Regional Agroclimate Characteristic and Its Multiple Teleconnections: A Case Study in the Jianghan Plain (JHP) Region

Agricultural production depends on local agroclimatic conditions to a great extent, affected by ENSO and other ocean-atmospheric climate modes. This paper analyzed the spatio-temporal distributions of climate elements in the Jianghan Plain (JHP), Central China, and explored the impacts from teleconn...

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Published in:Water
Main Authors: Wenhui Li, Dongguo Shao, Wenquan Gu, Donghao Miao
Format: Text
Language:English
Published: Multidisciplinary Digital Publishing Institute 2021
Subjects:
Online Access:https://doi.org/10.3390/w13192789
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spelling ftmdpi:oai:mdpi.com:/2073-4441/13/19/2789/ 2023-08-20T04:04:36+02:00 Regional Agroclimate Characteristic and Its Multiple Teleconnections: A Case Study in the Jianghan Plain (JHP) Region Wenhui Li Dongguo Shao Wenquan Gu Donghao Miao agris 2021-10-08 application/pdf https://doi.org/10.3390/w13192789 EN eng Multidisciplinary Digital Publishing Institute Water and Climate Change https://dx.doi.org/10.3390/w13192789 https://creativecommons.org/licenses/by/4.0/ Water; Volume 13; Issue 19; Pages: 2789 agricultural production agroclimatic condition ENSO teleconnection quantile regression Text 2021 ftmdpi https://doi.org/10.3390/w13192789 2023-08-01T02:54:08Z Agricultural production depends on local agroclimatic conditions to a great extent, affected by ENSO and other ocean-atmospheric climate modes. This paper analyzed the spatio-temporal distributions of climate elements in the Jianghan Plain (JHP), Central China, and explored the impacts from teleconnection patterns, aimed at providing references for dealing with climate change and guiding agricultural activities. Both linear and multifactorial regression models were constructed based on the frequentist quantile regression and Bayesian quantile regression method, with the daily meteorological data sets of 17 national stations in the plain and teleconnection climate characteristic indices. The results showed that precipitation in JHP had stronger spatial variability than evapotranspiration. El Niño probably induced less precipitation in summer while the weakening Arctic Oscillation might lead to more summertime precipitation. The Nash-Sutcliffe efficiency (NSE) of the multifactorial and linear regression model at the median level were 0.42–0.56 and 0.12–0.18, respectively. The mean relative error (MRE) ranged −2.95–−0.26% and −7.83–0.94%, respectively, indicating the much better fitting accuracy of the multiple climatic factors model. Meanwhile it confirmed that the agricultural climate in JHP was under the influence from multiple teleconnection patterns. Text Arctic Climate change MDPI Open Access Publishing Arctic Nash ENVELOPE(-62.350,-62.350,-74.233,-74.233) Sutcliffe ENVELOPE(-81.383,-81.383,50.683,50.683) Water 13 19 2789
institution Open Polar
collection MDPI Open Access Publishing
op_collection_id ftmdpi
language English
topic agricultural production
agroclimatic condition
ENSO
teleconnection
quantile regression
spellingShingle agricultural production
agroclimatic condition
ENSO
teleconnection
quantile regression
Wenhui Li
Dongguo Shao
Wenquan Gu
Donghao Miao
Regional Agroclimate Characteristic and Its Multiple Teleconnections: A Case Study in the Jianghan Plain (JHP) Region
topic_facet agricultural production
agroclimatic condition
ENSO
teleconnection
quantile regression
description Agricultural production depends on local agroclimatic conditions to a great extent, affected by ENSO and other ocean-atmospheric climate modes. This paper analyzed the spatio-temporal distributions of climate elements in the Jianghan Plain (JHP), Central China, and explored the impacts from teleconnection patterns, aimed at providing references for dealing with climate change and guiding agricultural activities. Both linear and multifactorial regression models were constructed based on the frequentist quantile regression and Bayesian quantile regression method, with the daily meteorological data sets of 17 national stations in the plain and teleconnection climate characteristic indices. The results showed that precipitation in JHP had stronger spatial variability than evapotranspiration. El Niño probably induced less precipitation in summer while the weakening Arctic Oscillation might lead to more summertime precipitation. The Nash-Sutcliffe efficiency (NSE) of the multifactorial and linear regression model at the median level were 0.42–0.56 and 0.12–0.18, respectively. The mean relative error (MRE) ranged −2.95–−0.26% and −7.83–0.94%, respectively, indicating the much better fitting accuracy of the multiple climatic factors model. Meanwhile it confirmed that the agricultural climate in JHP was under the influence from multiple teleconnection patterns.
format Text
author Wenhui Li
Dongguo Shao
Wenquan Gu
Donghao Miao
author_facet Wenhui Li
Dongguo Shao
Wenquan Gu
Donghao Miao
author_sort Wenhui Li
title Regional Agroclimate Characteristic and Its Multiple Teleconnections: A Case Study in the Jianghan Plain (JHP) Region
title_short Regional Agroclimate Characteristic and Its Multiple Teleconnections: A Case Study in the Jianghan Plain (JHP) Region
title_full Regional Agroclimate Characteristic and Its Multiple Teleconnections: A Case Study in the Jianghan Plain (JHP) Region
title_fullStr Regional Agroclimate Characteristic and Its Multiple Teleconnections: A Case Study in the Jianghan Plain (JHP) Region
title_full_unstemmed Regional Agroclimate Characteristic and Its Multiple Teleconnections: A Case Study in the Jianghan Plain (JHP) Region
title_sort regional agroclimate characteristic and its multiple teleconnections: a case study in the jianghan plain (jhp) region
publisher Multidisciplinary Digital Publishing Institute
publishDate 2021
url https://doi.org/10.3390/w13192789
op_coverage agris
long_lat ENVELOPE(-62.350,-62.350,-74.233,-74.233)
ENVELOPE(-81.383,-81.383,50.683,50.683)
geographic Arctic
Nash
Sutcliffe
geographic_facet Arctic
Nash
Sutcliffe
genre Arctic
Climate change
genre_facet Arctic
Climate change
op_source Water; Volume 13; Issue 19; Pages: 2789
op_relation Water and Climate Change
https://dx.doi.org/10.3390/w13192789
op_rights https://creativecommons.org/licenses/by/4.0/
op_doi https://doi.org/10.3390/w13192789
container_title Water
container_volume 13
container_issue 19
container_start_page 2789
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