SPI-based drought category prediction using loglinear models

Loglinear modeling for three-dimensional contingency tables was used with data from 14 rainfall stations located in Alentejo and Algarve region, southern of Portugal, for short term prediction of drought severity classes. Loglinear models were fitted to drought class transitions derived from Standardized Precipitation Index (SPI) time series computed in a 12-month time scale. Quasi-association loglinear models proved to be the most adequate in fitting all the 14 data series. Odds and respective confidence intervals were calculated in order to understand the drought evolution and to estimate the drought class transition probabilities. The validation of the predictions was performed for the 2004–2006 drought, particularly for periods when the drought was initiating and establishing, and when it was dissipating. Despite the contingency tables of drought class transitions present a strong diagonal tendency, results of three-dimensional loglinear modeling present good results when comparing predicted and observed drought classes with 1 and 2 months lead for those 14 sites. Only for a few cases predictions did not fully match the observed drought severity, mainly for 2-month lead and when the SPI values are near the limit of the severity class. It could be concluded that loglinear prediction of drought class transitions is a useful tool for short term drought warnin