On the "tuning" of autoconversion parameterizations in climate models

Autoconversion is a highly nonlinear process, which is usually evaluated in global climate models (GCMs) from the mean in-cloud value of the liquid-wa ter mixing ratio q(l)'. This biases the calculated autoconversion rate, and may explain why it usually seems to be necessary to reduce the autoconvers ion threshold to an unrealistically low value to obtain a realistic simulat ion in a GCM. Two versions of a threshold-dependent autoconversion paramete rization are compared in the CSIRO GCM. In the standard ("OLD") treatment, autoconversion occurs in a grid box whenever the mean in-cloud q(l)' exceed s the threshold q(crit), which is derived from a prescribed threshold cloud -droplet radius r(crit). In the modified ("NEW") version, the assumed subgr id moisture distribution from the model's condensation scheme is applied in each grid box to determine the fraction of the cloudy area in which q(l)' > q(crit), and autoconversion occurs in this fraction only. Simulations are performed using both treatments, for present-day and preindustrial distrib utions of cloud-droplet concentration, and using different values for r(cri t). Changing from the OLD to the NEW treatment means that r(crit) can be in creased from 7.5 mu m to a more realistic 9.3 mu m, while maintaining the g lobal-mean liquid-water path at about the same value. Simulations for prein dustrial and present-day conditions are compared, to see whether the change of scheme alters the modeled cloud-lifetime effect. It is found that the N EW scheme with r(crit) = 9.3 mu m gives a 0.5 W m(-2) (62%) stronger cloud- lifetime effect than the OLD scheme with r(crit) = 7.5 mu m.