scholarly journals Accuracy assessments of cloud droplet size retrievals from polarized reflectance measurements by the research scanning polarimeter

2012 ◽  
Vol 125 ◽  
pp. 92-111 ◽  
Author(s):  
Mikhail D. Alexandrov ◽  
Brian Cairns ◽  
Claudia Emde ◽  
Andrew S. Ackerman ◽  
Bastiaan van Diedenhoven
Keyword(s):  
Droplet Size ◽  
Cloud Droplet ◽  
Accuracy Assessments ◽  
Reflectance Measurements ◽  
Polarized Reflectance

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 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.

DROPLET FEEDBACK ON VAPOR IN A WARM CLOUD

2009 ◽  
Vol 23 (28n29) ◽  
pp. 5434-5443 ◽  
Author(s):  
ANTONIO CELANI ◽  
ANDREA MAZZINO ◽  
MARCO TIZZI
Keyword(s):  
Numerical Simulations ◽  
Droplet Size ◽  
Cloud Droplet ◽  
Direct Numerical Simulations ◽  
Cloud Droplets ◽  
Size Spectra ◽  
New Model ◽  
Warm Cloud ◽  
Local Reduction ◽  
The One

A new model to study the effect of turbulence on the cloud droplets in the condensation phase is proposed and its behavior investigated by direct numerical simulations. The model is a generalization of the one by Celani, Mazzino, Tizzi, New J. Phys.10, 075021 (2008), where the droplet feedback on vapor is now explicitly taken into account. Physically, it amounts to considering the fact that when a cloud droplet increases its size, vapor is subtracted from the ambient with the net result of a local reduction in the supersaturation field. It is shown how this effect plays to reduce the broadening of droplet size spectra in the condensation stage and thus to produce results in closer agreement with observations.

Calculation of Spectral Optical Constants Using Combined Ellipsometric and Reflectance Methods for Smooth and Rough Bulk Samples

2021 ◽  
pp. 000370282110478
Author(s):  
Gilles Fortin
Keyword(s):  
Rough Surface ◽  
Optical Constants ◽  
Sample Surface ◽  
Infrared Region ◽  
Homogeneous Sample ◽  
Specular Reflectance ◽  
Scattering Effects ◽  
Spectral Ranges ◽  
Reflectance Measurements ◽  
Polarized Reflectance

Spectra of the optical constants n and k of a substance are often deduced from spectroscopic measurements, performed on a thick and homogeneous sample, and from a model used to simulate these measurements. Spectra obtained for n and k using the ellipsometric method generally produce polarized reflectance simulations in strong agreement with the experimental measurements, but they sometimes introduce significant discrepancies over limited spectral ranges, whereas spectra of n and k obtained with the single-angle reflectance method require a perfectly smooth sample surface to be viable. This paper presents an alternative method to calculate n and k. The method exploits both ellipsometric measurements and s-polarized specular reflectance measurements, and compensates for potential surface scattering effects with the introduction of a specularity factor. It is applicable to bulk samples having either a smooth or a rough surface. It provides spectral optical constants that are consistent with s-polarized reflectance measurements. Demonstrations are performed in the infrared region using a glass slide (smooth surface) and a pellet of compressed ammonium sulfate powder (rough surface).

scholarly journals Remote sensing of cloud droplet radius profiles using solar reflectance from cloud sides – Part 1: Retrieval development and characterization

2019 ◽  
Vol 12 (2) ◽  
pp. 1183-1206 ◽  
Author(s):  
Florian Ewald ◽  
Tobias Zinner ◽  
Tobias Kölling ◽  
Bernhard Mayer
Keyword(s):  
Remote Sensing ◽  
Solar Radiation ◽  
Droplet Size ◽  
Cloud Droplet ◽  
Effective Radius ◽  
Radiative Properties ◽  
Trade Wind ◽  
Small Scale ◽  
Passive Remote Sensing ◽  
Remote Sensing Techniques

Abstract. Convective clouds play an essential role for Earth's climate as well as for regional weather events since they have a large influence on the radiation budget and the water cycle. In particular, cloud albedo and the formation of precipitation are influenced by aerosol particles within clouds. In order to improve the understanding of processes from aerosol activation, from cloud droplet growth to changes in cloud radiative properties, remote sensing techniques become more and more important. While passive retrievals for spaceborne observations have become sophisticated and commonplace for inferring cloud optical thickness and droplet size from cloud tops, profiles of droplet size have remained largely uncharted territory for passive remote sensing. In principle they could be derived from observations of cloud sides, but faced with the small-scale heterogeneity of cloud sides, “classical” passive remote sensing techniques are rendered inappropriate. In this work the feasibility is demonstrated to gain new insights into the vertical evolution of cloud droplet effective radius by using reflected solar radiation from cloud sides. Central aspect of this work on its path to a working cloud side retrieval is the analysis of the impact unknown cloud surface geometry has on effective radius retrievals. This study examines the sensitivity of reflected solar radiation to cloud droplet size, using extensive 3-D radiative transfer calculations on the basis of realistic droplet size resolving cloud simulations. Furthermore, it explores a further technique to resolve ambiguities caused by illumination and cloud geometry by considering the surroundings of each pixel. Based on these findings, a statistical approach is used to provide an effective radius retrieval. This statistical effective radius retrieval is focused on the liquid part of convective water clouds, e.g., cumulus mediocris, cumulus congestus, and trade-wind cumulus, which exhibit well-developed cloud sides. Finally, the developed retrieval is tested using known and unknown cloud side scenes to analyze its performance.

Simple inversion technique to obtain cloud droplet size parameters using solar aureole data

1981 ◽  
Vol 20 (9) ◽  
pp. 1511 ◽  
Author(s):  
Ting-i Wang ◽  
G. M. Lerfald ◽  
V. E. Derr
Keyword(s):  
Droplet Size ◽  
Cloud Droplet ◽  
Inversion Technique ◽  
Simple Inversion
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