Attribution of precipitation changes on a regional scale by neural network modeling: A case study (Articolo in rivista)

Type

• Articolo in rivista (Classe)
• Prodotto della ricerca (Classe)

Label

• Attribution of precipitation changes on a regional scale by neural network modeling: A case study (Articolo in rivista) (literal)

Anno

• 2010-01-01T00:00:00+01:00 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi

• 10.3390/w2030321 (literal)

Alternative label

• Pasini, A. (1); Langone, R (2) (2010)
  Attribution of precipitation changes on a regional scale by neural network modeling: A case study
  in Water (Basel); Molecular Diversity Preservation International-MDPI, Basel (Swaziland)
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Pasini, A. (1); Langone, R (2) (literal)

Pagina inizio

• 321 (literal)

Pagina fine

• 332 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume

• 2 (literal)

Rivista

• Water (Rivista)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali

• 12 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• 1) CNR, Institute of Atmospheric Pollution Research, via Salaria km 29.300, I-00015 Monterotondo Stazione, Rome, Italy; 2) Katholieke Universiteit Leuven, Department ESAT/SISTA, Leuven, Belgium; (literal)

Titolo

• Attribution of precipitation changes on a regional scale by neural network modeling: A case study (literal)

Abstract

• On a regional scale, climate variability masks any direct link between external forcings and precipitation values. Thus, the problem of attribution of precipitation changes splits into two distinct steps: understanding how forcings influence circulation patterns and finding relationships between these patterns and the behavior of precipitation. Here, we deal with this second step, by analyzing data about eight circulation indices and their influence on precipitation anomalies in an extended Italian Alpine region. The methods used are bivariate nonlinear analysis and neural network modeling. We identify the most influential circulation patterns in each season and work out neural network models that are able to substantially describe the climate variability of precipitation at this regional scale. (literal)

Editore

• Molecular Diversity Preservation International-MDPI (Editore)

Prodotto di

• Institute of Atmospheric pollution Research (IIA) (Istituto)
• Sviluppo e applicazione di modelli numerici atmosferici dalla scala urbana a quella continentale e globale (TA.P02.029.001) (Modulo)

Autore CNR

• ANTONELLO PASINI (Persona)

Insieme di parole chiave

• Keywords of "Attribution of precipitation changes on a regional scale by neural network modeling: A case study" (Insieme di parole chiave)

Incoming links:

Prodotto

• Institute of Atmospheric pollution Research (IIA) (Istituto)
• Sviluppo e applicazione di modelli numerici atmosferici dalla scala urbana a quella continentale e globale (TA.P02.029.001) (Modulo)

Autore CNR di

• ANTONELLO PASINI (Persona)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi

• Water (Rivista)

Editore di

• Molecular Diversity Preservation International-MDPI (Editore)

Insieme di parole chiave di

• Keywords of "Attribution of precipitation changes on a regional scale by neural network modeling: A case study" (Insieme di parole chiave)