Evidence map›Paper›PMID 35672611›Full record

ArticleEnvironmental monitoring and assessment2022

Impact of monsoon teleconnections on regional rainfall and vegetation dynamics in Haryana, India.

Abhilash Singh Chauhan, Surender Singh, Rajesh Kumar Singh Maurya, Abhishek Danodia

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In one paragraph

Article in Environmental monitoring and assessment, 2022. 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
1.4field-weighted citation impact, top 21% of its field
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, 13 citations in OpenAlex.

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

4 authors at 3 institutions in 1 country.

Abhilash Singh ChauhanDepartment of Agricultural Meteorology, CCS Haryana Agricultural University, Hisar-125004, Haryana, India. abhilashaanu92@hau.ac.in.ORCID http://orcid.org/0000-0002-2902-233X
Surender SinghDepartment of Agricultural Meteorology, CCS Haryana Agricultural University, Hisar-125004, Haryana, India.
Rajesh Kumar Singh MauryaSchool of Earth Ocean and Climate Sciences, Indian Institute of Technology (IIT), Bhubaneswar, Odisha, India.
Abhishek DanodiaAgriculture & Soils Department, Indian Institute of Remote Sensing (IIRS), Dehradun, India.
Chaudhary Charan Singh Haryana Agricultural University · INIndian Institute of Remote Sensing · INIndian Institute of Technology Bhubaneswar · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Our study has investigated the impact of El Niño-Southern Oscillation (ENSO) on spatio-temporal dynamics of Indian summer monsoon rainfall (ISMR) as well as vegetation for a period of 1980 to 2019 at regional scale in Haryana, India. The gridded rainfall datasets of India Meteorological Department (IMD) were examined on monthly and seasonal scale using various statistical methods like mean climatology, coefficient of variation, slope of linear, Sen's slope, Mann-Kendall Z statistic, and hierarchical cluster analysis. The influence of ENSO on spatial distribution of ISMR was observed, where we found increasing and decreasing rainfall patterns during La Niña and El Niño years, respectively. We attempted to establish a link between ISMR and various teleconnections using time series of the National Oceanic and Atmospheric Administration (NOAA) Physical Sciences Laboratory, and statistically significant and positive correlation was observed with the Southern Oscillation Index (SOI), whereas significantly negative correlations were observed with SST of Niño 3, Niño 3.4, and Niño 4 regions. The gridded datasets of the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis V5 (ERA5) were used to evaluate the influence of ENSO on atmospheric dynamics using lower and upper tropospheric wind circulation (850 hPa and200 hpa), vertically integrated moisture transport (VIMT), and surface moisture flux (SMF). We have used satellite-based normalised difference vegetation index (NDVI) datasets of the Global Inventory Monitoring and Modeling System (GIMMS) to investigate the impact of ENSO on vegetation dynamics of Haryana and found that NDVI values were higher and lower in case of La Niña and El Niño years, respectively.

Indexed as

El Nino-Southern OscillationEnvironmental MonitoringIndiaSeasonsWeatherEl NinoENSONDVIRainfallSpatio-temporal analysis

Identifiers

PMID35672611
OpenAlexW4281671893

What OpenQuestion holds

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Registered trials

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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.