Evaluating the performance of key ERA-Interim, ERA5 and ERA5-Land climate variables across Siberia

Abstract

Reanalysis datasets provide a continuous picture of the past climate for every point on Earth. They are especially useful in areas with few direct observations, such as Siberia. However, to ensure these datasets are sufficiently accurate they need to be validated against readings from meteorological stations. Here, we analyse how values of six climate variables—the minimum, mean and maximum 2-metre air temperature, snow depth (SD), total precipitation and wind speed (WSP)—from three reanalysis datasets—ERA-Interim, ERA5 and ERA5-Land—compare against observations from 29 meteorological stations across Siberia and the Russian Far East on a daily timescale from 1979 to 2019. All three reanalyses produce values of the mean and maximum daily 2-metre air temperature that are close to those observed, with the average absolute bias not exceeding 1.54°C. However, care should be taken for the minimum 2-metre air temperature during the summer months—there are nine stations where correlation values are <0.60 due to inadequate night-time cooling. The reanalysis values of SD are generally close to those observed after 1992, especially ERA5, when data from some of the meteorological stations began to be assimilated, but the reanalysis SD should be used with caution (if at all) before 1992 as the lack of assimilation leads to large overestimations. For low daily precipitation values the reanalyses provide good approximations, however they struggle to attain the extreme high values. Similarly, for the 10-metre WSP; the reanalyses perform well with speeds up to 2.5 ms−1 but struggle with those above 5.0 ms−1. For these variables, we recommend using ERA5 over ERA-Interim and ERA5-Land in future research. ERA5 shows minor improvements over ERA-Interim, and, despite an increased spatial resolution, there is no advantage to using ERA5-Land.