Canadian Ecodistrict Climate Normals 1961-1990
December, 1997 (revised)
Climate normals are available as a GIS database for Ecodistricts in Canada with monthly climatic normals for the 1961-1990 normals period. Ecodistrict boundaries were derived from version 2.2 of the Soil Landscapes of Canada (SLC coverage without lakes in it). The climate normals information originated from point-based weather station data obtained from Environment Canada (1994).
The data are made available as Dbase files, and may be viewed with database or spreadsheet software such as FoxPro, QuattroPro, or Lotus 1-2-3. Each variable's data file includes a key field called DISTRICT which is the ecodistrict id number, and provides a linkage to the ECODISTRICT GIS coverage available on this site. This coverage is also available as an ARCVIEW shape file near the bottom of this page. The data can thus be viewed spatially using ARCVIEW 3.0 or a similar GIS.
Temperature and Precipitation
The 1961-1990 data for temperature and precipitation included only stations with averages based on more than 19 years of data. Data from additional stations which had temperature and precipitation normals for the 1951-1980 period were also used to provide maximum station density, but these normals were first adjusted to the 1961-1990 period by comparison with nearby stations.
Monthly air temperature and precipitation variables (TMAX, TMIN, TMEAN, RAIN, SNOW and TOTALP) were interpolated using the Thiessen polygon method (generated using the GRASS GIS V.GEOM module). The Thiessen polygons were overlayed with Ecodistrict polygons, and an area-weighted value generated for each Ecodistrict. (Area-weighted polygon to polygon overlays were done using ARCINFO GIS based methods developed by AAFC and Pole Star Geomatics called PARS.) Polygons of stations which were more than 350 metres above the lowest elevation of each Ecodistrict were eliminated from the weighting procedure to avoid using stations at high elevations in mountainous terrain (e.g. in British Columbia) which were not considered to be representative of agricultural land. In a few cases where no representative climate stations were available, data for the Ecodistrict is indicated as missing (data field is filled with -999's). The amount of missing data varies with the variable and month, but affects at most about 16 out of the 1021 Ecodistricts. Separate Thiessen coverages were developed for temperature and for precipitation for each month to make use of all available station data.
|TMIN||Average daily minimum air temperature (o C)||Download data table dt_temp.dbf|
|TMAX||Average daily maximum air temperature (degrees Celsius)|
|TMEAN||Average daily mean air temperature (degrees Celsius)|
|RAIN||Total rainfall (mm)||Download data table dt_prec.dbf|
|SNOW||Total snowfall (cm)|
|TOTALP||Total precipitation (mm)|
Other Measured Variables
The remaining observed climate variables such as wind, solar radiation, vapour pressure, etc., monthly values were extracted for available years and then averaged. Only station averages that included 8 years or more of data were used for these variables (period of record was compromised to achieve adequate station density in these cases).
These variables (VP, WI, SH, SR and DP as defined in the table below) were interpolated using gridded surface interpolation methods, since the density of climate stations was generally inadequate for using the Thiessen approach. A grid with 1.5 minute Latitude and Longitude spacing was generated using the inverse distance method to weight the four stations nearest to each grid cell (using the GRASS GIS R.SURF.IDW2 module). For the variables extrapolated using this method, each monthly variable has a maximum, minimum and mean value determined for each Ecodistrict (i.e. the maximum is the highest, minimum is the lowest and mean is the average of all grid point values found within the district).
|VP||Mean hourly vapour pressure (kilopascals)||Download data table dt_vapp.dbf|
|WI||Mean hourly wind speed (km/hr)||Download data table dt_wind.dbf|
|SH||Total duration of bright sunshine (hrs)||Download data table dt_sunh.dbf|
|SR||Mean daily global solar radiation (megajoules/sq. metre/day)||Download data table dt_srad.dbf|
|DP||Mean hourly dew point temperature (degrees Celsius)||Download data table dt_dewp.dbf|
Average monthly and annual potential evapotranspiration (PE) were estimated from monthly climatic normals for each Ecodistrict using the Penman and the Thornthwaite methods. The Penman procedure was similar to that used in the WOFOST Crop Simulation Model (van Diepen et al. 1988), with some modifications. Daily normal values of climate variables required as input into the Penman equations were generated from monthly normals using the Brooks (1943) sine wave interpolation procedure. Wind speed was converted from the 10 metre height to 2 metres using the power law (Jensen 1973): U1 = U2 * (h1/h2)**0.2 where U1 and U2 are wind speeds at height h1 and h2 respectively. Daylength values were computed based on a computer subroutine called SOLARR (De Jong, personal communication). The Penman PE calculations were made on a daily basis assuming a grass cover with an albedo of 0.25 when average mean daily air temperatures were above 0 degrees Celsius. When temperatures were below freezing, an albedo of 0.75 for snow cover was assumed, similar to the procedure used in the Penman PE calculated for the Land Potential Data Base (Kirkwood et al. 1989). Negative daily PE values which could occur in winter were set to zero. Daily normal PE values were summed to obtain monthly and annual normal values for Penman PE.
Average monthly and annual Thornthwaite PE values and Water Deficits (WD) were computed using methods described by Thornthwaite and Mather (1957). WD values were estimated for soils with 100, 150, 200 and 250 mm available water-holding capacity using both the Penman and the Thornthwaite PE estimates. A precipitation surplus/deficit was computed by subtracting the PE from TOTALP (i.e. TOTALP-PE) using both the Penman and the Thornthwaite PE calculations.
Annual growing degree-days (GDD) above base temperatures of 0, 5, 10 and 15 degrees Celsius (GDD0, GDD5, GDD10 and GDD15) were computed from the monthly mean air temperature data. Brooks (1943) interpolation procedure was used to generate daily mean air temperatures from monthly values and daily growing degree-days were calculated by subtracting the base temperature from the mean daily temperature (negative values were set to zero). Daily values were summed to obtain the annual total. Calculating GDD from mean daily air temperatures involves some error near the start and end of the accumulation period, since the temperature averages include days when the temperature was below the base value. However, this procedure has been commonly accepted as being of sufficient accuracy (Chapman and Brown 1966).
The date of the growing season start (GSS) and end (GSE) were determined by the first and last day of the year when the mean daily air temperature equals or exceeds 5 degrees Celsius. This is generally considered to coincide with the growing period for perennial forage crops (Chapman and Brown 1966). Growing season length (GSL) was computed as GLS=GSE-GSS+1, where GSE and GSS are calendar (Julian) days.
Effective growing degree-days (EGDD) are GDD above 5 degrees Celsius adjusted for growing season and day length and are used in rating the suitability of land for spring-seeded small grains (Pettapiece, 1995). EGDD were computed from monthly temperature normals using the procedures outlined by Pettapiece, with the following modifications: i) since observed values of average fall frost dates were not available in the database, a procedure described by Sly et al. (1971) was used to estimate the average date of the first fall frost, on which seasonal accumulations of EGDD were ended; ii) a mathematical equation was fitted to the graph in Fig. A.1, page 67 of the Pettapiece (1995) report, which was then used to compute the daylength factor (DLF). EGDD are determined by multiplying seasonal GDD sumsby the DLF, which ranges from 1.0 at latitudes of 49 degrees N or lower, to 1.18 at latitudes of 61 degrees N or higher.
|P-PE||Precipitation surplus/deficit (mm)
|Download data table dt_ppe_p.dbf|
|Precipitation surplus/deficit (mm)
|Download data table dt_ppe_t.dbf|
|PE and WD||Potential Evapotranspiration and Water Deficit (mm)
Penman PE method
|Download data table dt_pewdp.dbf|
|Potential Evapotranspiration and Water Deficit (mm)
Thornthwaite PE method
|Download data table dt_pewdt.dbf|
|GDD0||Growing degree-days above 0 degrees Celsius||Download data table dt_gdd.dbf|
|GDD5||Growing degree-days above 5 degrees Celsius|
|GDD10||Growing degree-days above 10 degrees Celsius|
|GDD15||Growing degree-days above 15 degrees Celsius|
|GSS||Growing season start (calendar or Julian day)|
|GSE||Growing season end (calendar or Julian day)|
|GSL||Growing season length (days)|
|EGDD||Effective growing degree-days||Download data table dt_egdd.dbf|
|Download data file district.zip||ArcView Project file and supporting shape files for displaying climate data. (district.apr district.shp district.shx district.sbn district.sbx; decimal degree geographic projection). This file also includes copies of all the climate data in the separate .dbf files on this page. To extract, follow these instructions.|
|Download data table district.dbf||This file includes the minimum, maximum and area weighted mean
elevation for each Ecodistrict:
|Download data table dt_coord.dbf||This file contains the latitude and longitude in decimal degrees of the centroid of each Ecodistrict.|
Although each step of the development of the database was carefully validated, the authors cannot guarantee that there are no 'glitches' to be found in the data and would appreciate being informed of any data users come across where the procedures appear to have generated unreasonable results. Users of the data are cautioned that reliability of the interpolated data may be lower in areas of the country where climate stations are relatively sparse, e.g. in some regions of the north.
Brooks, C.E.P. 1943. Interpolation tables for daily values of meteorological elements. Quart. J. Royal Meteorol. Soc. 69 (300): 160-162.
Chapman, L.J. and Brown, D.M. 1966. The climates of Canada for agriculture. Canada Land Inventory Report No. 3, Environment Canada, Lands Directorate, Ottawa. 24pp. + maps.
Environment Canada. 1994. Canadian Monthly Climate Data and 1961-1990 Normals on CD-ROM. Environment Canada, Atmospheric Environment Service, Downsview, Ontario.
Jensen, M.E. (ed.) 1973. Consumptive use of water and irrigation requirements. Amer. Soc. Civil Engineers, New York, N.Y.
Kirkwood, V., Dumanski, J., Bootsma, A., Stewart, R.B. and Muma, R. 1989. The land potential data base for Canada - User's handbook. Agriculture Canada, Research Branch, Land Resource Research Centre, Tech. Bull. 1983-4E. 53 pp.
Pettapiece, W.W. (ed.) 1995. Land Suitability Rating System for Agricultural Crops. 1. Spring-seeded small grains. Agriculture and Agri-Food Canada, Research Branch, Centre for Land and Biological Resources Research, Tech. Bull. 1995-6E, 90 pp. + maps.
Sly, W., Robertson, G.W. and Coligado, M.C. 1971. Estimation of probable dates of temperatures near freezing from monthly temperature normals, station elevation, and astronomical data. Canada Department of Agriculture, Research Branch, Plant Research Institute, Agrometeorology Section, Ottawa, Tech. Bull. 79, 21 pp.
Thornthwaite, C.W. and Mather, J.R. 1957. Instructions and tables for computing potential evapotranspiration and the water balance. Drexel Institute of Technology, Publications in Climatology Vol X, No. 3, Centerton, New Jersey. 311 pp.
van Diepen, C.A., Rappoldt, C., Wolf, J. and van Keulen, H. 1988. CWFS Crop Growth Simulation Model WOFOST Documentation, Version 4.1. Centre for World Food Studies, Wageningen, The Netherlands. 299 pp.
Dr. R. de Jong, AAFC, Eastern Cereals and Oilseeds Research Centre, assisted in formulating the procedures for calculating Penman PE and daylength. His help in validating the Penman calculations is also very much appreciated. Source: This work was done by Pole Star Geomatics Inc. (PSG), under contract to Agriculture and Agri-Food Canada.