Evidence map›Paper›PMID 37852979›Full record

ArticleNature communications2023

Arctic weather variability and connectivity.

Jun Meng, Jingfang Fan, Uma S Bhatt, Jürgen Kurths

Abstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

4 authors.

Jun MengSchool of Science, Beijing University of Posts and Telecommunications, 100876, Beijing, China.
Jingfang FanSchool of Systems Science/Institute of Nonequilibrium Systems, Beijing Normal University, 100875, Beijing, China. jingfang@bnu.edu.cn.ORCID http://orcid.org/0000-0003-1954-4641
Uma S BhattGeophysical Institute, Department of Atmospheric Sciences, University of Alaska Fairbanks, Fairbanks, AK, 99775, USA.ORCID http://orcid.org/0000-0003-1056-3686
Jürgen KurthsPotsdam Institute for Climate Impact Research, Potsdam, 14412, Germany.ORCID http://orcid.org/0000-0002-5926-4276

Funding

National Natural Science Foundation of China (National Science Foundation of China) 12135003National Natural Science Foundation of China (National Science Foundation of China) 12275020
6 · The paper itself

Abstract

The Arctic's rapid sea ice decline may influence global weather patterns, making the understanding of Arctic weather variability (WV) vital for accurate weather forecasting and analyzing extreme weather events. Quantifying this WV and its impacts under human-induced climate change remains a challenge. Here we develop a complexity-based approach and discover a strong statistical correlation between intraseasonal WV in the Arctic and the Arctic Oscillation. Our findings highlight an increased variability in daily Arctic sea ice, attributed to its decline accelerated by global warming. This weather instability can influence broader regional patterns via atmospheric teleconnections, elevating risks to human activities and weather forecast predictability. Our analyses reveal these teleconnections and a positive feedback loop between Arctic and global weather instabilities, offering insights into how Arctic changes affect global weather. This framework bridges complexity science, Arctic WV, and its widespread implications.

Identifiers

PMID37852979
PMCPMC10584854

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.