scholarly journals Revisiting adiabatic fraction estimations in cumulus clouds: high-resolution simulations with a passive tracer

2021 ◽  
Vol 21 (21) ◽  
pp. 16203-16217
Author(s):  
Eshkol Eytan ◽  
Ilan Koren ◽  
Orit Altaratz ◽  
Mark Pinsky ◽  
Alexander Khain
Keyword(s):  
High Resolution ◽  
Accurate Description ◽  
Cloud Base ◽  
Passive Tracer ◽  
Cumulus Clouds ◽  
Microphysics Scheme ◽  
Convective Clouds ◽  
Open Questions ◽  
Bin Microphysics ◽  
Normalized Concentration

Abstract. The process of mixing in warm convective clouds and its effects on microphysics are crucial for an accurate description of cloud fields, weather, and climate. Still, they remain open questions in the field of cloud physics. Adiabatic regions in the cloud could be considered non-mixed areas and therefore serve as an important reference to mixing. For this reason, the adiabatic fraction (AF) is an important parameter that estimates the mixing level in the cloud in a simple way. Here, we test different methods of AF calculations using high-resolution (10 m) simulations of isolated warm cumulus clouds. The calculated AFs are compared with a normalized concentration of a passive tracer, which is a measure of dilution by mixing. This comparison enables the examination of how well the AF parameter can determine mixing effects and the estimation of the accuracy of different approaches used to calculate it. Comparison of three different methods to derive AF, with the passive tracer, shows that one method is much more robust than the others. Moreover, this method's equation structure also allows for the isolation of different assumptions that are often practiced when calculating AF such as vertical profiles, cloud-base height, and the linearity of AF with height. The use of a detailed spectral bin microphysics scheme allows an accurate description of the supersaturation field and demonstrates that the accuracy of the saturation adjustment assumption depends on aerosol concentration, leading to an underestimation of AF in pristine environments.

scholarly journals What is Adiabatic Fraction in Cumulus Clouds: High-Resolution Simulations with Passive Tracer

2021 ◽  
Author(s):  
Eshkol Eytan ◽  
Ilan Koren ◽  
Orit Altaratz ◽  
Mark Pinsky ◽  
Alexander Khain
Keyword(s):  
High Resolution ◽  
Cloud Base ◽  
Passive Tracer ◽  
Cumulus Clouds ◽  
Microphysics Scheme ◽  
Convective Clouds ◽  
Weather And Climate ◽  
Bin Microphysics ◽  
Open Question ◽  
Normalized Concentration

Abstract. The process of mixing in warm convective clouds and its effects on microphysics, is crucial for an accurate description of cloud fields, weather, and climate. Still, it remains an open question in the field of cloud physics. Adiabatic regions in the cloud could be considered as non-mixed areas and therefore serve as an important reference to mixing. Therefore, the adiabatic fraction (AF) is an important parameter that estimates the mixing level in the cloud in a simple way. Here, we test different methods of AF calculations using high-resolution (10 m) simulations of isolated warm Cumulus clouds. The calculated AFs are compared with a normalized concentration of a passive tracer, which is a measure of dilution by mixing. This comparison enables us to examine how well the AF parameter can determine mixing effects, and to estimate the accuracy of different approaches used to calculate it. The sensitivity of the calculated AF to the choice of different equations, vertical profiles, cloud base height, and its linearity with height are all tested. Moreover, the use of a detailed spectral bin microphysics scheme demonstrates that the accuracy of the saturation adjustment assumption depends on aerosol concentration, and leads to an underestimation of AF in pristine environments.

The adiabaticity of warm cumulus clouds simulated in high-resolution 

2021 ◽  
Author(s):  
Eshkol Eytan ◽  
Ilan Koren ◽  
Alexander Khain ◽  
Orit Altaratz ◽  
Mark Pinsky ◽  
...  
Keyword(s):  
High Resolution ◽  
Environmental Parameters ◽  
Liquid Water Content ◽  
Cumulus Clouds ◽  
Local Boundary ◽  
Aerosol Loading ◽  
Hebrew University ◽  
Key Variables ◽  
Microphysical Processes ◽  
Bin Microphysics

<p>The strong coupling between dynamic, thermodynamic, and microphysical processes and the numerous environmental parameters on which they depend makes clouds a highly complex system. Adiabatic regions (i.e., undiluted core) in the cloud allow to approximate in a simple way thermodynamic and microphysical profiles and provide local boundary conditions (i.e. core is a source of adiabatic values in each level). Mixing of the cloud with its environment affects both the cloud and the environmental properties. While environmental humidity, temperature and aerosol loading affect the clouds’ buoyancy and droplets size distribution (DSD), clouds simultaneously affect their surrounding via detrainment of droplets, humid air, and processed aerosols. Mixing occurs within a large spectrum of scales and leads to deviation of parts of the cloud from adiabaticity. The level of adiabaticity can be represented continuously by the adiabatic fraction (AF; defined as the ratio of the liquid water content to the theoretical adiabatic value). In this work we used the System of Atmosphere Modeling (SAM) with the Hebrew University Spectral Bin Microphysics to simulate a few isolated non-precipitating trade cumulus clouds (in different sizes and aerosol loading) in high resolution (10m). Passive tracer was added to all the simulations. We found cloudy volumes that contain both high tracer concentration and high AF (up to the clouds’ top), compared these two measures of mixing, and discuss their differences. The accuracy of AF calculations, based on different known methods is tested. For example, we show that the saturation adjustment assumption that is often used in AF calculations can lead to an underestimation of AF in pristine environments. This will mask microphysical effects and cause biases when comparing the adiabaticity of clouds under different aerosols loading. We show that the space spanned by the AF versus height in the cloud is a good measure for describing changes in cloud’s key variables in space and time (like temperature, updraft, and DSD properties). This space of AF vs height demonstrates how certain processes (e.g. in-cloud nucleation, mixing, evaporation, etc.) dominate different regions in the cloud (core, edge), and cause different dependence of the DSD on AF under different aerosols loading.</p>

scholarly journals Theoretical basis for convective invigoration due to increased aerosol concentration

2011 ◽  
Vol 11 (11) ◽  
pp. 5407-5429 ◽  
Author(s):  
Z. J. Lebo ◽  
J. H. Seinfeld
Keyword(s):  
Number Concentration ◽  
Latent Heating ◽  
Heating Rates ◽  
Microphysics Scheme ◽  
Convective Clouds ◽  
Aerosol Loading ◽  
Significant Difference ◽  
Deep Convective Clouds ◽  
Bin Microphysics ◽  
Cumulative Precipitation

Abstract. The potential effects of increased aerosol loading on the development of deep convective clouds and resulting precipitation amounts are studied by employing the Weather Research and Forecasting (WRF) model as a detailed high-resolution cloud resolving model (CRM) with both detailed bulk and bin microphysics schemes. Both models include a physically-based activation scheme that incorporates a size-resolved aerosol population. We demonstrate that the aerosol-induced effect is controlled by the balance between latent heating and the increase in condensed water aloft, each having opposing effects on buoyancy. It is also shown that under polluted conditions, increases in the CCN number concentration reduce the cumulative precipitation due to the competition between the sedimentation and evaporation/sublimation timescales. The effect of an increase in the IN number concentration on the dynamics of deep convective clouds is small and the resulting decrease in domain-averaged cumulative precipitation is shown not to be statistically significant, but may act to suppress precipitation. It is also shown that even in the presence of a decrease in the domain-averaged cumulative precipitation, an increase in the precipitation variance, or in other words, andincrease in rainfall intensity, may be expected in more polluted environments, especially in moist environments. A significant difference exists between the predictions based on the bin and bulk microphysics schemes of precipitation and the influence of aerosol perturbations on updraft velocity within the convective core. The bulk microphysics scheme shows little change in the latent heating rates due to an increase in the CCN number concentration, while the bin microphysics scheme demonstrates significant increases in the latent heating aloft with increasing CCN number concentration. This suggests that even a detailed two-bulk microphysics scheme, coupled to a detailed activation scheme, may not be sufficient to predict small changes that result from perturbations in aerosol loading.

scholarly journals The Importance of the Shape of Cloud Droplet Size Distributions in Shallow Cumulus Clouds. Part I: Bin Microphysics Simulations

2017 ◽  
Vol 74 (1) ◽  
pp. 249-258 ◽  
Author(s):  
Adele L. Igel ◽  
Susan C. van den Heever
Keyword(s):  
Droplet Size ◽  
Cloud Droplet ◽  
Relative Width ◽  
Size Distributions ◽  
Cumulus Clouds ◽  
Microphysics Scheme ◽  
Droplet Concentration ◽  
Shallow Cumulus ◽  
Bin Microphysics ◽  
Droplet Size Distributions

Abstract In this two-part study, the relationships between the width of the cloud droplet size distribution and the microphysical processes and cloud characteristics of nonprecipitating shallow cumulus clouds are investigated using large-eddy simulations. In Part I, simulations are run with a bin microphysics scheme and the relative widths (standard deviation divided by mean diameter) of the simulated cloud droplet size distributions are calculated. They reveal that the value of the relative width is higher and less variable in the subsaturated regions of the cloud than in the supersaturated regions owing to both the evaporation process itself and enhanced mixing and entrainment of environmental air. Unlike in some previous studies, the relative width is not found to depend strongly on the initial aerosol concentration or mean droplet concentration. Nonetheless, local values of the relative width are found to positively correlate with local values of the droplet concentrations, particularly in the supersaturated regions of clouds. In general, the distributions become narrower as the local droplet concentration increases, which is consistent with the difference in relative width between the supersaturated and subsaturated cloud regions and with physically based expectations. Traditional parameterizations for the relative width (or shape parameter, a related quantity) of cloud droplet size distributions in bulk microphysics schemes are based on cloud mean values, but the bin simulation results shown here demonstrate that more appropriate parameterizations should be based on the relationship between the local values of the relative width and the cloud droplet concentration.

scholarly journals Shallow cumulus properties as captured by adiabatic fraction in high-resolution LES simulations

2021 ◽  
Author(s):  
Eshkol Eytan ◽  
Alexander Khain ◽  
Mark Pinsky ◽  
Orit Altaratz ◽  
Jacob Shpund ◽  
...  
Keyword(s):  
High Resolution ◽  
Hydrological Cycle ◽  
Atmospheric Modeling ◽  
Trade Wind ◽  
Cumulus Clouds ◽  
Complex Processes ◽  
Cloud Properties ◽  
Shallow Cumulus ◽  
Hebrew University ◽  
Bin Microphysics

Abstract Shallow convective clouds are important players in Earth’s energy budget and hydrological cycle, and are abundant in the tropical and subtropical belts. They greatly contribute to the uncertainty in climate predictions, due to their unresolved, complex processes that include coupling between the dynamics and microphysics. Analysis of cloud structure can be simplified by considering cloud motions as a combination of moist adiabatic motions like adiabatic updrafts and turbulent motions leading to deviation from adiabaticity. In this work, we study the sizes and occurrence of adiabatic regions in shallow cumulus clouds during their growth and mature stages, and use the adiabatic fraction (AF) as a continuous metric to describe cloud processes and properties from the core to the edge. To do so, we simulate isolated trade wind cumulus clouds of different sizes using the System of Atmospheric Modeling (SAM) model in high-resolution (10 m) with the Hebrew University spectral bin microphysics (SBM). The fine features in the cloud’s dynamics and microphysics, including small near-adiabatic volumes and a thin transition zone at the edge of the cloud (∼20-40 m in width) are captured. The AF is shown to be an efficient measure for analyzing cloud properties and key processes determining the droplets-size-distribution formation and shape during the cloud evolution. Physical processes governing the properties of droplets size distributions at different cloud regions (e.g. core, edge) are analyzed in relation to AF.

scholarly journals Evaluation of Orographic Cloud Seeding Using a Bin Microphysics Scheme: Two-Dimensional Approach

2017 ◽  
Vol 56 (5) ◽  
pp. 1443-1462 ◽  
Author(s):  
István Geresdi ◽  
Lulin Xue ◽  
Roy Rasmussen
Keyword(s):  
Wrf Model ◽  
Cloud Formation ◽  
Two Dimensional ◽  
Diffusional Growth ◽  
Microphysics Scheme ◽  
Surface Precipitation ◽  
Convective Clouds ◽  
Seeding Effect ◽  
Orographic Clouds ◽  
Bin Microphysics

AbstractA new version of a bin microphysical scheme implemented into the Weather Research and Forecasting (WRF) Model was used to study the effect of glaciogenic seeding on precipitation formation in orographic clouds. The tracking of silver iodide (AgI) particles inside of water drops allows the proper simulation of the immersion nucleation. The ice formations by deposition, condensational freezing, and contact nucleation of AgI particles are also simulated in the scheme. Cloud formation—both stably stratified and convective—and the spread of AgI particles were simulated by idealized flow over a two-dimensional (2D) bell-shaped mountain. The results of numerical experiments show the following: (i) Only the airborne seeding enhances precipitation in stably stratified layer clouds. Seeding can reduce or enhance precipitation in convective clouds. AgI seeding can significantly affect the spatial distribution of the surface precipitation in orographic clouds. (ii) The positive seeding effect is primarily due to additional diffusional growth of AgI-nucleated ice crystals in layer clouds. In convective clouds, seeding-induced changes of both diffusion and riming processes determine the seeding effect. (iii) The seeding effect is inversely related to the natural precipitation efficiency. (iv) Bulk seeding parameterization is adequate to simulate AgI seeding impacts on wintertime orographic clouds. More uncertainties of ground-seeding effects are found between bulk and bin simulations.

scholarly journals Theoretical basis for convective invigoration due to increased aerosol concentration

2011 ◽  
Vol 11 (1) ◽  
pp. 2773-2842 ◽  
Author(s):  
Z. J. Lebo ◽  
J. H. Seinfeld
Keyword(s):  
Cloud Microphysics ◽  
Number Concentration ◽  
Latent Heating ◽  
Microphysics Scheme ◽  
Convective Clouds ◽  
Aerosol Loading ◽  
Significant Difference ◽  
Deep Convective Clouds ◽  
Bin Microphysics ◽  
Cumulative Precipitation

Abstract. The potential effects of increased aerosol loading on the development of deep convective clouds and resulting precipitation amounts are studied by employing the Weather Research and Forecasting (WRF) model as a detailed high-resolution cloud resolving model (CRM) with both detailed bulk and bin microphysics schemes. The bulk microphysics scheme incorporates a physically based parameterization of cloud droplet activation as well as homogeneous and heterogeneous freezing in order to explicitly resolve the possible aerosol-induced effects on the cloud microphysics. These parameterizations allow one to segregate the effects of an increase in the aerosol number concentration into enhanced cloud condensation nuclei (CCN) and/or ice nuclei (IN) concentrations using bulk microphysics. The bin microphysics scheme, with its explicit calculations of cloud particle collisions, is shown to better predict cumulative precipitation. Increases in the CCN number concentration may not have a monotonic influence on the cumulative precipitation resulting from deep convective clouds. We demonstrate that the aerosol-induced effect is controlled by the balance between latent heating and the increase in condensed water aloft, each having opposing effects on buoyancy. It is also shown that under polluted conditions and in relatively dry environments, increases in the CCN number concentration reduce the cumulative precipitation due to the competition between the sedimentation and evaporation/sublimation timescales. The effect of an increase in the IN number concentration on the dynamics of deep convective clouds is small, but may act to suppress precipitation. A comparison of the predictions using the bin and bulk microphysics schemes demonstrate a significant difference between the predicted precipitation and the influence of aerosol perturbations on updraft velocity within the convective core. The bulk microphysics scheme is shown to be unable to capture the changes in latent heating that occur as a result of changes in the CCN number concentration, while the bin microphysics scheme demonstrates significant increases in the latent heating aloft with increasing CCN number concentration. This suggests that a detailed two-bulk microphysics scheme, which is more computationally efficient than bin microphysics schemes, may not be sufficient, even when coupled to a detailed activation scheme, to predict small changes that result from perturbations in aerosol loading.

scholarly journals Core and margin in warm convective clouds – Part 1: Core types and evolution during a cloud's lifetime

2019 ◽  
Vol 19 (16) ◽  
pp. 10717-10738 ◽  
Author(s):  
Reuven H. Heiblum ◽  
Lital Pinto ◽  
Orit Altaratz ◽  
Guy Dagan ◽  
Ilan Koren
Keyword(s):  
Shell Model ◽  
Convective Cloud ◽  
Core Shell ◽  
Cumulus Clouds ◽  
Convective Clouds ◽  
The Core ◽  
Multiple Cores ◽  
Theoretical Predictions ◽  
Bin Microphysics ◽  
Negative Buoyancy

Abstract. The properties of a warm convective cloud are determined by the competition between the growth and dissipation processes occurring within it. One way to observe and follow this competition is by partitioning the cloud to core and margin regions. Here we look at three core definitions, namely positive vertical velocity (Wcore), supersaturation (RHcore), and positive buoyancy (Bcore), and follow their evolution throughout the lifetime of warm convective clouds. Using single cloud and cloud field simulations with bin-microphysics schemes, we show that the different core types tend to be subsets of one another in the following order: Bcore⊆RHcore⊆Wcore. This property is seen for several different thermodynamic profile initializations and is generally maintained during the growing and mature stages of a cloud's lifetime. This finding is in line with previous works and theoretical predictions showing that cumulus clouds may be dominated by negative buoyancy at certain stages of their lifetime. The RHcore–Wcore pair is most interchangeable, especially during the growing stages of the cloud. For all three definitions, the core–shell model of a core (positive values) at the center of the cloud surrounded by a shell (negative values) at the cloud periphery applies to over 80 % of a typical cloud's lifetime. The core–shell model is less appropriate in larger clouds with multiple cores displaced from the cloud center. Larger clouds may also exhibit buoyancy cores centered near the cloud edge. During dissipation the cores show less overlap, reduce in size, and may migrate from the cloud center.

scholarly journals On the Freezing Time of Supercooled Drops in Developing Convective Clouds

2017 ◽  
Author(s):  
Jing Yang ◽  
Zhien Wang ◽  
Andrew Heymsfield
Keyword(s):  
Laboratory Experiments ◽  
Shape Deformation ◽  
Size Distributions ◽  
Freezing Time ◽  
Particle Size Distributions ◽  
Microphysics Scheme ◽  
Convective Clouds ◽  
Lower Temperature ◽  
Bin Microphysics

Abstract. In this study, the particle size distributions (PSDs) measured in fresh developing maritime convective clouds sampled during the Ice in Clouds-Tropical (ICE-T) project are shown and compared with the PSDs modeled using a parcel model containing a spectral bin microphysics scheme. The observations suggest that the first ice in convective clouds is small. To interpret the observed ice PSDs, the freezing times and temperatures of supercooled drops are analyzed. The results indicate that the freezing time is longer for large drops than it is for small drops. Due to instrumental limitations, freezing drops cannot be identified until they exhibit obvious shape deformation. If the updraft is strong enough, large freezing drops can be carried upwards to a lower temperature than their nucleation temperature before obvious shape deformation occurs. In models, drop freezing is assumed to be instantaneous, which is not realistic; thus, the model yields a broader first ice PSD than is observed. This study allows us to interpret the observed ice PSDs in fresh developing convective clouds from the perspective of the freezing time of supercooled drops and notes the deficiency of instantaneous drop freezing in models. To better understand the mechanisms of drop freezing and ice initiation in convective clouds, more laboratory experiments and in situ measurements are needed in the future.

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