Evidence map›Paper›PMID 40595929›Full record

ArticleScientific reports2025

Analyzing the cyclical impact of sunspot activity and ENSO on precipitation patterns in Gilan province: a wavelet-based approach.

Mahboubeh Molavi-Arabshahi, Sara Eskandari

Abstract read
In one paragraph

Article in Scientific reports, 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
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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

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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

2 authors.

Mahboubeh Molavi-ArabshahiMathematics & Computer Science, Iran University of Science and Technology, Tehran, Iran. molavi@iust.ac.ir.
Sara EskandariMathematics & Computer Science, Iran University of Science and Technology, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study examines the influence of large-scale climatic phenomena-sunspot activity (SSN) and the El Niño-Southern oscillation (ENSO), represented by the Southern oscillation index (SOI) on precipitation, temperature, and dew point patterns in Gilan province, Iran. Using wavelet signal analysis, including continuous wavelet transforms (CWT), cross-wavelet transforms (XWT), wavelet coherence (WTC), and time-lag correlation analysis (TLCA), the research investigates temporal and frequency-domain relationships between these factors and regional climatic variables. A 73-year dataset (1951-2023) reveals cyclical patterns in SSN and SOI, correlating with significant 10-year periodicities in precipitation trends. The study further reveals ENSO and SSN's influence on long-term temperature and dew point fluctuations. While sunspot activity and ENSO both modulate climate variability, the study's scope is limited to Gilan province and excludes other atmospheric drivers or anthropogenic influences, which may also affect local hydrology. The findings suggest integrating solar and climatic indices into predictive models could improve long-term climate forecasts, supporting water resource management in this climate-sensitive region. This research provides novel insights for policymakers to address water-related challenges amid climatic variability by applying advanced wavelet methods to analyze multi-decadal interactions.

Indexed as

Dew pointEl Niño-Southern oscillation (ENSO)Precipitation patternsSunspot activity (SSN)TemperatureTime lag correlation analysis (TLCA)Wavelet signal analysis

Identifiers

PMID40595929
PMCPMC12214578

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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.