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...

Full description

Bibliographic Details
Published in:Water
Main Authors: Wenhui Li, Dongguo Shao, Wenquan Gu, Donghao Miao
Format: Article in Journal/Newspaper
Language:English
Published: MDPI AG 2021
Subjects:
agricultural production
agroclimatic condition
ENSO
teleconnection
quantile regression
Hydraulic engineering
TC1-978
Water supply for domestic and industrial purposes
TD201-500
Arctic
Nash
Sutcliffe
Climate change
Online Access:https://doi.org/10.3390/w13192789
https://doaj.org/article/8a853cbf6a0a4f92a5b264187862e7f7
Description
Summary: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.

Similar Items