Yan, Y. H., J. Z. Su, B. Q. Liu, L. B. Ma, X. Y. Rong, B. Liu, Y. L. Tang, and J. Li, 2025: Subseasonal prediction skill in the CAMS-CSM subseasonal-to-seasonal forecast system. Adv. Atmos. Sci., https://doi.org/10.1007/s00376-024-4072-3.
Citation: Yan, Y. H., J. Z. Su, B. Q. Liu, L. B. Ma, X. Y. Rong, B. Liu, Y. L. Tang, and J. Li, 2025: Subseasonal prediction skill in the CAMS-CSM subseasonal-to-seasonal forecast system. Adv. Atmos. Sci., https://doi.org/10.1007/s00376-024-4072-3.

Subseasonal Prediction Skill in the CAMS-CSM Subseasonal-to-Seasonal Forecast System

  • A subseasonal-to-seasonal (S2S) forecast system (FS) has recently been released based on the fully coupled Chinese Academy of Meteorological Sciences Climate System Model (CAMS-CSM). This study evaluated the subseasonal prediction skill of this system via a 21-year hindcast experiment for the period 2000–20 with eight ensemble members. Results showed moderate-to-high skill for the primary atmospheric variables. The most accurate predictions emerged in the cold season but were largely confined within tropical bands as the forecast lead time was increased. Compared with the NCEP S2S FS, the CAMS-CSM S2S FS showed comparable subseasonal skill for 500-hPa geopotential height, but slightly higher (lower) skill for precipitation (2-m temperature). The skillful lead time in the CAMS-CSM S2S FS for the Madden–Julian Oscillation and North Atlantic Oscillation reached 20 and 10 days, respectively, consistent with the NCEP S2S FS. Consequently, these findings guide future research on subseasonal predictability based on the CAMS-CSM S2S FS, and where efforts should be focused to improve the prediction system.
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