EFFECTS OF AN INDEX OF ATMOSPHERIC CIRCULATION ON STOCHASTIC PROPERTIES OF PRECIPITATION

Conditional chain-dependent processes are fit to time series of daily precipitation amounts given an index of large-scale atmospheric circul ation (i.e., either below or above normal monthly mean sea level press ure). Precipitation data for January at several locations in Californi a are analyzed. The two conditional daily models differ both in terms of the parameters of the occurrence process and of the intensity proce ss. Each of these daily effects contributes to changes in the distribu tion of monthly total precipitation associated with the circulation in dex. The process induced by combining the conditional daily models pro duces a variance for monthly total precipitation much closer to the ob served value than that for the corresponding unconditional chain-depen dent model.