Evidence map›Paper›PMID 40594717›Full record

ArticleScientific reports2025

Comprehensive global assessment of precipitation trend and pattern variability considering their distribution dynamics.

Mohammad Nazeri Tahroudi

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. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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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

1 author.

Mohammad Nazeri TahroudiDepartment of Water Engineering, Lorestan University, Khorramabad, Iran. nazeri.mh@lu.ac.ir.ORCID http://orcid.org/0000-0002-6871-2771

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding global precipitation patterns is crucial for addressing climate change impacts and ensuring water and food security. This study analyzes spatiotemporal variations, stationarity, heteroscedasticity, and distribution changes in global precipitation from 1891 to 2019 using multiple statistical approaches. Spatiotemporal analysis of global precipitation variability revealed divergent trends, with 32% and 21% of global regions exhibiting statistically significant increases (p < 0.05) and decreases in precipitation respectively (Based on modified Mann-Kendall test). Precipitation trends predominantly increased, particularly pronounced at 30°N latitude. Temporal regime shifts, identified through Pettitt tests and CUSUM analysis, clustered predominantly between 1955 and 1987, during which 38% of global regions experienced significant precipitation changes. Stationarity assessments further indicated non-stationary behavior in 78% of studied regions based of ADF and KPSS tests, suggesting widespread temporal dependency in precipitation patterns. These findings collectively highlight both the spatial heterogeneity and temporal non-stationarity characterizing contemporary hydroclimatic changes. Global precipitation analysis revealed pronounced spatial heterogeneity, with only 7% of regions showing regular precipitation concentration compared to 60% with moderate concentration and 33% exhibiting irregular regimes based on PCI index. Temporal analysis identified a significant shift (p < 0.05) toward increasingly irregular patterns in recent decades, suggesting intensifying hydroclimatic variability under climate change. Examination of statistical distributions across temporal breakpoints showed significant changes in 59% of cases, particularly concentrated in northern Asia (increasing), northern/northeastern North America (mostly increasing), South America (), the Middle East (Mostly decreasing), and Africa (Mostly decreasing). These findings collectively demonstrate both increasing spatiotemporal precipitation variability and fundamental changes in statistical properties, with notable regional disparities in distributional changes. The observed heteroscedasticity patterns further underscore the non-stationary nature of contemporary precipitation regimes.

Indexed as

Change point detectionHeteroscedasticityPrecipitation variabilityStationarityStatistical distribution

Identifiers

PMID40594717
PMCPMC12216219

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LicenceCC BY-NC-ND
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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.