✍ Scribed by Galambosi, Agnes; Duckstein, Lucien; Özelkan, Ertunga C.; Bogardi, Istvan
No coin nor oath required. For personal study only.
A fuzzy rule-based model (FRBM) is developed to analyse local monthly precipitation events conditioned on macrocirculation patterns and El Nin ˜o-Southern Oscillation (ENSO). A case study in Arizona is presented to illustrate the 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 given month; the output of the model is an estimate of local monthly precipitation. After analysing the basic properties of the precipitation events, fuzzy rules are constructed, and then the results are interpreted and compared with those of a multivariate linear regression model. Using two goodness-of-fit criteria, first, the root mean squared error (RMSE) and then the correlation between the model results and the observed values, the FRBM is found to perform better than the multiple linear regression model for the Arizona case investigated. The results show that the FRBM can provide a good basis for future work to downscale general circulation model results to study local precipitation under climate change. The results of using only SOI lags or CP frequencies as inputs, which are also presented here, clearly show how much the results are improved using both inputs jointly instead of only one.
📜 SIMILAR VOLUMES
State commodity promotions, which promote food and agricultural products produced within a state's borders, are becoming widespread. Even though they are funded through tax revenues, there is little analysis on their effects. This study evaluates consumer awareness of Arizona's program and their pre