DOI: 10.1002/jgrd.50723
论文题名: A stochastic fractional dynamics model of space-time variability of rain
作者: Kundu P.K. ; Travis J.E.
刊名: Journal of Geophysical Research Atmospheres
ISSN: 21698996
出版年: 2013
卷: 118, 期: 18 起始页码: 10277
结束页码: 10295
语种: 英语
英文关键词: anomalous diffusion
; ground validation
; radar and rain gauge data
; rainfall statistics
; spectral model
; TRMM precipitation data
Scopus关键词: Difference equations
; Gages
; NASA
; Radar
; Rain gages
; Random processes
; Statistics
; Stochastic models
; Stochastic systems
; Anomalous diffusion
; Ground validations
; Rain gauge data
; Rainfall statistics
; Spectral modeling
; Trmm precipitation datum
; Rain
; estimation method
; parameterization
; radar imagery
; raingauge
; spatiotemporal analysis
; statistical analysis
; stochasticity
; timescale
; tropical environment
; Australia
; Melbourne
; Pacific Ocean
; Victoria [Australia]
英文摘要: Rainfall varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, which allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and time scales. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and on the Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to fit the second moment statistics of radar data at the smaller spatiotemporal scales. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well at these scales without any further adjustment. Key Points Space-time variability of rainfall is described by a random processThe process is governed by a stochastic equation of fractional orderThe model spectrum can fit the statistics of both radar and rain gauge data ©2013. American Geophysical Union. All Rights Reserved. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/63320
Appears in Collections: 影响、适应和脆弱性 气候减缓与适应
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作者单位: Joint Center for Earth Systems Technology, University of Maryland, Baltimore County, 5523 Research Park Drive, Baltimore, MD 21228, United States; Joint Center for Earth Systems Technology, NASA Goddard Space Flight Center, Greenbelt, MD, United States; Department of Mathematics and Statistics, University of Maryland, Baltimore County, Baltimore, MD, United States
Recommended Citation:
Kundu P.K.,Travis J.E.. A stochastic fractional dynamics model of space-time variability of rain[J]. Journal of Geophysical Research Atmospheres,2013-01-01,118(18)