APEC climate center multi-model ensemble dataset for seasonal climate prediction.

Yoo-Bin Yhang, Chang-Mook Lim, Daeun Jeong
Author Information
  1. Yoo-Bin Yhang: APEC Climate Center, Busan, Korea. ybyhang@apcc21.org. ORCID
  2. Chang-Mook Lim: APEC Climate Center, Busan, Korea.
  3. Daeun Jeong: APEC Climate Center, Busan, Korea.

Abstract

The multi-model ensemble (MME) technique is useful for obtaining reliable climate information. The Asia-Pacific Economic Cooperation Climate Center (APCC) has provided well-constructed MME data and individual model data included in the MME. This study examines the prediction skill of the APCC MME, focusing on 2-m temperature, precipitation, and sea surface temperature. For the overall evaluation of the APCC MME, the hindcast skill was assessed for the period of 1991-2010 for four sets of APCC MME representing the operational model suites from 2019 to 2022. The forecast skill was also evaluated to demonstrate actual predictability from 2019 to 2022. Hindcast validation showed a modest improvement, indicating continuous enhancement. In addition, it was demonstrated that the forecast skill was consistently maintained. These seasonal forecast data can provide valuable insights for decision-making across various sectors, helping mitigate risks and optimize resource management.

References

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  2. J Geophys Res Atmos. 2020 Mar 16;125(5): [PMID: 33959467]
  3. Sci Data. 2025 Feb 20;12(1):303 [PMID: 39979360]

Word Cloud

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