scholarly journals The impact of fluctuations and correlations in droplet growth by collision–coalescence revisited – Part 1: Numerical calculation of post-gel droplet size distribution

2017 ◽  
Vol 17 (11) ◽  
pp. 6895-6905 ◽  
Author(s):  
Lester Alfonso ◽  
Graciela B. Raga
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Sol Gel ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Stochastic Simulation Algorithm ◽  
Droplet Growth ◽  
Sol Gel Transition ◽  
The Impact ◽  
Gel Transition

Abstract. The impact of stochastic fluctuations in cloud droplet growth is a matter of broad interest, since stochastic effects are one of the possible explanations of how cloud droplets cross the size gap and form the raindrop embryos that trigger warm rain development in cumulus clouds. Most theoretical studies on this topic rely on the use of the kinetic collection equation, or the Gillespie stochastic simulation algorithm. However, the kinetic collection equation is a deterministic equation with no stochastic fluctuations. Moreover, the traditional calculations using the kinetic collection equation are not valid when the system undergoes a transition from a continuous distribution to a distribution plus a runaway raindrop embryo (known as the sol–gel transition). On the other hand, the stochastic simulation algorithm, although intrinsically stochastic, fails to adequately reproduce the large end of the droplet size distribution due to the huge number of realizations required. Therefore, the full stochastic description of cloud droplet growth must be obtained from the solution of the master equation for stochastic coalescence. In this study the master equation is used to calculate the evolution of the droplet size distribution after the sol–gel transition. These calculations show that after the formation of the raindrop embryo, the expected droplet mass distribution strongly differs from the results obtained with the kinetic collection equation. Furthermore, the low-mass bins and bins from the gel fraction are strongly anticorrelated in the vicinity of the critical time, this being one of the possible explanations for the differences between the kinetic and stochastic approaches after the sol–gel transition. Calculations performed within the stochastic framework provide insight into the inability of explicit microphysics cloud models to explain the droplet spectral broadening observed in small, warm clouds.

scholarly journals The impact of fluctuations and correlations in droplet growth by collision-coalescence revisited. Part I: Numerical calculation of post-gel droplet size distribution

2016 ◽  
Author(s):  
Lester Alfonso ◽  
Graciela B. Raga
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Sol Gel ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Stochastic Simulation Algorithm ◽  
Droplet Growth ◽  
Sol Gel Transition ◽  
The Impact ◽  
Gel Transition

Abstract. The impact of stochastic fluctuations in cloud droplet growth is a matter of broad interest, since stochastic effects are one of the possible explanations of how cloud droplets cross the size-gap and form the raindrop embryos that trigger warm rain development in cumulus clouds. Most theoretical studies in this topic rely on the use of the kinetic collection equation, or the stochastic simulation algorithm (Gillespie 1975). However, the kinetic collection equation is a deterministic equation with no stochastic fluctuations. Moreover, the traditional calculations using the kinetic collection equation are not valid when the system undergoes a transition from a continuous distribution to a distribution plus a runaway raindrop embryo (known as the sol-gel transition). On the other hand, the stochastic simulation algorithm, although intrinsically stochastic, fails to reproduce adequately the large end of the droplet size distribution due to the huge number of realizations required. Therefore, the full stochastic description of cloud droplet growth must be obtained from the solution of the master equation for stochastic coalescence. In this study the master equation is used to calculate the evolution of the droplet size distribution after the sol-gel transition. These calculations show that after the formation of the raindrop embryo, the expected droplet mass distribution strongly differs from the results obtained with the kinetic collection equation. Furthermore, the low mass bins and bins from the gel fraction are strongly anti-correlated in the vicinity of the critical time, this being one of the possible explanations for the differences between the kinetic and stochastic approaches after the sol-gel transition. Calculations performed within the stochastic framework provide insight into the inability of explicit microphysics cloud models to explain the droplet spectral broadening observed in small, warm clouds.

scholarly journals Aerosol indirect effect from turbulence-induced broadening of cloud-droplet size distributions

2016 ◽  
Vol 113 (50) ◽  
pp. 14243-14248 ◽  
Author(s):  
Kamal Kant Chandrakar ◽  
Will Cantrell ◽  
Kelken Chang ◽  
David Ciochetto ◽  
Dennis Niedermeier ◽  
...  
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Aerosol Concentration ◽  
Droplet Radius ◽  
Droplet Growth ◽  
Moist Convection ◽  
Concentration Changes ◽  
Precipitation Formation

The influence of aerosol concentration on the cloud-droplet size distribution is investigated in a laboratory chamber that enables turbulent cloud formation through moist convection. The experiments allow steady-state microphysics to be achieved, with aerosol input balanced by cloud-droplet growth and fallout. As aerosol concentration is increased, the cloud-droplet mean diameter decreases, as expected, but the width of the size distribution also decreases sharply. The aerosol input allows for cloud generation in the limiting regimes of fast microphysics (τc<τt) for high aerosol concentration, and slow microphysics (τc>τt) for low aerosol concentration; here, τc is the phase-relaxation time and τt is the turbulence-correlation time. The increase in the width of the droplet size distribution for the low aerosol limit is consistent with larger variability of supersaturation due to the slow microphysical response. A stochastic differential equation for supersaturation predicts that the standard deviation of the squared droplet radius should increase linearly with a system time scale defined as τs−1=τc−1+τt−1, and the measurements are in excellent agreement with this finding. The result underscores the importance of droplet size dispersion for aerosol indirect effects: increasing aerosol concentration changes the albedo and suppresses precipitation formation not only through reduction of the mean droplet diameter but also by narrowing of the droplet size distribution due to reduced supersaturation fluctuations. Supersaturation fluctuations in the low aerosol/slow microphysics limit are likely of leading importance for precipitation formation.

Broadening of the Cloud Droplet Size Distribution due to Thermal Radiative Cooling: Turbulent Parcel Simulations

2020 ◽  
Vol 77 (6) ◽  
pp. 1993-2010
Author(s):  
Mares Barekzai ◽  
Bernhard Mayer
Keyword(s):  
Thermal Radiation ◽  
Droplet Size ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Growth Efficiency ◽  
Droplet Growth ◽  
Radiative Cooling ◽  
Radiative Effect ◽  
Diffusional Growth ◽  
The Impact

Abstract Despite impressive advances in rain forecasts over the past decades, our understanding of rain formation on a microphysical scale is still poor. Droplet growth initially occurs through diffusion and, for sufficiently large radii, through the collision of droplets. However, there is no consensus on the mechanism to bridge the condensation coalescence bottleneck. We extend the analysis of prior methods by including radiatively enhanced diffusional growth (RAD) to a Markovian turbulence parameterization. This addition increases the diffusional growth efficiency by allowing for emission and absorption of thermal radiation. Specifically, we quantify an upper estimate for the radiative effect by focusing on droplets close to the cloud boundary. The strength of this simple model is that it determines growth-rate dependencies on a number of parameters, like updraft speed and the radiative effect, in a deterministic way. Realistic calculations with a cloud-resolving model are sensitive to parameter changes, which may cause completely different cloud realizations and thus it requires considerable computational power to obtain statistically significant results. The simulations suggest that the addition of radiative cooling can lead to a doubling of the droplet size standard deviation. However, the magnitude of the increase depends strongly on the broadening established by turbulence, due to an increase in the maximum droplet size, which accelerates the production of drizzle. Furthermore, the broadening caused by the combination of turbulence and thermal radiation is largest for small updrafts and the impact of radiation increases with time until it becomes dominant for slow synoptic updrafts.

scholarly journals Remote sensing of water cloud droplet size distributions using the backscatter glory: a case study

2004 ◽  
Vol 4 (5) ◽  
pp. 1255-1263 ◽  
Author(s):  
B. Mayer ◽  
M. Schröder ◽  
R. Preusker ◽  
L. Schüller
Keyword(s):  
Remote Sensing ◽  
Size Distribution ◽  
Droplet Size ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Single Scattering ◽  
Effective Radius ◽  
Radiative Properties ◽  
High Angular Resolution ◽  
Size Distributions

Abstract. Cloud single scattering properties are mainly determined by the effective radius of the droplet size distribution. There are only few exceptions where the shape of the size distribution affects the optical properties, in particular the rainbow and the glory directions of the scattering phase function. Using observations by the Compact Airborne Spectrographic Imager (CASI) in 180° backscatter geometry, we found that high angular resolution aircraft observations of the glory provide unique new information which is not available from traditional remote sensing techniques: Using only one single wavelength, 753nm, we were able to determine not only optical thickness and effective radius, but also the width of the size distribution at cloud top. Applying this novel technique to the ACE-2 CLOUDYCOLUMN experiment, we found that the size distributions were much narrower than usually assumed in radiation calculations which is in agreement with in-situ observations during this campaign. While the shape of the size distribution has only little relevance for the radiative properties of clouds, it is extremely important for understanding their formation and evolution.

scholarly journals Broadening of Cloud Droplet Spectra through Eddy Hopping: Turbulent Entraining Parcel Simulations

2018 ◽  
Vol 75 (10) ◽  
pp. 3365-3379 ◽  
Author(s):  
Gustavo C. Abade ◽  
Wojciech W. Grabowski ◽  
Hanna Pawlowska
Keyword(s):  
Droplet Size ◽  
Turbulent Mixing ◽  
Cloud Condensation Nuclei ◽  
Cloud Droplet ◽  
Cloud Microphysics ◽  
Droplet Growth ◽  
Size Spectrum ◽  
Entrainment Rate ◽  
The Mean ◽  
The Impact

This paper discusses the effects of cloud turbulence, turbulent entrainment, and entrained cloud condensation nuclei (CCN) activation on the evolution of the cloud droplet size spectrum. We simulate an ensemble of idealized turbulent cloud parcels that are subject to entrainment events modeled as a random process. Entrainment events, subsequent turbulent mixing inside the parcel, supersaturation fluctuations, and the resulting stochastic droplet activation and growth by condensation are simulated using a Monte Carlo scheme. Quantities characterizing the turbulence intensity, entrainment rate, CCN concentration, and the mean fraction of environmental air entrained in an event are all specified as independent external parameters. Cloud microphysics is described by applying Lagrangian particles, the so-called superdroplets. These are either unactivated CCN or cloud droplets that grow from activated CCN. The model accounts for the addition of environmental CCN into the cloud by entraining eddies at the cloud edge. Turbulent mixing of the entrained dry air with cloudy air is described using the classical linear relaxation to the mean model. We show that turbulence plays an important role in aiding entrained CCN to activate, and thus broadening the droplet size distribution. These findings are consistent with previous large-eddy simulations (LESs) that consider the impact of variable droplet growth histories on the droplet size spectra in small cumuli. The scheme developed in this work is ready to be used as a stochastic subgrid-scale scheme in LESs of natural clouds.

scholarly journals Evaluating the capabilities and uncertainties of droplet measurements for the fog droplet spectrometer (FM-100)

2012 ◽  
Vol 5 (9) ◽  
pp. 2237-2260 ◽  
Author(s):  
J. K. Spiegel ◽  
P. Zieger ◽  
N. Bukowiecki ◽  
E. Hammer ◽  
E. Weingartner ◽  
...  
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Stochastic Approach ◽  
Mie Scattering ◽  
Size Distributions ◽  
Literature Study ◽  
Size Spectra ◽  
Wind Speeds

Abstract. Droplet size spectra measurements are crucial to obtain a quantitative microphysical description of clouds and fog. However, cloud droplet size measurements are subject to various uncertainties. This work focuses on the error analysis of two key measurement uncertainties arising during cloud droplet size measurements with a conventional droplet size spectrometer (FM-100): first, we addressed the precision with which droplets can be sized with the FM-100 on the basis of the Mie theory. We deduced error assumptions and proposed a new method on how to correct measured size distributions for these errors by redistributing the measured droplet size distribution using a stochastic approach. Second, based on a literature study, we summarized corrections for particle losses during sampling with the FM-100. We applied both corrections to cloud droplet size spectra measured at the high alpine site Jungfraujoch for a temperature range from 0 °C to 11 °C. We showed that Mie scattering led to spikes in the droplet size distributions using the default sizing procedure, while the new stochastic approach reproduced the ambient size distribution adequately. A detailed analysis of the FM-100 sampling efficiency revealed that particle losses were typically below 10% for droplet diameters up to 10 μm. For larger droplets, particle losses can increase up to 90% for the largest droplets of 50 μm at ambient wind speeds below 4.4 m s−1 and even to >90% for larger angles between the instrument orientation and the wind vector (sampling angle) at higher wind speeds. Comparisons of the FM-100 to other reference instruments revealed that the total liquid water content (LWC) measured by the FM-100 was more sensitive to particle losses than to re-sizing based on Mie scattering, while the total number concentration was only marginally influenced by particle losses. Consequently, for further LWC measurements with the FM-100 we strongly recommend to consider (1) the error arising due to Mie scattering, and (2) the particle losses, especially for larger droplets depending on the set-up and wind conditions.

scholarly journals Cloud heterogeneity on cloud and aerosol above cloud properties retrieved from simulated total and polarized reflectances

2018 ◽  
Vol 11 (6) ◽  
pp. 3627-3643 ◽  
Author(s):  
Céline Cornet ◽  
Laurent C.-Labonnote ◽  
Fabien Waquet ◽  
Frédéric Szczap ◽  
Lucia Deaconu ◽  
...  
Keyword(s):  
Size Distribution ◽  
Droplet Size ◽  
Optical Thickness ◽  
Incidence Angle ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Cloud Droplet Size Distribution ◽  
Fractional Cloud ◽  
Cloud Optical Thickness ◽  
Heterogeneity Effects

Abstract. Simulations of total and polarized cloud reflectance angular signatures such as the ones measured by the multi-angular and polarized radiometer POLDER3/PARASOL are used to evaluate cloud heterogeneity effects on cloud parameter retrievals. Effects on optical thickness, albedo, effective radius and variance of the cloud droplet size distribution and aerosol parameters above cloud are analyzed. Three different clouds that have the same mean optical thicknesses were generated: the first with a flat top, the second with a bumpy top and the last with a fractional cloud cover. At small scale (50 m), for oblique solar incidence, the illumination effects lead to higher total but also polarized reflectances. The polarized reflectances even reach values that cannot be predicted by the 1-D homogeneous cloud assumption. At the POLDER scale (7 km × 7 km), the angular signature is modified by a combination of the plane–parallel bias and the shadowing and illumination effects. In order to quantify effects of cloud heterogeneity on operational products, we ran the POLDER operational algorithms on the simulated reflectances to retrieve the cloud optical thickness and albedo. Results show that the cloud optical thickness is greatly affected: biases can reach up to −70, −50 or +40 % for backward, nadir and forward viewing directions, respectively. Concerning the albedo of the cloudy scenes, the errors are smaller, between −4.7 % for solar incidence angle of 20∘ and up to about +8 % for solar incidence angle of 60∘. We also tested the heterogeneity effects on new algorithms that allow retrieving cloud droplet size distribution and cloud top pressures and also aerosol above clouds. Contrary to the bi-spectral method, the retrieved cloud droplet size parameters are not significantly affected by the cloud heterogeneity, which proves to be a great advantage of using polarized measurements. However, the cloud top pressure obtained from molecular scattering in the forward direction can be biased up to about 60 hPa (around 550 m). Concerning the aerosol optical thickness (AOT) above cloud, the results are different depending on the available angular information. Above the fractional cloud, when only side scattering angles between 100 and 130∘ are available, the AOT is underestimated because of the plane–parallel bias. However, for solar zenith angle of 60∘ it is overestimated because the polarized reflectances are increased in forward directions.

scholarly journals Simultaneous retrieval of aerosol and cloud properties during the MILAGRO field campaign

2011 ◽  
Vol 11 (13) ◽  
pp. 6245-6263 ◽  
Author(s):  
K. Knobelspiesse ◽  
B. Cairns ◽  
J. Redemann ◽  
R. W. Bergstrom ◽  
A. Stohl
Keyword(s):  
Optical Properties ◽  
Size Distribution ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Droplet Size ◽  
Cloud Droplet ◽  
Droplet Size Distribution ◽  
Cloud Droplet Size Distribution ◽  
Distribution Parameters ◽  
Aerosol Properties

Abstract. Estimation of Direct Climate Forcing (DCF) due to aerosols in cloudy areas has historically been a difficult task, mainly because of a lack of appropriate measurements. Recently, passive remote sensing instruments have been developed that have the potential to retrieve both cloud and aerosol properties using polarimetric, multiple view angle, and multi spectral observations, and therefore determine DCF from aerosols above clouds. One such instrument is the Research Scanning Polarimeter (RSP), an airborne prototype of a sensor on the NASA Glory satellite, which unfortunately failed to reach orbit during its launch in March of 2011. In the spring of 2006, the RSP was deployed on an aircraft based in Veracruz, Mexico, as part of the Megacity Initiative: Local and Global Research Observations (MILAGRO) field campaign. On 13 March, the RSP over flew an aerosol layer lofted above a low altitude marine stratocumulus cloud close to shore in the Gulf of Mexico. We investigate the feasibility of retrieving aerosol properties over clouds using these data. Our approach is to first determine cloud droplet size distribution using the angular location of the cloud bow and other features in the polarized reflectance. The selected cloud was then used in a multiple scattering radiative transfer model optimization to determine the aerosol optical properties and fine tune the cloud size distribution. In this scene, we were able to retrieve aerosol optical depth, the fine mode aerosol size distribution parameters and the cloud droplet size distribution parameters to a degree of accuracy required for climate modeling. This required assumptions about the aerosol vertical distribution and the optical properties of the coarse aerosol size mode. A sensitivity study was also performed to place this study in the context of future systematic scanning polarimeter observations, which found that the aerosol complex refractive index can also be observed accurately if the aerosol optical depth is larger than roughly 0.8 at a wavelength of (0.555 μm).

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