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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...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8530289/ https://www.ncbi.nlm.nih.gov/pubmed/34673805 http://dx.doi.org/10.1371/journal.pone.0258549 |
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author | Pan, Ziwu Zhu, Jun Liu, Junjie Gu, Jiangyan Liu, Zhenzhen Qin, Fen Pan, Yu |
author_facet | Pan, Ziwu Zhu, Jun Liu, Junjie Gu, Jiangyan Liu, Zhenzhen Qin, Fen Pan, Yu |
author_sort | Pan, Ziwu |
collection | PubMed |
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 | Online Article Text |
id | pubmed-8530289 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-85302892021-10-22 Estimation of air temperature and the mountain-mass effect in the Yellow River Basin using multi-source data Pan, Ziwu Zhu, Jun Liu, Junjie Gu, Jiangyan Liu, Zhenzhen Qin, Fen Pan, Yu PLoS One Research Article 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. Public Library of Science 2021-10-21 /pmc/articles/PMC8530289/ /pubmed/34673805 http://dx.doi.org/10.1371/journal.pone.0258549 Text en © 2021 Pan et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Pan, Ziwu Zhu, Jun Liu, Junjie Gu, Jiangyan Liu, Zhenzhen Qin, Fen Pan, Yu Estimation of air temperature and the mountain-mass effect in the Yellow River Basin using multi-source data |
title | 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_short | 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 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8530289/ https://www.ncbi.nlm.nih.gov/pubmed/34673805 http://dx.doi.org/10.1371/journal.pone.0258549 |
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