S u MMARYAn explicit microphysical parametrization including ice physics was developed for use in the NCARPenn State Mesoscale Model Version 5 (MM5). This scheme includes three options of increasing complexity to represent the hydrometeor species. The scheme is evaluated by comparing model simulations with two well observed winter storms that occurred during the Winter Icing and Storms Project. The evaluation focused on the prediction of supercooled liquid water (SLW), which is of particular importance to aircraft icing. The intercomparisons showed that:1. The double-moment microphysical scheme, in which both ice mixing ratios and number concentrations were predicted, performed best, with close agreement to the observed fields.2. The single-moment schemes, in which the mixing ratio of ice species are predicted and number concentration specified, performed reasonably well if a diagnostic equation for No,,, the Y-intercept of the assumed exponential snow distribution, is allowed to vary with snow mixing ratio.3. Accurate microphysical simulations of SLW in shallow upslope clouds and cyclonic storms required accurate simulations of the kinematic and thermodynamic structure and evolution of the storms.Though the two storms were dynamically different, the SLW formed through a balance of the condensational growth of cloud water and the depletion of cloud water by deposition and riming of snow andlor graupel for both storms. The results of this study suggest that accurate prediction of SLW over limited areas of the country may be possible using the current microphysical parametrization and high-resolution grids (6x < 10 km).

A coupled atmospheric/wildfire behavior model is described that utilizes physics-based process models to represent wildfire behavior. Five simulations are presented, four of which are highly idealized situations that are meant to illustrate some of the dependencies of the model on environmental conditions. The fifth simulation consists of a fire burning in complex terrain with non-homogeneous vegetation and realistic meteorological conditions. The simulated fire behavior develops out of the coupling of a set of very complex processes and not from prescribed rules based on empirical data. This represents a new direction in wildfire modeling that we believe will eventually help decision makers and land managers do their jobs more effectively.

[1] In this paper results from a cloud-resolving model that can efficiently examine the impact of aerosol on nondrizzling stratus clouds will be shown. Because the model tracks aerosol and cloud droplets in a Lagrangian framework, it does not suffer from numerical errors associated with advection, and unlike most Eulerian approaches, the method can track cloud boundaries as they move across a grid cell. After illustrating the capability of the model to reproduce various observed cloud statistics such as the cloud water mixing ratio and the mean cloud droplet radius from the DYCOMS-II field program, the ability of the model to assess the impact of changes in aerosol number and composition on a stratus deck will be highlighted. Specifically, by using activation curves appropriate for soluble, insoluble, or a mixture of both types of aerosol and for certain extreme aerosol regimes, i.e., a majority of the aerosol are hydrophobic carbon aerosol, limiting situations were examined to bound their impact on clouds. However, though these situations may be somewhat extreme, they could occasionally occur in the atmosphere, e.g., an oceanic stratus field downwind of a large ship or an urban area. Not unexpectedly, results from these simulations support previous ship track observations that for increasing aerosol numbers, cloud droplet number concentrations increase, whereas cloud droplet radii decrease. However, these simulations also suggest that the correlation between cloud droplet number concentration and aerosol number concentration may be not only a function of aerosol number concentration but also aerosol types and/or cloud dynamics.

We present a multiscale study examining the impact of a regional exchange of nuclear weapons on global climate. Our models investigate multiple phases of the effects of nuclear weapons usage, including growth and rise of the nuclear fireball, ignition and spread of the induced firestorm, and comprehensive Earth system modeling of the oceans, land, ice, and atmosphere. This study follows from the scenario originally envisioned by Robock, Oman, Stenchikov, et al. (2007, https://doi.org/10.5194/acp-7-2003-2007), based on the analysis of Toon et al. (2007, https://doi.org/10.5194/acp-7-1973-2007), which assumes a regional exchange between India and Pakistan of fifty 15 kt weapons detonated by each side. We expand this scenario by modeling the processes that lead to production of black carbon, in order to refine the black carbon forcing estimates of these previous studies. When the Earth system model is initiated with 5 × 109 kg of black carbon in the upper troposphere (approximately from 9 to 13 km), the impact on climate variables such as global temperature and precipitation in our simulations is similar to that predicted by previously published work. However, while our thorough simulations of the firestorm produce about 3.7 × 109 kg of black carbon, we find that the vast majority of the black carbon never reaches an altitude above weather systems (approximately 12 km). Therefore, our Earth system model simulations conducted with model‐informed atmospheric distributions of black carbon produce significantly lower global climatic impacts than assessed in prior studies, as the carbon at lower altitudes is more quickly removed from the atmosphere. In addition, our model ensembles indicate that statistically significant effects on global surface temperatures are limited to the first 5 years and are much smaller in magnitude than those shown in earlier works. None of the simulations produced a nuclear winter effect. We find that the effects on global surface temperatures are not uniform and are concentrated primarily around the highest arctic latitudes, dramatically reducing the global impact on human health and agriculture compared with that reported by earlier studies. Our analysis demonstrates that the probability of significant global cooling from a limited exchange scenario as envisioned in previous studies is highly unlikely, a conclusion supported by examination of natural analogs, such as large forest fires and volcanic eruptions.

An explicit microphysical parametrization including ice physics was developed for use in the NCARPenn State Mesoscale Model Version 5 (MM5). This scheme includes three options of increasing complexity to represent the hydrometeor species. The scheme is evaluated by comparing model simulations with two well observed winter storms that occurred during the Winter Icing and Storms Project. The evaluation focused on the prediction of supercooled liquid water (SLW), which is of particular importance to aircraft icing. The intercomparisons showed that:1. The double-moment microphysical scheme, in which both ice mixing ratios and number concentrations were predicted, performed best, with close agreement to the observed fields.2. The single-moment schemes, in which the mixing ratio of ice species are predicted and number concentration specified, performed reasonably well if a diagnostic equation for No,,, the Y-intercept of the assumed exponential snow distribution, is allowed to vary with snow mixing ratio.3. Accurate microphysical simulations of SLW in shallow upslope clouds and cyclonic storms required accurate simulations of the kinematic and thermodynamic structure and evolution of the storms.Though the two storms were dynamically different, the SLW formed through a balance of the condensational growth of cloud water and the depletion of cloud water by deposition and riming of snow andlor graupel for both storms. The results of this study suggest that accurate prediction of SLW over limited areas of the country may be possible using the current microphysical parametrization and high-resolution grids (6x < 10 km).A more direct approach to forecasting SLW with a forecast model would use the model-generated vertical motion field to produce SLW and the ice crystal fields to deplete the SLW. This approach has been extensively used in cloud models based on explicit microphysical schemes (Lin et al. 1983), with relatively good success for convective, summertime storms (Murakami 1990). Winter storms, however, typically require largerscale models for proper simulation, including the incorporation of time-dependent lateral boundary conditions and synoptic-scale forcing. The recent studies by Kuo and Low-Nam (1 990), Stewart (1992), Bruintjes et al. (1994), Modica et al. (1 994), Stewart et al. ( 1 995), Rasmussen et al. (1993, and Tremblay et al. (1996) have shown good success in simulating the dynamics of winter storms using mesoscale models. The simulation of precipitation and SLW using explicit microphysical schemes in mesoscale models, however, has received less attention.In this paper we present a microphysical parametrization with three options of hydrometeor representation based on previous schemes and some new aspects. Using this parametrization, we evaluate the performance of the National Center for Atmospheric Research (NCAR)Penn State Mesoscale Model Version 5 (MM5) in simulating SLW in winter storms over the continental US, using data from two well-studied storms during the Winter Icing and Storms Project (WISP, R...