Assessment of the marine heatwaves prediction performance of the short-term climate prediction system FIO-CPS v2.0

In recent years, the frequent occurrence of marine heatwaves (MHWs) has affected the ecological environment and caused considerable socioeconomic impact. Consequently, MHWs prediction has received increasing attention. This study aims to evaluate the short-term (months to interannual timescales) MHWs prediction skill of the First Institute of Oceanography-Climate Prediction System version 2.0 (FIO-CPS v2.0) by using three statistical metrics including symmetric extremal dependence index (SEDI), forecast accuracy (FA), and Brier skill score (BSS). The results revealed that FIO-CPS v2.0 can better predict MHWs in tropical regions, especially in the tropical central and eastern Pacific Ocean, in which the SEDI, FA, and BSS values reached 0.73, 0.92, and 0.27 at the 1-month lead time, respectively. However, the MHWs prediction ability of FIO-CPS v2.0 has spring prediction barriers owing to the driving factors of ENSO. Moreover, further analysis revealed a definite relationship between the ability to predict MHWs and the ability to predict MHWs duration. The prediction skill of FIO-CPS v2.0 appears to be better for long-duration MHWs than for short-duration MHWs. Under the influence of global warming, FIO-CPS v2.0 can reproduce the increase in MHWs duration observed in recent years, and the prediction skill of some regions has been relatively high in the last 15 years. This study deepens the understanding of the prediction ability of FIO-CPS v2.0, and provides an important reference for the application of short-term prediction of MHWs. • MHWs prediction performance evaluation based on monthly output from FIO-CPS v2.0 • SEDI, FA, and BSS were used to evaluate the ability of MHWs prediction. • FIO-CPS v2.0 predicts MHWs better in tropical regions with longer-duration MHWs.

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Publication Details

Journal
Weather and Climate Extremes
Published
2025-02-20
DOI
https://doi.org/10.1016/j.wace.2025.100757
Citations
1
Primary Topic
Climate variability and models
Type
article
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1.11
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article

Assessment of the marine heatwaves prediction performance of the short-term climate prediction system FIO-CPS v2.0

Zhenya Song, Chan Joo Jang, Yuanlin Wang, Ying Bao et al.
1 citations
Weather and Climate Extremes
Climate variability and models
1.11
article

Assessment of the marine heatwaves prediction performance of the short-term climate prediction system FIO-CPS v2.0

Zhenya Song, Chan Joo Jang, Yuanlin Wang, Ying Bao, Yajuan Song
article en
1 citations

Abstract

In recent years, the frequent occurrence of marine heatwaves (MHWs) has affected the ecological environment and caused considerable socioeconomic impact. Consequently, MHWs prediction has received increasing attention. This study aims to evaluate the short-term (months to interannual timescales) MHWs prediction skill of the First Institute of Oceanography-Climate Prediction System version 2.0 (FIO-CPS v2.0) by using three statistical metrics including symmetric extremal dependence index (SEDI), forecast accuracy (FA), and Brier skill score (BSS). The results revealed that FIO-CPS v2.0 can better predict MHWs in tropical regions, especially in the tropical central and eastern Pacific Ocean, in which the SEDI, FA, and BSS values reached 0.73, 0.92, and 0.27 at the 1-month lead time, respectively. However, the MHWs prediction ability of FIO-CPS v2.0 has spring prediction barriers owing to the driving factors of ENSO. Moreover, further analysis revealed a definite relationship between the ability to predict MHWs and the ability to predict MHWs duration. The prediction skill of FIO-CPS v2.0 appears to be better for long-duration MHWs than for short-duration MHWs. Under the influence of global warming, FIO-CPS v2.0 can reproduce the increase in MHWs duration observed in recent years, and the prediction skill of some regions has been relatively high in the last 15 years. This study deepens the understanding of the prediction ability of FIO-CPS v2.0, and provides an important reference for the application of short-term prediction of MHWs. • MHWs prediction performance evaluation based on monthly output from FIO-CPS v2.0 • SEDI, FA, and BSS were used to evaluate the ability of MHWs prediction. • FIO-CPS v2.0 predicts MHWs better in tropical regions with longer-duration MHWs.

Weather and Climate ExtremesVol. 48
Korea Institute of Ocean Science and Technology (KR), Ministry of Natural Resources (CN), Qingdao National Laboratory for Marine Science and Technology (CN), First Institute of Oceanography (CN)
Climate action
Openalex Percentile: Top 27%
Climate variability and models
1.11
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