An Observational Wish List for the Evaluation of Microphysical and Dynamical Processes within Cloud Resolving Models (Invited Presentation)

The representation of aerosol and cloud microphysical processes with cloud resolving models has made significant progress over the last decade. Such improvements include the advancement of multi-moment bulk schemes, spectral bin techniques and prognostic aerosol parameterizations, facilitated in part by rapidly developing computational capabilities. However, it could be argued that the development of aerosol and microphysical parameterizations has recently outpaced the measurements necessary for their evaluation and subsequent development, and that we are in need of an observational revolution as we strive towards improving our predictions of cloud processes.

While there are a number of microphysical aspects of cloud resolving models that would greatly benefit from observational evaluation, the following factors will serve as the focus of this talk: vertical velocity, supersaturation, the three dimensional characterization of aerosols, hydrometeor size distributions and the in-cloud ratios of liquid water to ice. Most of these factors are intricately linked, often through non-linear feedbacks. Assessing the relevance of each of these factors therefore often requires simultaneously evaluating other related factors. For example, it has been observed that vertical velocity within convective storms is frequently overestimated when compared with Doppler velocity measurements. These updraft inaccuracies have been attributed to weaknesses in ice phase microphysics schemes. Assessing the vertical motions in models therefore requires not only an evaluation of the dynamical factors contributing to vertical velocity but also the microphysical processes involved. The microphysical processes are in turn impacted by the supersaturation and hydrometeor size distributions, which themselves are impacted by the amount and type of aerosols ingested by storm systems. Thus it is imperative to obtain simultaneous observations of several critical cloud factors if we are to make significant progress in evaluating our numerical models.

The role played by each of these factors within cloud systems, the range of response that errors in their misrepresentation can cause, the current state of observations of these factors and suggestions for enhancements of such observations in the future will be presented.