Evidence map›Paper›PMID 31919374›Full record

ArticleScientific reports2020

Long-term spatio-temporal precipitation variations in China with precipitation surface interpolated by ANUSPLIN.

Binbin Guo, Jing Zhang, Xianyong Meng, Tingbao Xu, Yongyu Song

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
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  4. Estimation of above-ground carbon stock ofFrontiers in plant science · 2025
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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

5 authors.

Binbin GuoBeijing Laboratory of Water Resources Security, Capital Normal University, Beijing, 100048, China.
Jing ZhangBeijing Laboratory of Water Resources Security, Capital Normal University, Beijing, 100048, China. maggie2008zj@yahoo.com.
Xianyong MengCollege of Resources and Environmental Sciences, China Agricultural University (CAU), Beijing, 100094, China. xymeng@cau.edu.cn.
Tingbao XuFenner School of Environment and Society, The Australian National University, Canberra, ACT 2601, Australia.
Yongyu SongBeijing Laboratory of Water Resources Security, Capital Normal University, Beijing, 100048, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Climate changes significantly impact environmental and hydrological processes. Precipitation is one of the most significant climatic parameters and its variability and trends have great influences on environmental and socioeconomic development. We investigate the spatio-temporal variability of precipitation occurrence frequency, mean precipitation depth, PVI and total precipitation in China based on long-term precipitation series from 1961 to 2015. As China's topography is diverse and precipitation is affected by topography strongly, ANUSPLIN can model the effect of topography on precipitation effectively is adopted to generate the precipitation interpolation surface. Mann-Kendall trend analysis and simple linear regression was adopted to examine long-term trend for these indicators. The results indicate ANUSPLIN precipitation surface is reliable and the precipitation variation show different regional and seasonal trend. For example, there is a sporadic with decreasing frequency precipitation trend in spring and a uniform with increasing frequency trend in summer in Yangtze Plain, which may affect spring ploughing and alteration of flood risk for this main rice-production areas of China. In north-western China, there is a uniform with increasing precipitation frequency and intensity trend, which is beneficial for this arid region. Our study could be helpful for other counties with similar climate types.

Identifiers

PMID31919374
PMCPMC6952358

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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.