High-latitude Asia (above 60°N) is highly sensitive to global climate change. Warming has led to frequent extreme climate events and has produced important impacts on both the ecological environment and social economy. However, station observations are scarce and there is limited climate change research in the region. Reanalysis data is a potential alternative to scarce observations, but its suitability in high-latitude Asia has not been well evaluated. In this study, we systematically evaluate the abilities of five reanalysis datasets (MERRA-2, CFSR, ERA-Interim, JRA-55, and ERA5) and one gridded observation dataset (CPC) to characterize mean/extreme temperature and precipitation in high-latitude Asia through comparison with GHCN-D station observations. All six datasets reasonably reproduce spatial and temporal variations in mean/extreme temperature and precipitation over the region and match well with the observed climatology. Of these datasets, CPC shows the best performance for mean/extreme temperature and precipitation in high-latitude Asia, because it is produced through interpolation of station observations. Among the five reanalysis datasets, ERA5 overall shows the best agreement with observed spatiotemporal changes in mean/extreme temperature and precipitation, although it is not superior for all variables. Temperature is generally characterized better than precipitation in these datasets. These results will be helpful for the selection and improvement of reanalyses and thus further climate research in high-latitude Asia.
- climate extremes
- extreme temperature and precipitation
- high-latitude Asia
- reanalysis validation