Abstract. The Meso-NH Atmospheric Simulation System is a joint e ort of the Centre National de Recherches Me te orologiques and Laboratoire d'Ae rologie. It comprises several elements; a numerical model able to simulate the atmospheric motions, ranging from the large meso-alpha scale down to the micro-scale, with a comprehensive physical package, a¯exible ®le manager, an ensemble of facilities to prepare initial states, either idealized or interpolated from meteorological analyses or forecasts, a¯exible post-processing and graphical facility to visualize the results, and an ensemble of interactive procedures to control these functions. Some of the distinctive features of this ensemble are the following: the model is currently based on the Lipps and Hemler form of the anelastic system, but may evolve towards a more accurate form of the equations system. In the future, it will allow for simultaneous simulation of several scales of motion, by the so-called``interactive grid-nesting technique''. It allows for the in-line computation and accumulation of various terms of the budget of several quantities. It allows for the transport and di usion of passive scalars, to be coupled with a chemical module. It uses the relatively new Fortran 90 compiler. It is tailored to be easily implemented on any UNIX machine. Meso-NH is designed as a research tool for small and meso-scale atmospheric processes. It is freely accessible to the research community, and we have tried to make it as``user-friendly'' as possible, and as general as possible, although these two goals sometimes appear contradictory. The present paper presents a general description of the adiabatic formulation and some of the basic validation simulations. A list of the currently available physical parametrizations and initialization methods is also given. A more precise description of these aspects will be provided in a further paper.

[1] Observations made during the TWP-ICE campaign are used to drive and evaluate thirteen cloud-resolving model simulations with periodic lateral boundary conditions. The simulations employ 2D and 3D dynamics, one-and two-moment microphysics, several variations on large-scale forcing, and the use of observationally derived aerosol properties to prognose droplet numbers. When domain means are averaged over a 6-day active monsoon period, all simulations reproduce observed surface precipitation rate but not its structural distribution. Simulated fractional areas covered by convective and stratiform rain are uncorrelated with one another, and are both variably overpredicted by up to a factor of $2. Stratiform area fractions are strongly anticorrelated with outgoing longwave radiation (OLR) but are negligibly correlated with ice water path (IWP), indicating that ice spatial distribution controls OLR more than mean IWP. Overpredictions of OLR tend to be accompanied by underpredictions of reflected shortwave radiation (RSR). When there are two simulations differing only in microphysics scheme or large-scale forcing, the one with smaller stratiform area tends to exhibit greater OLR and lesser RSR by similar amounts. After $10 days, simulations reach a suppressed monsoon period with a wide range of mean precipitable water vapor, attributable in part to varying overprediction of cloud-modulated radiative flux divergence compared with observationally derived values. Differences across the simulation ensemble arise from multiple sources, including dynamics, microphysics, and radiation treatments. Close agreement of spatial and temporal averages with observations may not be expected, but the wide spreads of predicted stratiform fraction and anticorrelated OLR indicate a need for more rigorous observation-based evaluation of the underlying micro-and macrophysical properties of convective and stratiform structures.

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Abstract. Transport and scavenging of chemical constituents in deep convection is important to understanding the composition of the troposphere and therefore chemistryclimate and air quality issues. High resolution cloud chemistry models have been shown to represent convective processing of trace gases quite well. To improve the representation of sub-grid convective transport and wet deposition in large-scale models, general characteristics, such as species mass flux, from the high resolution cloud chemistry models can be used. However, it is important to understand how these models behave when simulating the same storm. The intercomparison described here examines transport of six species. CO and O 3 , which are primarily transported, show good agreement among models and compare well with observations. Models that included lightning production of NO x reasonably predict NO x mixing ratios in the anvil compared with observations, but the NO x variability is much larger than that seen for CO and O 3 . Predicted anvil mixing ratios of the soluble species, HNO 3 , H 2 O 2 , and CH 2 O, exhibit significant differences among models, attributed to different schemes in these models of cloud processing including the role of the Correspondence to: M. C. Barth (barthm@ucar.edu) ice phase, the impact of cloud-modified photolysis rates on the chemistry, and the representation of the species chemical reactivity. The lack of measurements of these species in the convective outflow region does not allow us to evaluate the model results with observations.

A bulk microphysical scheme which predicts the concentrations and mixing ratios of cloud droplets and raindrops is presented. The scheme draws its originality from the use of generalized gamma law as basis functions for the drop size distributions and also from the attention paid to performing analytical integrations of most of the microphysical transfer rates. The numerical representation of each process has been reviewed throughout and specific tests have been made to evaluate separately the accuracy of the scheme compared with a bin-size model. The scheme, which depends on the specification of a few input parameters shaping the activation spectrum, is incorporated in a three-dimensional non-hydrostatic model with some applications given in a companion paper (Part m.

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Abstract. A simple parametric relationship is established between factors describing the shape of cloud condensation nuclei (CCN) activation spectra and observable properties of the aerosol population they grow on (size distribution and solubility). This is done independently for maritime and continental aerosol types because of their very different characteristics. The data used for the multiple statistical adjustments in the procedure described in this paper are generated by running a numerical model of aerosol growth coupled to a simple cloud droplet activation scheme. Each aerosol population (maritime and continental) is assumed to be of homogeneous chemical composition, lognormally distributed and with variable solubility. The parameterization is then evaluated using a large set of aerosol populations with randomized properties. Finally, the study presents a preliminary analysis of the most important aerosol properties that influence the shape of the CCN spectra. An idealized scenario of a clean maritime boundary layer cloud perturbed by anthropogenic emissions (such as the ship track problem) illustrates the capability of the parameterization to selectively increfise the cloud droplet concentration in a partially polluted cloud. The calibration results presented in this paper are not meant to be the definitive activation spectra produced by any lognormally distributed aerosols. These results are indeed a step toward an objective initialization of CCN spectra and hence toward the computation of cloud droplet concentrations based on measurable multimodal aerosol features, as required by three-dimensional numerical models with a coupled interactive aerosol module.