SPI drought class prediction using log-linear models applied to wet and dry seasons

Publication date: Available online 11 November 2015 Source:Physics and Chemistry of the Earth, Parts A/B/C Author(s): Elsa E. Moreira A log-linear modelling for 3-dimensional contingency tables was used with categorical time series of SPI drought class transitions for prediction of monthly drought severity. Standardized Precipitation Index (SPI) time series in 12- and 6-month time scales were computed for 10 precipitation time series relative to GPCC datasets with 2.5 degrees spatial resolution located over Portugal and with 112 years length (1902 to 2014). The aim was modelling two-month step class transitions for the wet and dry seasons of the year and then obtain probability ratios – Odds – as well as their respective confidence intervals to estimate how probable a transition is compared to another. The prediction results produced by the modelling applied to wet and dry season separately, for the 6- and the 12-month SPI time scale, were compared with the results produced by the same modelling without the split, using skill scores computed for the entire time series length. Results point to good prediction performances ranging from 70-80% in the percentage of corrects (PC) and 50-70% in the Heidke skill score (HSS), with the highest scores obtained when the modelling is applied to the SPI12. The adding up of the wet and dry seasons introduced in the modelling brought improvements in the predictions, of about 0.9-4% in the PC and 1.3-6.8% in the HSS, being the high...

Source: Physics and Chemistry of the Earth, Parts ABC - November 13, 2015 Category: Science Source Type: research