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(1996)
Verificação estatı́stica do modelo global do CPTEC. (Statistical verification of CPTEC global model
(1990)
A survey of common verification methods in meteorology
G. Mellor, Tetsuji Yamada (1982)
Development of a turbulence closure model for geophysical fluid problemsReviews of Geophysics, 20
Wilbur Chen, H. Dool (1995)
Forecast skill and low-frequency variability in NMC DERF90 experimentsMonthly Weather Review, 123
(1983)
The sensitivity of the time - mean large - scale flow to cumulus convection in the ECMWF model
R. Wobus, E. Kalnay (1995)
Three years of operational prediction of forecast skill at NMCMonthly Weather Review, 123
J. Sela (1980)
Spectral Modeling at the National Meteorological CenterMonthly Weather Review, 108
Y. Xue, P. Sellers, J. Kinter, J. Shukla (1991)
A Simplified Biosphere Model for Global Climate StudiesJournal of Climate, 4
A. Lacis, J. Hansen (1974)
A parameterization for the absorption of solar radiation in the earth's atmosphereJournal of the Atmospheric Sciences, 31
(1987)
The development and verification of a cloud prediction model for the ECMWF model
Harshvardhan, R. Davies, D. Randall, T. Corsetti (1987)
A fast radiation parameterization for atmospheric circulation modelsJournal of Geophysical Research, 92
P. Sellers, Y. Mintz, Y. Sud, A. Dalcher (1986)
A Simple Biosphere Model (SIB) for Use within General Circulation ModelsJournal of the Atmospheric Sciences, 43
(1986)
Manual of the E-physics
(1974)
1974: A parameterization for the absorption of solar radiation in the earth’s atmosphere
NWP model skill as obtained from the standard statistics applied to derived atmospheric fields such as thermal advection and moisture convergence is different from that obtained by the same statistics applied to basic model output fields such as temperature or wind components. An analysis with a combination of two simple wave functions shows that the errors in the forecast of the phase of the shortwave component are overwhelmingly more important. For an error of 2°° longitude in the phase forecast of the shortwave component (wavenumber ∼∼20) the correlation coefficient for the derived fields is only 0.7 whereas it is nearly 0.9 for the basic variable fields. The prediction range of useful forecasts in terms of the derived variables decreases drastically in comparison to that obtained with the simple variables. These aspects are demonstrated with the Centro de Previsão de Tempo e Estudos Climááticos––Center for Ocean––Land––Atmosphere studies operational NWP model in two real synoptic cases that are representative of active weather situations in austral winter over the southern half of South America.
Weather and Forecasting – American Meteorological Society
Published: May 5, 1998
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