Long-range, time-varying statistical prediction of annual precipitation in a Mediterranean remote site

In the Mediterranean basin, climate change signals are often representative of atmospheric transients in precipitation patterns. Remote mountaintop rainfall stations are far from human influence and can more easily unveil climate signals to improve the accuracy of long-term forecasts. In this study, the world's longest annual precipitation time-series (1884-2021) from a remote station, the Montevergine site (1284 m a.s.l.) in southern Italy, was investigated to explain its forecast performance in the coming decades, offering a representative case study for the central Mediterranean. For this purpose, a Seasonal AutoRegressive-exogenous Time Varying process with Exponential Generalised Autoregressive Conditional Heteroscedasticity (SARX(TVAR)-EGARCH) model was developed for the training period 1884-1991, validated for the interval 1992-2021, and used to make forecasts for the time-horizon 2022-2051, with the support of an exogenous variable (dipole mode index). Throughout this forecast period, the dominant feature is the emergence of an incipient and strong upward drought trend in precipitation until 2035. After this change-point, rainfall increases again, more slightly, but with considerable values towards the end of the forecast period. Although uncertainties remain, the results are promising and encourage the use of SARX(TVAR)-EGARCH in climate studies and forecasts in mountain sites.