A prognostic model of cloud cover based on Satellite data (Articolo in rivista)

Type
Label
  • A prognostic model of cloud cover based on Satellite data (Articolo in rivista) (literal)
Anno
  • 2004-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1029/2003GL018329 (literal)
Alternative label
  • Goswami, P. (a); Liberti, G.L. (b) (2004)
    A prognostic model of cloud cover based on Satellite data
    in Geophysical research letters
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Goswami, P. (a); Liberti, G.L. (b) (literal)
Pagina inizio
  • L01101-1 (literal)
Pagina fine
  • L01101-4 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 31 (literal)
Rivista
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 31 (literal)
Note
  • Scopu (literal)
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • (a) CSIR, Centre for Mathematical Modelling and Computer Simulation, Bangalore, India (b) Istituto di Scienze Atmosfera e del Clima-CNR, Rome, Italy (literal)
Titolo
  • A prognostic model of cloud cover based on Satellite data (literal)
Abstract
  • Large uncertainties still remain about the mechanisms of genesis and interaction of clouds in a large scale environment. Through a semi-empirical dynamical model using hourly data from TOGA-COARE IOP (130E-180E and 15S-15N, 01.11.91-28.02.92), we show that the convective activity leading to clouds is a self-regulating, threshold process embedded in a large-scale environment. The convective activity is prescribed through a of hourly fractional cloud cover while the environmental forcings are defined in terms large-scale moist state defined in terms of the average brightness temperature. A prognostic model is then developed for cloud cover as the dynamical variable. To validate the model we integrate it with a given initial condition from observed data. The model reproduces the observed spatio-temporal structure of the cloud with a remarkable degree of success. We identify and quantify two thresholds for large-scale forcing for genesis and intensity of high clouds. (literal)
Prodotto di
Autore CNR

Incoming links:


Prodotto
Autore CNR di
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi
data.CNR.it