Validation and Comparison of Climate Reanalysis Data in the East Asian Monsoon Region

Abstract

Understanding East Asian monsoon (EAM) has been a crucial issue due to its socio-economic effects on one-fifth of the world’s population and its interactions with the global climate system. However, the reliabilities of climate reanalysis data are still uncertain at varying temporal and spatial scales. In this study, we examined the correlations and differences for climate reanalyses with weather observations and suggested the best climate reanalysis for the EAM region. The three reanalyses of ERA5, JRA55, and NCEP2 along with a gridded observation (CRU) were evaluated using the correlation coefficients (Pearson, Spearman, and Kendall), difference statistics (RMSE and bias), and Taylor diagrams, comparing their annual and seasonal temperatures and precipitations with those from the total of 537 weather stations across China, North Korea, South Korea, and Japan. We found that ERA5 showed the best performance in reproducing temporal variations in temperature with the highest correlations in annual, summer, and autumn, and the smallest RMSEs and biases for all seasons and annually. For precipitation, among the three reanalysis datasets, ERA5 had the highest correlations, annually and in four seasons, with the smallest RMSEs, annually and in spring, summer and autumn, and the smallest biases, annually and in summer and autumn. Regarding spatial variations, ERA5 was also the most suitable reanalysis data in representing the annual and seasonal climatological averages.

Keywords

• climate reanalysis
• correlation
• bias
• evaluation
• monsoon
• East Asia