title: Application of an ensemble technique based on singular spectrum analysis to daily rainfall forecasting.
abstract: In previous work, we have proposed a constructive methodology for temporal data learning supported by results and prescriptions related to the embedding theorem, and using the singular spectrum analysis both in order to reduce the effects of the possible discontinuity of the signal and to implement an efficient ensemble method. In this paper we present new results concerning the application of this approach to the forecasting of the individual rain-fall intensities series collected by 135 stations distributed in the Tiber basin. The average RMS error of the obtained forecasting is less than 3mm of rain.
authors.affiliation: Istituto Nazionale per la Fisica della Materia, Via Dodecaneso 35, I-16146, Genova, Italy.
authors.forename: Daniela
authors.initials: D
authors.lastname: Baratta
authors.forename: Giovambattista
authors.initials: G
authors.lastname: Cicioni
authors.forename: Francesco
authors.initials: F
authors.lastname: Masulli
authors.forename: Léonard
authors.initials: L
authors.lastname: Studer
mesh_terms: D005544:Forecasting / Q000379:methods*; D011891:Rain; D013057:Spectrum Analysis / Q000379:methods