Intraseasonal Variability Associated with Wet Monsoons in Southeast Arizona

The intraseasonal evolution of the North American monsoon in southeast Arizona during the 1980-93 period is investigated using a neural network-based nonlinear classification technique known as the self-organizing map (SOM). The goal of the SOM algorithm is to discover meaningful low-dimensional structures hidden in the high-dimensional observations. Various daily lagged atmospheric fields (850-hPa meridional winds, 700-hPa specific humidity, 500-hPa geopotential heights, and 850-500-hPa thickness) for the summer season (June-July-August-September) of the 1980-93 period are used in the nonlinear classification of monsoon modes. Special emphasis is given to the wettest monsoon modes. The neural network classification successfully captures the multidimensional interaction of the atmospheric variables during the monsoon evolution, and shows monsoon ''bursts'' and ''breaks'' in a given year. Spectral analysis of daily summer rainfall in the study area reveals a significant peak in the 12-18-day band; a secondary and significant peak is also found near 40 days. Thus, monsoon bursts and breaks seem to be modulated by low-frequency variability.