A COMPARISON OF METHODS TO ESTIMATED DAILY GLOBAL SOLAR IRRADIATION FROM OTHER CLIMATIC VARIABLES ON THE CANADIAN PRAIRIES

Historic estimates of daily global solar irradiation are often require d for climatic impact studies. Regression equations with daily global solar irradiation, H, as the dependent variable and other climatic var iables as the independent variables provide a practical way to estimat e H at locations where it is not measured. They may also have potentia l to estimate H before 1953, the year of the first routine H measureme nts in Canada. This study compares several regression equations for ca lculating H on the Canadian prairies. Simple linear regression with da ily bright sunshine duration as the dependent variable accounted for 9 0% of the variation of H in summer and 75% of the variation of H in wi nter. Linear regression with the daily air temperature range as the de pendent variable accounted for 45% of the variation of H in summer and only 6% of the variation of H in winter. Linear regression with preci pitation status (wet or dry) as the dependent variable accounted for o nly 35% of the summer-time variation in H, but stratifying other regre ssion analyses into wet and dry days reduced their root-mean-squared e rrors. For periods with sufficiently dense bright sunshine observation s (i.e. after 1960), however, H was more accurately estimated from spa tially interpolated bright sunshine duration than from locally observe d air temperature range or precipitation status. The daily air tempera ture range and precipitation status may have utility for estimating H for periods before 1953, when they are the only widely available clima tic data on the Canadian prairies. Between 1953 and 1989, a period of large climatic variation, the regression coefficients did not vary sig nificantly between contrasting years with cool-wet, intermediate and w arm-dry summers. They should apply equally well earlier in the century .