Evidence map›Paper›PMID 40282563›Full record

ArticleEntropy (Basel, Switzerland)2025

A Revisit of Large-Scale Patterns in Middle Stratospheric Circulation Variations.

Ningning Tao, Xiaosong Chen, Fei Xie, Yongwen Zhang, Yan Xia, Xuan Ma, Han Huang, Hongyu Wang

Abstract read
In one paragraph

Article in Entropy (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Ningning TaoSchool of Systems Science, Beijing Normal University, Beijing 100875, China.ORCID 0009-0000-9217-9025
Xiaosong ChenSchool of Systems Science, Beijing Normal University, Beijing 100875, China.ORCID 0000-0001-9994-2011
Fei XieSchool of Systems Science, Beijing Normal University, Beijing 100875, China.ORCID 0000-0003-2891-3883
Yongwen ZhangData Science Research Center, Faculty of Science, Kunming University of Science and Technology, Kuming 650500, China.
Yan XiaSchool of Systems Science, Beijing Normal University, Beijing 100875, China.ORCID 0000-0001-8664-5325
Xuan MaSchool of Systems Science, Beijing Normal University, Beijing 100875, China.
Han HuangSchool of Systems Science, Beijing Normal University, Beijing 100875, China.
Hongyu WangSchool of Systems Science, Beijing Normal University, Beijing 100875, China.

Funding

National Key R&D Program of China grant 2023YFE0109000National Natural Science Foundation of China grants 12135003 and 12305044
6 · The paper itself

Abstract

Variations in stratospheric atmospheric circulation significantly impact tropospheric weather and climate. Understanding these variations not only aids in better prediction of tropospheric weather and climate but also provides guidance for the development and flight trajectories of stratospheric aircraft. Our understanding of the stratosphere has made remarkable progress over the past 100 years. However, we still lack a comprehensive perspective on large-scale patterns in stratospheric circulation, as the stratosphere is a typical complex system. To address this gap, we employed the eigen microstate approach (EMA) to revisit the characteristics of zonal wind from 70-10 hPa from 1980 to 2022, based on ERA5 reanalysis data. Our analysis focused on the three leading modes, corresponding to variations in the strength of the quasi-biennial oscillation (QBO) and the stratospheric atmospheric circulations in the Arctic and Antarctic, respectively. After filtering out high-frequency components from the temporal evolutions of these modes, a significant 11-year cycle was observed in the Antarctic stratospheric atmospheric circulation mode, potentially linked to the 11-year solar cycle. In contrast, the Arctic stratospheric atmospheric circulation mode showed a 5-6-year cycle without evidence of an 11-year periodicity. This difference is likely due to the timing of polar vortex breakdowns: the Antarctic polar vortex breaks up later, experiencing its greatest variability in late spring and early summer, making it more susceptible to solar radiation effects, unlike the Arctic polar vortex, which peaks in winter and early spring. The fourth mode exhibits characteristics of a Southern Hemisphere dipole and shows a significant correlation with the Antarctic stratospheric atmospheric circulation mode, leading it by about two months. We designed a linear prediction model that successfully demonstrated its predictive capability for the Antarctic polar vortex.

Indexed as

eigen microstate approachlarge-scale patternsstratospheric variations

Identifiers

PMID40282563
PMCPMC12025683

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.