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The impact of giant sea salt aerosols released from breaking waves on rain formation in marine boundary layer clouds is studied using large-eddy simulations (LES). We perform simulations of marine cumuli and stratocumuli for various concentrations of cloud condensation nuclei (CCN) and giant CCN (GCCN). Cloud microphysics are modeled with a Lagrangian method that provides key improvements in comparison to previous LES of GCCN that used Eulerian bin microphysics. We find that GCCN significantly increase precipitation in stratocumuli. This effect is strongest for low and moderate CCN concentrations. GCCN are found to have a smaller impact on precipitation formation in cumuli. These conclusions are in agreement with field measurements. We develop a simple parameterization of the effect of GCCN on precipitation, accretion, and autoconversion rates in marine stratocumuli. Significance Statement Breaking sea waves release salt particles into the atmosphere. Cloud droplets formed on these salt particles can grow larger than droplets formed on other smaller particles. Therefore, sea salt particles can be important for rain formation over oceans. To investigate this effect, we performed idealized computer simulations of stratocumulus and cumulus clouds. Sea salt particles were modeled with an unprecedented precision thanks to the use of an emerging modeling method. In our simulations sea salt particles significantly enhance rain formation in stratocumuli, but not in cumuli. Our study has implications for climate models, because stratocumuli are important for Earth’s energy budget and for rain enhancement experiments.

In this study, the super droplet-method (SDM) is used in large-eddy simulations of an isolated cumulus congestus observed during the 1995 Small Cumulus Microphysics Study field project in order to ...

Representation of cloud microphysics is a key aspect of simulating clouds. From the early days of cloud modeling, numerical models have relied on an Eulerian approach for all cloud and thermodynamic and microphysics variables. Over time the sophistication of microphysics schemes has steadily increased, from simple representations of bulk masses of cloud and rain in each grid cell, to including different ice particle types and bulk hydrometeor concentrations, to complex schemes referred to as bin or spectral schemes that explicitly evolve the hydrometeor size distributions within each model grid cell. As computational resources grow, there is a clear trend toward wider use of bin schemes, including their use as benchmarks to develop and test simplified bulk schemes. We argue that continuing on this path brings fundamental challenges difficult to overcome. The Lagrangian particle-based probabilistic approach is a practical alternative in which the myriad of cloud and precipitation particles present in a natural cloud is represented by a judiciously selected ensemble of point particles called superdroplets or superparticles. The advantages of the Lagrangian particle-based approach when compared to the Eulerian bin methodology are explained, and the prospects of applying the method to more comprehensive cloud simulations—for instance, targeting deep convection or frontal cloud systems—are discussed.

In a chaotic system, like moist convection, it is difficult to separate the impact of a physical process from effects of natural variability. This is because modifying even a small element of the system physics typically leads to a different system evolution and it is difficult to tell whether the difference comes from the physical impact or it merely represents a different flow realization. This paper discusses a relatively simple and computationally efficient modelling methodology that allows separation of the two. The methodology is referred to as the piggybacking approach. The idea is to use two sets of thermodynamic variables (the temperature, water vapor, and all aerosol, cloud, and precipitation variables) in a single cloud simulation. The two sets differ in a specific element of the physics, such as aerosol properties, microphysics parameterization, large-scale forcing, environmental profiles, etc. One thermodynamic set is coupled to the dynamics and drives the simulated flow, and the other set piggybacks the flow, that is, thermodynamic variables are carried by the flow but they do not affect it. By switching the two sets (i.e. the set driving the simulation becomes the piggybacking one, and vice versa), the impact on the cloud dynamics can be evaluated. This paper provides details of the method and reviews results of its application to such problems as the postulated deep convection invigoration in polluted environments, the impact of changes in environmental profiles (e.g., due to climate change) on convective dynamics, and the role of cloud-layer heterogeneities for shallow convective cloud field evolution. Prospects for applying piggybacking technique to other areas of atmospheric simulation (e.g., weather prediction or geoengineering) are also mentioned.

We report the development of a novel Lagrangian microphysics methodology for simulations of warm ice-free clouds. The approach applies the traditional Eulerian method for the momentum and continuous thermodynamic fields such as the temperature and water vapor mixing ratio, and uses Lagrangian super-droplets to represent condensed phase such as cloud droplets and drizzle or rain drops. In other applications of the Lagrangian warm-rain microphysics, the super-droplets outside clouds represent unactivated cloud condensation nuclei (CCN) that become activated upon entering a cloud and can further grow through diffusional and collisional processes. The original methodology allows for the detailed study of not only effects of CCN on cloud microphysics and dynamics, but also CCN processing by a cloud. However, when cloud processing is not of interest, a simpler and computationally more efficient approach can be used with super-droplets forming only when CCN is activated and no super-droplet existing outside a cloud. This is possible by applying the Twomey activation scheme where the local supersaturation dictates the concentration of cloud droplets that need to be present inside a cloudy volume, as typically used in Eulerian bin microphysics schemes. Since a cloud volume is a small fraction of the computational domain volume, the Twomey super-droplets provide significant computational advantage when compared to the original super-droplet methodology. Additional advantage comes from significantly longer time steps that can be used when modeling of CCN deliquescence is avoided. Moreover, other formulation of the droplet activation can be applied in case of low vertical resolution of the host model, for instance, linking the concentration of activated cloud droplets to the local updraft speed. This paper discusses the development and testing of the Twomey super-droplet methodology, focusing on the activation and diffusional growth. Details of the activation implementation, transport of super-droplets in the physical space, and the coupling between super-droplets and the Eulerian temperature and water vapor field are discussed in detail. Some of these are relevant to the original super-droplet methodology as well and to the ice phase modeling using the Lagrangian approach. As a computational example, the scheme is applied to an idealized moist thermal rising in a stratified environment, with the original super-droplet methodology providing a benchmark to which the new scheme is compared.

In the atmosphere, microphysics refers to the microscale processes that affect cloud and precipitation particles and is a key linkage among the various components of Earth's atmospheric water and energy cycles. The representation of microphysical processes in models continues to pose a major challenge leading to uncertainty in numerical weather forecasts and climate simulations. In this paper, the problem of treating microphysics in models is divided into two parts: (i) how to represent the population of cloud and precipitation particles, given the impossibility of simulating all particles individually within a cloud, and (ii) uncertainties in the microphysical process rates owing to fundamental gaps in knowledge of cloud physics. The recently developed Lagrangian particle‐based method is advocated as a way to address several conceptual and practical challenges of representing particle populations using traditional bulk and bin microphysics parameterization schemes. For addressing critical gaps in cloud physics knowledge, sustained investment for observational advances from laboratory experiments, new probe development, and next‐generation instruments in space is needed. Greater emphasis on laboratory work, which has apparently declined over the past several decades relative to other areas of cloud physics research, is argued to be an essential ingredient for improving process‐level understanding. More systematic use of natural cloud and precipitation observations to constrain microphysics schemes is also advocated. Because it is generally difficult to quantify individual microphysical process rates from these observations directly, this presents an inverse problem that can be viewed from the standpoint of Bayesian statistics. Following this idea, a probabilistic framework is proposed that combines elements from statistical and physical modeling. Besides providing rigorous constraint of schemes, there is an added benefit of quantifying uncertainty systematically. Finally, a broader hierarchical approach is proposed to accelerate improvements in microphysics schemes, leveraging the advances described in this paper related to process modeling (using Lagrangian particle‐based schemes), laboratory experimentation, cloud and precipitation observations, and statistical methods., Key Points Microphysics is an important component of weather and climate models, but its representation in current models is highly uncertainTwo critical challenges are identified: representing cloud and precipitation particle populations and knowledge gaps in cloud physicsA possible blueprint for addressing these challenges is proposed to accelerate progress in improving microphysics schemes

Nature photonics 14(6), 391 - 397 (2020). doi:10.1038/s41566-020-0607-z, The European XFEL is a hard X-ray free-electron laser (FEL) based on a high-electron-energy superconducting linear accelerator. The superconducting technology allows for the acceleration of many electron bunches within one radio-frequency pulse of the accelerating voltage and, in turn, for the generation of a large number of hard X-ray pulses. We report on the performance of the European XFEL accelerator with up to 5,000 electron bunches per second and demonstrating a full energy of 17.5 GeV. Feedback mechanisms enable stabilization of the electron beam delivery at the FEL undulator in space and time. The measured FEL gain curve at 9.3 keV is in good agreement with predictions for saturated FEL radiation. Hard X-ray lasing was achieved between 7 keV and 14 keV with pulse energies of up to 2.0 mJ. Using the high repetition rate, an FEL beam with 6 W average power was created., Published by Nature Publ. Group, London [u.a.]

A simple methodology is proposed to extract impacts of cloud microphysics on macrophysical cloud-field properties in large-eddy simulations of shallow convection. These impacts are typically difficult to assess because of natural variability of the simulated cloud field. The idea is to use two sets of thermodynamic variables driven by different microphysical schemes or by a single scheme with different parameters as applied here. The first set is coupled to the dynamics as in the standard model, and the second set is applied diagnostically—that is, driven by the flow but without the feedback on the flow dynamics. Having the two schemes operating in the same flow pattern allows for extracting the impact with high confidence. For illustration, the method is applied to simulations of precipitating shallow convection applying a simple bulk representation of warm-rain processes. Because of natural variability, the traditional approach provides an uncertain estimate of the impact of cloud droplet concentration on the mean cloud-field rainfall even with an ensemble of simulations. In contrast, the impact is well constrained while applying the new methodology. The method can even detect minuscule changes of the mean cloud cover and liquid water path despite their large temporal fluctuations and different evolutions within the ensemble.

This paper presents observations and simple numerical modeling of drizzle processes in subtropical marine stratocumulus. Flight-long statistics from DYCOMS-II flights are derived and examples of small-scale cloud and drizzle observations are presented. The small-scale observations highlight the complexity of the natural system and the deficiency of an approach where single values of relevant parameters are used to describe the entire cloud system. Together with previously published analysis of ACE-2 flights, DYCOMS-II statistics are compared to the output of a kinematic (prescribed flow) model of drizzle processes in stratocumulus. Such a model has previously been used to validate simplified approaches to cloud microphysics, and it can be used in the future as a “superparameterization” of microphysical processes within stratocumulus-topped marine boundary layer. The focus is on separating the impact of the cloud depth from the impact of the cloud droplet concentration, with deeper and lower-droplet-concentration clouds both leading to more drizzle. The kinematic model reduces the stratocumulus-topped marine boundary layer dynamics to a single circulation cell that spans the entire boundary-layer depth. The model produces significantly less drizzle than estimated from the observations, and possible reasons for such a discrepancy are discussed. However, the model does reproduce observationally-based relationships between drizzle and such cloud parameters as cloud depth, droplet concentration, or maximum droplet size near the cloud top. To quantify the observed reductions of the cloud water and droplet concentration, a twin experiment approach is used, with and without collision/coalescence. The results show that observed reduction of cloud water content and droplet concentration may result from scavenging of cloud droplets by drizzle drops, in addition to processes by design excluded from the model, such as entrainment.

This paper presents application of the EULAG model combined with a sophisticated double-moment warm-rain microphysics scheme to the model intercomparison case based on RICO (Rain in Cumulus over Ocean) field observations. As the simulations progress, the cloud field gradually deepens and a relatively sharp temperature and moisture inversions develop in the lower troposphere. Two contrasting aerosol environments are considered, referred to as pristine and polluted, together with two contrasting subgridscale mixing scenarios, the homogeneous and the extremely inhomogeneous mixing. Pristine and polluted environments feature mean cloud droplet concentrations around 40 and 150 mg−1, respectively, and large differences in the rain characteristics. Various measures are used to contrast evolution of macroscopic cloud field characteristics, such as the mean cloud fraction, the mean cloud width, or the height of the center of mass of the cloud field, among others. Macroscopic characteristics appear similar regardless of the aerosol characteristics or the homogeneity of the subgrid-scale mixing.

A b s t r a c t This paper describes implementation of the warm-rain bin microphysics in a LES model based on the EULAG fluid flow solver. The binmicrophysics EULAG is applied to the case of shallow nonprecipitating tropical convection to investigate the impact of the secondary activation of cloud droplets above the cloud base. In a previous study applying the EULAG model with the double-moment bulk warm-rain microphysics scheme, the in-cloud activation was shown to have significant implications for the mean microphysical and optical characteristics of the cloud field. By contrasting the simulations with and without in-cloud activation as in the previous study, we show that the in-cloud activation has qualitatively similar but quantitatively smaller eect. In particular, the concentration of cloud droplets in the bin simulation without in-cloud activation decreases with height not as strongly as in corresponding simulations applying the double-moment bulk scheme.

This paper presents a hybrid approach to model warm-rain processes, merging the diverse schemes of bulk and detailed (bin) microphysics. In the bulk scheme, the key assumption is that the exact saturation is maintained inside a cloud. In contrast, the supersaturation inside a cloud is predicted in the bin scheme and is applied to calculate the diffusional growth of cloud droplets. Predicting the supersaturation is numerically cumbersome, however, and typically requires spatial and temporal resolutions that are significantly higher than those that can be applied in the bulk scheme. At the same time, supersaturations inside clouds are small, and the condensate amounts in bulk and bin schemes differ insignificantly. This critical observation forms a starting point for the hybrid bulk–bin approach. In this approach, when the cloud water first appears, the activation scheme inserts cloud droplets at the low end of the bin representation. Subsequent diffusional and eventually accretional growth shift the spectrum toward larger sizes so that the saturation inside a cloud is maintained. Details of the hybrid approach are discussed in this paper, and the validation against the traditional bin scheme in a framework of the adiabatic rising parcel is presented. Before the scheme can be applied to the multidimensional cloud model, a 1D advection–condensation problem of Grabowski and Smolarkiewicz is used to address the issue of the numerical difficulties that finite-difference schemes experience near cloud edges. In the bulk case, these are in the form of condensation rate overshoots and undershoots; and this aspect requires special attention in the hybrid scheme. A novel approach is developed that provides a physically consistent solution near cloud edges using the hybrid bulk–bin scheme. The key is to allow grid boxes near the edges to be partly cloudy and to include spectral changes of cloud droplets that take this into account. Application of the hybrid scheme to an idealized 2D problem of moist thermal rising from rest and producing rain illustrates the application of the scheme to practical problems of cloud dynamics and warm-rain microphysics.

Quantitative parameterization of turbulent collision of cloud droplets represents a major unsolved problem in cloud physics. Here a hybrid direct simulation tool is used specifically to quantify the turbulent enhancement of the gravitational collision-coalescence. Simulation results show that air turbulence can enhance the collision kernel by an average factor of about 2, and the observed trends are supported by scaling arguments. An impact study using the most realistic collection kernel suggests that cloud turbulence can significantly reduce the time for warm rain initiation. Areas for further development of the hybrid simulation and the impact study are indicated. Copyright © 2009 Royal Meteorological Society

This paper presents a straightforward approach to mitigate the problem of spurious cloud-edge supersaturation in high-spatial-resolution cloud models (e.g., moist large-eddy simulation models). The central idea, following a 1989 J. Atmos. Sci. paper by Grabowski, is that supersaturation predicted by the supersaturation equation should be used to adjust the temperature and moisture solutions, rather than the other way around as in the standard approach in cloud modeling, where the temperature and moisture solutions are used to diagnose the supersaturation. Details of the adjustment scheme are discussed and illustrated through simple one-dimensional tests applying a two-moment warm-rain microphysics scheme that predicts the in-cloud supersaturation. Extension of this approach to bin microphysics models is also outlined.

We discuss the progress in the R&D program for a future upgrade of the European XFEL facility, namely for an operation in the continuous wave (cw) and long pulse (lp) modes, which will allow for significantly more flexibility in the electron and photon beam time structure. Results of cw/lp runs with preseries XFEL cryomodules and status of components needed for the new operation modes are presented here.

A key factor limiting the reliability of simulations of anthropogenic climate change is the inability to accurately represent the various effects of clouds on climate. Despite the best efforts of the community, the problem has resisted solution for several decades. The reasons for this are briefly reviewed and it is argued that it will be many more decades before the problem can be solved through the approaches to cloud parameterization that have been used up to now. An alternative approach, called superparameterization, is then outlined, in which high-resolution cloud system-resolving models (CSRMs) are used in place of the conventional cloud parameterizations. Tests performed with the Community Atmosphere Model show that superparameterizations can give more realistic simulations of the current climate, including greatly improved simulations of the Madden–Julian oscillation and other tropical wave disturbances. Superparameterizations increase the cost of climate simulation by a factor of several hundred dollars, but can make efficient use of massively parallel computers. In addition, superparameterizations make it possible for a climate model to converge to a global CSRM as the horizontal grid spacing of the climate model decreases to a few kilometers. No existing global atmospheric model has this convergence property. Superparameterizations have the potential to greatly increase the reliability of climate change simulations.

This paper documents the impact of ice microphysics on the multiscale organization of tropical convection as simulated in two-dimensional cloud-resolving model simulations. Results from simulations which apply warm-rain microphysics are compared with results from a simulation which includes ice processes presented previously in this journal. In these simulations, moist convection and large-scale dynamics interact on an unprecedented range of spatial and temporal scales, albeit within a limited two-dimensional dynamical framework. In general, the large-scale organization of convection is similar in all simulations, although the scale and propagation speed of convectively-coup led gravity waves are different between the warm-rain and ice simulations. The most striking differences are on the mesoscale. The warm-rain simulations feature mesoscale convective systems with a reduced stratiform component and shorter life cycle than mesoscale systems in the simulation with ice microphysics. These impacts are consistent with previous modelling studies of the impact of ice microphysics on organized convection. It is hypothesized that the shorter life cycle of mesoscale convective systems in warm-rain simulations influences scale selection of the large-scale convectively-coup led gravity waves. Moreover, the vertical transport of horizontal momentum is affected as well. To the author's knowledge this is the first time the impact of cloud microphysics on mesoscale convective systems is shown to affect the coupling between deep convection and large-scale perturbations in the tropics. Copyright © 2003 Royal Meteorological Society

The recently reported nonhydrostatic anelastic numerical model for simulating a range of atmospheric processes on scales from micro to planetary is extended to moist processes. A theoretical formulation of moist precipitating thermodynamics follows the standard cloud models; that is, it explicitly treats the formation of cloud condensate and the subsequent development and fallout of precipitation. In order to accommodate a broad range of temporal scales, the customized numerical algorithm merges the explicit scheme for the thermodynamics with the semiimplicit scheme for the dynamics, where the latter is essential for the computational efficiency of the global model. The coarse spatial resolutions used in present global models result in a disparity between the timescales of the fluid flow and the much shorter timescales associated with phase-change processes and precipitation fallout. To overcome this difficulty the approach based on the method of averages is employed, where fast processes are evaluated with adequately small time steps (and lower accuracy) over the large time step of the model, to provide an accurate approximation to the large time step integral of fast forcings in the stiff system. This approach allows for stable integrations when cloud processes are poorly resolved and it converges to the formulation standard in cloud models as the resolution increases. The theoretical developments are tested in simulations of small-, meso-, and planetary-scale idealized moist atmospheric flows. Results from the smallscale simulations demonstrate that the proposed approach compares favorably with traditional explicit techniques used in cloud models. Planetary simulations, on the other hand, illustrate an ability to capture moist processes in low-resolution large-scale flows.

This paper discusses impacts of cloud and precipitation processes on macrophysical properties of shallow convective clouds as simulated by a large-eddy model applying warm-rain bin microphysics. Simulations with and without collision-coalescence are considered with CCN concentrations of 30, 60, 120, and 240 mg−1. Simulations with collision-coalescence include either the traditional gravitational collision kernel or a novel kernel that includes enhancements due to the small-scale cloud turbulence. Simulations with droplet collisions were discussed in Wyszogrodzki et al. (2013) focusing on the impact of the turbulent collision kernel. The current paper expands that analysis and puts model results in the context of previous studies. Despite a significant increase of the drizzle/rain with the decrease of CCN concentration, enhanced by the impact of the small-scale turbulence, impacts on the macroscopic cloud field characteristics are relatively minor. We document a clear feedback between cloud-scale processes and the mean environmental profiles that increases with the amount of drizzle/rain. Model results show a systematic shift in the cloud top height distributions, with an increasing contributions of deeper clouds and an overall increase of the number of cloudy columns for stronger precipitating cases. We argue that this is consistent with the explanation suggested in Wyszogrodzki et al. (2013) namely, the increase of drizzle/rain leading to a more efficient condensate off-loading in the upper parts of the cloud field. An additional effect involves suppressing cloud droplet evaporation near cloud edges in low-CCN simulations as documented in previous studies. We pose a question whether the effects of cloud turbulence on drizzle/rain formation can be corroborated by remote sensing observations, for instance, from space. Although a clear signal is extracted from model results, we argue that the answer is negative due to uncertainties caused by the temporal variability of the shallow convective cloud field, sampling and spatial resolution of the satellite data, and overall accuracy of remote sensing retrievals.

This paper discusses the role cloud microphysics play in the tropical climate. It is argued that this problem can best be studied within the context of a cloud-resolving model because of complicated interactions among cloud dynamics, cloud microphysics, radiative processes, and surface processes. Two sets of highly idealized cloud-resolving simulations are discussed. In each set, the simulations differ only in the parameters applied in the representation of cloud microphysics. The simulations are run until quasi-equilibrium between sinks and sources of moisture and energy is achieved. The comparisons between simulations applying dramatically different parameters exposes the effects of cloud microphysics on the mean state of the tropical atmosphere and on the tropical climate. The first set considers large-scale flow driven by sea surface temperature gradients and prescribed radiative cooling. The cloud microphysics appears to have minor effects on the large-scale flow as well as temperature and m...

Large-scale conditions during the 7-day period of Phase III of the Global Atmospheric Research Program Atlantic Tropical Experiment are used to study effects of cloud microphysics on the convecting tropical atmosphere. Two-dimensional numerical experiments evaluate the effects of extreme changes to the cloud microphysics in the cloud resolving model. The main conclusions are the following. (a) Extreme changes in cloud microphysics affect the temperature and moisture profiles in a way that approximately retains relative humidity profiles in all experiments. (b) With prescribed radiative tendencies, effects of cloud microphysics on surface processes are paramount. Extreme changes in warm rain microphysics indirectly affect the temperature and moisture profiles by modifying surface sensible and latent heat fluxes. For instance, smaller raindrops, and to a lesser degree slower conversion of cloud water into rain, result in enhanced updraft and downdraft cloud mass fluxes, a colder and drier boundary ...

Two- and three-dimensional simulations of cloud systems for the period of 1–7 September 1974 in phase III of the Global Atmospheric Research Programme (GARP) Atlantic Tropical Experiment (GATE) are performed using the approach discussed in Part I of this paper. The aim is to reproduce cloud systems over the GATE B-scale sounding array. Comparison is presented between three experiments driven by the same large-scale conditions: (i) a fully three-dimensional experiment, (ii) a two-dimensional experiment that is an east–west section of the three-dimensional case, and (iii) a high-resolution version of the two-dimensional experiment. Differences between two- and three-dimensional frameworks and those related to spatial resolution are analyzed. The three-dimensional experiment produced a qualitatively realistic organization of convection: nonsquall clusters, a squall line, and scattered convection and transitions between regimes were simulated. The two-dimensional experiments produced convective organ...

This paper discusses cloud microphysical processes essential for the large-scale tropical circulations and the tropical climate, as well as the strategy to include them in large-scale models that resolve cloud dynamics. The emphasis is on the ice microphysics, which traditional cloud models consider in a fairly complex manner and where a simplified approach is desirable. An extension of the classical warm rain bulk parameterization is presented. The proposed scheme retains simplicity of the warm rain parameterization (e.g., only two classes of condensed water are considered) but introduces two important modifications for temperatures well below freezing:1) the saturation conditions are prescribed based on saturation with respect to ice, not water; and 2) growth characteristics and terminal velocities of precipitation particles are representative for ice particles, not raindrops. Numerical tests suggest that, despite its simplicity, the parameterization is able to capture essential aspects of the ...

A dynamical model, in conjunction with a microphysical model designed to predict evolution of cloud droplet spectra, is employed to perform two-dimensional simulations of a small nonprecipitating cumulus cloud in the presence of wind shear. Upshear–downshear differences in terms of entrainment sites, mixing zones, degree of dilution, and spectral properties are investigated and compared to some observations. Results show no systematic differences between the upshear and downshear sides of individual cloud turrets composed of cloudy air of rather uniform age. However, important differences in the spectral properties are noted between new cloudy air growing on the upshear side of the cloud and older cloudy volumes dissipating on the downshear side of the cloud. It is found that stronger wind shear inhibits the interaction between cloud turrets of different ages.

This paper discusses cloud simulations aiming at quantitative assessment of the effects of cloud turbulence on rain development in shallow ice-free convective clouds. Cloud fields from large-eddy simulations (LES) applying the bin microphysics with the collision kernel enhanced by cloud turbulence are compared to those with the standard gravitational collision kernel. Simulations for a range of cloud condensation nuclei (CCN) concentrations are contrasted. Details of the turbulent kernel and how it is used in LES simulations are presented. Because of the disparity in spatial scales between the bottom-up numerical studies guiding the turbulent kernel development and the top-down LES simulations of cloud dynamics, we address the consequence of the turbulence intermittency in the unresolved range of scales on the mean collision kernel applied in LES. We show that intermittency effects are unlikely to play an important role in the current simulations. Highly-idealized single-cloud simulations are used to illustrate two mechanisms that operate in cloud field simulations. First, the microphysical enhancement leads to earlier formation of drizzle through faster autoconversion of cloud water into drizzle, as suggested by previous studies. Second, more efficient removal of condensed water from cloudy volumes when a turbulent collection kernel is used leads to an increased cloud buoyancy and enables clouds to reach higher levels. This is the dynamical enhancement. Both mechanisms seem to operate in the cloud field simulations. The microphysical enhancement leads to the increased drizzle and rain inside clouds in simulations with high CCN. In low-CCN simulations with significant surface rainfall, dynamical enhancement allows maintenance of the cloud water path despite significant increase of the precipitation water path and dramatically increased mean surface rain accumulation. These results call for future modeling and observational studies to corroborate the findings.

A formal framework is established for the way in which cloud-resolving numerical models are used to investigate the role of precipitating cloud systems in climate and weather forecasting models. Emphasis is on models with periodic lateral boundary conditions that eliminate unrealistic numerically generated circulations caused by open boundary conditions in long-term simulations. Defined in this formalism is the concept of large-scale forcing and the cloud-environment interactions that are consistent with the periodic boundary conditions. Two-dimensional numerical simulations of the evolution of cloud systems during 1–7 September 1974 in Phase III of the Global Atmospheric Research Program Atlantic Tropical Experiment (GATE) are conducted. Based on the above formalism, a simple technique is used to force an anelastic cloud-resolving model with evolving large-scale horizontal wind field and large-scale forcing for the temperature and moisture obtained from the GATE data. The 7-day period selected i...

This paper discusses two-time-level semi-Lagrangian approximations for the bulk warm-rain microphysics embedded in the framework of an anelastic cloud model. The central theoretical issue is a semi-Lagrangian integration of the rain-evolution equation. Because departure points of rain trajectories differ from those of flow trajectories and the terminal velocity of the precipitation depends on the concentration of the precipitation itself, effective semi-Lagrangian approximations are not necessarily straightforward. Some simplifying assumptions are adopted that compromise formal accuracy and computational efficiency of the method. Theoretical considerations are illustrated with idealized simulations of precipitating thermal convection and orographically forced clouds. Comparisons with corresponding results obtained using a more traditional, flux-form Eulerian cloud model document highly competitive performance of the semi-Lagrangian approach. Although derived for the warm-rain parameterization, th...

In this project, we focused on applications of the new warm-rain and ice microphysics schemes to simulate various cloud systems. The overall goal was either to evaluate and improve specific aspects of the schemes (through comparisons with ARM/ASR observations) or to understand the coupling between aerosols, cloud microphysics and cloud dynamics in variety of situations. These studies are relevant to the indirect impact of atmospheric aerosols on climate. Below we report on selected key aspects of the research and then list all peer-reviewed papers that acknowledge support from this grant. Overall, studies partially supported by this grant resulted in 30 peer-reviewed publications (listed below), several dozens of conference presentations (including posters and oral presentations at the ASR Science Team Meetings), and two PhD dissertations. More detailed summaries of our accomplishments are included in yearly reports. Here we summarize only major efforts.

Progress in the development of the PetaScale implementation of the anelastic EULAG model combined with the warm-rain bulk and bin microphysics schemes, as well its application to multiscale cloud modeling, are presented. A new three-dimensional (3D) model domain decomposition is implemented to increase model performance and scalability. We investigate performance of the code on IBM BlueGene/L and Cray XT4/XE6 architectures. The scalability results show significant improvement of the new domain decomposition over the previous 2D decomposition used as the standard in many geophysical fluid flow models.

Topical treatment of gastric mucosa with capsaicin (cap) increases gastric mucosal blood flow (GMBF) and protects the mucosa from injury by acidified bile salts. The purpose of this study was to test the hypothesis that this hyperemia related "cytoprotection" is mediated by nitric oxide. Male Sprague-Dawley rats were anesthetized and the glandular stomach (blood supply intact) was chambered between two plastic rings. Animals were divided into four groups. All groups received a 5-min topical saline exposure. Groups 1 and 2 received iv saline or nitro-L-arginine methyl ester (L-NAME, 25 mg/kg iv), a specific nitric oxide inhibitor, 5 min prior to baseline treatment, followed by a 15-min preinjury period of saline and a 15-min injury period of 10 mM acidified taurocholate (ATC, pH 1.2). Groups 3 and 4 were treated as above except topical cap (160 microM) was used during the preinjury period. GMBF was measured with a laser Doppler flowmeter (ml/min/100 g tissue). Injury was assessed grossly (grade 0-3), histologically (grade 0-3), and by measuring DNA content of a 5-min N-acetylcysteine wash (DNAE). Baseline GMBF of 30 +/- 1.5 significantly decreased to 15 +/- 1.2 in group 1 versus group 2 (P0.05). When topical ATC was used GMBF increased to 59 +/- 4.9 and 25 +/- 2.8, respectively. Injury by grade and DNAE was not significantly different between these groups. GMBF during cap exposure was 42 +/- 4 and 22 +/- 2 in groups 3 and 4, respectively. Graded histologic and gross injuries were significantly worse in group 4 compared to group 3 (P0.05).(ABSTRACT TRUNCATED AT 250 WORDS)

A simple numerical model designed to predict the evolution of cloud droplet spectra with special emphasis on the role of entrainment is developed for a case of nonprecipitating cloud. The model assumes that the cloud water mixing ratio at any grid location is equal to that predicted by a cloud model using bulk microphysics; that is, supersaturation/undersaturation inside cloud is neglected. Locally, only undiluted droplet concentrations are assumed to exist; any average dilution of cloud droplet concentration observed over a grid volume is interpreted as an effect of internal structure within the grid, with undiluted cloudy patches coexisting with those that are cloud free. Activation of cloud condensation nuclei is assumed to always produce the same initial spectrum of cloud droplets. Further condensational growth of this initial spectrum produces a set of base functions that are used to represent droplet spectral evolution. The microphysical model, combined with the two-dimensional cloud model ...

We present an approach to simulate cloud radar signals on the basis of cloud model output, the radar simulator. The simulator is being developed to aid validation of the cloud model. The cloud model applies double-moment bulk warm-rain and ice schemes developed by Morrison and Grabowski. 1, 2 As an input, the simulator uses profiles of the mixing ratios and number concentrations of cloud droplets, rain/drizzle drops, and ice crystals, as well as the air temperature. For the ice crystals, the rimed mass fraction predicted by the ice scheme is also used. The simulator applies precomputed look-up tables containing scattering properties of cloud and precipitation particles, such as reflectivities, extinction and absorption coefficients. For each grid point, the coefficients are integrated over particle size distributions and summed over hydrometeor types. Consistent with assumptions in the cloud model microphysical scheme, modified gamma size distributions are assumed for cloud droplets and ice crystals, whereas the exponential Marshall-Palmer size distribution is assumed for the rain/drizzle drops. Application of the radar simulator to a simulation of clouds observed during the TWP-ICE campaign over northern Australia is presented.

Deriving a new photopolymerization model incorporating a unimolecular termination agent we show a spatial scale dependence on recording fidelity. Larger scale structures narrow, while smaller structures are unaffected, potentially increasing microholographic storage density.

We propose a method for making low loss ring resonators in self processing photopolymers via direct-write lithography. This direct-write method compensates radiation mode coupling to first order, significantly reducing bend loss.

Holographic photopolymers develop permanent index change via the polymerization and subsequent diffusion of monomer. It is well-known that to achieve high-fidelity recording, the rate of polymerization must be small in comparison to the rate of diffusion, particularly for strong exposures that consume significant fractions of the available monomer. When this condition is violated, polymerization is slowed in high-intensity regions by the local depletion of monomer, resulting in broadening of recorded features. This paper shows that a diffusing inhibitor has analogous dynamics controlled by the ratio of inhibitor diffusion rate to inhibition rate. When the ratio is small, inhibitor is locally depleted in bright regions, resulting in localized acceleration of polymerization. This causes recorded index features to be narrower than the incident optical exposure. Theoretical, numerical and experimental studies are used to illustrate this fact and show that this narrowing can be used to compensate for the broadening caused by monomer dynamics. Both effects are emphasized for rapid, strong recordings, suggesting that an inhibitor may be used to increase recording fidelity in this limit.

The number of layers of a micro-holographic disk is limited by wavefront aberration which is strongly dependent on the photopolymer initiation, termination and inhibition kinetics. 3D metrology is used to validate predicted index profiles.

This paper presents results from ground-based remote sensing of optical properties of shallow convective clouds over the Nauru ARM site using the technique developed in McFarlane et al. (J. Geophys. Res. 2002). Herein, the results of a pilot study are presented with analysis of about six months of cloud data. The effective radius (re) shows large spatial variability, with the frequency of occurrence relatively narrow near the cloud base, and gradually widening aloft. Available column data for LWC and re allow derivation of the pdf of the optical thickness tau. The pdf shows that clouds with tau in the range 5 to 10 are most frequent, but there is a long tail with clouds up to tau = 100. These results are discussed in the context of traditional observations of cloud microstructure using an instrumented aircraft.

We demonstrate a three-dimensional direct-write lithography system capable of writing deeply buried, localized index structures into diffusion-mediated photopolymer. The system is similar to that used for femtosecond writing in glass, but has a number of advantages including greater flexibility in the writing media and the ability to use low power, inexpensive, continuous-wave lasers. This system writes index structures both parallel and perpendicular to the writing beam in different types of photopolymers, providing control over the feature size and shape. We demonstrate that this system can be used to create single-mode waveguides that are deeply embedded in the photopolymer medium.

Models of the index response of diffusion photopolymers typically assume that polymerization is proportional to optical intensity. However, common radical initiators self-terminate. This reduces the polymerization rate and has been shown in steady state to result in polymerization that is proportional to the square root of intensity. We examine the impact of sublinear polymerization rate on the spatial distribution of index in volume photopolymers. In contrast to previous work based on spatial frequency harmonics, we consider a Gaussian focus and examine the index in the spatial domain. This can thus be thought of as the impulse response of the material which, due to the nonlinear response, is not the Fourier transform of the previous studies. We show that sublinear polymerization rate dramatically impacts the spatial confinement of the index response. A case of particular interest to applications such as shift-multiplexed holography is a Gaussian beam translated orthogonal to its axis. In this geometry, a square-root material response yields an index profile of infinite axial dimension. We verify this prediction experimentally. The axial confinement of cationic (linear) photopolymer is shown to be significantly smaller than a radical (sublinear) photopolymer under the same writing conditions, confirming the prediction.

We proposed a new kind of setup for the automatic control of the quality of micro lens array, which is based on semiderivative real filter. With the use of the 4f correlator setup with a semiderivative filter placed in the Fourier plane and connected with the camera, it is possible to examine phase objects. Such a setup is shift invariant, so it enables us to simultaneously examine a set of identical elements, such as a micro lens array. Additionally, the same setup allows for a simultaneous measurement of both thin and thick phase objects. It is also possible to measure a wide range of phase gradients. The article presents the results of simulations where the semiderivative filter was used to measure phase objects such as cylindrical and spherical lenses. A special emphasis was placed upon checking how the proposed setup works for a number of similar phase optical elements, such as microlens arrays. The article also presents an analysis of how various technological limitations can influence the quality and the precision of the results obtained. Further on, it shows the initial results of the use of 3D lithography to produce semiderivative filters.

Three-dimensional direct-write lithography can be used to pattern waveguides into diffusion photopolymer using low-power CW lasers as an alternative to femtosecond writing in glass. We show that polymer chemistry permits significant control of waveguide shape.

We demonstrate a novel fiber to waveguide coupling in which fiber ends are encapsulated in photopolymer and located by specialized microscopes. Optical waveguides are formed directly off of the fiber cores via 3D direct-write lithography.

We demonstrate deeply buried localized index structures in photopolymer written by three dimensional direct write lithography. High-fidelity cross-sections of these weak index structures are measured by a new form of diffraction tomography without phase reconstruction.

Traditional planar lightwave circuits fabricated from lithographically-patterned waveguides in glasses, semi-conductors or polymers cannot accommodate the wide range of materials required by typical optical devices. In addition, such waveguides are nearly always defined in the material surface and thus can support only a limited density of interconnects and suffer poor performance at waveguide crossings. Furthermore, the inflexibility of lithographic approaches -- including both waveguides and "silicon-bench" methods -- requires optical sub-components with unreasonable and expensive tolerances. We propose an alternative integrated optics platform based on 3D direct-write lithography into an optically addressable encapsulant. Arbitrary micro-optics are first embedded in a liquid monomer which is then cured into a semi-solid pre-polymer. It is essential that this step take place with minimal shrinkage to avoid stresses. A scanning confocal microscope then nondestructively identifies the component locations and their tolerances. The controller customizes the circuit design to accommodate these tolerances and then scans a 0.3 to 0.6 NA focus within the volume of the holographic polymer to create waveguides, lenses or other passive interconnects with one micron resolution. A final incoherent exposure cures and solidifies the polymer, finishing the process. The resulting hybrid optoelectronic circuits contain 3D routed waveguides interconnecting active and passive micro-optic devices in environmentally robust, hermetically sealed packages. A feature of particular interest is the ability to write waveguides directly off of the tips of embedded fibers, passively interfacing the circuits to fiber. We show that polymers developed for holographic data storage have the properties required for this application.

Photopolymers developed for holographic data storage have good optical quality in millimeter-thick films, very low shrinkage and large index change. We show that these materials will support single-mode waveguides created via three-dimensional direct-write lithography.

We study the potentialities of three dimensional micro-optical pathway blocks combining refractive microlens arrays, reflective micro-prisms and diffractive fan-out elements, to enhance the functionalities of short-distance intra-chip optical interconnects. As an example, we demonstrate the possibility to enhance the point-to-point interconnection functionality to that of broadcasting data over a chip. We also investigate the limitations imposed by the physical dimensions of the refractive and diffractive micro-optical components. We then illustrate this example by a quantitatively elaborated design of a fan-out element from a VCSEL array to a detector array with a 1 to 9 signal broadcasting for every source. Furthermore we show that with the use of DOE’s we can achieve a broadcasting functionality that can lead towards reconfigurable optical interconnects, with the aid of wavelength sensitive resonant cavity detectors and WDM-inspired interconnection schemes.

A scaled-oxide low-threshold P-channel trench gated DMOS employing a 12 Mcell/in/sup 2/. (2 Mcell/cm/sup 2/) closed-cell design, 8-V gate rating and 30-V drain rating is described. Measured specific resistances of 900 /spl mu//spl Omega/-cm/sup 2/ at V/sub G/S=2.7 V and 700 /spl mu//spl Omega/-cm/sup 2/. At V/sub GS/=4.5 V represent the lowest R/sub DSA/ values ever reported for a P-channel DMOS with a 37-V breakdown. The benefit of a 3X scaling of gate oxide thickness is shown by measurement, analytical and numerical modeling to produce a 1.6-V reduction in threshold, a 75% reduction in channel resistance and a 45% reduction in overall trench DMOS on-resistance at V/sub GS/=4.5 V. High density 30-V planar DMOS die resistance is shown to be 3.7X that of the scaled-oxide trench DMOS at V/sub GS/=4.5 V.

A 30-V bidirectionally blocking battery disconnect switch (BDS) for use in multiplexed-battery multimedia-notebook computers is described and demonstrated, comprising a multichip SO-16 packaged combination of a BiC/DMOS control IC and two back-to-back configured 32 Mcell/in/sup 2/ P-channel TrenchFETs. The control IC combines ground-referenced 3- to 5-V logic inputs with 2 kV ESD protection, level shifting to a 30 V supply rail, a 4 /spl mu/sec typical turn-on delay, multichannel 1.5 /spl mu/sec guaranteed break-before-make (BBM) operation, and 20 V voltage clamping protecting the gates of the highside TrenchFET switches. Total series BDS on-resistance is measured at 30 to 50 m/spl Omega/ over the 7 to 20 V specified input range consistent with 3 and 4-cell Li ion battery pack design, having 10 nA off-state and 2 /spl mu/A on-state supply currents, well below the currents required by charge-pumped highside N-channel solutions.

A new concept to control TrenchFET avalanche breakdown using an evenly distributed array of voltage clamps in a 1-of-n cell arrangement is introduced, improving on-resistance without sacrificing device ruggedness. Using this technique, a 32 Mcell/in/sup 2/ (5 Mcell/cm/sup 2/) 30-V N-channel TrenchFET with over 1 million active cells is reported having a die resistance of 2.0 m/spl Omega/ and a total packaged on-resistance of 3.1 m/spl Omega/. For V/sub GS/=10 V and a 20-V gate rating, a measured R/sub DS/A of 0.25 m/spl Omega/-cm/sup 2/ is 49% that of a previous-generation 12 Mcell/in/sup 2/ design. Empirically calibrated 3D device simulations illustrate that improved epitaxial current spreading accounts for 31% of the resistance reduction in this density range. TrenchFET avalanche current densities exceeding 950 A/cm/sup 2/ predicted by simulation are confirmed by unclamped inductive switching (UIS) measurements.