Robust stochastic seasonal precipitation scenarios

摘要

In this paper, a stochastic statistical forecasting methodology is employed for long-term predictions of winter precipitation over Greece. Lagged climatic indices and North Atlantic (NA) sea-level pressure (SLP) field are explored as potential predictors of the teleconnection. Rather than employing traditional stationary models, two dynamic regression-model ling schemes are analysed and validated and their parameter variation is interpreted. Dynamic regression models, in contrast to static (constant parameter) regression models, have time variable parameters (TVPs) evaluated through recursive optimisation and are suitable for analysis of non-stationary phenomena like most atmospheric processes.