulated in this Appendix and the form in which they are expressed have been dictated largely by the requirements for specific values in several sections of the change beginBritish Columbiachange end Building Code. These elements include the Ground Snow Loads, Wind Pressures, Design Temperatures, Heating Degree-Days, One-Day and 15-Minute Rainfalls, the Annual Total Precipitation values and Seismic Data. The following notes briefly explain the significance of these particular elements in building design, and indicate which weather observations were used and how they were analyzed to yield the required design values.
In Table C-2., Design Data for Selected Locations in change beginBritish Columbiachange end (referred to in this Appendix as the Table), design weather recommendations and elevations are listed for change begin100change end locations, which have been chosen based on a variety of reasons. Many incorporated cities and towns with significant populations are included unless located close to larger cities. For sparsely populated areas, many smaller towns and villages are listed. Other locations have been added to the list when the demand for climatic design recommendations at these sites has been significant. The named locations refer to the specific latitude and longitude defined by the Gazetteer of Canada (Natural Resources Canada), available from Publishing and Depository Services Canada, Public Works and Government Services Canada, Ottawa, Ontario K1A 0S5. The elevations are given in metres and refer to heights above sea level.
Almost all of the weather observations used in preparing the Table were, of necessity, observed at inhabited locations. To estimate design values for arbitrary locations, the observed or computed values for the weather stations were mapped and interpolated appropriately. Where possible, adjustments have been applied for the influence of elevation and known topographical effects. Such influences include the tendency of cold air to collect in depressions, for precipitation to increase with elevation, and for generally stronger winds near large bodies of water. Elevations have been added to the Table because of their potential to significantly influence climatic design values.
Since interpolation from the values in the Table to other locations may not be valid due to local and other effects, Environment Canada will provide climatic design element recommendations for locations not listed in the Table. Local effects are particularly significant in mountainous areas, where the values apply only to populated valleys and not to the mountain slopes and high passes, where very different conditions are known to exist.

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Changing and Variable Climates
Climate is not static. At any location, weather and climatic conditions vary from season to season, year to year, and over longer time periods (climate cycles). This has always been the case. change beginIn fact, evidence is mounting that the climates of Canada are changing and will continue to change significantly into the future.change end When estimating climatic design loads, this variability can be considered using appropriate statistical analysis, data records spanning sufficient periods, and meteorological judgement. The analysis generally assumes that the past climate will be representative of the future climate.
Past and ongoing modifications to atmospheric chemistry (from greenhouse gas emissions and land use changes) are expected to alter most climatic regimes in the future change begindespite the success of the most ambitious greenhouse gas mitigation plans.(10) Some regions could see an increase in the frequency and intensity of many weather extremes, which will accelerate weathering processes. Consequently, many buildings will need to be designed, maintained and operated to adequately withstand ever changing climatic loads.change end
change beginSimilar to global trends, the last decade in Canada was noted as the warmest in instrumented record. Canada has warmed, on average, at almost twice the rate of the global average increase, while the western Arctic is warming at a rate that is unprecedented over the past 400 years.(10) Mounting evidence from Arctic communities indicates that rapid changes to climate in the North have resulted in melting permafrost and impacts from other climate changes have affected nearly every type of built structure. Furthermore, analyses of Canadian precipitation data shows that many regions of the country have, on average, also been tending towards wetter conditions.(10) In the United States, where the density of climate monitoring stations is greater, a number of studies have found an unambiguous upward trend in the frequency of heavy to extreme precipitation events, with these increases coincident with a general upward trend in the total amount of precipitation. Climate change model results, based on an ensemble of global climate models worldwide, project that future climate warming rates will be greatest in higher latitude countries such as Canada.(11)change end
January Design Temperatures
A building and its heating system should be designed to maintain the inside temperature at some pre-determined level. To achieve this, it is necessary to know the most severe weather conditions under which the system will be expected to function satisfactorily. Failure to maintain the inside temperature at the pre-determined level will not usually be serious if the temperature drop is not great and if the duration is not long. The outside conditions change beginused for designchange end should, therefore, not be the most severe in many years, but should be the somewhat less severe conditions that are occasionally but not greatly exceeded.
The January design temperatures are based on an analysis of January air temperatures only. Wind and solar radiation also affect the inside temperature of most buildings and may need to be considered for energy-efficient design.
The January design temperature is defined as the lowest temperature at or below which only a certain small percentage of the hourly outside air temperatures in January occur. In the past, a total of 158 stations with records from all or part of the period 1951-66 formed the basis for calculation of the 2.5 and 1% January temperatures. Where necessary, the data were adjusted for consistency. Since most of the temperatures were observed at airports, design values for the core areas of large cities could be 1 or 2°C milder, although the values for the outlying areas are probably about the same as for the airports. No adjustments were made for this urban island heat effect. The design values for the next 20 to 30 years will probably differ from these tabulated values due to year-to-year climate variability and global climate change resulting from change beginthe impact ofchange end human activities on atmospheric chemistry.
The design temperatures were reviewed and updated using hourly temperature observations from change begin480change end stations for change begina 25-year period up to 2006 with at least 8 years of complete data. These data are consistent with data shown for Canadian locations in the 2009 Handbook of Fundamentals(12) published by the American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE). The most recent 25 years of record were used to provide a balance between accounting for trends in the climate and the sampling variation owing to year-to-year variation. The 1% and 2.5% values used for the design conditions represent percentiles of the cumulative frequency distribution of hourly temperatures and correspond to January temperatures that are colder for 8 and 19 hours, respectively, on average over the long term.change end
The 2.5% January design temperature is the value ordinarily used in the design of heating systems. In special cases, when the control of inside temperature is more critical, the 1% value may be used. Other temperature-dependent climatic design parameters may be considered for future issues of this document.
July Design Temperatures
A building and its cooling and dehumidifying system should be designed to maintain the inside temperature and humidity at certain pre-determined levels. To achieve this, it is necessary to know the most severe weather conditions under which the system is expected to function satisfactorily. Failure to maintain the inside temperature and humidity at the pre-determined levels will usually not be serious if the increases in temperature and humidity are not great and the duration is not long. The outside conditions used for design should, therefore, not be the most severe in many years, but should be the somewhat less severe conditions that are occasionally but not greatly exceeded.
The summer design temperatures in this Appendix are based on an analysis of July air temperatures and humidities. Wind and solar radiation also affect the inside temperature of most buildings and may, in some cases, be more important than the outside air temperature. More complete summer and winter design information can be obtained from Environment Canada.
change beginThe July design dry-bulb and wet-bulb temperatures were reviewed and updated using hourly temperature observations from 480 stations for a 25-year period up to 2006. These data are consistent with data shown for Canadian locations in the 2009 Handbook of Fundamentals(12) published by ASHRAE. As with January design temperatures, data from the most recent 25-year period were analyzed to reflect any recent climatic changes or variations. The 2.5% values used for the dry- and wet-bulb design conditions represent percentiles of the cumulative frequency distribution of hourly dry- and wet-bulb temperatures and correspond to July temperatures that are higher for 19 hours on average over the long term.change end
Heating Degree-Days
The rate of consumption of fuel or energy required to keep the interior of a small building at 21°C when the outside air temperature is below 18°C is roughly proportional to the difference between 18°C and the outside temperature. Wind speed, solar radiation, the extent to which the building is exposed to these elements and the internal heat sources also affect the heat required and may have to be considered for energy-efficient design. For average conditions of wind, radiation, exposure, and internal sources, however, the proportionality with the temperature difference generally still holds.
Since the fuel required is also proportional to the duration of the cold weather, a convenient method of combining these elements of temperature and time is to add the differences between 18°C and the mean temperature for every day in the year when the mean temperature is below 18°C. It is assumed that no heat is required when the mean outside air temperature for the day is 18°C or higher.
Although more sophisticated computer simulations using other forms of weather data have now almost completely replaced degree-day-based calculation methods for estimating annual heating energy consumption, degree-days remain a useful indicator of relative severity of climate and can form the basis for certain climate-related Code requirements.
change beginThe degree-days below 18°C were compiled for 1300 stations for the 25-year period ending in 2006. This analysis period is consistent with the one used to derive the design temperatures described above and with the approach used by ASHRAE.(12)change end
A difference of only one Celsius degree in the mean annual temperature will cause a difference of 250 to 350 in the Celsius degree-days. Since differences of 0.5 of a Celsius degree in the mean annual temperature are quite likely to occur between two stations in the same town, heating degree-days cannot be relied on to an accuracy of less than about 100 degree-days.
Heating degree-day values for the core areas of larger cities can be 200 to 400 degree-days less (warmer) than for the surrounding fringe areas. The observed degree-days, which are based on daily temperature observations, are often most representative of rural settings or the fringe areas of cities.
change beginClimatic Data for Energy Consumption Calculations
The climatic elements tabulated in this Appendix represent commonly used design values but do not include detailed climatic profiles, such as hourly weather data. Where hourly values of weather data are needed for the purpose of simulating the annual energy consumption of a building, they can be obtained from multiple sources, such as Environment Canada, Natural Resources Canada, the Regional Conservation Authority and other such public agencies that record this information. Hourly weather data are also available from public and private agencies that format this information for use with annual energy consumption simulation software; in some cases, these data have been incorporated into the software.change end
Snow Loads
The roof of a building should be able to support the greatest weight of snow that is likely to accumulate on it in many years. Some observations of snow on roofs have been made in Canada, but not enough to form the basis for estimating roof snow loads throughout the country. Similarly, observations of the weight, or water equivalent, of the snow on the ground have not been available in digital form in the past. The observations of roof loads and water equivalents are very useful, as noted below, but the measured depth of snow on the ground is used to provide the basic information for a consistent set of snow loads.
The estimation of the design snow load on a roof from snow depth observations involves the following steps:
  1. The depth of snow on the ground, which has an annual probability of exceedance of 1-in-50, is computed.
  2. The appropriate unit weight is selected and used to convert snow depth to loads, Ss.
  3. The load, Sr, which is due to rain falling on the snow, is computed.
  4. Because the accumulation of snow on roofs is often different from that on the ground, adjustments are applied to the ground snow load to provide a design snow load on a roof.
The annual maximum depth of snow on the ground has been assembled for 1618 stations for which data has been recorded by the Atmospheric Environment Service (AES). The period of record used varied from station to station, ranging from 7 to 38 years. These data were analyzed using a Gumbel extreme value distribution fitted using the method of moments(1) as reported by Newark et al.(2) The resulting values are the snow depths, which have a probability of 1-in-50 of being exceeded in any one year.
The unit weight of old snow generally ranges from 2 to 5 kN/m3, and it is usually assumed in Canada that 1 kN/m3 is the average for new snow. Average unit weights of the seasonal snow pack have been derived for different regions across the country(3) and an appropriate value has been assigned to each weather station. Typically, the values average 2.01 kN/m3 east of the continental divide (except for 2.94 kN/m3 north of the treeline), and range from 2.55 to 4.21 kN/m3 west of the divide. The product of the 1-in-50 snow depth and the average unit weight of the seasonal snow pack at a station is converted to the snow load (SL) in units of kilopascals (kPa).
Except for the mountainous areas of western Canada, the values of the ground snow load at AES stations were normalized assuming a linear variation of the load above sea level in order to account for the effects of topography. They were then smoothed using an uncertainty-weighted moving-area average in order to minimize the uncertainty due to snow depth sampling errors and site-specific variations. Interpolation from analyzed maps of the smooth normalized values yielded a value for each location in the Table, which could then be converted to the listed code values (Ss) by means of an equation in the form:
where b is the assumed rate of change of SL with elevation at the location and Z is the location’s elevation above mean sea level (MSL). Although they are listed in the Table of Design Data to the nearest tenth of a kilopascal, values of Ss typically have an uncertainty of about 20%. Areas of sparse data in northern Canada were an exception to this procedure. In these regions, an analysis was made of the basic SL values. The effects of topography, variations due to local climates, and smoothing were all subjectively assessed. The values derived in this fashion were used to modify those derived objectively.
For the mountainous areas of British Columbia, a more complex procedure was required to account for the variation of loads with terrain and elevation. Since the AES observational network often does not have sufficient coverage to detail this variability in mountainous areas, additional snow course observations were obtained from the provincial government of British Columbia. The additional data allowed detailed local analysis of ground snow loads on a valley-by-valley basis. Similar to other studies, the data indicated that snow loads above a critical or reference level increased according to either a linear or quadratic relation with elevation. The determination of whether the increase with elevation was linear or quadratic, the rate of the increase and the critical or reference elevation were found to be specific to the valley and mountain ranges considered. At valley levels below the critical elevation, the loads generally varied less significantly with elevation. Calculated valley- and range-specific regression relations were then used to describe the increase of load with elevation and to normalize the AES snow observations to a critical or reference level. These normalized values were smoothed using a weighted moving-average.
Tabulated values cannot be expected to indicate all the local differences in Ss. For this reason, especially in complex terrain areas, values should not be interpolated from the Table for unlisted locations. The values of Ss in the Table apply for the elevation and the latitude and longitude of the location, as defined by the Gazetteer of Canada. Values at other locations can be obtained from Environment Canada.
The heaviest loads frequently occur when the snow is wetted by rain, thus the rain load, Sr, was estimated to the nearest 0.1 kPa and is provided in the Table. When values of Sr are added to Ss, this provides a 1-in-50-year estimate of the combined ground snow and rain load. The values of Sr are based on an analysis of about 2100 weather station values of the 1-in-50-year one-day maximum rain amount. This return period is appropriate because the rain amounts correspond approximately to the joint frequency of occurrence of the one-day rain on maximum snow packs. For the purpose of estimating rain on snow, the individual observed one-day rain amounts were constrained to be less than or equal to the snow pack water equivalent, which was estimated by a snow pack accumulation model reported by Bruce and Clark.(4)
The results from surveys of snow loads on roofs indicate that average roof loads are generally less than loads on the ground. The conditions under which the design snow load on the roof may be taken as a percentage of the ground snow load are given in Subsection 4.1.6. of the Code. The Code also permits further decreases in design snow loads for steeply sloping roofs, but requires substantial increases for roofs where snow accumulation may be more rapid due to such factors as drifting. Recommended adjustments are given in the User’s Guide – NBC 2010, Structural Commentaries (Part 4 of Division B).

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Annual Total Precipitation
Total precipitation is the sum in millimetres of the measured depth of rainwater and the estimated or measured water equivalent of the snow (typically estimated as 0.1 of the measured depth of snow, since the average density of fresh snow is about 0.1 that of water).
The average annual total precipitation amounts in the Table have been interpolated from an analysis of precipitation observations from 1379 stations for the 30-year period from 1961 to 1990.
Annual Rainfall
The total amount of rain that normally falls in one year is frequently used as a general indication of the wetness of a climate, and is therefore included in this Appendix. See also Moisture Index below.
Rainfall Intensity
Roof drainage systems are designed to carry off rainwater from the most intense rainfall that is likely to occur. A certain amount of time is required for the rainwater to flow across and down the roof before it enters the gutter or drainage system. This results in the smoothing out of the most rapid changes in rainfall intensity. The drainage system, therefore, need only cope with the flow of rainwater produced by the average rainfall intensity over a period of a few minutes, which can be called the concentration time.
In Canada, it has been customary to use the 15-minute rainfall that will probably be exceeded on an average of once in 10 years. The concentration time for small roofs is much less than 15 minutes and hence the design intensity will be exceeded more frequently than once in 10 years. The safety factors in Book II (Plumbing Systems) of the British Columbia Building Code will probably reduce the frequency to a reasonable value and, in addition, the occasional failure of a roof drainage system will not be particularly serious in most cases.
change beginThe rainfall intensity values were updated for the 2012 edition of the Code using observations of annual maximum 15-minute rainfall amounts from 485 stations with 10 or more years of record, including data up to 2007 for some stations. Ten-year return period values—the 15-minute rainfall having a probability of 1-in-10 of being exceeded in any year— were calculated by fitting the annual maximum values to the Gumbel extreme value distribution(1) using the method of moments. The updated values are compiled from the most recent short-duration rainfall intensity-duration-frequency (IDF) graphs and tables available from Environment Canada.change end
It is very difficult to estimate the pattern of rainfall intensity in mountainous areas, where precipitation is extremely variable and rainfall intensity can be much greater than in other types of areas. Many of the observations for these areas were taken at locations in valley bottoms or in extensive, fairly level areas.

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One-Day Rainfall
If for any reason a roof drainage system becomes ineffective, the accumulation of rainwater may be great enough in some cases to cause a significant increase in the load on the roof. In previous editions of this information, it had been common practice to use the maximum one-day rainfall ever observed for estimating the additional load. Since the length of record for weather stations is quite variable, the maximum one-day rainfall amounts in previous editions often reflected the variable length of record at nearby stations as much as the climatology. As a result, the maximum values often differed greatly within relatively small areas where little difference should be expected. The current values have been standardized to represent the one-day rainfall amounts that have 1 chance in 50 of being exceeded in any one year or the 1-in-50-year return value one-day rainfalls.
The one-day rainfall values were change beginupdated using daily rainfall observations from more than 3500 stations with 10 years or more of record, including data up to 2008 for some stations. The 50-year return period values were calculated by fitting the annual maximum one-day rainfall observations to the Gumbel extreme value distributionchange end using the method of moments.(1)
Rainfall frequency observations can vary considerably over time and space. This is especially true for mountainous areas, where elevation effects can be significant. In other areas, small-scale intense storms or local influences can produce significant spatial variability in the data. As a result, the analysis incorporates some spatial smoothing.

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Moisture Index (MI)
Moisture index (MI) values were developed through the work of a consortium that included representatives from industry and researchers from the Institute for Research in Construction at NRC.10 The MI is an indicator of the moisture load imposed on a building by the climate and is used in Part 9 to define the minimum levels of protection from precipitation to be provided by cladding assemblies on exterior walls.
It must be noted, in using MI values to determine the appropriate levels of protection from precipitation, that weather conditions can vary markedly within a relatively small geographical area. Although the values provided in the Table give a good indication of the average conditions within a particular region, some caution must be exercised when applying them to a locality that is outside the region where the weather station is located.
MI is calculated from a wetting index (WI) and a drying index (DI).
Wetting Index (WI)
To define, quantitatively, the rainwater load on a wall, wind speed and wind direction have to be taken into consideration in addition to rainfall, along with factors that can affect exposure, such as nearby buildings, vegetation and topography. Quantitative determination of load, including wind speed and wind direction, can be done. However, due to limited weather data, it is not currently possible to provide this information for most of the locations identified in the Table.
This lack of information, however, has been shown to be non-critical for the purpose of classifying locations in terms of severity of rain load. The results of the research indicated that simple annual rainfall is as good an indicator as any for describing rainwater load. That is to say, for Canadian locations, and especially once drying is accounted for, the additional sensitivity provided by hourly directional rainfall values does not have a significant effect on the order in which locations appear when listed from wet to dry.
Consequently, the wetting index (WI) is based on annual rainfall and is normalized based on 1000 mm.
Drying Index (DI)
Temperature and relative humidity together define the drying capacity of ambient air. Based on simple psychrometrics, values were derived for the locations listed in the Table using annual average drying capacity normalized based on the drying capacity at Lytton, B.C. The resultant values are referred to as drying indices (DI).
Determination of Moisture Index (MI)
The relationship between WI and DI to correctly define moisture loading on a wall is not known. The MI values provided in the Table are based on the root mean square values of WI and 1-DI, with those values equally weighted. This is illustrated in Figure C-1. The resultant MI values are sufficiently consistent with industry’s understanding of climate severity with respect to moisture loading as to allow limits to be identified for the purpose of specifying where additional protection from precipitation is required.
Figure C-A-A
Derivation of moisture index (MI) based on normalized values for wetting index (WI) and drying index (DI)
Notes to Figure C-A-A:

(1)
MI equals the hypotenuse of the triangle defined by WIN and 1-DIN
Driving Rain Wind Pressure (DRWP)
The presence of rainwater on the face of a building, with or without wind, must be addressed in the design and construction of the building envelope so as to minimize the entry of water into the assembly. Wind pressure on the windward faces of a building will promote the flow of water through any open joints or cracks in the facade.
Driving rain wind pressure (DRWP) is the wind load that is coincident with rain, measured or calculated at a height of 10 m. The values provided in the Table represent the loads for which there is 1 chance in 5 of being reached or exceeded in any one year, or a probability of 20% within any one year. Approximate adjustments for height can be made using the values for Ce given in Sentence 4.1.7.1.(5) as a multiplier.
Because of inaccuracies in developing the DRWP values related to the averaging of extreme wind pressures, the actual heights of recording anemometers, and the use of estimated rather than measured rainfall values, the values are considered to be higher than actual loads(9) Thus the actual probability of reaching or exceeding the DRWP in a particular location is less than 20% per year and these values can be considered to be conservative.
DRWP can be used to determine the height to which wind will drive rainwater up enclosed vertical conduits. This provides a conservative estimate of the height needed for fins in window extrusions and end dams on flashings to control water ingress. This height can be calculated as:
Note that the pressure difference across the building envelope may be augmented by internal pressures induced in the building interior by the wind. These additional pressures can be estimated using the information provided in the Commentary entitled Wind Load and Effects of the User’s Guide – NBC 2010, Structural Commentaries (Part 4 of Division B).
Wind Effects
All structures need to be designed to ensure that the main structural system and all secondary components, such as cladding and appurtenances, will withstand the pressures and suctions caused by the strongest wind likely to blow at that location in many years. Some flexible structures, such as tall buildings, slender towers and bridges, also need to be designed to minimize excessive wind-induced oscillations or vibrations.
At any time, the wind acting upon a structure can be treated as a mean or time-averaged component and as a gust or unsteady component. For a small structure, which is completely enveloped by wind gusts, it is only the peak gust velocity that needs to be considered. For a large structure, the wind gusts are not well correlated over its different parts and the effects of individual gusts become less significant. The User’s Guide – NBC 2010, Structural Commentaries (Part 4 of Division B) evaluates the mean pressure acting on a structure, provide appropriate adjustments for building height and exposure and for the influence of the surrounding terrain and topography (including wind speed-up for hills), and then incorporate the effects of wind gusts by means of the gust factor, which varies according to the type of structure and the size of the area over which the pressure acts.
The wind speeds and corresponding velocity pressures used in the Code are regionally representative or reference values. The reference wind speeds are nominal one-hour averages of wind speeds representative of the 10 m height in flat open terrain corresponding to Exposure A or open terrain in the terminology of the User’s Guide – NBC 2010, Structural Commentaries (Part 4 of Division B). The reference wind speeds and wind velocity pressures are based on long-term wind records observed at a large number of weather stations across Canada.
change beginReference wind velocity pressures in previous versions of the Code since 1961 were based mostly on records of hourly averaged wind speeds (i.e. the number of miles of wind passing an anemometer in an hour) from over 100 stations with 10 to 22 years of observations ending in the 1950s. The wind pressure values derived from these measurements represented true hourly wind pressures.change end
change beginThe reference wind velocity pressures were reviewed and updated for the 2012 edition of the Code. The primary data set used for the analysis comprised wind records compiled from about 135 stations with hourly averaged wind speeds and from 465 stations with aviation (one- or two-minute average) speeds or surface weather (ten-minute average) speeds observed once per hour at the top of the hour; the periods of record used ranged from 10 to 54 years. In addition, peak wind gust records from 400 stations with periods of record ranging from 10 to 43 years were used. Peak wind gusts (gust durations of approximately 3 to 7 seconds) were used to supplement the primary once-per-hour observations in the analysis.change end
change beginSeveral steps were involved in updating the reference wind values. Where needed, speeds were adjusted to represent the standard anemometer height above ground of 10 m. The data from years when the anemometer at a station was installed on the top of a lighthouse or building were eliminated from the analysis since it is impractical to adjust for the effects of wind flow over the structure. (Most anemometers were moved to 10 m towers by the 1960s.) Wind speeds of the various observation types—hourly averaged, aviation, surface weather and peak wind gust—were adjusted to account for different measure durations to represent a one-hour averaging period and to account for differences in the surface roughness of flat open terrain at observing stations.change end
change beginThe annual maximum wind speed data was fitted to the Gumbel distribution using the method of moments(1) to calculate hourly wind speeds having the annual probability of occurrence of 1-in-10 and 1-in-50 (10-year and 50-year return periods). The values were plotted on maps, then analyzed and abstracted for the locations in Table C-2.change end
The wind velocity pressures, q, were calculated in Pascals using the following equation:
where ρ is an average air density for the windy months of the year and V is wind speed in metres per second. While air density depends on both air temperature and atmospheric pressure, the density of dry air at 0°C and standard atmospheric pressure of 1.2929 kg/m3 was used as an average value for the wind pressure calculations. As explained by Boyd(6), this value is within 10% of the monthly average air densities for most of Canada in the windy part of the year.
change beginAs a result of the updating procedure, the 1-in-50 reference wind velocity pressures remain unchanged for most of the locations listed in Table C-2; both increases and decreases were noted for the remaining locations. Many of the decreases resulted from the fact that anemometers at most of the stations used in the previous analysis were installed on lighthouses, airport hangers and other structures. Wind speeds on the tops of buildings are often much higher compared to those registered by a standard 10 m tower. Eliminating anemometer data recorded on the tops of buildings from the analysis resulted in lower values at several locations.change end
Hourly wind speeds that have 1 chance in 10 and 50* of being exceeded in any one year were analyzed using the Gumbel extreme value distribution fitted using the method of moments with correction for sample size. Values of the 1-in-30-year wind speeds for locations in the Table were estimated from a mapping analysis of wind speeds. The 1-in-10- and 1-in-50-year speeds were then computed from the 1-in-30-year speeds using a map of the dispersion parameter that occurs in the Gumbel analysis.(1)

* Wind speeds that have a one-in-”n”-year chance of being exceeded in any year can be computed from the one-in-10 and one-in-50 return values in the Table using the following equation:
Table C-1. has been arranged to give pressures to the nearest one-hundredth of a kPa and their corresponding wind speeds. The value of “q” in kPa is assumed to be equal to 0.00064645 V2, where V is given in m/s.

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Table C-1
Wind Speeds
Forming part of Appendix C
q V   q V   q V   q V
kPa m/s   kPa m/s   kPa m/s   kPa m/s
0.15 15.2   0.53 28.6   0.91 37.5   1.29 44.7
0.16 15.7   0.54 28.9   0.92 37.7   1.30 44.8
0.17 16.2   0.55 29.2   0.93 37.9   1.31 45.0
0.18 16.7   0.56 29.4   0.94 38.1   1.32 45.2
0.19 17.1   0.57 29.7   0.95 38.3   1.33 45.4
0.20 17.6   0.58 30.0   0.96 38.5   1.34 45.5
0.21 18.0   0.59 30.2   0.97 38.7   1.35 45.7
0.22 18.4   0.60 30.5   0.98 38.9   1.36 45.9
0.23 18.9   0.61 30.7   0.99 39.1   1.37 46.0
0.24 19.3   0.62 31.0   1.00 39.3   1.38 46.2
0.25 19.7   0.63 31.2   1.01 39.5   1.39 46.4
0.26 20.1   0.64 31.5   1.02 39.7   1.40 46.5
0.27 20.4   0.65 31.7   1.03 39.9   1.41 46.7
0.28 20.8   0.66 32.0   1.04 40.1   1.42 46.9
0.29 21.2   0.67 32.2   1.05 40.3   1.43 47.0
0.30 21.5   0.68 32.4   1.06 40.5   1.44 47.2
0.31 21.9   0.69 32.7   1.07 40.7   1.45 47.4
0.32 22.2   0.70 32.9   1.08 40.9   1.46 47.5
0.33 22.6   0.71 33.1   1.09 41.1   1.47 47.7
0.34 22.9   0.72 33.4   1.10 41.3   1.48 47.8
0.35 23.3   0.73 33.6   1.11 41.4   1.49 48.0
0.36 23.6   0.74 33.8   1.12 41.6   1.50 48.2
0.37 23.9   0.75 34.1   1.13 41.8   1.51 48.3
0.38 24.2   0.76 34.3   1.14 42.0   1.52 48.5
0.39 24.6   0.77 34.5   1.15 42.2   1.53 48.6
0.40 24.9   0.78 34.7   1.16 42.4   1.54 48.8
0.41 25.2   0.79 35.0   1.17 42.5   1.55 49.0
0.42 25.5   0.80 35.2   1.18 42.7   1.56 49.1
0.43 25.8   0.81 35.4   1.19 42.9   1.57 49.3
0.44 26.1   0.82 35.6   1.20 43.1   1.58 49.4
0.45 26.4   0.83 35.8   1.21 43.3   1.59 49.6
0.46 26.7   0.84 36.0   1.22 43.4   1.60 49.7
0.47 27.0   0.85 36.3   1.23 43.6   1.61 49.9
0.48 27.2   0.86 36.5   1.24 43.8   1.62 50.1
0.49 27.5   0.87 36.7   1.25 44.0   1.63 50.2
0.50 27.8   0.88 36.9   1.26 44.1   1.64 50.4
0.51 28.1   0.89 37.1   1.27 44.3   1.65 50.5
0.52 28.4   0.90 37.3   1.28 44.5   1.66 50.7
Seismic Hazard
The parameters used to represent seismic hazard for specific geographical locations are the 5%-damped horizontal spectral acceleration values for 0.2, 0.5, 1.0, and 2.0 second periods and the horizontal Peak Ground Acceleration (PGA) value that have a 2% probability of being exceeded in 50 years. The four spectral parameters are deemed sufficient to define spectra closely matching the shape of the Uniform Hazard Spectra (UHS). Hazard values are 50th percentile (median) values based on a statistical analysis of the earthquakes that have been experienced in Canada and adjacent regions.(13)(14)(15)(16) The median was chosen over the mean because the mean is affected by the amount of epistemic uncertainty incorporated into the analysis. It is the view of the Geological Survey of Canada and the members of the change beginStanding Committee on Earthquake Designchange end that the estimation of the epistemic uncertainty is still too incomplete to adopt into the Code.
change beginThe seismic hazard values were updated for the 2012 edition of the Code by replacing the quadratic fit that generated the 2006 British Columbia Building Code values with a newly developed 8-parameter fit to the ground motion relations used for earthquakes in eastern, central and north-eastern Canada. In 2005, it was recognized that, while the quadratic fit provided a good approximation in the high-hazard zones, it was rather conservative at short periods, but not at long periods, for the low-hazard zones; however, as the design values are small in the low-hazard zones, the approximation was accepted. The 8-parameter fit gives a good fit across all zones. In general, PGA and short-period spectral values are reduced, while long-period values are increased. The 2012 values have the following engineering implications: geotechnical design levels (based on PGA values) are reduced, the design forces for short-period buildings are reduced, and the design forces for tall buildings are increased. Since zones of low seismicity cover a large part of the country, the seismic information for about 550 of the 650 localities listed in Table C-2 has changed (often in a minor way); only some western localities are unaffected.change end
Further details regarding the representation of seismic hazard can be found in the Commentary on Design for Seismic Effects in the User’s Guide – NBC 2010, Structural Commentaries (Part 4 of Division B).
References
Lowery, M.D. and Nash, J.E., A comparison of methods of fitting the double exponential distribution. J. of Hydrology, 10 (3), pp. 259–275, 1970.
Newark, M.J., Welsh, L.E., Morris, R.J. and Dnes, W.V. Revised Ground Snow Loads for the 1990 NBC of Canada. Can. J. Civ. Eng., Vol. 16, No. 3, June 1989.
Newark, M.J. A New Look at Ground Snow Loads in Canada. Proceedings, 41st Eastern Snow Conference, Washington, D.C., Vol. 29, pp. 59-63, 1984.
Bruce, J.P. and Clark, R.H. Introduction to Hydrometeorology. Pergammon Press, London, 1966.
Yip, T.C. and Auld, H. Updating the 1995 National Building Code of Canada Wind Pressures. Proceedings, Electricity '93 Engineering and Operating Conference, Montreal, paper 93-TR-148.
Boyd, D.W. Variations in Air Density over Canada. National Research Council of Canada, Division of Building Research, Technical Note No. 486, June 1967.
Basham, P.W. et al. New Probabilistic Strong Seismic Ground Motion Source Maps of Canada: a Compilation of Earthquake Source Zones, Methods and Results. Earth Physics Branch Open File Report 82-33, p. 205, 1982.
Skerlj, P.F. and Surry, D. A Critical Assessment of the DRWPs Used in CAN/CSA-A440-M90. Tenth International Conference on Wind Engineering, Wind Engineering into the 21st Century, Larsen, Larose & Livesay (eds), 1999 Balkema, Rotterdam, ISBN 90 5809 059 0.
Cornick, S., Chown, G.A., et al. Committee Paper on Defining Climate Regions as a Basis for Specifying Requirements for Precipitation Protection for Walls. Institute for Research in Construction, National Research Council, Ottawa, April 2001.
Environment Canada, Climate Trends and Variation Bulletin: Annual 2007, 2008.
Intergovernmental Panel on Climate Change (IPCC), Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. S. Solomon, D. Qin, M. Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor and H.L. Miller (Eds.). Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 996 pp., 2007.
American Society of Heating, Refrigerating, and Air-conditioning Engineers, Handbook of Fundamentals, Chapter 14 – Climatic Design Information, Atlanta, GA, 2009.
Adams, J. and Halchuk, S. Fourth generation seismic hazard maps of Canada: Values for Canadian localities in the 2010 National Building Code of Canada. Geological Survey of Canada Open File, 2009.
Halchuk, S. and Adams, J. Fourth generation seismic hazard maps of Canada: Maps and grid values to be used with the 2010 National Building Code of Canada. Geological Survey of Canada Open File, 2009.
Adams, J. and Atkinson, G.M. Development of Seismic Hazard Maps for the 2005 National Building Code of Canada. Canadian Journal of Civil Engineering 2003; 30: 255-271.
Heidebrecht, A.C. Overview of seismic provisions of the proposed 2005 edition of the National Building Code of Canada. Canadian Journal of Civil Engineering 2003; 30: 241-254.

contentHistory

Table C-2
Design Data for Selected Locations in Canada
Forming part of Appendix C
Location Elev., m Design Temperature Degree-Days Below 18°C 15 Min. Rain, mm One Day Rain, 1/50, mm Ann. Rain, mm Moist. Index Ann. Tot. Ppn., mm Driving Rain Wind Pressures, Pa, 1/5 Snow Load, kPa, 1/50 Hourly Wind Pressures, kPa

Seismic Data(1)

January July 2.5%
2.5% °C 1% °C Dry °C Wet °C

Ss

Sr

1/10 1/50

Sa(0.2)

Sa(0.5)

Sa(1.0)

Sa(2.0)

PGA
100 Mile House 1040 -30 -32 29 17 5030 10 48 300 0.44 425 60 2.6 0.3 0.27 0.35 0.28 0.17 0.099 0.058 0.14
Abbotsford 70 -8 -10 29 20 2860 12 112 1525 1.59 1600 160 2.0 0.3 0.34 0.44 0.99 0.66 0.32 0.17 0.49
Agassiz 15 -9 -11 31 21 2750 8 128 1650 1.71 1700 160 2.4 0.7 0.36 0.47 0.67 0.50 0.29 0.16 0.32
Alberni 12 -5 -8 31 19 3100 10 144 1900 2.00 2000 220 3.0 0.4 0.25 0.32 0.75 0.55 0.30 0.16 0.35
Ashcroft 305 -24 -27 34 20 3700 10 37 250 0.25 300 80 1.7 0.1 0.29 0.38 0.33 0.26 0.16 0.093 0.16
Bamfield 20 -2 -4 23 17 3080 13 170 2870 2.96 2890 280 1.0 0.4 0.39 0.50 1.1 0.89 0.45 0.20 0.49
Beatton River 840 -37 -39 26 18 6300 15 64 330 0.53 450 80 3.3 0.1 0.23 0.30 0.095 0.057 0.026 0.014 0.036
Bella Bella 25 -5 -7 23 18 3180 13 145 2715 2.82 2800 350 2.6 0.8 0.39 0.50 0.38 0.25 0.14 0.081 0.18
Bella Coola 40 -14 -18 27 19 3560 10 140 1500 1.85 1700 350 5.5 0.8 0.30 0.39 0.38 0.24 0.13 0.075 0.18
Burns Lake 755 -31 -34 26 17 5450 12 54 300 0.56 450 100 3.4 0.2 0.30 0.39 0.095 0.062 0.043 0.028 0.046
Cache Creek 455 -24 -27 34 20 3700 10 37 250 0.25 300 80 1.7 0.2 0.30 0.39 0.33 0.25 0.16 0.091 0.16
Campbell River 20 -5 -7 26 18 3000 10 116 1500 1.59 1600 260 3.3 0.4 0.40 0.52 0.63 0.46 0.28 0.15 0.28
Carmi 845 -24 -26 31 19 4750 10 64 325 0.38 550 60 3.9 0.2 0.29 0.38 0.28 0.17 0.090 0.053 0.14
Castlegar 430 -18 -20 32 20 3580 10 54 560 0.64 700 60 4.2 0.1 0.27 0.34 0.27 0.16 0.081 0.045 0.14
Chetwynd 605 -35 -38 27 18 5500 15 70 400 0.58 625 60 2.4 0.2 0.31 0.40 0.24 0.14 0.064 0.035 0.12
Chilliwack 10 -9 -11 30 20 2780 8 139 1625 1.68 1700 160 2.2 0.3 0.36 0.47 0.76 0.52 0.30 0.16 0.36
Comox 15 -7 -9 27 18 3100 10 106 1175 1.28 1200 260 2.6 0.4 0.40 0.52 0.66 0.49 0.29 0.16 0.30
Courtenay 10 -7 -9 28 18 3100 10 106 1400 1.49 1450 260 2.6 0.4 0.40 0.52 0.65 0.48 0.28 0.16 0.30
Cranbrook 910 -26 -28 32 18 4400 12 59 275 0.30 400 100 3.0 0.2 0.25 0.33 0.27 0.16 0.080 0.045 0.14
Crescent Valley 585 -18 -20 31 20 3650 10 54 675 0.75 850 80 4.2 0.1 0.25 0.33 0.27 0.16 0.081 0.045 0.14
Crofton 5 -4 -6 28 19 2880 8 86 925 1.06 950 160 1.8 0.2 0.31 0.40 1.1 0.74 0.37 0.18 0.54
Dawson Creek 665 -38 -40 27 18 5900 18 75 325 0.49 475 100 2.5 0.2 0.31 0.40 0.11 0.070 0.035 0.021 0.063
Dease Lake 800 -37 -40 24 15 6730 10 45 265 0.55 425 380 2.6 0.1 0.23 0.30 0.095 0.063 0.048 0.032 0.046
Dog Creek 450 -28 -30 29 17 4800 10 48 275 0.41 375 100 1.8 0.2 0.27 0.35 0.32 0.25 0.15 0.088 0.16
Duncan 10 -6 -8 28 19 2980 8 103 1000 1.13 1050 180 1.8 0.4 0.30 0.39 1.1 0.74 0.37 0.18 0.54
Elko 1065 -28 -31 30 19 4600 13 64 440 0.48 650 100 3.6 0.2 0.31 0.40 0.27 0.16 0.080 0.045 0.14
Fernie 1010 -27 -30 30 19 4750 13 118 860 0.88 1175 100 4.5 0.2 0.31 0.40 0.27 0.16 0.078 0.044 0.14
Fort Nelson 465 -39 -42 28 18 6710 15 70 325 0.56 450 80 2.4 0.1 0.23 0.30 0.095 0.057 0.034 0.022 0.040
Fort St. John 685 -35 -37 26 18 5750 15 72 320 0.50 475 100 2.8 0.1 0.30 0.39 0.096 0.061 0.032 0.019 0.054
Glacier 1145 -27 -30 27 17 5800 10 70 625 0.83 1500 80 9.4 0.2 0.25 0.32 0.27 0.16 0.078 0.044 0.13
Gold River 120 -8 -11 31 18 3230 13 200 2730 2.80 2850 250 2.6 0.6 0.25 0.32 0.80 0.64 0.33 0.15 0.35
Golden 790 -27 -30 30 17 4750 10 55 325 0.57 500 100 3.7 0.2 0.27 0.35 0.26 0.15 0.075 0.041 0.13
Grand Forks 565 -19 -22 34 20 3820 10 48 390 0.47 475 80 2.8 0.1 0.31 0.40 0.27 0.17 0.083 0.047 0.14
Greenwood 745 -20 -23 34 20 4100 10 64 430 0.51 550 80 4.0 0.1 0.31 0.40 0.27 0.17 0.085 0.049 0.14
Hope 40 -13 -15 31 20 3000 8 139 1825 1.88 1900 140 2.8 0.7 0.48 0.63 0.63 0.47 0.28 0.15 0.29
Jordan River 20 -1 -3 22 17 2900 12 170 2300 2.37 2370 250 1.2 0.4 0.43 0.55 0.99 0.78 0.40 0.17 0.47
Kamloops 355 -23 -25 34 20 3450 13 42 225 0.23 275 80 1.8 0.2 0.31 0.40 0.28 0.17 0.10 0.061 0.14
Kaslo 545 -17 -20 30 19 3830 10 55 660 0.82 850 80 2.8 0.1 0.24 0.31 0.27 0.16 0.080 0.045 0.14
Kelowna 350 -17 -20 33 20 3400 12 43 260 0.29 325 80 1.7 0.1 0.31 0.40 0.28 0.17 0.094 0.056 0.14
Kimberley 1090 -25 -27 31 18 4650 12 59 350 0.38 500 100 3.0 0.2 0.25 0.33 0.27 0.16 0.079 0.044 0.14
Kitimat Plant 15 -16 -18 25 16 3750 13 193 2100 2.19 2500 220 5.5 0.8 0.37 0.48 0.37 0.24 0.13 0.073 0.18
Kitimat Townsite 130 -16 -18 24 16 3900 13 171 1900 2.00 2300 220 6.5 0.8 0.37 0.48 0.37 0.24 0.13 0.073 0.18
Ladysmith 80 -7 -9 27 19 3000 8 97 1075 1.20 1160 180 2.4 0.4 0.31 0.40 1.1 0.72 0.36 0.18 0.53
Langford 80 -4 -6 27 19 2750 9 135 1095 1.22 1125 220 1.8 0.3 0.31 0.40 1.2 0.79 0.37 0.18 0.58
Lillooet 245 -21 -23 34 20 3400 10 70 300 0.31 350 100 2.1 0.1 0.34 0.44 0.60 0.44 0.26 0.14 0.27
Lytton 325 -17 -20 35 20 3300 10 70 330 0.33 425 80 2.8 0.3 0.33 0.43 0.60 0.44 0.26 0.14 0.27
Mackenzie 765 -34 -38 27 17 5550 10 50 350 0.54 650 60 5.1 0.2 0.25 0.32 0.23 0.13 0.061 0.034 0.12
Masset 10 -5 -7 17 15 3700 13 80 1350 1.54 1400 400 1.8 0.4 0.48 0.61 0.53 0.39 0.30 0.16 0.26
McBride 730 -29 -32 29 18 4980 13 54 475 0.64 650 60 4.3 0.2 0.27 0.35 0.27 0.16 0.076 0.042 0.14
McLeod Lake 695 -35 -37 27 17 5450 10 50 350 0.54 650 60 4.1 0.2 0.25 0.32 0.18 0.10 0.051 0.029 0.095
Merritt 570 -24 -27 34 20 3900 8 54 240 0.24 310 80 1.8 0.3 0.34 0.44 0.34 0.26 0.16 0.094 0.17
Mission City 45 -9 -11 30 20 2850 13 123 1650 1.71 1700 160 2.4 0.3 0.33 0.43 0.93 0.63 0.31 0.17 0.46
Montrose 615 -16 -18 32 20 3600 10 54 480 0.56 700 60 4.1 0.1 0.27 0.35 0.27 0.16 0.081 0.045 0.14
Nakusp 445 -20 -22 31 20 3560 10 60 650 0.78 850 60 4.4 0.1 0.25 0.33 0.27 0.16 0.080 0.045 0.14
Nanaimo 15 -6 -8 27 19 3000 10 91 1000 1.13 1050 200 2.3 0.4 0.39 0.50 1.0 0.69 0.35 0.18 0.50
Nelson 600 -18 -20 31 20 3500 10 59 460 0.57 700 60 4.2 0.1 0.25 0.33 0.27 0.16 0.080 0.045 0.14
Ocean Falls 10 -10 -12 23 17 3400 13 260 4150 4.21 4300 350 3.9 0.8 0.46 0.59 0.38 0.25 0.14 0.078 0.18
Osoyoos 285 -14 -17 35 21 3100 10 48 275 0.28 310 60 1.1 0.1 0.31 0.40 0.29 0.19 0.12 0.071 0.14
Parksville 40 -6 -8 26 19 3200 10 91 1200 1.31 1250 200 2.4 0.4 0.39 0.50 0.86 0.61 0.32 0.17 0.42
Penticton 350 -15 -17 33 20 3350 10 48 275 0.28 300 60 1.3 0.1 0.35 0.45 0.28 0.18 0.11 0.065 0.14
Port Alberni 15 -5 -8 31 19 3100 10 161 1900 2.00 2000 240 3.0 0.4 0.25 0.32 0.76 0.57 0.30 0.16 0.36
Port Alice 25 -3 -6 26 17 3010 13 200 3300 3.38 3340 220 1.1 0.4 0.25 0.32 0.65 0.43 0.24 0.14 0.28
Port Hardy 5 -5 -7 20 16 3440 13 150 1775 1.92 1850 220 0.9 0.4 0.40 0.52 0.43 0.31 0.17 0.10 0.20
Port McNeill 5 -5 -7 22 17 3410 13 128 1750 1.89 1850 260 1.1 0.4 0.40 0.52 0.43 0.36 0.19 0.10 0.20
Port Renfrew 20 -3 -5 24 17 2900 13 200 3600 3.64 3675 270 1.1 0.4 0.40 0.52 1.0 0.81 0.41 0.18 0.45
Powell River 10 -7 -9 26 18 3100 10 80 1150 1.27 1200 220 1.9 0.4 0.39 0.51 0.67 0.49 0.29 0.16 0.31
Prince George 580 -32 -36 28 18 4720 15 54 425 0.58 600 80 3.4 0.2 0.29 0.37 0.13 0.079 0.040 0.026 0.070
Prince Rupert 20 -13 -15 19 15 3900 13 160 2750 2.84 2900 240 1.9 0.4 0.42 0.54 0.38 0.25 0.15 0.086 0.18
Princeton 655 -24 -29 33 19 4250 10 43 235 0.35 350 80 2.9 0.6 0.28 0.36 0.42 0.31 0.19 0.11 0.20
Qualicum Beach 10 -7 -9 27 19 3200 10 96 1200 1.31 1250 200 2.2 0.4 0.41 0.53 0.82 0.58 0.31 0.17 0.39
Queen Charlotte City 35 -6 -8 21 16 3520 13 110 1300 1.47 1350 360 1.8 0.4 0.48 0.61 0.62 0.57 0.46 0.24 0.33
Quesnel 475 -31 -33 30 17 4650 10 50 380 0.51 525 80 3.0 0.1 0.24 0.31 0.27 0.16 0.075 0.041 0.13
Revelstoke 440 -20 -23 31 19 4000 13 55 625 0.80 950 80 7.2 0.1 0.25 0.32 0.27 0.16 0.080 0.045 0.14
Salmon Arm 425 -19 -24 33 21 3650 13 48 400 0.47 525 80 3.5 0.1 0.30 0.39 0.27 0.16 0.082 0.046 0.14
Sandspit 5 -4 -6 18 15 3450 13 86 1300 1.47 1350 500 1.8 0.4 0.60 0.78 0.56 0.48 0.40 0.20 0.29
Sechelt 25 -6 -8 27 20 2680 10 75 1140 1.27 1200 160 2.2 0.4 0.37 0.48 0.87 0.61 0.33 0.17 0.43
Sidney 10 -4 -6 26 18 2850 8 96 825 0.97 850 160 1.1 0.2 0.33 0.42 1.2 0.80 0.37 0.19 0.60
Smith River 660 -45 -47 26 17 7100 10 64 300 0.58 500 40 2.8 0.1 0.23 0.30 0.51 0.31 0.15 0.086 0.25
Smithers 500 -29 -31 26 17 5040 13 60 325 0.60 500 120 3.2 0.2 0.31 0.40 0.11 0.080 0.053 0.034 0.059
Sooke 20 -1 -3 21 16 2900 9 130 1250 1.37 1280 220 1.3 0.3 0.37 0.48 1.1 0.75 0.36 0.18 0.53
Squamish 5 -9 -11 29 20 2950 10 140 2050 2.12 2200 160 3.2 0.7 0.39 0.50 0.72 0.52 0.30 0.16 0.33
Stewart 10 -17 -20 25 16 4350 13 135 1300 1.47 1900 180 7.9 0.8 0.28 0.36 0.30 0.19 0.11 0.063 0.15
Tahsis 25 -4 -6 26 18 3150 13 200 3845 3.91 3900 300 1.1 0.4 0.26 0.34 0.87 0.69 0.36 0.16 0.38
Taylor 515 -35 -37 26 18 5720 15 72 320 0.49 450 100 2.3 0.1 0.31 0.40 0.095 0.060 0.031 0.018 0.053
Terrace 60 -19 -21 27 17 4150 13 120 950 1.08 1150 200 5.4 0.6 0.28 0.36 0.34 0.21 0.11 0.065 0.16
Tofino 10 -2 -4 20 16 3150 13 193 3275 3.36 3300 300 1.1 0.4 0.53 0.68 1.2 0.94 0.48 0.21 0.52
Trail 440 -14 -17 33 20 3600 10 54 580 0.65 700 60 4.1 0.1 0.27 0.35 0.27 0.16 0.081 0.045 0.14
Ucluelet 5 -2 -4 18 16 3120 13 180 3175 3.26 3200 280 1.0 0.4 0.53 0.68 1.2 0.94 0.48 0.21 0.53
Vancouver Region                                          
Burnaby (Simon Fraser Univ.) 330 -7 -9 25 17 3100 10 150 1850 1.93 1950 160 2.9 0.7 0.36 0.47 0.93 0.63 0.32 0.17 0.46
Cloverdale 10 -8 -10 29 20 2700 10 112 1350 1.44 1400 160 2.5 0.2 0.34 0.44 1.1 0.72 0.33 0.17 0.54
Haney 10 -9 -11 30 20 2840 10 134 1800 1.86 1950 160 2.4 0.2 0.34 0.44 0.97 0.65 0.32 0.17 0.48
Ladner 3 -6 -8 27 19 2600 10 80 1000 1.14 1050 160 1.3 0.2 0.36 0.46 1.1 0.73 0.35 0.18 0.54
Langley 15 -8 -10 29 20 2700 10 112 1450 1.53 1500 160 2.4 0.2 0.34 0.44 1.1 0.71 0.33 0.17 0.53
New Westminster 10 -8 -10 29 19 2800 10 134 1500 1.59 1575 160 2.3 0.2 0.34 0.44 0.99 0.66 0.33 0.17 0.49
North Vancouver 135 -7 -9 26 19 2910 12 150 2000 2.07 2100 160 3.0 0.3 0.35 0.45 0.88 0.61 0.33 0.17 0.44
Richmond 5 -7 -9 27 19 2800 10 86 1070 1.20 1100 160 1.5 0.2 0.35 0.45 1.0 0.68 0.34 0.18 0.50
Surrey (88 Ave & 156 St.) 90 -8 -10 29 20 2750 10 128 1500 1.58 1575 160 2.4 0.3 0.34 0.44 1.0 0.69 0.33 0.17 0.52
Vancouver
(City Hall)
40 -7 -9 28 20 2825 10 112 1325 1.44 1400 160 1.8 0.2 0.35 0.45 0.94 0.64 0.33 0.17 0.46
Vancouver
(Granville & 41 Ave)
120 -6 -8 28 20 2925 10 107 1325 1.44 1400 160 1.9 0.3 0.35 0.45 0.95 0.65 0.34 0.17 0.47
West Vancouver 45 -7 -9 28 19 2950 12 150 1600 1.69 1700 160 2.4 0.2 0.37 0.48 0.88 0.62 0.33 0.17 0.43
Vernon 405 -20 -23 33 20 3600 13 43 350 0.41 400 80 2.2 0.1 0.31 0.40 0.27 0.17 0.083 0.047 0.14
Victoria Region                                          
Victoria
(Gonzales Hts)
65 -4 -6 24 17 2700 9 91 600 0.82 625 220 1.5 0.3 0.44 0.57 1.2 0.82 0.38 0.19 0.61
Victoria
(Mt Tolmie)
125 -6 -8 24 16 2700 9 91 775 0.96 800 220 2.1 0.3 0.48 0.63 1.2 0.82 0.38 0.19 0.61
Victoria 10 -4 -6 24 17 2650 8 91 800 0.98 825 220 1.1 0.2 0.44 0.57 1.2 0.82 0.38 0.18 0.61
Whistler 665 -17 -20 30 20 4180 10 85 845 0.99 1215 160 9.5 0.9 0.25 0.32 0.63 0.47 0.28 0.16 0.29
White Rock 30 -5 -7 25 20 2620 10 80 1065 1.17 1100 160 2.0 0.2 0.34 0.44 1.1 0.76 0.35 0.18 0.57
Williams Lake 615 -30 -33 29 17 4400 10 48 350 0.47 425 80 2.4 0.2 0.27 0.35 0.28 0.16 0.096 0.056 0.14
Youbou 200 -5 -8 31 19 3050 10 161 2000 2.09 2100 200 3.9 0.7 0.25 0.32 1.0 0.69 0.35 0.18 0.50change end
Notes to Table C-2:

(1) Refer to the Commentary on Design for Seismic Effects in the Structural Commentaries on the National Building Code of Canada 2010 for more detailed data on seismic parameters in selected metropolitan areas.

contentHistory