in Sicily

• Main Author: Di Mauro
• Other Authors: The Pennsylvania State University CiteSeerX Archives
• Format: Text
• Language: English
• Subjects: North Atlantic; North Atlantic oscillation
• Online Access: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.623.6544; http://hydrologydays.colostate.edu/papers_2007/cancelliere_et_al_paper.pdf

Abstract. Drought monitoring and forecasting is essential for an effective drought preparedness and mitigation. The use of large-scale climatic patterns, such as El Nino Southern Oscillation (ENSO), North Atlantic Oscillation (NAO) or European Block-ing (EB), can potentially improve the forecasting of drought evolution in time and space, provided the influence of such indices on the climatic variability in a region is verified. In the present paper, a stochastic model for the seasonal forecasting of the Stan-dardized Precipitation Index (SPI), developed in previous works, is extended in order to include information from NAO index. In particular SPI forecasts at a generic time horizon M are analytically determined, in terms of conditional expectation, as a func-tion of a finite number of past observations of SPI and NAO, assuming a multivariate normal as the underlying distribution. In addition, an expression of the Mean Square Error (MSE) of prediction is also derived, which allows confidence intervals of pre-diction to be estimated. The forecasting performance of the model is verified by hindcasting observed SPI values computed on monthly areal average precipitation se-ries observed in Sicily and validation is carried out by repeatedly applying a jack-knife scheme. Preliminary results of the comparison between the model based only on the past observations of SPI values and the one that includes also the NAO index, seem to in-dicate a slight improvement of the latter model. Such results however cannot be con-sidered conclusive and further analyses are needed in order to better assess the use of NAO as a predictor for droughts in Sicily. 1.