2023Journal of Marine Science and EngineeringOpen access

Evaluating Changes in the Multiyear Predictability of the Pacific Decadal Oscillation Using Model Analogs since 1900

Yanling Wu, Xiaoqin Yan

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Abstract

In this study, we investigate the changes in the multiyear predictability of the Pacific decadal oscillation (PDO) since 1900. A newly developed method, the model-analog method, is used to hindcast the PDO from 1900 to 2015. Model-analog hindcast provides comparable PDO prediction skills with the traditional assimilation-initialized forecast but with much lower computational costs. Our results show that PDO prediction skills have significantly changed over time. Specifically, the PDO could skillfully be predicted up to 5 years in advance in 1910–1960, but it can only be predicted 2–3 years in advance after 1960. We attribute these changes to the strength of the re-emergence process, where deep oceanic mixed layer temperature anomalies from one winter reappear in the following winters. In the high-prediction-skill period, the stronger re-emergence process provides more predictable information, leading to enhanced multiyear prediction skills. Our study offers new insights into the multiyear predictability of the PDO over a long-time frame and sheds light on the reasons behind the low prediction skill of the PDO.

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In this study, we investigate the changes in the multiyear predictability of the Pacific decadal oscillation (PDO) since 1900. A newly developed method, the model-analog method, is used to hindcast the PDO from 1900 to 2015. Model-analog hindcast provides comparable PDO prediction skills with the traditional assimilation-initialized forecast but with much lower computational costs. Our results show that PDO prediction skills have significantly changed over time. Specifically, the PDO could skillfully be predicted up to 5 years in advance in 1910–1960, but it can only be predicted 2–3 years in advance after 1960. We attribute these changes to the strength of the re-emergence process, where deep oceanic mixed layer temperature anomalies from one winter reappear in the following winters. In the high-prediction-skill period, the stronger re-emergence process provides more predictable information, leading to enhanced multiyear prediction skills. Our study offers new insights into the multiyear predictability of the PDO over a long-time frame and sheds light on the reasons behind the low prediction skill of the PDO.

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Available abstract

In this study, we investigate the changes in the multiyear predictability of the Pacific decadal oscillation (PDO) since 1900. A newly developed method, the model-analog method, is used to hindcast the PDO from 1900 to 2015. Model-analog hindcast provides comparable PDO prediction skills with the traditional assimilation-initialized forecast but with much lower computational costs. Our results show that PDO prediction skills have significantly changed over time. Specifically, the PDO could skillfully be predicted up to 5 years in advance in 1910–1960, but it can only be predicted 2–3 years in advance after 1960. We attribute these changes to the strength of the re-emergence process, where deep oceanic mixed layer temperature anomalies from one winter reappear in the following winters. In the high-prediction-skill period, the stronger re-emergence process provides more predictable information, leading to enhanced multiyear prediction skills. Our study offers new insights into the multiyear predictability of the PDO over a long-time frame and sheds light on the reasons behind the low prediction skill of the PDO.

Key concepts: Predictability, Hindcast, Pacific decadal oscillation, Climatology, Environmental science, Data assimilation, Forecast skill, Oscillation (cell signaling)

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