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Lagrangian Cloud Model (LCM) is a mixed Eulerian/Lagrangian approach to atmospheric large eddy simulation (LES), with two‐way coupling between Eulerian dynamics and thermodynamics and Lagrangian microphysics. Since Lagrangian representation of microphysics does not suffer from numerical diffusion in the radius space and solves full droplet growth equations, it may be considered an alternative for the bin approach. This paper documents the development of LCM to include collision/coalescence processes. The proposed algorithm maps Lagrangian parcels collision/coalescence events on the specified two‐dimensional grid, with the first dimension spanning aerosol radius and the second dimension spanning the cloud droplet radius. The proposed approach is capable of representation of aerosol activation, deactivation, transport inside the droplets, and processing by clouds and in the future may be used to investigate details of these processes. As an illustration, LCM with collision/coalescence is used to investigate effects of aerosols on cloud microphysics and dynamics for a marine stratocumulus cloud. Two extreme cases are considered that represent low and high aerosol concentrations. It is shown that the aerosol type significantly affects cloud microphysics as well as cloud dynamics. In agreement with previous studies, a larger entrainment rate is simulated for the high aerosol concentration. For the low aerosol concentration, intense collision/coalescence and drizzle modify the aerosol size distribution, reducing the concentration in the dry radius range of 0.02 to 0.2 μm and increasing the concentration for dry radii larger than 0.3 μm.

Gravity waves (GWs) play an important role in many atmospheric processes. However, the observation-based understanding of GWs is limited, and representing them in numerical models is difficult. Recent studies show that small islands can be intense sources of GWs, with climatologically significant effects on the atmospheric circulation. South Georgia, in the South Atlantic, is a notable source of such “small island” waves. GWs are usually too small scale to be resolved by current models, so their effects are represented approximately using resolved model fields (parameterization). However, the small-island waves are not well represented by such parameterizations, and the explicit representation of GWs in very-high-resolution models is still in its infancy. Steep islands such as South Georgia are also known to generate low-level wakes, affecting the flow hundreds of kilometers downwind. These wakes are also poorly represented in models. We present results from the South Georgia Wave Experiment (SG-WEX) for 5 July 2015. Analysis of GWs from satellite observations is augmented by radiosonde observations made from South Georgia. Simulations were also made using high-resolution configurations of the Met Office Unified Model (UM). Comparison with observations indicates that the UM performs well for this case, with realistic representation of GW patterns and low-level wakes. Examination of a longer simulation period suggests that the wakes generally are well represented by the model. The realism of these simulations suggests they can be used to develop parameterizations for use at coarser model resolutions.

This paper presents application of the Weather Research and Forecasting (WRF) model to limited-area modeling of atmospheric processes over the subtropical south-eastern Pacific, with the emphasis on the stratocumulus-topped boundary layer. The simulations cover a domain from the VAMOS (Variability of the American Monsoon Systems) Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) field project conducted in the subtropical south-eastern Pacific in October and November 2008. We focus on a day where the UK's BAe-146 research aircraft encountered Pockets of Open Cells (POCs) at the very western edge of its flight track, rather than on the entire campaign as investigated in previous limited-area modeling studies. Model results are compared to aircraft observations with the main conclusion that the simulated stratocumulus-topped boundary layer is significantly too shallow. This appears to be a combination of an already too shallow boundary layer in the dataset used to provide initial and lateral boundary conditions, and the inability of the WRF model to increase the boundary-layer height. Several sensitivity simulations, applying different subgrid-scale parameterizations available in the model, a larger computational domain and longer simulations, as well as a different dataset providing initial and lateral boundary conditions were all tried to improve the simulation. These changes appeared to have a rather small effect on the results. The model does simulate the formation of mesoscale cloud-free regions that one might consider similar to Pockets of Open Cells observed in nature. However, formation of these regions does not seem to be related to drizzle-induced transition from open- to closed-cell circulations as simulated by LES models. Instead, the cloud-free regions appear to result from mesoscale variations of the lower-tropspheric vertical velocity. Areas of negative vertical velocity with minima (a few cm s−1) near the boundary layer top seem to induce direct evaporation of the cloud layer. It remains to be seen in LES studies whether the mechanism seen in the model is realistic or if it is simply an artifact of interactions between resolved and parameterized processes.

Atmospheric gravity waves (GWs) play an important role in atmospheric dynamics but accurately representing them in general circulation models (GCMs) is challenging. This is especially true for orographic GWs generated by wind flow over small mountainous islands in the Southern Ocean. Currently, these islands lie in the “grey zone” of global model resolution, where they are neither fully resolved nor fully parameterised. It is expected that as GCMs approach the spatial resolution of current high-resolution local-area models, small-island GW sources may be resolved without the need for parameterisations. But how realistic are the resolved GWs in these high-resolution simulations compared to observations? Here, we test a high-resolution (1.5 km horizontal grid, 118 vertical levels) local-area configuration of the Met Office Unified Model over the mountainous island of South Georgia (54∘ S, 36∘ W), running without GW parameterisations. The island's orography is well resolved in the model, and real-time boundary conditions are used for two time periods during July 2013 and June–July 2015. We compare simulated GWs in the model to coincident 3-D satellite observations from the Atmospheric Infrared Sounder (AIRS) on board Aqua. By carefully sampling the model using the AIRS resolution and measurement footprints (denoted as model sampled as AIRS hereafter), we present the first like-for-like comparison of simulated and observed 3-D GW amplitudes, wavelengths and directional GW momentum flux (GWMF) over the island using a 3-D S-transform method. We find that the timing, magnitude and direction of simulated GWMF over South Georgia are in good general agreement with observations, once the AIRS sampling and resolution are applied to the model. Area-averaged zonal GWMF during these 2 months is westward at around 5.3 and 5.6 mPa in AIRS and model sampled as AIRS datasets respectively, but values directly over the island can exceed 50 mPa. However, up to 35 % of the total GWMF in AIRS is actually found upwind of the island compared to only 17 % in the model sampled as AIRS, suggesting that non-orographic GWs observed by AIRS may be underestimated in our model configuration. Meridional GWMF results show a small northward bias (∼20 %) in the model sampled as AIRS that may correspond to a southward wind bias compared to coincident radiosonde measurements. Finally, we present one example of large-amplitude (T′≈15–20 K at 45 km altitude) GWs at short horizontal wavelengths (λH≈30–40 km) directly over the island in AIRS measurements that show excellent agreement with the model sampled as AIRS. This suggests that orographic GWs in the full-resolution model with T′≈45 K and λH≈30–40 km can occur in reality. Our study demonstrates that not only can high-resolution local-area models simulate realistic stratospheric GWs over small mountainous islands but the application of satellite sampling and resolution to these models can also be a highly effective method for their validation.

This article discusses a potential impact of turbulent velocity fluctuations of the air on a drizzle formation in Cumulus clouds. Two different representations of turbulent velocity fluctuations for a microphysics formulated in a Lagrangian framework are discussed - random walk model and the interpolation, and its effect on microphysical properties of the cloud investigated. Turbulent velocity fluctuations significantly enhances velocity differences between colliding droplets, especially those having small sizes. As a result drizzle forms faster in simulations including a representation of turbulence. Both representations of turbulent velocity fluctuations, random walk and interpolation, have similar effect on droplet spectrum evolution, but interpolation of the velocity does account for a possible anisotropy in the air velocity. All discussed simulations show relatively large standard deviation (\\(\\)1\\(m\\)) of the cloud droplet distribution from the onset of cloud formation is observed. Because coalesence processes aerosol inside cloud droplets, detail information about aerosol is available. Results from numerical simulations show that changes in aerosol spectrum due to aerosol processing during droplet coalescence are relatively small during \\(\\)20 min. of the cloud evolution simulated with numerical model. Drizzle forms initially near the cloud edge, either near the cloud top, where the mass of water is the largest, or near the entrainment eddies.

In this paper a LES model with Lagrangian representation of microphysics is used to simulate stratucumulus clouds in idealized 2D set-up based on the VOCALS observations. The general features of the cloud simulated by the model, such as cloud water mixing ratio and cloud droplet number profile agree well with the observations. The model can capture observed relation between aerosol distribution and concentration measured below the cloud and cloud droplet number. Averaged over the whole cloud droplet spectrum from the numerical model and observed droplet spectrum are similar, with the observations showing a higher concentration of droplets bigger than 25 m. Much bigger differences are present when comparing modelled and observed droplet spectrum on specific model level. Despite the fact that microphysics is formulated in a Lagrangian framework the standard deviation of the cloud droplet distribution is larger than 1 m. There is no significant narrowing of the cloud droplet distribution in the up-drafts, but the distribution in the up-drafts is narrower than in the down-drafts. Modelled and observed standard deviation profiles agree well with observations for moderate/high cloud droplet numbers, with much narrower than observed droplet spectrum for low droplet number. Model results show that a significant percentage of droplets containing aerosol bigger than 0.3 m didn't reach activation radius, yet exceeding 1 m, what is typically measured as a cloud droplets. Also, the relationship between aerosol sizes and cloud droplet sizes is complex; there is a broad range of possible cloud droplet sizes for a given aerosol size.

Lightning frequency is now readily measured, thanks to a series of recently developed satellite-borne instruments. The study of the relationship between lightning frequency and thundercloud ice crystal content, a parameter important in climate modeling and global warming, is noted.

This chapter provides a brief account of the parameters that are important in understanding this subject, together with results from work that is being carried out at BRE to address them. At present, there is little recommended guidance on designing effectively to ventilate urban buildings by natural or low-energy means, while at the same time minimizing the ingress of external pollutants. Although there is a growing interest in the subject, there is still a current lack of fundamental understanding of the complex flow regimes and external pollutant sources and the ways in which these interact with ventilation processes and consequently with indoor air quality. It has therefore, become necessary to investigate in detail how external pollution affects the indoor environment, with a view to developing low-energy ventilation guidelines for buildings in urban conurbations.