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June 24, 2025

A century of seasonal forecast improvement for Western Pacific Subtropical High driven by Indo-Pacific ocean

Seasonal evolving regression patterns of observed SST during two time periods. Regression of (a) D(-1)JF(0), (b) MAM(0), and (c) JJA(0) SSTAs onto WPSH index during the period from 1901 to 1950. (d)–(f) same as (d)–(f), but for 1961–2010. Stippling indicates 90% confidence level of shaded fields. The blue and red boxes represent Nino3.4 and NIO region, respectively. Credit: Journal of Geophysical Research: Atmospheres (2025). DOI: 10.1029/2025JD043354
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Seasonal evolving regression patterns of observed SST during two time periods. Regression of (a) D(-1)JF(0), (b) MAM(0), and (c) JJA(0) SSTAs onto WPSH index during the period from 1901 to 1950. (d)–(f) same as (d)–(f), but for 1961–2010. Stippling indicates 90% confidence level of shaded fields. The blue and red boxes represent Nino3.4 and NIO region, respectively. Credit: Journal of Geophysical Research: Atmospheres (2025). DOI: 10.1029/2025JD043354

The Western Pacific Subtropical High (WPSH) functions like Earth's atmospheric traffic controller, directing summer monsoon flows that regulate rainfall and temperatures across East Asia. When this high-pressure system misbehaves, the consequences can be dramatic—from the devastating Yangtze River floods of 1931 and 1998, to 2020's endless rainy season, and the record-shattering 2022 heat waves that baked the Yangtze basin.

These extremes underscore the urgent need to predict the WPSH's variations. Yet our understanding remains incomplete. While researchers have made significant progress in studying the WPSH's seasonal behavior over recent decades, a critical question persists: How has its predictability evolved over longer timescales?

A team of climate scientists reveal how our ability to predict the WPSH has transformed over the past century. Published in the , the research shows the prediction skill of summer WPSH has significantly improved since the 1960s compared to earlier decades. What's behind this prediction breakthrough? The answer lies in increasingly robust oceanic signals from the Indo-Pacific region.

"We identified three persistent oceanic predictors of WPSH variability that serve as crucial sources of predictable signals," said first author Wanheng Ye from the Institute of Atmospheric 鶹Ժics at the Chinese Academy of Sciences. These predictors include sea surface temperature anomalies in the tropical central‐eastern Pacific, tropical North Atlantic, and Indo‐Pacific.

Notably, the Indo‐Pacific has emerged as the most significant contributor to WPSH prediction skill, accounting for 59% after 1960, compared to 40% before 1950. This shift is mainly attributed to two factors: the systematic improvement in the quality and coverage of observational data, and an enhancement in the quasi-biennial variability of El Niño-Southern Oscillation since the 1960s.

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"This centennial analysis gives us insight into how oceanic drivers have systematically improved WPSH forecasting," said corresponding author Shuai Hu. "Before 1950, limited sea surface temperature predictability constrained our ability to forecast the WPSH. The post-1960 era brought a remarkable transformation. The strengthened predictable signals emerging from three-ocean interactions began dominating over atmospheric noise from distant regions like the North Atlantic."

By quantifying the evolving contributions of three oceanic regions across a 100-year period, this study establishes a new framework for understanding WPSH predictability. The findings demonstrate how shifting oceanic influences have gradually transformed our ability to make accurate seasonal forecasts.

More information: Wanheng Ye et al, Enhanced Seasonal Prediction Skill of the Western Pacific Subtropical High Over the Past Century, Journal of Geophysical Research: Atmospheres (2025).

Journal information: Journal of Geophysical Research - Atmospheres

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Seasonal forecast skill for the Western Pacific Subtropical High (WPSH) has markedly improved since the 1960s, primarily due to stronger and more predictable oceanic signals from the Indo-Pacific. The Indo-Pacific now accounts for 59% of WPSH prediction skill, up from 40% before 1950, reflecting enhanced sea surface temperature data and increased El Niño-Southern Oscillation variability.

This summary was automatically generated using LLM.