13th Conference on Applied Climatology and the 10th Conference on Aviation, Range, and Aerospace Meteorology

Tuesday, 14 May 2002: 9:00 AM
Stochastic Daily Rainfall Generation in Southeast Arizona
Huey-hong Hsieh, Univ. of Arizona, Tucson, AZ; and J. Stone, P. Guertin, and D. D. Slack
Thunderstorm rainfall in semi-arid area has very high spatial and temporal variability. Knowledge of the spatial characteristics of thunderstorm rainfall is important for the increasing demands of distributed hydrological modeling. Rainfall data from the semiarid USDA-ARS Walnut Gulch Experimental Watershed (WGEW) are used to investigate the spatial characteristics of thunderstorm rainfall in southeast Arizona and to develop a daily thunderstorm rainfall generator. WGEW has a very dense rain-gage network (1 gage per 2 km2) and very comprehensive historical records (over 40 years). These data have been used to identify the following physical characteristics of thunderstorm rainfall: the transition probabilities, thunderstorm cell size, orientation, maximum rainfall depth within a storm cell and storm center location. The following statistical characteristics have been identified from an analysis of the WGEW data: the storm center locations on WGEW have a Poisson distribution, the maximum depth within a storm cell has a lognormal distribution, the shape of a storm cell is elliptical with an average major axis length to the minor axis length ratio of 1.55 and the orientation of a storm cell is primarily NW or NE. The storm coverage and the maximum rainfall depth within a storm cell have a linear relationship after a logarithmic transformation. Storm occurrences have higher frequencies during the last two weeks of July and the first two weeks of August than other wet periods (July ~ September). The stochastic daily summer rainfall generator being developed based on the statistical characteristics above is being tested by comparing the simulation results with long-term historical records of representative gages on WGEW.

Supplementary URL: