Analysis of near-surface biases in ERA-Interim over the Canadian Prairies

We quantify the biases in the diurnal cycle of temperature in ERA-Interim for both warm and cold season using hourly climate station data for four stations in Saskatchewan from 1979-2006. The warm season biases increase as opaque cloud cover decreases, and change substantially from April to October. The bias in mean temperature increases almost monotonically from small negative values in April to small positive values in the fall. Under clear skies, the bias in maximum temperature is of the order of -1oC in June and July, and -2oC in spring and fall; while the bias in minimum temperature increases almost monotonically from +1oC in spring to +2.5oC in October. The bias in the diurnal temperature range falls under clear skies from -2.5oC in spring to -5oC in fall. The cold season biases with surface snow have a different structure. The biases in maximum, mean and minimum temperature with a stable BL reach +1oC, +2.6oC and +3oC respectively in January under clear skies. The cold season bias in diurnal range increases from about -1.8oC in the fall to positive values in March. These diurnal biases in 2-m temperature and their seasonal trends are consistent with a high bias in both the diurnal and seasonal amplitude of the model ground heat flux, and a warm season daytime bias resulting from the model fixed leaf area index. Our results can be used as bias corrections in agricultural modeling that use these reanalysis data, and also as a framework for understanding model biases.

Plain English summary

Global model forecasts and analyses of temperature are used for many purposes, including agriculture, where accuracy is needed to estimate crop growth. This paper uses long term temperature records from climate stations in Saskatchewan on the Canadian Prairies to show how the biases in the maximum and minimum temperature in a European Weather Centre reanalysis vary with season and cloud cover; so that these biases can be corrected.

AGU JAMES link

Related Topics

• Canadian Prairies,
• Climate,
• Clouds,
• Datasets,
• Land-surface,
• Reanalysis&FX