A STATISTICAL-MODEL FOR EXTREME PRECIPITATION

The Statistical distribution of 1-day (one reading in 24 hours) and 24 -hour (several readings in 24 hours) annual maxima is considered and a transformed extreme value type 1 distribution function (TDF) that inc ludes a probable maximum (PM) value is suggested. The distribution fun ction fits standardized annual maximum station values from Iceland and Washington State very well. A generalized distribution function, deri ved from the TDF, is suggested. To use it, two local parameters have t o be known; the 5-year event, M5, that must be picked from a map and a slope factor, C-i, that is a function of the coefficient of variation . The variation of C-i between independent observation stations is ass umed to be random, and guidelines on how a C-i may be selected are dis cussed, The generalized distribution function is used to calculate qua ntile estimates and a local probable maximum precipitation (PMP). Regi onal PMPs can be calculated by maximizing this value. Two independent sets of C-i's compare favorably: (1) a statistical set compiled from t he British Natural Environment Resource Council (NERC) PMP envelope an d (2) a meteorological set calculated from U.S. National Weather Servi ce estimates of PMP for Washington State, The regional PMP estimates c alculated from the generalized distribution also compare favorably wit h the NERC PMPs, except that the estimates for low M5 produce up to 33 % lower PMPs. This difference may be explained by a number of factors that are also discussed.