Yoshimura et al., 2006 have shown that the solutions may be sensitive to the choice parameterization schemes: they found an increase in TC number over the Indian Ocean if the model used the Kuo
cumulus parameterization but a decrease if the Arkawa - Schubert
cumulus parameterization scheme was used.
A caveat is that all GCMs as well many TC models (including GFDL's) that have been used for climate change experiments employ hydrostatic approximation and «
cumulus parameterization».
Yao, and D. Kim, 2015: Constraints on
cumulus parameterization from simulations of observed MJO events.
A mass - flux
cumulus parameterization scheme for large - scale models: description and test with observations.
Not exact matches
Parameterizations of cloud microphysics,
cumulus clouds, and aerosol - cloud interactions in regional / global climate models
The Cloud, Aerosol, and Complex Terrain Interactions (CACTI) experiment in the Sierras de Córdoba mountain range of north - central Argentina is designed to improve understanding of cloud life cycle and organization in relation to environmental conditions so that
cumulus, microphysics, and aerosol
parameterizations in multi-scale models can be improved.
The Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign in the Sierras de Córdoba mountain range of north - central Argentina is designed to improve understanding of cloud life cycle and organization in relation to environmental conditions so that
cumulus, microphysics, and aerosol
parameterizations in multiscale models can be improved.
Part III: Separation of
parameterization biases in single - column model CAM5 simulations of shallow
cumulus.
de Roode, S.R., A.P. Siebesma, H.J. Jonker, and Y. de Voogd, 2012:
Parameterization of the Vertical Velocity Equation for Shallow
Cumulus Clouds.
«The authors demonstrate that model estimates of climate sensitivity can be strongly affected by the manner through which
cumulus cloud condensate is converted into precipitation in a model's convection
parameterization, processes that are only crudely accounted for in GCMs.
This concern is supported by Zhao et al. (2016), [19] who found that by varying the
cumulus convective precipitation
parameterization in the new GFDL AM4 model they could engineer its climate sensitivity over a wide range without being able to find any clear observational constraint that favoured one version of the model over the others.