Robust stochastic seasonal precipitation scenarios

• Published in: International Journal of Climatology
• Main Authors: Kioutsioukis, Ioannis, Rapsomanikis, Spyridon, Loupa, Rea
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2006
• Subjects: North Atlantic; North Atlantic oscillation
• Online Access: http://dx.doi.org/10.1002/joc.1351; https://api.wiley.com/onlinelibrary/tdm/v1/articles/10.1002%2Fjoc.1351; https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/joc.1351

Abstract 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‐modelling 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. The analysis of the spectrum with non‐stationary models points out that the most influential seasonal components of the winter precipitation anomalies have periods of 14 and 3.5 years, explain 40% of its variance, possess significant amplitude change and correlate significantly with the North Atlantic Oscillation Index Anomaly (NAOIA) and Southern Oscillation Index Anomaly, indicating their climatic origin. Furthermore, the forecasting skill of the dynamic models ( R 2 = 0.71), in addition to reproducing the peaks, was found superior even to the hindcasting skill of the stationary model ( R 2 = 0.55). Copyright © 2006 Royal Meteorological Society