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Outstanding performance of ERA5 reanalysis temperature in China since the 1950s and quantification of its abnormal error in 1965–1966

Jiaxue Lin,Hanyu Zhang,Sihao Wei,Qiya Xu,Zichen Li,Qingxiang Li

Published 2025 in Quarterly Journal of the Royal Meteorological Society

ABSTRACT

Reanalyses are essential for climate change research and operational forecasting. Among the widely used reanalyses, ERA5 stands out as one of the most popular, with its latest version, extending back to 1940, released in 2023. However, a systematic comparative evaluation of ERA5's full‐period dataset in China is lacking. This study compares the surface air temperature (SAT) data from ERA5 with those from four other extended reanalysis products (20CRv3, 20CRv3‐ERA5, CERA‐20C and ERA5‐Land), using the recently updated High‐Resolution version of China global Land Surface Air Temperature (C‐LSAT HR) as the benchmark dataset. The comparison focuses on climatology, long‐term trends, and SAT variations over China. Our findings reveal that all three centennial‐scale reanalyses significantly underestimate the warming trend in China since the early 20th century. Overall, ERA5 performs the best across all above evaluation aspects. However, the system and random errors in the years 1965 and 1966 are considerably larger than usual, primarily due to the lack of observations as input data. Further analysis using station observations as the “reference truth” shows that these anomalous errors persist throughout both years, with an overall cold bias of −0.74°C (1965) and −0.67°C (1966). The magnitude of the errors varies by season and region, with the most pronounced increase observed during the summer months. The mean absolute error (MAE) (mean bias error – MBE) in the summers of 1965 and 1966 increases by 0.44°C (−0.59°C) and 0.50°C (−0.65°C), respectively. Spatially, ERA5 records the largest system biases in the summer for southern Xinjiang and in the autumn for the eastern Tibetan Plateau, with the MAE increase exceeding 3°C in these regions. The most significant contribution ratio of root‐mean‐squared error (RMSE) for abnormal years (IRMSE) occurs in the summer in South China and southern Xinjiang, where it exceeds 15% at most stations, although the average MAE increase for South China is only 1˜2°C.

PUBLICATION RECORD

  • Publication year

    2025

  • Venue

    Quarterly Journal of the Royal Meteorological Society

  • Publication date

    2025-06-25

  • Fields of study

    Not labeled

  • Identifiers
    DOI 10.1002/qj.5042
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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