Based on our earlier investigation on the performance of the National Center for Atmospheric Research Community Climate Model Version 2 (CCM2), we have incorporated into this model a physically-based cloud package. This package allows for the prognostic computation of cloud liquid water which is advected using the semi-Lagrangrian transport scheme of CCM2 the formation of anvil clouds from deep convective systems, and the coupling of physically based cloud optical properties to the CCM2`s shortwave and longwave radiation treatment. In this paper, the effect of the cloud package is assessed by comparing the January results of the simulation to model output from a control run over the same period using the original version of CCM2. The model ...
This paper introduces the concept of cloud-climate feedback along with its role in the sensitivity o...
Convection and clouds affect atmospheric temperature, moisture and wind fields through the heat of c...
To test the impact of modeling uncertainties and biases on the simulation of cloud feedbacks, severa...
Using the National Center for Atmospheric Research (NCAR) general circulation model (CCM2), a suite...
Uncertainties in representing the atmospheric water cycle are major obstacles to the accurate predic...
Clouds and cloud-radiation interactions contribute most to uncertainty in climate predictions in cli...
A parameterization is introduced for the prediction of cloud water in the National Center for Atmosp...
Cloud fraction, which varies greatly among general circulation models, plays a crucial role in simul...
Uncertainties in representing the atmospheric water cycle are major obstacles to an accurate predict...
A prognostic cloud fraction and prognostic condensate scheme (PC2) has been developed for the Met Of...
Our ability to study and quantify the impact of cloud-radiation interactions in studying global scal...
To evaluate and improve the treatment of clouds and radiation by the climate models of the National ...
Conducting probabilistic climate projections with a particular climate model requires the ability to...
Climate models are an important tool in understanding the mechanisms of the climate system and for p...
A methodology is described for testing the simulation of tropical convective clouds by models throug...
This paper introduces the concept of cloud-climate feedback along with its role in the sensitivity o...
Convection and clouds affect atmospheric temperature, moisture and wind fields through the heat of c...
To test the impact of modeling uncertainties and biases on the simulation of cloud feedbacks, severa...
Using the National Center for Atmospheric Research (NCAR) general circulation model (CCM2), a suite...
Uncertainties in representing the atmospheric water cycle are major obstacles to the accurate predic...
Clouds and cloud-radiation interactions contribute most to uncertainty in climate predictions in cli...
A parameterization is introduced for the prediction of cloud water in the National Center for Atmosp...
Cloud fraction, which varies greatly among general circulation models, plays a crucial role in simul...
Uncertainties in representing the atmospheric water cycle are major obstacles to an accurate predict...
A prognostic cloud fraction and prognostic condensate scheme (PC2) has been developed for the Met Of...
Our ability to study and quantify the impact of cloud-radiation interactions in studying global scal...
To evaluate and improve the treatment of clouds and radiation by the climate models of the National ...
Conducting probabilistic climate projections with a particular climate model requires the ability to...
Climate models are an important tool in understanding the mechanisms of the climate system and for p...
A methodology is described for testing the simulation of tropical convective clouds by models throug...
This paper introduces the concept of cloud-climate feedback along with its role in the sensitivity o...
Convection and clouds affect atmospheric temperature, moisture and wind fields through the heat of c...
To test the impact of modeling uncertainties and biases on the simulation of cloud feedbacks, severa...