Cloud Size Distribution Research Articles

X-ray occultations in active galactic nuclei: Physical properties of eclipsing clouds as part of the broad-line region cloud ensemble

Context. Short-term X-ray variability in active galactic nuclei (AGNs) can be explained as being due to varying X-ray absorption induced by the temporary occultation of the primary X-ray source, when moving absorbing clouds cross the line of sight to the X-ray source itself. Earlier work suggests that these absorbing clouds have physical properties similar to those of broad-line region (BLR) emitting clouds and are located in the same spatial region. Aims. We intend to extract physical information on each individual absorber associated with any given occultation event detected in our sample and to analyse general properties of the cloud ensemble whose components can produce X-ray eclipses. Methods. From the analysis of previously detected occultation events, two ‘observables’ characterising each single occultation event can be derived: the peak fractional hardness ratio variation (ΔHR/HR) and the duration of the event normalised by a characteristic eclipse timescale evaluated for each AGN source. To determine the eclipsing cloud properties, we devised a procedure a) based on simplifying assumptions on the geometry of both the X-ray source and the cloud-like gas condensations, and on the cloud X-ray absorbing properties in the energy range of interest (2–10 keV), and b) relying on a set of simulated instrumental responses from both XMM and Suzaku relevant instruments to different incoming X-ray spectra, absorbed with varying absorber column density and maximum covering factor during the occultation. Thus, we derived information on the individual cloud producing any given occultation event, determining the cloud radius normalised to that of the X-ray source, the spatial location of the cloud, and an estimate of the cloud gas number density for reasonable values of the equivalent absorber column density. Results. The physical properties of eclipsing clouds that we obtained are consistent with those of BLR clouds. We can exclude the dominance, in the ensemble cloud size distribution, of clouds larger than about 10–12 times the Schwarzschild radius characterising each AGN, and we do not find any significant dependence of the cloud physical size on the distance from the central black hole, in agreement with the results of our previous work. As for the number density of these gas condensations, with our procedure we obtained values within a range of ∼109 − 1011 cm−3, which is consistent with the estimates derived from broad emission line analysis.

Cloud Versus Void Chord Length Distributions (LvL) as a Measure for Cloud Field Organization

AbstractCloud organization impacts the radiative effects and precipitation patterns of the cloud field. Deviating from randomness, clouds exhibit either clustering or a regular grid structure, characterized by the spacing between clouds and the cloud size distribution. The two measures are coupled but do not fully define each other. Here, we present the deviation from randomness of the cloud‐ and void‐chord length distributions as a measure for both factors. We introduce the LvL representation and an associated 2D score that allow for unambiguously quantifying departure from well‐defined baseline randomness in cloud spacing and sizes. This approach demonstrates sensitivity and robustness in classifying cloud field organization types. Its delicate sensitivity unravels the temporal evolution of a single cloud field, providing novel insights into the underlying governing processes.

Observations of the macrophysical properties of cumulus cloud fields over the tropical western Pacific and their connection to meteorological variables

Abstract. The poor representation of the macrophysical properties of shallow oceanic cumuli in climate models contributes to the large uncertainty in cloud feedback. These properties are also difficult to measure because it requires high-resolution satellite imagery that is seldomly collected over ocean. Here, we examine cumulus cloud macrophysical properties, their size, shape, and spatial distributions, over the tropical western Pacific using 170 15 m resolution scenes from Terra's Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) collected during the 2019 Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) mission. The average cloud fraction (CF) was 0.12, half of which was contributed by clouds less than 1.6 km in area-equivalent diameter. This compared well to Terra's Multi-angle Imaging SpectroRadiometer (MISR) resolution-corrected CF of 0.14 but less than the 0.19 measured by Terra's Moderate Resolution Imaging Spectroradiometer (MODIS). The cloud size distribution exhibited a power law form with an exponent of 2.93 and an area–perimeter power law with a dimension of 1.25. ASTER, MISR, and CAMP2Ex aircraft lidar showed excellent agreement in the cloud top height (CTH) distribution peak altitude of ∼ 750 m. We examined cumulus properties in relation to meteorological variables and found that the variation in mean CTH is controlled most by the total column water vapor, lower-tropospheric stability (LTS), and estimated inversion strength (EIS). The variation in CF is most controlled by surface wind speed and near-cloud relative humidity instead of LTS/EIS, suggesting the need to improve low-cloud parameterizations in climate models that use LTS/EIS based on stratocumulus studies.

A Satellite Observational Study of Topographical Effects on Daytime Shallow Convective Clouds

Shallow convective clouds (SCCs) frequently occur over mountainous terrain. However, previous studies have mostly focused on SCCs over flat surfaces. Here, the effects of mountainous terrains on the cloud size distributions (CSDs) and spatial distributions of SCCs are investigated using data obtained from the Landsat-8 satellite. We find that the CSDs are well-described by double power laws separated by scale breaks. The CSDs are controlled by two parameters, i.e., the scale breaks and the number of clouds with sizes between 0.2 and 1 times the scale breaks. We also find that the number of clouds generally increases with the elevation. In particular, the number of clouds larger than the scale breaks increases faster than that of the smaller clouds. The sizes of the larger clouds (the 90th and 95th percentiles) increase with the elevation, while the sizes of the smaller clouds are not sensitive to the elevation. It is suggested that the variations of cloud numbers and sizes with elevation should be used together with the CSDs to describe the cloud fields over mountainous terrains.

Lagrangian and Eulerian Supersaturation Statistics in Turbulent Cloudy Rayleigh–Bénard Convection: Applications for LES Subgrid Modeling

Abstract Turbulent fluctuations of scalar and velocity fields are critical for cloud microphysical processes, e.g., droplet activation and size distribution evolution, and can therefore influence cloud radiative forcing and precipitation formation. Lagrangian and Eulerian water vapor, temperature, and supersaturation statistics are investigated in direct numerical simulations (DNS) of turbulent Rayleigh–Bénard convection in the Pi Convection Cloud Chamber to provide a foundation for parameterizing subgrid-scale fluctuations in atmospheric models. A subgrid model for water vapor and temperature variances and covariance and supersaturation variance is proposed, valid for both clear and cloudy conditions. Evaluation of phase change contributions through an a priori test using DNS data shows good performance of the model. Supersaturation is a nonlinear function of temperature and water vapor, and relative external fluxes of water vapor and heat (e.g., during entrainment-mixing and phase change) influence turbulent supersaturation fluctuations. Although supersaturation has autocorrelation and structure functions similar to the independent scalars (temperature and water vapor), the autocorrelation time scale of supersaturation differs. Relative scalar fluxes in DNS without cloud make supersaturation PDFs less skewed than the adiabatic case, where they are highly negatively skewed. However, droplet condensation changes the PDF shape response: it becomes positively skewed for the adiabatic case and negatively skewed when the sidewall relative fluxes are large. Condensation also increases correlations between water vapor and temperature in the presence of relative scalar fluxes but decreases correlations for the adiabatic case. These changes in correlation suppress supersaturation variability for the nonadiabatic cases and increase it for the adiabatic case. Implications of this work for subgrid microphysics modeling using a Lagrangian stochastic scheme are also discussed.

Fitting Cumulus Cloud Size Distributions From Idealized Cloud Resolving Model Simulations

AbstractWhereas it is now widely accepted that cumulus cloud sizes are power‐law distributed, characteristic exponents reported in the literature vary greatly, generally taking values between 1 and >3. Although these differences might be explained by variations in environmental conditions or physical processes organizing the cloud ensembles, the use of improper fitting methods may also introduce large biases. To address this issue, we propose to use a combination of maximum likelihood estimation and goodness‐of‐fit tests to provide more robust power‐law fits while systematically identifying the size range over which these fits are valid. The procedure is applied to cloud size distributions extracted from two idealized high‐resolution simulations displaying different organization characteristics. Overall, power‐laws are found to be outperformed by alternative distributions in almost all situations. When clouds are identified based on a condensed water path threshold, using power‐laws with an exponential cutoff yields the best results as it provides superior fits in the tail of the cloud size distributions. For clouds identified using a combination of water content and updraft velocity thresholds in the free troposphere, no substantial improvement over pure power‐laws can be found when considering more complex two‐parameter distributions. In this context however, exponential distributions provide results that are as good as, if not better than power‐laws. Finally, it is demonstrated that the emergence of scale free behaviors in cloud size distributions is related to exponentially distributed cloud cores merging as they are brought closer to each other by underlying organizing mechanisms.

Reconciling Observations of Solar Irradiance Variability With Cloud Size Distributions

AbstractClouds cast shadows on the surface and locally enhance solar irradiance by absorbing and scattering sunlight, resulting in fast and large solar irradiance fluctuations on the surface. Typical spatiotemporal scales and driving mechanisms of this intra‐day irradiance variability are not well known, hence even 1 day ahead forecasts of variability are inaccurate. Here, we use long‐term, high‐frequency solar irradiance observations combined with satellite imagery, numerical simulations, and conceptual modeling to show how irradiance variability is linked to the cloud size distribution. Cloud shadow sizes are distributed according to a power law over multiple orders of magnitude, deviating only from the cloud size distribution due to cloud edge transparency at scales below ≈750 m. Locally cloud‐enhanced irradiance occurs as frequently as shadows, and is similarly driven mostly by boundary layer clouds, but distributed over a smaller range of scales. We reconcile studies of solar irradiance variability with those on clouds, which brings fundamental understanding to what drives irradiance variability. Our findings have implications not only for weather and climate modeling, but also for solar energy and photosynthesis by vegetation, where detailed knowledge of surface solar irradiance is essential.

A granular mechanics model study of the influence of non-spherical shape on aggregate collisions

Collisions between granular aggregates influence the size distribution of dust clouds. Granular aggregates may possess non-spherical shapes as a result of, for instance, previous collision processes. Here, we study aggregate collisions using a granular mechanics simulation code. Collisions between spherical aggregates are compared to collisions of ellipsoidal aggregates of equal mass. As the most prominent result, we find that the growth velocity, i.e., the velocity above which the post-collision aggregates are smaller than before collision, is generally reduced for ellipsoidal aggregates. The reason hereto lies in the less compact structure of ellipsoids which allows for a larger degree of fragmentation in a ‘rim peel-off’ mechanism. On the other hand, relative fragment distributions are only little influenced by aggregate shape.

High-spatial-resolution retrieval of cloud droplet size distribution from polarized observations of the cloudbow

Abstract. The cloud droplet size distribution is often described by a gamma distribution defined by the effective radius and the effective variance. The effective radius is directly related to the cloud's optical thickness, which influences the radiative properties of a cloud. The effective variance affects, among other things, the evolution of precipitation. Both parameters can be retrieved from measurements of the cloudbow. The cloudbow (or rainbow) is an optical phenomenon that forms due to the single scattering of radiation by liquid cloud droplets at the cloud edge. The polarized radiance of the cloudbow crucially depends on the cloud droplet size distribution. The effective radius and the effective variance can be retrieved by fitting model simulations (stored in a lookup table) to polarized cloudbow observations. This study uses measurements from the wide-field polarization-sensitive camera of the spectrometer of the Munich Aerosol Cloud Scanner (specMACS) aboard the German “High Altitude and LOng range research aircraft” (HALO). Along with precise cloud geometry data derived by a stereographic method, a geolocalization of the observed clouds is possible. Observations of the same cloud from consecutive images are combined into one radiance measurement from multiple angles. Two case studies of trade-wind cumulus clouds measured during the EUREC4A (ElUcidating the RolE of Cloud-Circulation Coupling in ClimAte) field campaign are presented, and the cloudbow technique is demonstrated. The results are combined into maps of the effective radius and the effective variance with a 100 m × 100 m spatial resolution and large coverage (across-track swath width of 8 km). The first case study shows a stratiform cloud deck with distinct patches of large effective radii up to 40 µm and a median effective variance of 0.11. specMACS measures at a very high angular resolution (binned to 0.3∘) which is necessary when large droplets are present. The second case study consists of small cumulus clouds (diameters of approximately 2 km). The retrieved effective radius is 7.0 µm, and the effective variance is 0.08 (both median values). This study demonstrates that specMACS is able to determine the droplet size distribution of liquid water clouds even for small cumulus clouds, which are a problem for traditional droplet size retrievals based on total reflectances.

Horizontal geometry of trade wind cumuli – aircraft observations from a shortwave infrared imager versus a radar profiler

Abstract. This study elaborates on how aircraft-based horizontal geometries of trade wind cumulus clouds differ whether a one-dimensional (1D) profiler or a two-dimensional (2D) imager is used. While nadir profiling devices are limited to a 1D realization of the cloud transect size, with limited representativeness of horizontal cloud extension, 2D imagers enhance our perspectives by mapping the horizontal cloud field. Both require high resolutions to detect the lower end of the cloud size spectrum. In this regard, the payload aboard the HALO (High Altitude and LOng Range Research Aircraft) achieves a comparison and also a synergy of both measurement systems. Using the NARVAL II (Next-Generation Aircraft Remote-Sensing for Validation Studies) campaign, we combine HALO observations from a 35.2 GHz cloud and precipitation radar (1D) and from the hyperspectral 2D imager specMACS (Munich Aerosol Cloud Scanner), with a 30 times higher along-track resolution, and compare their cloud masks. We examine cloud size distributions in terms of sensitivity to sample size, resolution and the considered field of view (2D or 1D). This specifies impacts on horizontal cloud sizes derived from the across-track perspective of the high-resolution imager in comparison to the radar curtain. We assess whether and how the trade wind field amplifies uncertainties in cloud geometry observations along 1D transects through directional cloud elongation. Our findings reveal that each additional dimension, no matter of the device, causes a significant increase in observed clouds. The across-track field yields the highest increase in the cloud sample. The radar encounters difficulties in characterizing the trade wind cumuli size distribution. More than 60 % of clouds are subgrid scale for the radar. The radar has issues in the representation of clouds shorter than 200 m, as they are either unresolved or are incorrectly displayed as single grid points. Very shallow clouds can also remain unresolved due to too low radar sensitivity. Both facts deteriorate the cloud size distribution significantly at this scale. Double power law characteristics in the imager-based cloud size distribution do not occur in radar observations. Along-track measurements do not necessarily cover the predominant cloud extent and inferred geometries' lack of representativeness. Trade wind cumuli show horizontal patterns similar to ellipses, with a mean aspect ratio of 3:2 and having tendencies of stronger elongation with increasing cloud size. Instead of circular cloud shape estimations based on the 1D transect, elliptic fits maintain the cloud area size distribution. Increasing wind speed tends to stretch clouds more and tilts them into the wind field, which makes transect measurements more representative along this axis.

Limitations of Separate Cloud and Rain Categories in Parameterizing Collision‐Coalescence for Bulk Microphysics Schemes

AbstractWarm rain collision‐coalescence has been persistently difficult to parameterize in bulk microphysics schemes. We use a flexible bulk microphysics scheme with bin scheme process parameterizations, called AMP, to investigate reasons for the difficulty. AMP is configured in a variety of ways to mimic bulk schemes and is compared to simulations with the bin scheme upon which AMP is built. We find that an important limitation in traditional bulk schemes is the use of separate cloud and rain categories. When the drop size distribution is instead represented by a continuous distribution, the simulation of cloud‐to‐rain conversion is substantially improved. We also find large sensitivity to the threshold size to distinguish cloud and rain in traditional schemes; substantial improvement is found by decreasing the threshold from 40 to 25 μm. Neither the use of an assumed functional form for the size distribution nor the choice of predicted distribution moments has a large impact on the ability of AMP to simulate rain production. When predicting four total moments of the liquid drop size distribution, either with a traditional two‐category, two‐moment scheme with a reduced size threshold, or a four‐moment single‐category scheme, errors in the evolution of mass and the cloud size distribution are similar, but the single‐category scheme has a substantially better representation of the rain size distribution. Optimal moment combinations for the single‐category approach are investigated and appear to be linked more to the information content they provide for constraining the size distributions than to their correlation with collision‐coalescence rates.

Cloud Morphology Evolution in Arctic Cold‐Air Outbreak: Two Cases During COMBLE Period

AbstractCloud feedbacks play an important role in Arctic warming. Cloud morphology, for example, cloud size and spatial distributions, is among key factors that directly impact their radiative effects. In this work, we use two cases observed during the Cold‐air Outbreak (CAO) in the Marine Boundary Layer Experiment (COMBLE) to study the evolution of cloud size distributions as an air mass is advected from the Arctic over a comparatively warm ocean and cloud mesoscale organization changes from rolls to cells. Cloud objects are identified from Moderate Resolution Imaging Spectroradiometer (MODIS) reflectance images through an object segmentation procedure and roll breakup is identified by homogeneities in cloud water path (CWP). Roll breakup is found to be accompanied by a local minimum in wind shear and local maxima in cloud size and marine cold air outbreak index. The mean cloud horizontal aspect ratio has weak fetch dependency and is around 2 in roll, transition, and cell regimes. Regardless of distance from the ice edge, smaller clouds (<10 km2) dominate the population number but not cloud cover. Cloud size distributions show bimodality in transition and cell regimes. For clouds with comparable sizes, mean nearest neighbor distances normalized by equivalent cloud radius converge to a single value for all regimes and for all but the smallest clouds, suggesting that clouds of comparable sizes in CAOs are separated by distance proportional to their sizes. The presented statistical results pave the way to evaluating model simulated cloud organizations during CAO events.

A Radiative Transfer Simulator for PACE: Theory and Applications

A radiative transfer simulator was developed to compute the synthetic data of all three instruments onboard NASA’s Plankton Aerosol, Cloud, ocean Ecosystem (PACE) observatory, and at the top of the atmosphere (TOA). The instrument suite includes the ocean color instrument (OCI), the Hyper-Angular Rainbow Polarimeter 2 (HARP2), and the Spectro-Polarimeter for Planetary Exploration 1 (SPEXone). The PACE simulator is wrapped around a monochromatic radiative transfer model based on the successive order of scattering (RTSOS), which accounts for atmosphere and ocean coupling, polarization, and gas absorption. Inelastic scattering, including Raman scattering from pure ocean water, fluorescence due to chlorophyll, and colored dissolved organic matter (CDOM), is also simulated. This PACE simulator can be used to explore the sensitivity of the hyperspectral and polarized reflectance of the Earth system with tunable atmosphere and ocean parameters, which include aerosol and cloud number concentration, refractive indices, and size distribution, ocean particle microphysical parameters, and solar and sensor-viewing geometry. The PACE simulator is used to study two important case studies. One is the impact of the significant uncertainty in pure ocean water absorption coefficient to the radiance field in the ultraviolet (UV) spectral region, which can be as much as 6%. The other is the influence of different amounts of brown carbon aerosols and CDOM on the polarized radiance field at TOA. The percentage variation of the radiance field due to CDOM is mostly for wavelengths smaller than 600 nm, while brown aerosols affect the whole spectrum from 350 to 890 nm, primarily due to covaried soot aerosols. Both case studies are important for aerosol and ocean color remote sensing and have not been previously reported in the literature.

Summertime Continental Shallow Cumulus Cloud Detection Using GOES-16 Satellite and Ground-Based Stereo Cameras at the DOE ARM Southern Great Plains Site

Summertime continental shallow cumulus clouds (ShCu) are detected using Geostationary Operational Environmental Satellite (GOES)-16 reflectance data, with cross-validation by observations from ground-based stereo cameras at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. A ShCu cloudy pixel is identified when the GOES reflectance exceeds the clear-sky surface reflectance by a reflectance detection threshold of ShCu, ΔR. We firstly construct diurnally varying clear-sky surface reflectance maps and then estimate the ∆R. A GOES simulator is designed, projecting the clouds reconstructed by stereo cameras towards the surface along the satellite’s slanted viewing direction. The dynamic ShCu detection threshold ΔR is determined by making the GOES cloud fraction (CF) equal to the CF from the GOES simulator. Although there are temporal variabilities in ΔR, cloud fractions and cloud size distributions can be well reproduced using a constant ΔR value of 0.045. The method presented in this study enables daytime ShCu detection, which is usually falsely reported as clear sky in the GOES-16 cloud mask data product. Using this method, a new ShCu dataset can be generated to bridge the observational gap in detecting ShCu, which may transition into deep precipitating clouds, and to facilitate further studies on ShCu development over heterogenous land surface.

Retrieval of particle size distribution of polar stratospheric clouds based on Wide-Angle Color and Polarization Analysis

The intensive polar stratospheric vortex in the Arctic that shifted to northern Europe in the winter of 2019–2020 caused low temperatures and the frequent occurrence of polar stratospheric clouds followed by a significant decrease in the total ozone content. Polarimetry and multi-color photometry using all-sky cameras in Lovozero (Murmansk Region, Russia, 68.0°N, 35.1°E) together with a new method of cloud field separation against the twilight background allowed for finding the light scattering characteristics related to the particle size distribution of polar stratospheric clouds. The results are compared with lidar and balloon experiments. The conditions of the appearance of visually bright polar stratospheric clouds of type I are discussed.

Interpreting the Diurnal Cycle of Clouds and Precipitation in the ARM GoAmazon Observations: Shallow to Deep Convection Transition

AbstractThe Green Ocean Amazon (GoAmazon) 2014/5 field campaign data are used to study the diurnal cycle of clouds and precipitation. Through a careful classification of days with shallow cumulus, congestus and deep convection, we investigate the major differences among locally generated convection regimes and the most important environmental factors governing the shallow‐to‐deep convection transition. On shallow cumulus days, a greater sensible heat flux drives deeper boundary layer growth, which entrains drier free‐tropospheric air and lowers the relative humidity, thus leading to a significantly higher cloud base than those on days with deeper convection. Congestus and deep convection regimes exhibit distinct cloud top height distributions with noticeable differences in the vertical wind shear in the mid‐troposphere, suggesting an important role of wind shear in limiting the vertical extent of convection. On deep convection days, with preexisting nocturnal convection or cold‐pools from external disturbances, the timing of peak surface precipitation (12:00–13:00 LST) tends to be in‐phase with the diurnal variation in surface fluxes. However, it takes longer for local deep convection to develop without these disturbances. A plume model with thermodynamic and dynamical constraints is developed to explore the relative importance of various convection‐controlling factors. Initial cloud‐base vertical velocity and buoyancy are important in helping parcels ascend to the level of free convection (LFC). After parcels reach the LFC, entrainment of environmental air and lower free troposphere humidity become crucial in determining cloud top. Entrainment rate differentiates among convection regimes, which may be tied to the cloud size distribution at cloud base.

New insights on polar mesospheric cloud particle size distributions from a two-satellite common volume study

The particle size distribution of Polar Mesospheric Clouds (PMC) is closely related to the fundamental processes of cloud formation and evolution. Still, despite substantial observational efforts, specific details about the particle size distribution have remained obscure. In this study, we aim at deriving more constraints on PMC size distributions by combining optical measurements from two satellite instruments observing a common PMC volume. We use a special set of 2D tomographic limb observations from the Optical Spectrograph and Infrared Imager System (OSIRIS) on the Odin satellite from 2010 to 2011 in the latitude range 78° N to 80° N and compare these to simultaneous PMC observations from the nadir-viewing Cloud Imaging and Particle Size (CIPS) instrument on the AIM satellite. A key goal is to find the assumption on the mathematical shape of the particle size distribution that should be applied to a vertically resolving limb-viewing instrument to reach consistent size results compared to the column-integrated ice distribution as seen by a nadir-viewing instrument. Our results demonstrate that viewing geometry and sampling volume of each instrument must be carefully considered and that the same size distribution assumption cannot simultaneously describe a column-integrated and a local height-resolved size distribution. In particular, applying the standard Gaussian assumption, used by many earlier PMC studies, to both limb and nadir observation leads to an overestimate of particle sizes seen by OSIRIS by about 10 nm as compared to CIPS. We show that the agreement can be improved if a Log-normal assumption with a broad distribution width around σ = 1.42 is adopted for OSIRIS. A reason for this broad distribution best describing the OSIRIS observations we suggest the large retrieval volume of the limb measurement. Gravity waves and other small-scale processes can cause horizontal variations and a co-existence of a wide range of particle populations in the sampling volume. Horizontal integration then leads to apparently much broader size distributions than encountered in a small horizontal sampling volume.

Polarization signatures of Mars dust and clouds: Prospects for future spacecraft observations

The study of polarized sunlight scattered from planetary atmospheres provides diagnostic tools that can help explore the possible composition and size distribution of clouds and aerosol particles. Previous studies have shown the potential of this technique in studying Water clouds on Earth and in the discovery of Sulphuric Acid clouds on Venus. The atmosphere of Mars is unique as it hosts three different types of aerosols: water (H2O) ice, carbon dioxide (CO2) ice and dust. We considered scenarios analogous to Martian conditions and calculated the single and multiple scattering polarization for Martian dust, water ice and carbon dioxide ice with the help of a Radiative Transfer algorithm for Nadir and Limb spacecraft observation positions. The polarization features (-Q/I) of Mars atmosphere have low amplitude and have been found to be within the range of ±0.1 in the Nadir/Limb geometry for the spherical, spheroidal and cylindrical shapes considered here. We study its dependence upon the observation geometry, shape, size and composition of the scatterer. Future spacecraft studies of microphysical properties of dust and clouds through polarization will reveal the nature of condensation processes active in the Martian atmosphere.

Improving the Physical Basis for Updraft Dynamics in Deep Convection Parameterizations

AbstractThis article presents a new deep convective parameterization that determines cloud characteristics based on a specified cloud size distribution. The vertical profiles of cloud properties are determined by analytic equations, which formulate entrainment with an inverse relationship to cloud width. In line with recent studies of large eddy simulations (LES), cloud widths are assumed to be constant with height and vertical mass flux (M) characteristics of the clouds are therefore regulated by the vertical velocity profile. The parameterization is configured to work with existing cloud baseMclosure formulations, with the closure predicting the total cloud area rather than the cloud baseMdirectly. Analytic formula are also used to connect the vertical wind shear magnitude to the cloud size distribution, wherein larger shear magnitudes result in more numerous large updrafts than weaker shear magnitudes, which is in line with recent research results. The parameterization is compared against 10 deep convective LES with varying thermodynamic and vertical wind shear profiles. Results show dramatic improvements in the prediction of normalizedM, detrainment, and the properties of detrained air over the existing Zhang and McFarlane (1995) scheme. In particular, the new model is able to correctly portray the transition from a bottom‐heavyMprofile in weakly sheared environments, to a top‐heavyMprofile in strongly sheared environments.

On the Abundance and Common Properties of Continental, Organized Shallow (Green) Clouds

Warm convective clouds play a significant role in the earth's energy and water budgets. However, they still pose a challenge in climate research as their feedback to predicted thermodynamic changes is highly uncertain and considered critical to the overall climate system's response. The focus of this study is continental, organized shallow convective clouds that, although they are spread globally and form in a variety of environments, seem to have common properties. One of these properties seems to be their preferred formation over vegetated areas, thus referred hereafter as green Cu. In this article, we present new observations of emerging universality and explore them using a method that combines fine- and coarse-resolution remote-sensing data sets. First, we use Moderate Resolution Imaging Spectroradiometer (MODIS) true-color images to visually classify cloud fields into different classes and identify green Cu fields. We show that the level and type of organization and the properties of these fields (e.g., cloud size distribution and cloud fraction) are similar throughout the world, regardless of their location. Second, we match the corresponding MODIS level-3 cloud properties to the identified cloud classes, and based on this data sets statistics, we develop a detection method for green Cu along ten years of measurements (2003-2012). We examine the geographical distribution and seasonality of this class and show that these fields are highly abundant over many continental areas and indeed mostly in the vicinity of vegetated regions.