A new cirrus cloud parameterization for the ICOLMDZ atmospheric general circulation model (AGCM) is presented. It is built using prognostic equations for cloud fraction and cloud water vapor, and the processes that affect these quantities are parameterized. In particular, the tendency in ice crystal mass concentration due to changes in water phases is calculated, as is the macroscale mixing of cirrus clouds with their environment. The parameterization simulates ice supersaturation in clear sky, an ubiquitous metastable phenomenon in the upper troposphere that is necessary for the formation of in situ cirrus clouds. Our parameterization also allows for cirrus clouds to be sub- and supersaturated with respect to ice. It is evaluated on a case study of a warm conveyor belt cirrus cloud forming and dissipating above the Paris region. The representation of high cloud cover is improved with the new parameterization relative to the standard version of the cloud scheme in comparison to observations, as is the representation of water vapor. In particular, the upper tropospheric dry bias from ICOLMDZ is corrected, although it is replaced by a wet bias in some cases. As for the standard parameterization, ice fallspeed velocity is a major parameter for tuning the ice water content, but the new parameterization allows ice water content and cloud cover to be tuned separately.

Temperature and water vapor are known to fluctuate on multiple scales. In this study 27 years of airborne measurements of temperature and relative humidity from IAGOS (In-service Aircraft for a Global Observing System) are used to parameterize the distribution of water vapor in the upper troposphere and lower stratosphere (UTLS). The parameterization is designed to simulate water vapor fluctuations within gridboxes of atmospheric general circulation models (AGCMs) with typical size of a few tens to a few hundreds kilometers. The distributions currently used in such models are often not supported by observations at high altitude. More sophisticated distributions are key to represent ice supersaturation, a physical phenomenon that plays a major role in the formation of natural cirrus and contrail cirrus. Here the observed distributions are fitted with a beta law whose parameters are adjusted from the gridbox mean variables. More specifically the standard deviation and skewness of the distributions are expressed as empirical functions of the average temperature and specific humidity, two typical prognostic variables of AGCMs. Thus, the distribution of water vapor is fully parameterized for a use in these models. The new parameterization simulates the observed distributions with a determination coefficient always greater than 0.917, with a mean value of 0.997. Moreover, the ice supersaturation fraction in a model gridbox is well simulated with a determination coefficient of 0.983. The parameterization is robust to a selection of various geographical subsets of data and to gridbox sizes varying between 25 to 300 km.