Understanding temporal and spatial complexity of precipitation distribution in Xinjiang, China
Theoretical and Applied Climatology，2016，123（2）：321–333 | 2016年01月28日 | 10.1007/s00704-014-1364-z
Based on the observed data during the period from 1958 to 2012 in Xinjiang, China, we investigated the temporal and spatial complexity of precipitation distribution by using an integrative approach combining the phase space reconstruction (PSR), correlation dimension (CD), variogram, and cokriging interpolation. The CD values showed that the precipitation dynamic is a complex and chaotic system, and its complexity decreases along with the increase of temporal scale. To describe the precipitation dynamics, it needs at least four independent variables at daily scale, and at least three independent variables at monthly scale, whereas at least two independent variables are needed at seasonal and annual scales. The spatial variation of CD value at daily and monthly scales is described by the exponential variogram model, whereas that at seasonal and annual scale needs to be respectively described by the spherical and Gaussian variogram model. The higher CD values mainly distribute on complex landform such as mountain areas, whereas the lower CD values mainly distribute on the flat landform such as basin area, which indicate that the spatial complexity of precipitation distribution is derived from the complex landform.
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