HR: 1330h
AN: H23A-07    [Abstracts]
TI: A continuous spatial-temporal stochastic rainfall model based on historical data
AU: * Zhang, Z
EM: zpzhang@stanfordalumni.org
AF: University of Chicago, CISES 5734 S Ellis Ave, Chicago, IL 60637 United States
AU: Switzer, P
AF: Stanford University, Sequoia Hall 390 Serra Mall, Stanford, CA 94305 United States
AB: The goal of the work is to model continuous spatial-temporal rainfall characteristics on the watershed scale, and present the model as a tool for further analysis of rainfall properties such as spatial and temporal average and extreme values of rainfall intensities, and for simulating rainfall scenarios to be used by models that study the response and evolution of rainfall-sensitive systems. The modeled rainfall process is event-based and has a hierarchical structure: rainfall occurs in storms, which in turn consist of rain generating patches, each having a random size and a random rainfall intensity. Randomly located patches form a spatial Boolean field; the storm is modeled by a spatial field moving across the region of interest. Fitting the spatially-temporally continuous model makes use of relations between spatial objects (rain patches) and their linear transects, which correspond to historical records at fixed rain gauges. Hourly historical data at eight stations in Alabama are used for illustrating estimation, properties and possible applications of the model.
DE: 1854 Precipitation (3354)
DE: 1869 Stochastic processes
DE: 3329 Mesoscale meteorology
SC: Hydrology [H]
MN: 2005 Joint Assembly