Spatial Distribution of Diurnal Rainfall Variation in Summer over China Using K-means Algorithm
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Abstract:
In order to obtain an objective spatial distribution map of diurnal rainfall variation, this study uses the Kmeans clustering algorithm to mine hourly gridded rainfall data over China. Firstly, a large enough number is used to cluster the hourly precipitation at each pixel. Then, according to the peak time of diurnal rainfall variation, the clusters with similar peak time are merged. Each merged cluster corresponds to one type of diurnal rainfall variation, and the locations of grid cells in each cluster form the map of diurnal rainfall variation over China. The results indicate that the characteristic of diurnal variation of rainfall amount is dominated by the diurnal variation of rainfall frequency. In addition, the regions prevailing nocturnal rainfall present a spatial pattern ranged from west to east, and the peak times of the nocturnal rainfall regions show a timedelay propagation from west to east. Taking an overlay analysis between the regions prevailing nocturnal rainfall and terrain, the spatial pattern of the regions prevailing nocturnal rainfall can be well explained by the propagation of the rain belt driven by the MPS (MountainPlain Solenoid) circulation. Overall, the results of this paper can provide clues for the mechanism study of diurnal rainfall variation and also provide a reference for studying the spatial distribution of diurnal rainfall variations in other regions.
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Supported by:Beijing E-Tiller Technology Development Co., Ltd.
Supported by:Beijing E-Tiller Technology Development Co., Ltd.