Fuzzified effect of ENSO and macrocirculation patterns on precipitation: An Arizona case study

A fuzzy rule-based model (FRBM) is developed to analyse local monthly preci pitation events conditioned on macrocirculation patterns and El Nino-Southe rn Oscillation (ENSO). A case study in Arizona is presented to illustrate t he methodology. The inputs of the FRBM are those Southern Oscillation Index (SOI) values which have high absolute lag correlation with monthly Arizona precipitation and the frequencies of all circulation patterns (CPs) in a g iven month; the output of the model is an estimate of local monthly precipi tation. After analysing the basic properties of the precipitation events, f uzzy rules are constructed, and then the results are interpreted and compar ed with those of a multivariate linear regression model. Using two goodness -of-fit criteria, first, the root mean squared error (RMSE) and then the co rrelation between the model results and the observed values, the FRBM is fo und to perform better than the multiple linear regression model for the Ari zona case investigated. The results show that the FRBM can provide a good b asis for future work to downscale general circulation model results to stud y local precipitation under climate change. The results of using only SOI l ags or CP frequencies as inputs, which are also presented here, clearly sho w how much the results are improved using both inputs jointly instead of on ly one. Copyright (C) 1999 Royal Meteorological Society.