We have developed a new cloud model, CARMA Cloud, for the NCAR Community Earth System Model that is designed to simplify the cloud model and improve its representation of cloud aerosol interactions. Rapid, unexpected, global warming since 2003 seems to be due to a combination of cloud feedback to global warming and strong response to aerosol changes. While the model is currently aimed at terrestrial cloud physics, the basic code has recently been used for exo-planet studies, and an early version of the model was used for studies of Martian ice clouds.
All current climate models assume that rain and snow are separate entities and can be represented with minimal information such as cloud mass and particle numbers. The Community Aerosol and Radiation Model for Atmospheres, CARMA, instead, computes the particle size distributions for the clouds which unites cloud and rain, as well as ice crystals and snow. The model also includes dust and sulfate aerosols inside of the ice clouds, one step towards improving cloud aerosol interactions.
CARMA shows, in agreement with observations, that there is a continuous distribution of particles between rain and cloud as well as ice and snow, showing the major assumption of cloud and rain with distinct modes in other cloud models is wrong. In addition, it shows that satellite data from MODIS do not span a wide enough size range to measure cloud mass. Therefore, the disagreement between models, showing liquid water content rises with cloud number density, and satellite observations showing the opposite, is likely due to misinterpreting the satellite data.
The global albedo of the modeled clouds is very sensitive to details of the calculation of rain formation, and to the interaction of clouds and aerosols. In the model, we tune several key parameters (aerosol activation, coagulation/coalescence kernel) to create the best case that’s in alignment with observations regarding liquid/ice water path, liquid/ice water content, and radiative properties.
Continued evolution of the model is expected to make the cloud aerosol interactions more realistic and to improve computational eWiciency.