scholarly journals Dynamics of Subsiding Shells in Actively Growing Clouds with Vertical Updrafts

2020 ◽  
Vol 77 (4) ◽  
pp. 1353-1369 ◽  
Author(s):  
Vishnu Nair ◽  
Thijs Heus ◽  
Maarten van Reeuwijk
Keyword(s):  
Shell Thickness ◽  
Large Scale ◽  
Cloud Environment ◽  
Initial State ◽  
Cumulus Clouds ◽  
Mean Velocity ◽  
Flow Parameters ◽  
Shallow Cumulus ◽  
Order Of Magnitude ◽  
Self Similar

Abstract The dynamics of a subsiding shell at the edges of actively growing shallow cumulus clouds with updrafts is analyzed using direct numerical simulation. The actively growing clouds have a fixed in-cloud buoyancy and velocity. Turbulent mixing and evaporative cooling at the cloud edges generate a subsiding shell that grows with time. A self-similar regime is observed for first- and second-order moments when normalized with respective maximum values. Internal scales derived from integral properties of the flow problem are identified. A self-similarity analysis using these scales reveals that contrary to classical self-similar flows, the turbulent kinetic energy budget terms and velocity moments scale according to the buoyancy and not with the mean velocity. The shell thickness is observed to increase linearly with time. The buoyancy scale remains time invariant and is set by the initial cloud–environment thermodynamics. The shell accelerates ballistically with a magnitude set by the saturation value of the buoyancy of the cloud–environment mixture. In this regime, the shell is buoyancy driven and independent of the in-cloud velocity. Relations are obtained for predicting the shell thickness and minimum velocities by linking the internal scales with external flow parameters. The values thus calculated are consistent with the thickness and velocities observed in typical shallow cumulus clouds. The entrainment coefficient is a function of the initial state of the cloud and the environment, and is shown to be on the same order of magnitude as fractional entrainment rates calculated for large-scale models.

Experimental and Numerical Characterization of the Flow Around the Keel of a Yacht

2008 ◽  
Author(s):  
Renata M. B. Chaves ◽  
Atila P. S. Freire ◽  
Alexandre T. P. Alho
Keyword(s):  
Laboratory Data ◽  
Turbulence Models ◽  
Detailed Comparison ◽  
Mean Velocity ◽  
Flow Parameters ◽  
Numerical Characterization ◽  
Sst Model ◽  
Order Of Magnitude ◽  
Measured Flow ◽  
Turbulence Data

The present work carries out a detailed comparison between numerical computations for the flow around the keel and the bulb of a sailboat and some newly obtained laboratory data. Two typical turbulence models are tested: the eddy-viscosity SST model and the second-moment model BSL-RSM-ω. Hot-wire anemometry (HWA) and particle image velocimetry (PIV) are used to characterize the flow around the keel and the bulb of a yacht. The experiments are conducted in a low speed wind tunnel. Measured flow parameters include the mean velocity profiles and second order moments. Both turbulence models are shown to perform well regarding mean velocity and global predictions. Turbulence data predictions, however, are shown to be erroneous by at least one order of magnitude.

Large-scale vertical motion and its influence on cloudiness

2020 ◽  
Author(s):  
Geet George ◽  
Bjorn Stevens ◽  
Sandrine Bony ◽  
Marcus Klingebiel
Keyword(s):  
Large Scale ◽  
Vertical Motion ◽  
Cumulus Clouds ◽  
Shallow Cumulus ◽  
Integrated Water Vapour ◽  
Thermodynamics And Dynamics ◽  
Lifting Condensation Level ◽  
The Impact ◽  
First Time

<p>This study uses measurements from the <em>Elucidating the Role of Clouds-Circulation Coupling in Climate</em>, EUREC<sup>4</sup>A and the second <em>Next-Generation Aircraft Remote Sensing for Validation</em>, NARVAL2 campaigns to investigate the influence of large-scale environmental conditions on cloudiness. For the first time, these campaigns provide divergence measurements, making it possible to explore the impact of large-scale vertical motions on clouds. We attempt to explain the cloudiness through the varying thermodynamics and dynamics in the different environments.  For most of the NARVAL2 case-studies, cloudiness is poorly related to thermodynamical factors such as sea-surface temperature and lower tropospheric stability. Factors such as integrated water vapour and pressure velocity (ω) at 500 hPa and 700 hPa can be used to distinguish between actively convecting and suppressed regions, but they are not useful in determining the variation in cloudiness among suppressed cases. We find that ω in the boundary layer (up to ∼2 km) has a more direct control on the low-level cloudiness in these regions, than that in the upper layers. We use a simplistic method to show that ω at the lifting condensation level can be used to determine the cloud cover of shallow cumulus clouds. Thus, we argue that cloud schemes in models should not rely only on thermodynamical information, but also on dynamical predictors.</p>

scholarly journals Theoretical Understanding of the Linear Relationship between Convective Updrafts and Cloud-Base Height for Shallow Cumulus Clouds. Part I: Maritime Conditions

2019 ◽  
Vol 76 (8) ◽  
pp. 2539-2558 ◽  
Author(s):  
Youtong Zheng
Keyword(s):  
Cooling Rate ◽  
Large Scale ◽  
Buoyancy Flux ◽  
Cloud Base ◽  
Radiative Cooling ◽  
Cumulus Clouds ◽  
Shallow Cumulus ◽  
Surface Buoyancy ◽  
Cloud Base Height ◽  
Surface Buoyancy Flux

Abstract Zheng and Rosenfeld found linear relationships between the convective updrafts and cloud-base height zb using ground-based observations over both land and ocean. The empirical relationships allow for a novel satellite remote sensing technique of inferring the cloud-base updrafts and cloud condensation nuclei concentration, both of which are important for understanding aerosol–cloud–climate interactions but have been notoriously difficult to retrieve from space. In Part I of a two-part study, a theoretical framework is established for understanding this empirical relationship over the ocean. Part II deals with continental cumulus clouds. Using the bulk concept of mixed-layer (ML) model for shallow cumulus, I found that this relationship arises from the conservation law of energetics that requires the radiative flux divergence of an ML to balance surface buoyancy flux. Given a certain ML radiative cooling rate per unit mass Q, a deeper ML (higher zb) undergoes more radiative cooling and requires stronger surface buoyancy flux to balance it, leading to stronger updrafts. The rate with which the updrafts vary with zb is modulated by Q. The cooling rate Q manifests strong resilience to external large-scale forcing that spans a wide range of climatology, allowing the slope of the updrafts–zb relationship to remain nearly invariant. This causes the relationship to manifest linearity. The physical mechanism underlying the resilience of Q to large-scale forcing, such as free-tropospheric moisture and sea surface temperature, is investigated through the lens of the radiative transfer theory (two-stream Schwarzschild equations) and an ML model for shallow cumulus.

scholarly journals The turbulent/non-turbulent interface bounding a far wake

2002 ◽  
Vol 451 ◽  
pp. 383-410 ◽  
Author(s):  
DAVID K. BISSET ◽  
JULIAN C. R. HUNT ◽  
MICHAEL M. ROGERS
Keyword(s):  
Large Scale ◽  
Turbulence Models ◽  
Passive Scalar ◽  
Reynolds Stresses ◽  
Mean Velocity ◽  
Velocity Fluctuations ◽  
Eddy Motion ◽  
Order Of Magnitude ◽  
Fixed Reference ◽  
Velocity Variances

The velocity fields of a turbulent wake behind a flat plate obtained from the direct numerical simulations of Moser et al. (1998) are used to study the structure of the flow in the intermittent zone where there are, alternately, regions of fully turbulent flow and non-turbulent velocity fluctuations on either side of a thin randomly moving interface. Comparisons are made with a wake that is ‘forced’ by amplifying initial velocity fluctuations. A temperature field T, with constant values of 1.0 and 0 above and below the wake, is transported across the wake as a passive scalar. The value of the Reynolds number based on the centreplane mean velocity defect and half-width b of the wake is Re ≈ 2000.The thickness of the continuous interface is about 0.07b, whereas the amplitude of fluctuations of the instantaneous interface displacement yI(t) is an order of magnitude larger, being about 0.5b. This explains why the mean statistics of vorticity in the intermittent zone can be calculated in terms of the probability distribution of yI and the instantaneous discontinuity in vorticity across the interface. When plotted as functions of y−yI the conditional mean velocity 〈U〉 and temperature 〈T〉 profiles show sharp jumps at the interface adjacent to a thick zone where 〈U〉 and 〈T〉 vary much more slowly.Statistics for the conditional vorticity and velocity variances, available in such detail only from DNS data, show how streamwise and spanwise components of vorticity are generated by vortex stretching in the bulges of the interface. While mean Reynolds stresses (in the fixed reference frame) decrease gradually in the intermittent zone, conditional stresses are roughly constant and then decrease sharply towards zero at the interface. Flow fields around the interface, analysed in terms of the local streamline pattern, confirm and explain previous results that the advancement of the vortical interface into the irrotational flow is driven by large-scale eddy motion.Terms used in one-point turbulence models are evaluated both conventionally and conditionally in the interface region, and the current practice in statistical models of approximating entrainment by a diffusion process is assessed.

scholarly journals The Role of Shallow Cloud Moistening in MJO and Non-MJO Convective Events over the ARM Manus Site

2015 ◽  
Vol 72 (12) ◽  
pp. 4797-4820 ◽  
Author(s):  
David M. Zermeño-Díaz ◽  
Chidong Zhang ◽  
Pavlos Kollias ◽  
Heike Kalesse
Keyword(s):  
Large Scale ◽  
Lower Troposphere ◽  
Liquid Water Content ◽  
Cumulus Clouds ◽  
Low Level ◽  
Freezing Level ◽  
Shallow Cumulus ◽  
Before And After ◽  
Shallow Clouds ◽  
Atmospheric Radiation Measurement

Abstract Observations from the Atmospheric Radiation Measurement Program (ARM) site at Manus Island in the western Pacific and (re)analysis products are used to investigate moistening by shallow cumulus clouds and by the circulation in large-scale convective events. Large-scale convective events are defined as rainfall anomalies larger than one standard deviation for a minimum of three consecutive days over a 10° × 10° domain centered at Manus. These events are categorized into two groups: Madden–Julian oscillation (MJO) events, with eastward propagation, and non-MJO events, without propagation. Shallow cumulus clouds are identified as continuous time–height echoes from 1-min cloud radar observations with their tops below the freezing level and their bases within the boundary layer. Daily moistening tendencies of shallow clouds, estimated from differences between their mean liquid water content and precipitation over their presumed life spans, and those of physical processes and advection from (re)analysis products are compared with local moistening tendencies from soundings. Increases in low-level moisture before rainfall peaks of MJO and non-MJO events are evident in both observations and reanalyses. Before and after the rainfall peaks of these events, precipitating and nonprecipitating shallow clouds exist all the time, but their occurrence fluctuates randomly. Their contributions to moisture tendencies through evaporation of condensed water are evident. These clouds provide perpetual background moistening to the lower troposphere but do not cause the observed increase in low-level moisture leading to rainfall peaks. Such moisture increase is mainly caused by anomalous nonlinear zonal advection.

scholarly journals Boundary Layer and Shallow Cumulus Clouds in a Medium-Range Forecast of a Large-Scale Weather System

2005 ◽  
Vol 133 (7) ◽  
pp. 1938-1960 ◽  
Author(s):  
Stéphane Bélair ◽  
Jocelyn Mailhot ◽  
Claude Girard ◽  
Paul Vaillancourt
Keyword(s):  
Boundary Layer ◽  
Large Scale ◽  
Deep Convection ◽  
Cumulus Clouds ◽  
Weather System ◽  
Low Level ◽  
Boundary Layer Clouds ◽  
Shallow Cumulus ◽  
Medium Range Forecast ◽  
Medium Range

Abstract The role and impact that boundary layer and shallow cumulus clouds have on the medium-range forecast of a large-scale weather system is discussed in this study. A mesoscale version of the Global Environmental Multiscale (GEM) atmospheric model is used to produce a 5-day numerical forecast of a midlatitude large-scale weather system that occurred over the Pacific Ocean during February 2003. In this version of GEM, four different schemes are used to represent (i) boundary layer clouds (including stratus, stratocumulus, and small cumulus clouds), (ii) shallow cumulus clouds (overshooting cumulus), (iii) deep convection, and (iv) nonconvective clouds. Two of these schemes, that is, the so-called MoisTKE and Kuo Transient schemes for boundary layer and overshooting cumulus clouds, respectively, have been recently introduced in GEM and are described in more detail. The results show that GEM, with this new cloud package, is able to represent the wide variety of clouds observed in association with the large-scale weather system. In particular, it is found that the Kuo Transient scheme is mostly responsible for the shallow/intermediate cumulus clouds in the rear portion of the large-scale system, whereas MoisTKE produces the low-level stratocumulus clouds ahead of the system. Several diagnostics for the rear portion of the system reveal that the role of MoisTKE is mainly to increase the vertical transport (diffusion) associated with the boundary layer clouds, while Kuo Transient is acting in a manner more consistent with convective stabilization. As a consequence, MoisTKE is not able to remove the low-level shallow cloud layer that is incorrectly produced by the GEM nonconvective condensation scheme. Kuo Transient, in contrast, led to a significant reduction of these nonconvective clouds, in better agreement with satellite observations. This improved representation of stratocumulus and cumulus clouds does not have a large impact on the overall sea level pressure patterns of the large-scale weather system. Precipitation in the rear portion of the system, however, is found to be smoother when MoisTKE is used, and significantly less when the Kuo Transient scheme is switched on.

Large-eddy simulations of turbulent mixing layers using the stretched-vortex model

2011 ◽  
Vol 671 ◽  
pp. 507-534 ◽  
Author(s):  
T. W. MATTNER
Keyword(s):  
Large Scale ◽  
Large Eddy Simulations ◽  
Mixing Layers ◽  
Reynolds Stresses ◽  
Mean Velocity ◽  
Subgrid Model ◽  
Large Eddy ◽  
Schmidt Numbers ◽  
Self Similar ◽  
Large Scale Flow

The stretched-vortex subgrid model is used to run large-eddy simulations of temporal mixing layers at various Reynolds and Schmidt numbers, with different initial and boundary conditions. A self-similar flow is obtained, during which the growth rate, mean velocity and Reynolds stresses are in accord with experimental results. However, predictions of the amount of mixed fluid, and of the variation in its composition across the layer, are excessive, especially at high Schmidt number. More favourable comparisons between experiment and simulation are obtained when the large-scale flow is quasi-two-dimensional; however, such states are not self-similar and not sustainable. Present model assumptions lead to predictions of the continued subgrid spectrum with a viscous cutoff that is dependent on grid resolution.

Evaluation of the physics suite in NOAA’s GFSv16 using field-campaign observations and diagnosis of physics tendencies

2021 ◽  
Author(s):  
Jian-Wen Bao ◽  
Sara Michelson ◽  
Evelyn Grell
Keyword(s):  
Large Scale ◽  
Prediction Models ◽  
Weather Prediction ◽  
Atmospheric Environment ◽  
Cumulus Clouds ◽  
Western Atlantic ◽  
Field Campaign ◽  
Parameterization Schemes ◽  
Shallow Cumulus ◽  
The Impact

<p>Shallow cumulus clouds play an important role in the weather in the Atlantic Tropical Convergence Zone.  Their interaction with the atmospheric environment and oceanic mixing processes has a significant impact on the convective organization and tropical dynamics.  It is still a scientific challenge for numerical weather prediction models to accurately simulate them due to deficiencies in the model’s representation of physical processes. </p><p>In this study, we investigate how the physics parameterization schemes in NOAA’s most recent operational global forecast system (GFSv16) perform in the simulation of shallow cumulus clouds in the western Atlantic in terms of their interaction with the large-scale atmospheric dynamics.  Previous studies have indicated that the impact of physics parameterization schemes on model’s tendencies during the first few hours can provide critical information on their suitability for short- and medium-range forecasts.<strong> </strong> Therefore, we first evaluate the GFSv16 forecasts against the observations obtained from the European field campaign called the ATOMIC/EUREC4A that occurred between 12 January and 23 February 2020.  We then diagnose the sensitivity of the GFSv16 physics tendencies to changes to the physics parameterization schemes over the first 6 hours of the forecast, which is the timescale before dynamical feedback becomes significant. Using the information from the observational evaluation and physics tendency diagnosis, we further explore possible improvement in the physical process representation that can positively affect the physics tendencies and lead to overall forecast improvement beyond 6 hours.</p>

scholarly journals A Cloud Microphysics Parameterization for Shallow Cumulus Clouds Based on Lagrangian Cloud Model Simulations

2018 ◽  
Vol 75 (11) ◽  
pp. 4031-4047 ◽  
Author(s):  
Yign Noh ◽  
Donggun Oh ◽  
Fabian Hoffmann ◽  
Siegfried Raasch
Keyword(s):  
Cloud Model ◽  
Cloud Microphysics ◽  
Heaviside Function ◽  
Mixing Ratio ◽  
Cumulus Clouds ◽  
Cloud Droplets ◽  
Shallow Cumulus ◽  
Initial Stage ◽  
Accretion Rates ◽  
The Moment

Abstract Cloud microphysics parameterizations for shallow cumulus clouds are analyzed based on Lagrangian cloud model (LCM) data, focusing on autoconversion and accretion. The autoconversion and accretion rates, A and C, respectively, are calculated directly by capturing the moment of the conversion of individual Lagrangian droplets from cloud droplets to raindrops, and it results in the reproduction of the formulas of A and C for the first time. Comparison with various parameterizations reveals the closest agreement with Tripoli and Cotton, such as and , where and are the mixing ratio and the number concentration of cloud droplets, is the mixing ratio of raindrops, is the threshold volume radius, and H is the Heaviside function. Furthermore, it is found that increases linearly with the dissipation rate and the standard deviation of radius and that decreases rapidly with while disappearing at > 3.5 μm. The LCM also reveals that and increase with time during the period of autoconversion, which helps to suppress the early precipitation by reducing A with smaller and larger in the initial stage. Finally, is found to be affected by the accumulated collisional growth, which determines the drop size distribution.

scholarly journals Nebula: ultra-efficient mapping-free structural variant genotyper

2021 ◽  
Author(s):  
Parsoa Khorsand ◽  
Fereydoun Hormozdiari
Keyword(s):  
Large Scale ◽  
Structural Variants ◽  
Sequencing Technologies ◽  
Generic Framework ◽  
Common Genetic Variants ◽  
Order Of Magnitude ◽  
Complex Events ◽  
Comparable Accuracy ◽  
Using Data ◽  
Computational Resources

Abstract Large scale catalogs of common genetic variants (including indels and structural variants) are being created using data from second and third generation whole-genome sequencing technologies. However, the genotyping of these variants in newly sequenced samples is a nontrivial task that requires extensive computational resources. Furthermore, current approaches are mostly limited to only specific types of variants and are generally prone to various errors and ambiguities when genotyping complex events. We are proposing an ultra-efficient approach for genotyping any type of structural variation that is not limited by the shortcomings and complexities of current mapping-based approaches. Our method Nebula utilizes the changes in the count of k-mers to predict the genotype of structural variants. We have shown that not only Nebula is an order of magnitude faster than mapping based approaches for genotyping structural variants, but also has comparable accuracy to state-of-the-art approaches. Furthermore, Nebula is a generic framework not limited to any specific type of event. Nebula is publicly available at https://github.com/Parsoa/Nebula.

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