Near-surface biases in ERA5 over the Canadian Prairies
We quantify the biases in the diurnal cycle of air temperature in ERA5, using hourly climate station data for four stations in Saskatchewan, Canada. Compared with ERA-Interim, the biases in ERA5 have been greatly reduced, and show no differences with snow cover. We compute fits to the ERA5 mean air temperature biases based on ERA5 effective cloud albedo. They can be used to improve the ERA5 diurnal cycle of air temperature for modeling agricultural processes. Diurnally, ERA5 has a negative wind speed bias, which increases quasi-linearly with wind speed, and is greater in the daytime than at night. We evaluate ERA5 precipitation against the original climate station precipitation data, and a second generation adjusted precipitation dataset by Mekis and Vincent . For the warm season, ERA5 has a high bias of 8±9% above the Mekis dataset. ERA5 is -22±7% below the Mekis estimate in winter, suggesting that their correction with snow may be too large. It is likely that the ERA5 precipitation bias is small, which is encouraging for agricultural modelling. Data from a BSRN site near Regina shows that the biases in the downwelling shortwave and longwave radiation estimates in ERA5 are small, and have changed little from ERA-Interim. We showed that the annual cycle of the Saskatchewan surface energy and water budgets in ERA5 are realistic. In particular the damping of extremes in summer precipitation by the extraction of soil water is comparable in ERA5 to our earlier observational estimate based on gravity satellite data.
Contribution to field. Global model reanalyses 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 that the biases in the diurnal cycle of 2-m temperature in the most recent European Weather Centre reanalysis, known as ERA5, are much smaller than in the earlier reanalysis known as ERA-Interim. Significantly, these temperature biases now show no anomalies with snow cover.
Betts, A.K., D.Z. Chan and R.L. Desjardins (2019), Near-surface biases in ERA5 over the Canadian Prairies. Front. Environ. Sci. doi: 10.3389/fenvs.2019.00129