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[1] Present-day shortcomings in the representation of upper tropospheric ice clouds in general circulation models (GCMs) lead to errors in weather and climate forecasts as well as account for a source of uncertainty in climate change projections. An ongoing challenge in rectifying these shortcomings has been the availability of adequate, high-quality, global observations targeting ice clouds and related precipitating hydrometeors. In addition, the inadequacy of the modeled physics and the often disjointed nature between model representation and the characteristics of the retrieved/observed values have hampered GCM development and validation efforts from making effective use of the measurements that have been available. Thus, even though parameterizations in GCMs accounting for cloud ice processes have, in some cases, become more sophisticated in recent years, this development has largely occurred independently of the global-scale measurements. With the relatively recent addition of satellite-derived products from Aura/Microwave Limb Sounder (MLS) and CloudSat, there are now considerably more resources with new and unique capabilities to evaluate GCMs. In this article, we illustrate the shortcomings evident in model representations of cloud ice through a comparison of the simulations assessed in the Intergovernmental Panel on Climate Change Fourth Assessment Report, briefly discuss the range of global observational resources that are available, and describe the essential components of the model parameterizations that characterize their ''cloud'' ice and related fields. Using this information as background, we (1) discuss some of the main considerations and cautions that must be taken into account in making model-data comparisons related to cloud ice, (2) illustrate present progress and uncertainties in applying satellite cloud ice (namely from MLS and CloudSat) to model diagnosis, (3) show some indications of model improvements, and finally (4) discuss a number of remaining questions and suggestions for pathways forward.

[1] A two-dimensional cloud-resolving model with detailed spectral bin microphysics is used to examine the effect of aerosols on three different deep convective cloud systems that developed in different geographic locations: south Florida, Oklahoma, and the central Pacific. A pair of model simulations, one with an idealized low cloud condensation nuclei (CCN) (clean) and one with an idealized high CCN (dirty environment), is conducted for each case. In all three cases, rain reaches the ground earlier for the low-CCN case. Rain suppression is also evident in all three cases with high CCN. However, this suppression only occurs during the early stages of the simulations. During the mature stages of the simulations the effects of increasing aerosol concentration range from rain suppression in the Oklahoma case to almost no effect in the Florida case to rain enhancement in the Pacific case. The model results suggest that evaporative cooling in the lower troposphere is a key process in determining whether high CCN reduces or enhances precipitation. Stronger evaporative cooling can produce a stronger cold pool and thus stronger low-level convergence through interactions with the low-level wind shear. Consequently, precipitation processes can be more vigorous. For example, the evaporative cooling is more than two times stronger in the lower troposphere with high CCN for the Pacific case. Sensitivity tests also suggest that ice processes are crucial for suppressing precipitation in the Oklahoma case with high CCN. A comparison and review of other modeling studies are also presented.

During the past two decades, convective scale models have advanced sufficiently to study the dynamic and microphysical processes associated with mesoscale convective systems. The basic features of these models are that they are non-hydrostatic and include a good representation of microphysical pro cesses. The Goddard Cumulus Ensemble (GCE) model has been extensively applied to study cloud-environment interactions, cloud interaction and merg ers, air-sea interaction, cloud draft structure and trace gas transport. The GCE model has improved signifi cantly during the past decade. For example, ice-microphysical processes, and solar and infrared radiative transfer pro cesses have been included. These model improvements allow the GCE model to study cloud-radiation interaction, cloud-radiation-climate relations and to develop rain retrieval algorithms for Tropical Rainfall Measuring Mission (TRMM). In Part I, a full description of the GCE model is presented, as well as several sensitivity tests associated with its assumptions. In Part II (Simpson and Ta o, 1993), we will review GCE model applications to cloud precipitating processes and to the Tropical Rainfall Measuring Mission (TRMM), a joint U.S.-Japan satellite project to measure rain and latent heat release over the global tropics.

[1] A three-dimensional (3-D) cloud-scale chemical transport model that includes a parameterized source of lightning NO x on the basis of observed flash rates has been used to simulate six midlatitude and subtropical thunderstorms observed during four field projects. Production per intracloud (P IC ) and cloud-to-ground (P CG ) flash is estimated by assuming various values of P IC and P CG for each storm and determining which production scenario yields NO x mixing ratios that compare most favorably with in-cloud aircraft observations. We obtain a mean P CG value of 500 moles NO (7 kg N) per flash. The results of this analysis also suggest that on average, P IC may be nearly equal to P CG , which is contrary to the common assumption that intracloud flashes are significantly less productive of NO than are cloud-to-ground flashes. This study also presents vertical profiles of the mass of lightning NO x after convection based on 3-D cloud-scale model simulations. The results suggest that following convection, a large percentage of lightning NO x remains in the middle and upper troposphere where it originated, while only a small percentage is found near the surface. The results of this work differ from profiles calculated from 2-D cloud-scale model simulations with a simpler lightning parameterization that were peaked near the surface and in the upper troposphere (referred to as a ''C-shaped'' profile). The new model results (a backward C-shaped profile) suggest that chemical transport models that assume a C-shaped vertical profile of lightning NO x mass may place too much mass near the surface and too little in the middle troposphere.