Multidecadal Variation in the Seasonal Predictability of Winter PNA and Its Sources

Yao, Wangjie; Yan, Xiaolei; Tang, Youmin; Yang, Dong; Tan, Xiao; Song, Xunshu; Liu, Ting

doi:10.1029/2022gl099393

Cited by 3 publications

(3 citation statements)

References 49 publications

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“…It is also important to understand why different signals show different periods of reduced skill (e.g., why the PC1 skill minimum leads the PC2 skill minimum by 10 years). Other suggestions for multi-decadal variability in hindcast skill include poor representation of air-sea coupling in seasonal hindcast models (Yao et al, 2022), which was important in the real world in the middle of the century.…”

Section: Discussionmentioning

confidence: 99%

Multi-decadal skill variability in predicting the spatial patterns of ENSO events

Wright,

Weisheimer,

Woollings

2024

Preprint

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Seasonal hindcasts have previously been demonstrated to show multi-decadal variability in skill across the twentieth century in indices describing El-Niño Southern Oscillation (ENSO), which drives global seasonal predictability. Here, we analyse the skill of predicting ENSO events’ magnitude and spatial pattern, in the CSF-20C coupled seasonal hindcasts in 1901-2010. We find minima in the skill of predicting the first (in 1930-1950) and second (in 1940-1960) principal components of sea-surface temperature (SST) in the tropical Pacific. This minimum is also present in the spatial correlation of SSTs, in 1930-1960. The skill reduction is explained by lower ENSO magnitude and variance in 1930-1960, as well as decreased SST persistence. The SST skill minima project onto surface winds, leading to worse predictions in coupled hindcasts compared to hindcasts using prescribed SSTs. Questions remain about the offset between the first and second principal components’ skill minima, and how the skill minima impact the extra-tropics.

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Section: Discussionmentioning

confidence: 99%

Multi-decadal skill variability in predicting the spatial patterns of ENSO events

Wright,

Weisheimer,

Woollings

2024

Preprint

View full text Add to dashboard Cite

show abstract

“…It is also important to understand why different signals show different periods of reduced skill (e.g., why the PC1 skill minimum leads the PC2 skill minimum by 10 years). Other suggestions for multi‐decadal variability in hindcast skill include poor representation of air‐sea coupling in seasonal hindcast models (Yao et al., 2022), which was important in the real world in the middle of the century.…”

Section: Discussionmentioning

confidence: 99%

Multi‐Decadal Skill Variability in Predicting the Spatial Patterns of ENSO Events

Wright,

Weisheimer,

Woollings

2024

Geophysical Research Letters

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Seasonal hindcasts have previously been demonstrated to show multi‐decadal variability in skill across the twentieth century in indices describing El‐Niño Southern Oscillation (ENSO), which drives global seasonal predictability. Here, we analyze the skill of predicting ENSO events' magnitude and spatial pattern, in the CSF‐20C coupled seasonal hindcasts in 1901–2010. We find minima in the skill of predicting the first (in 1930–1950) and second (in 1940–1960) principal components of sea‐surface temperature (SST) in the tropical Pacific. This minimum is also present in the spatial correlation of SSTs, in 1930–1960. The skill reduction is explained by lower ENSO magnitude and variance in 1930–1960, as well as decreased SST persistence. The SST skill minima project onto surface winds, leading to worse predictions in coupled hindcasts compared to hindcasts using prescribed SSTs. Questions remain about the offset between the first and second principal components' skill minima, and how the skill minima impact the extra‐tropics.

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“…The PNA index has proven effective in predicting and understanding the AR frequency at both monthly and seasonal timescales. With the PNA index’s notable predictability over 1 to 2 months ( 23 , 24 ), this relationship suggests the potential for enhancing AR frequency predictions in the EUS.…”

Section: Introductionmentioning

confidence: 93%

Atmospheric rivers over eastern US affected by Pacific/North America pattern

Dong,

Zhao,

Tan

et al. 2024

Sci. Adv.

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Atmospheric rivers (ARs) play important roles in various extreme weather events across the US. While AR features in western US have been extensively studied, there remains limited understanding of their variability in the eastern US (EUS). Using both observations and a state-of-the-art climate model, we find a significant increase (~10% dec −1 ) in winter AR frequency in the EUS during the past four decades. This trend is closely linked to recent changes in the Pacific/North America (PNA) teleconnection pattern, accompanied by a poleward shift of the mid-latitude jet stream. We further reveal a strong correlation ( R = 0.8; P < 0.001) between interannual variations in AR occurrence and the PNA index. This linkage has been verified in various model simulations. A statistical model, built on this linkage, has proven effective in predicting the AR frequency using the PNA index at both monthly and seasonal scales. These promising results have important implications for addressing concerns related to AR-associated extreme precipitation and flooding in this region.

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Multidecadal Variation in the Seasonal Predictability of Winter PNA and Its Sources

Abstract: As a prominent atmospheric low-frequency variability, the Pacific-North American (PNA) teleconnection pattern is an important atmospheric bridge that links changes in the tropical and extratropical Pacific (Alexander

Cited by 3 publications

References 49 publications

Multi-decadal skill variability in predicting the spatial patterns of ENSO events

Multi-decadal skill variability in predicting the spatial patterns of ENSO events

Multi‐Decadal Skill Variability in Predicting the Spatial Patterns of ENSO Events

Atmospheric rivers over eastern US affected by Pacific/North America pattern

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