Meteorology and Atmospheric Physics

, Volume 69, Issue 1–2, pp 23–38 | Cite as

A parameterization of radiative fluxes suitable for use in a statistical-dynamical model

  • S. H. Franchito
  • V. Brahmananda Rao
  • R. Ramos da Silva


A parameterization of shortwave and longwave radiation fluxes derived from detailed radiative transfer models is included in a global primitive equation statistical-dynamical model (SDM) with two bulk atmospheric layers. The model is validated comparing the model simulations with the observed mean annual and seasonal zonally averaged climate. The results show that the simulation of the shortwave and longwave radiation fluxes matches well with the observations. The SDM variables such as surface and 500 hPa temperatures, zonal winds at 250 hPa and 750 hPa, vertical velocity at 500 hPa and precipitation are also in good agreement with the observations. A comparison between the results obtained with the present SDM and those with the previous version of the model indicates that the model results improved when the parameterization of the radiative fluxes based on detailed radiative transfer models are included into the SDM.

The SDM is used to investigate its response to the greenhouse effect. Sensitivity experiments regarding the doubling of CO2 and the changing of the cloud amount and height are performed. In the case 2×CO2 the model results are consistent with those obtained from GCMs, showing a warming of the climate system. An enhancement of the greenhouse effect is also noted when the cloud layer is higher. However, an increase of the cloud amount in all the latitude belts provokes an increase of the surface temperature near poles and a decrease in all the other regions. This suggests that the greenhouse effect overcomes the albedo effect in the polar latitudes and the opposite occurs in other regions. In all the experiments the changes in the surface temperature are larger near poles, mainly in the Southern Hemisphere.


Surface Temperature Southern Hemisphere Vertical Velocity Zonal Wind Climate System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag 1998

Authors and Affiliations

  • S. H. Franchito
    • 1
  • V. Brahmananda Rao
    • 1
  • R. Ramos da Silva
    • 2
  1. 1.Instituto Nacional de Pesquisas EspaciasINPESão José dos CampsoBrazil
  2. 2.AgronomyIowa State UniversityAmesUSA

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