DOI: 10.5194/hess-18-4671-2014
Scopus记录号: 2-s2.0-84913554488
论文题名: The effect of flow and orography on the spatial distribution of the very short-term predictability of rainfall from composite radar images
作者: Foresti L ; , Seed A
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2014
卷: 18, 期: 11 起始页码: 4671
结束页码: 4686
语种: 英语
Scopus关键词: Clustering algorithms
; Fast Fourier transforms
; Lagrange multipliers
; Meteorological radar
; Radio communication
; Spatial distribution
; Stochastic models
; Stochastic systems
; Velocity
; Autocorrelation functions
; K-Means clustering algorithm
; Lagrangian coordinate
; Multiplicative cascades
; Spatial power spectrums
; Spatially inhomogeneous
; Stochastic simulations
; Victoria , Australia
; Rain
; Fourier transform
; orography
; power law
; precipitation assessment
; radar imagery
; rainfall
; spatial distribution
; spatial resolution
; weather forecasting
; Australia
; Victoria [Australia]
英文摘要: The spatial distribution and scale dependence of the very short-term predictability of precipitation by Lagrangian persistence of composite radar images is studied under different flow regimes in connection with the presence of orographic features. Data from the weather radar composite of eastern Victoria, Australia, a 500 × 500 km2 domain at 10 min temporal and 2 × 2 km2 spatial resolutions, covering the period from February 2011 to October 2012, were used for the analyses. The scale dependence of the predictability of precipitation is considered by decomposing the radar rainfall field into an eight-level multiplicative cascade using a fast Fourier transform. The rate of temporal development of precipitation in Lagrangian coordinates is estimated at each level of the cascade under different flow regimes, which are stratified by applying a k-means clustering algorithm on the diagnosed velocity fields. The predictability of precipitation is measured by its lifetime, which is derived by integrating the Lagrangian auto-correlation function. The lifetimes were found to depend on the scale of the feature as a power law, which is known as dynamic scaling, and to vary as a function of flow regime. The lifetimes also exhibit significant spatial variability and are approximately a factor of 2 longer on the upwind compared with the downwind slopes of terrain features. The scaling exponent of the spatial power spectrum also shows interesting geographical differences. These findings provide opportunities to perform spatially inhomogeneous stochastic simulations of space-time precipitation to account for the presence of orography, which may be integrated into design storm simulations and stochastic precipitation nowcasting systems. © Author(s) 2014. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78069
Appears in Collections: 气候变化事实与影响
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作者单位: Royal Meteorological Institute of Belgium, Brussels, Belgium; Bureau of Meteorology, Centre for Australian Weather and Climate Research, Melbourne, Australia
Recommended Citation:
Foresti L,, Seed A. The effect of flow and orography on the spatial distribution of the very short-term predictability of rainfall from composite radar images[J]. Hydrology and Earth System Sciences,2014-01-01,18(11)