%0 Journal Article %1 Chen2016Spatiotemporal %A Chen, Y. %A Wang, J. H. %A Xiao, W. H. %A Zhou, Y. Y. %A Wang, L. T. %A Song, X. Y. %D 2016 %J IOP Conference Series: Earth and Environmental Science %K precip climate climatology flooding obs China %P 012060+ %R 10.1088/1755-1315/39/1/012060 %T Spatiotemporal variation of precipitation based on three indicators in the flood season in Beijing %U http://dx.doi.org/10.1088/1755-1315/39/1/012060 %V 39 %X This paper attempts to analyze the spatiotemporal variation of precipitation in Beijing in terms of three indicators, i.e., the total precipitation, the maximum daily precipitation, and the maximum 5h precipitation in the flood season, with data collected from 20 meteorological stations from 1975 to 2012 (June to September). The Mann-Kendall nonparametric test, the linear regression, and five-year moving average were used. The results showed that: (i) the three indicators showed a decreasing trend; however, from 1975 to 1995 and from 1995 to 2012, the precipitation in the flood season showed an increasing trend with an increasing rate of 3.36 and 2.90mm/a, respectively. (ii) The indicators demonstrated a similar spatial variation. The high value precipitation areas were mainly in the northern and central parts of the city. The central districts had increasing centers with maximum increasing rates of 0.35, 0.65, and 0.49mm/a, respectively. However, the northern part exhibited different degrees of decreasing trends. (iii) The increase in the precipitation in the city center was mainly due to the urban heat island effect and the change in the underlying surface. The temperature gradient was intensified due to the topography in the city center and the northern suburb, causing a decreasing trend of precipitation.

@article{Chen2016Spatiotemporal, abstract = {This paper attempts to analyze the spatiotemporal variation of precipitation in Beijing in terms of three indicators, i.e., the total precipitation, the maximum daily precipitation, and the maximum 5h precipitation in the flood season, with data collected from 20 meteorological stations from 1975 to 2012 (June to September). The Mann-Kendall nonparametric test, the linear regression, and five-year moving average were used. The results showed that: (i) the three indicators showed a decreasing trend; however, from 1975 to 1995 and from 1995 to 2012, the precipitation in the flood season showed an increasing trend with an increasing rate of 3.36 and 2.90mm/a, respectively. (ii) The indicators demonstrated a similar spatial variation. The high value precipitation areas were mainly in the northern and central parts of the city. The central districts had increasing centers with maximum increasing rates of 0.35, 0.65, and 0.49mm/a, respectively. However, the northern part exhibited different degrees of decreasing trends. (iii) The increase in the precipitation in the city center was mainly due to the urban heat island effect and the change in the underlying surface. The temperature gradient was intensified due to the topography in the city center and the northern suburb, causing a decreasing trend of precipitation.}, added-at = {2018-06-18T21:23:34.000+0200}, author = {Chen, Y. and Wang, J. H. and Xiao, W. H. and Zhou, Y. Y. and Wang, L. T. and Song, X. Y.}, biburl = {https://www.bibsonomy.org/bibtex/2ea9f670068b1ddb690fcf13750e83647/pbett}, citeulike-article-id = {14128322}, citeulike-linkout-0 = {http://dx.doi.org/10.1088/1755-1315/39/1/012060}, doi = {10.1088/1755-1315/39/1/012060}, interhash = {fd4b980d0ff90de26c15f3f91c9ed5d3}, intrahash = {ea9f670068b1ddb690fcf13750e83647}, issn = {1755-1307}, journal = {IOP Conference Series: Earth and Environmental Science}, keywords = {precip climate climatology flooding obs China}, month = aug, pages = {012060+}, posted-at = {2016-09-01 16:16:46}, priority = {2}, timestamp = {2018-08-22T09:32:01.000+0200}, title = {Spatiotemporal variation of precipitation based on three indicators in the flood season in Beijing}, url = {http://dx.doi.org/10.1088/1755-1315/39/1/012060}, volume = 39, year = 2016 }