RAINFALL DISAGGREGATION USING ADJUSTING PROCEDURES ON A POISSON CLUSTER MODEL - Koutsoyiannis D.; Onof C. (My University, 2001)
A disaggregation methodology for the generation of hourly data that aggregate up to given daily totals is developed. This combines a rainfall simulation model based upon the Bartlett-Lewis process with proven techniques developed for the purpose of adjusting the finer scale (hourly) values so as to obtain the required coarser scale (daily) values. The methodology directly answers the question of the possible extension of the short hourly time-series with the use of longer-term daily data at the same point and provides the theoretical basis for an operational use of this methodology when no hourly data are available. The algorithm has been validated in full test mode in the case where hourly data are available. Specifically, two case studies (from the UK and US) are examined whose results indicate a good performance of the methodology in preserving the most important statistical properties of the rainfall process.
Keywords: RAINFALL; DISAGGREGATION; STOCHASTIC PROCESSES; POINT PROCESSES