The impact of ENSO and macrocirculation patterns on precipitation under climate change

The possible impact of El Niño-Southern Oscillation (ENSO) and macrocirculation patterns (CPs) on local precipitation are examined and analyzed here under climate change conditions. First the relationship between the input and output variables under present conditions is established using two models, a fuzzy rule-based model (FRBM) and a multivariate linear regression model (MLRM), then this historical relationship is extended under climate change conditions. The input variables for these models consist of lagged ENSO-data (represented by the Southern Oscillation Index, SOI) and 500 hPa height data clustered into macrocirculation patterns over the western United States, while the output is an estimate of monthly local precipitation at selected Arizona stations. To overcome the lack of SOI data under climate change, several scenarios are constructed by perturbing the historical SOI data in a design of experiments framework. The results of the experimental design show that, in general, the precipitation amount seems to decrease under climate change. While the stations and months have differences, as expected, the perturbed scenarios do not show significant differences.