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Long-term spatio-temporal precipitation variations in China with precipitation surface interpolated by ANUSPLIN
Climate changes significantly impact environmental and hydrological processes. Precipitation is one of the most significant climatic parameters and its variability and trends have great influences on environmental and socioeconomic development. We investigate the spatio-temporal variability of preci...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6952358/ https://www.ncbi.nlm.nih.gov/pubmed/31919374 http://dx.doi.org/10.1038/s41598-019-57078-3 |
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author | Guo, Binbin Zhang, Jing Meng, Xianyong Xu, Tingbao Song, Yongyu |
author_facet | Guo, Binbin Zhang, Jing Meng, Xianyong Xu, Tingbao Song, Yongyu |
author_sort | Guo, Binbin |
collection | PubMed |
description | Climate changes significantly impact environmental and hydrological processes. Precipitation is one of the most significant climatic parameters and its variability and trends have great influences on environmental and socioeconomic development. We investigate the spatio-temporal variability of precipitation occurrence frequency, mean precipitation depth, PVI and total precipitation in China based on long-term precipitation series from 1961 to 2015. As China’s topography is diverse and precipitation is affected by topography strongly, ANUSPLIN can model the effect of topography on precipitation effectively is adopted to generate the precipitation interpolation surface. Mann–Kendall trend analysis and simple linear regression was adopted to examine long-term trend for these indicators. The results indicate ANUSPLIN precipitation surface is reliable and the precipitation variation show different regional and seasonal trend. For example, there is a sporadic with decreasing frequency precipitation trend in spring and a uniform with increasing frequency trend in summer in Yangtze Plain, which may affect spring ploughing and alteration of flood risk for this main rice-production areas of China. In north-western China, there is a uniform with increasing precipitation frequency and intensity trend, which is beneficial for this arid region. Our study could be helpful for other counties with similar climate types. |
format | Online Article Text |
id | pubmed-6952358 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-69523582020-01-13 Long-term spatio-temporal precipitation variations in China with precipitation surface interpolated by ANUSPLIN Guo, Binbin Zhang, Jing Meng, Xianyong Xu, Tingbao Song, Yongyu Sci Rep Article Climate changes significantly impact environmental and hydrological processes. Precipitation is one of the most significant climatic parameters and its variability and trends have great influences on environmental and socioeconomic development. We investigate the spatio-temporal variability of precipitation occurrence frequency, mean precipitation depth, PVI and total precipitation in China based on long-term precipitation series from 1961 to 2015. As China’s topography is diverse and precipitation is affected by topography strongly, ANUSPLIN can model the effect of topography on precipitation effectively is adopted to generate the precipitation interpolation surface. Mann–Kendall trend analysis and simple linear regression was adopted to examine long-term trend for these indicators. The results indicate ANUSPLIN precipitation surface is reliable and the precipitation variation show different regional and seasonal trend. For example, there is a sporadic with decreasing frequency precipitation trend in spring and a uniform with increasing frequency trend in summer in Yangtze Plain, which may affect spring ploughing and alteration of flood risk for this main rice-production areas of China. In north-western China, there is a uniform with increasing precipitation frequency and intensity trend, which is beneficial for this arid region. Our study could be helpful for other counties with similar climate types. Nature Publishing Group UK 2020-01-09 /pmc/articles/PMC6952358/ /pubmed/31919374 http://dx.doi.org/10.1038/s41598-019-57078-3 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Guo, Binbin Zhang, Jing Meng, Xianyong Xu, Tingbao Song, Yongyu Long-term spatio-temporal precipitation variations in China with precipitation surface interpolated by ANUSPLIN |
title | Long-term spatio-temporal precipitation variations in China with precipitation surface interpolated by ANUSPLIN |
title_full | Long-term spatio-temporal precipitation variations in China with precipitation surface interpolated by ANUSPLIN |
title_fullStr | Long-term spatio-temporal precipitation variations in China with precipitation surface interpolated by ANUSPLIN |
title_full_unstemmed | Long-term spatio-temporal precipitation variations in China with precipitation surface interpolated by ANUSPLIN |
title_short | Long-term spatio-temporal precipitation variations in China with precipitation surface interpolated by ANUSPLIN |
title_sort | long-term spatio-temporal precipitation variations in china with precipitation surface interpolated by anusplin |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6952358/ https://www.ncbi.nlm.nih.gov/pubmed/31919374 http://dx.doi.org/10.1038/s41598-019-57078-3 |
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