Estimation of air temperature and the mountain-mass effect in the Yellow River Basin using multi-source data.

Quantitative studies of the multiple factors influencing the mountain-mass effect, which causes higher temperatures in mountainous than non-mountainous regions, remain insufficient. This study estimated the air temperature in the Yellow River Basin, which spans three different elevation ranges, usin...

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Autores principales:	Ziwu Pan, Jun Zhu, Junjie Liu, Jiangyan Gu, Zhenzhen Liu, Fen Qin, Yu Pan
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/d8a4db907a99446f850cdc1f65a3cef1
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spelling	oai:doaj.org-article:d8a4db907a99446f850cdc1f65a3cef12021-12-02T20:16:40ZEstimation of air temperature and the mountain-mass effect in the Yellow River Basin using multi-source data.1932-620310.1371/journal.pone.0258549https://doaj.org/article/d8a4db907a99446f850cdc1f65a3cef12021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0258549https://doaj.org/toc/1932-6203Quantitative studies of the multiple factors influencing the mountain-mass effect, which causes higher temperatures in mountainous than non-mountainous regions, remain insufficient. This study estimated the air temperature in the Yellow River Basin, which spans three different elevation ranges, using multi-source data to address the uneven distribution of regional meteorological stations. The differences in mountain-mass effect for different geomorphic regions at the same altitude were then compared. The Manner-Kendall nonparametric test was used to analyse time series changes in temperature. Moreover, we employed the geographically weighted regression (GWR) model, with MODIS land-surface and air-temperature data, station-based meteorological data, vertical temperature gradients corresponding to the 2000-2015 period, and elevation data, to estimate the correlation between monthly mean surface temperature and air temperature in the Yellow River Basin. The following major results were obtained. (1) The GWR method and ground station-based observations enhanced the accuracy of air-temperature estimates with an error of only ± 0.74°C. (2) The estimated annual variations in the spatial distributions of 12-month average temperatures showed that the upper Tibetan Plateau is characterised by low annual air temperatures with a narrow spatial distribution, whereas north-eastern areas upstream of the Inner Mongolia Plateau are characterised by higher air temperatures. Changes in the average monthly air temperature were also high in the middle and lower reaches, with a narrow spatial distribution. (3) Considering the seasonal variation in the temperature lapse rate, the mountain-mass effect in the Yellow River Basin was very high. In the middle of each season, the variation of air temperature at a given altitude over the Tibetan Plateau was higher than that over the Loess Plateau and Jinji Mountain. The results of this study reveal the unique temperature characteristics of the Yellow River Basin according to its geomorphology. Furthermore, this research contributes to quantifying mountain-mass effects.Ziwu PanJun ZhuJunjie LiuJiangyan GuZhenzhen LiuFen QinYu PanPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 10, p e0258549 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Ziwu Pan Jun Zhu Junjie Liu Jiangyan Gu Zhenzhen Liu Fen Qin Yu Pan Estimation of air temperature and the mountain-mass effect in the Yellow River Basin using multi-source data.
description	Quantitative studies of the multiple factors influencing the mountain-mass effect, which causes higher temperatures in mountainous than non-mountainous regions, remain insufficient. This study estimated the air temperature in the Yellow River Basin, which spans three different elevation ranges, using multi-source data to address the uneven distribution of regional meteorological stations. The differences in mountain-mass effect for different geomorphic regions at the same altitude were then compared. The Manner-Kendall nonparametric test was used to analyse time series changes in temperature. Moreover, we employed the geographically weighted regression (GWR) model, with MODIS land-surface and air-temperature data, station-based meteorological data, vertical temperature gradients corresponding to the 2000-2015 period, and elevation data, to estimate the correlation between monthly mean surface temperature and air temperature in the Yellow River Basin. The following major results were obtained. (1) The GWR method and ground station-based observations enhanced the accuracy of air-temperature estimates with an error of only ± 0.74°C. (2) The estimated annual variations in the spatial distributions of 12-month average temperatures showed that the upper Tibetan Plateau is characterised by low annual air temperatures with a narrow spatial distribution, whereas north-eastern areas upstream of the Inner Mongolia Plateau are characterised by higher air temperatures. Changes in the average monthly air temperature were also high in the middle and lower reaches, with a narrow spatial distribution. (3) Considering the seasonal variation in the temperature lapse rate, the mountain-mass effect in the Yellow River Basin was very high. In the middle of each season, the variation of air temperature at a given altitude over the Tibetan Plateau was higher than that over the Loess Plateau and Jinji Mountain. The results of this study reveal the unique temperature characteristics of the Yellow River Basin according to its geomorphology. Furthermore, this research contributes to quantifying mountain-mass effects.
format	article
author	Ziwu Pan Jun Zhu Junjie Liu Jiangyan Gu Zhenzhen Liu Fen Qin Yu Pan
author_facet	Ziwu Pan Jun Zhu Junjie Liu Jiangyan Gu Zhenzhen Liu Fen Qin Yu Pan
author_sort	Ziwu Pan
title	Estimation of air temperature and the mountain-mass effect in the Yellow River Basin using multi-source data.
title_short	Estimation of air temperature and the mountain-mass effect in the Yellow River Basin using multi-source data.
title_full	Estimation of air temperature and the mountain-mass effect in the Yellow River Basin using multi-source data.
title_fullStr	Estimation of air temperature and the mountain-mass effect in the Yellow River Basin using multi-source data.
title_full_unstemmed	Estimation of air temperature and the mountain-mass effect in the Yellow River Basin using multi-source data.
title_sort	estimation of air temperature and the mountain-mass effect in the yellow river basin using multi-source data.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/d8a4db907a99446f850cdc1f65a3cef1
work_keys_str_mv	AT ziwupan estimationofairtemperatureandthemountainmasseffectintheyellowriverbasinusingmultisourcedata AT junzhu estimationofairtemperatureandthemountainmasseffectintheyellowriverbasinusingmultisourcedata AT junjieliu estimationofairtemperatureandthemountainmasseffectintheyellowriverbasinusingmultisourcedata AT jiangyangu estimationofairtemperatureandthemountainmasseffectintheyellowriverbasinusingmultisourcedata AT zhenzhenliu estimationofairtemperatureandthemountainmasseffectintheyellowriverbasinusingmultisourcedata AT fenqin estimationofairtemperatureandthemountainmasseffectintheyellowriverbasinusingmultisourcedata AT yupan estimationofairtemperatureandthemountainmasseffectintheyellowriverbasinusingmultisourcedata
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Estimation of air temperature and the mountain-mass effect in the Yellow River Basin using multi-source data.

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