Cloud Droplet Size Distribution Research Articles

Application of aircraft observations over Beijing in cloud microphysical property retrievals from CloudSat

Cloud microphysical property retrievals from the active microwave instrument on a satellite require the cloud droplet size distribution obtained from aircraft observations as a priori data in the iteration procedure. The cloud lognormal size distributions derived from 12 flights over Beijing, China, in 2008–09 were characterized to evaluate and improve regional CloudSat cloud water content retrievals. We present the distribution parameters of stratiform cloud droplet (diameter <500 μm and <1500 μm) and discuss the effect of large particles on distribution parameter fitting. Based on three retrieval schemes with different lognormal size distribution parameters, the vertical distribution of cloud liquid and ice water content were derived and then compared with the aircraft observations. The results showed that the liquid water content (LWC) retrievals from large particle size distributions were more consistent with the vertical distribution of cloud water content profiles derived from in situ data on 25 September 2006. We then applied two schemes with different a priori data derived from flight data to CloudSat overpasses in northern China during April-October in 2008 and 2009. The CloudSat cloud water path (CWP) retrievals were compared with Moderate Resolution Imaging Spectroradiometer (MODIS) liquid water path (LWP) data. The results indicated that considering a priori data including large particle size information can significantly improve the consistency between the CloudSat CWP and MODIS CWP. These results strongly suggest that it is necessary to consider particles with diameters greater than 50 μm in CloudSat LWC retrievals.

Effects of entrainment and mixing on droplet size distributions in warm cumulus clouds

AbstractA long‐standing problem in cloud physics is the broadening of the cloud droplet spectrum in warm cumulus clouds. To isolate the changes of the droplet size distribution (DSD) due to entrainment and turbulent mixing, we used the Explicit Mixing Parcel Model (EMPM). The EMPM explicitly represents spatial variability due to entrainment and turbulent mixing down to the smallest turbulence scales in a one‐dimensional domain. Several thousand individual droplets evolve by condensation or evaporation according to their local environments. We used EMPM results to characterize the evolution of the DSD due to entrainment and isobaric mixing for a wide range of conditions in a 20 m domain, including variations in entrained environmental air fraction, the turbulence dissipation rate, the size of the entrained blobs, and the relative humidity of the entrained air. We found that the broadening of the DSD due to entrainment and isobaric mixing for a specific value of the entrained air relative humidity depends only on the eddy mixing time scale and the LWC after mixing. Broadening increases substantially as the evaporation time scale decreases due to decreasing relative humidity of the entrained air. Our results also show that it is possible to parameterize the effects of entrainment and mixing on the droplet number concentration. The comprehensive results obtained for one set of values of entrained air relative humidity, droplet size, and droplet concentration should be extended to other values.

Reply to comment by Yangang Liu et al. on “Cloud droplet spectral width relationship to CCN spectra and vertical velocity”

Reply to comment by Yangang Liu et al. on “Cloud droplet spectral width relationship to CCN spectra and vertical velocity”

Relationship between cloud characteristics and radar reflectivity based on aircraft and cloud radar co-observations

Cloud properties were investigated based on aircraft and cloud radar co-observation conducted at Yitong, Jilin, Northeast China. The aircraft provided in situ measurements of cloud droplet size distribution, while the millimeter-wavelength cloud radar vertically scanned the same cloud that the aircraft penetrated. The reflectivity factor calculated from aircraft measurements was compared in detail with simultaneous radar observations. The results showed that the two reflectivities were comparable in warm clouds, but in ice cloud there were more differences, which were probably associated with the occurrence of liquid water. The acceptable agreement between reflectivities obtained in water cloud confirmed that it is feasible to derive cloud properties by using aircraft data, and hence for cloud radar to remotely sense cloud properties. Based on the dataset collected in warm clouds, the threshold of reflectivity to diagnose drizzle and cloud particles was studied by analyses of the probability distribution function of reflectivity from cloud particles and drizzle drops. The relationship between reflectivity factor (Z) and cloud liquid water content (LWC) was also derived from data on both cloud particles and drizzle. In comparison with cloud droplets, the relationship for drizzle was blurred by many scatter points and thus was less evident. However, these scatters could be partly removed by filtering out the drop size distribution with a large ratio of reflectivity and large extinction coefficient but small effective radius. Empirical relationships of Z-LWC for both cloud particles and drizzle could then be derived.

On the sensitivity of cloud effective radius retrieval based on spectral method to bi-modal droplet size distribution: A semi-analytical model

The bi-spectral solar reflective method is widely used to infer cloud optical thickness (τ) and effective radius (re) from satellite cloud reflectance observations. An important assumption often made in this method is that cloud droplet size distribution (DSD) follows the monomodal Gamma or Lognormal distributions, with a fixed variance. However, it is known that the warm rain processes, e.g., collision–coalescence, can broaden cloud DSD and even lead to bi-modal size distribution. In this study, a semi-analytical model is developed to better understand the retrieved re based on the monomodal DSD assumption when the true DSD is bi-modal. The results based on this model agree well with the results from rigorous radiative transfer simulations. The model reveals that the re retrieval based on the monomodal DSD assumption tends to underestimate the re of the true bi-modal DSD. This bias is due to the nonlinear relationship between cloud droplet single-scattering albedo and cloud droplet size. The degree of this underestimation is found to increase with re and the width of the DSD. The model also indicates that the underestimation more strongly affects the 3.7µm band than in the 2.1µm band retrievals; leading to smaller 3.7µm band re retrieval than that based on 2.1µm. It is also demonstrated through numerical tests that cloud optical thickness retrieval shows little sensitivity to the cloud microphysics assumption and is relatively accurate. This is probably because the asymmetry factor of cloud droplet varies within a relatively small range, and therefore limits the impact of cloud microphysics on τ retrieval. This study has several implications, in particular for understanding the potential impact of drizzle on cloud re retrieval. Future work is needed to evaluate the model in more realistic cloud field.

Empirical relationship between entrainment rate and microphysics in cumulus clouds

The relationships between fractional entrainment rate and key microphysical quantities (e.g., liquid water content, droplet number concentration, volume mean radius, and standard deviation of cloud droplet size distributions) in shallow cumuli are empirically examined using in situ aircraft observations from the Routine Atmospheric Radiation Measurement Aerial Facility Clouds with Low Optical Water Depths Optical Radiative Observations (RACORO) field campaign over the Atmospheric Radiation Measurement Southern Great Plains site. The results show that the microphysical quantities examined generally exhibit strong relationships with entrainment rate and that the relationships collectively suggest the dominance of homogeneous entrainment mixing, which is unfavorable to the formation of large droplets and the initiation of warm rain in the clouds. The dominance of the homogeneous mixing mechanism is further substantiated by the dependency on entrainment rate of relationships among various microphysical variables and of cloud droplet size distributions. The dominance of this mechanism is also quantitatively confirmed by examining the degree of homogeneous mixing in the clouds. The dominance of homogeneous mixing may be an important reason why none of the cumulus clouds studied was drizzling.

Cell model of in-cloud scavenging of highly soluble gases

We investigate mass transfer during absorption of highly soluble gases such as HNO3, H2O2 by stagnant cloud droplets in the presence of inert admixtures. Thermophysical properties of the gases and liquids are assumed to be constant. Diffusion interactions between droplets, caused by the overlap of depleted of soluble gas regions around the neighboring droplets, are taken into account in the approximation of a cellular model of a gas–droplet suspension whereby a suspension is viewed as a periodic structure consisting of the identical spherical cells with periodic boundary conditions at the cell boundary. Using this model we determined temporal and spatial dependencies of the concentration of the soluble trace gas in a gaseous phase and in a droplet and calculated the dependence of the scavenging coefficient on time. We found that scavenging coefficient for gas absorption by cloud droplets remains constant and sharply decreases only at the final stage of absorption. In the calculations we employed a Monte Carlo method and assumed gamma size distribution of cloud droplets. It is shown that despite of the comparable values of Henry's law constants for the hydrogen peroxide (H2O2) and the nitric acid (HNO3), the nitric acid is scavenged more effectively by cloud droplets than the hydrogen peroxide due to a major affect of the dissociation reaction on HNO3 scavenging. It is demonstrated that scavenging of highly soluble gases by cloud droplets leads to strong decrease of soluble trace gas concentration in the interstitial air. We obtained also analytical expressions for the “equilibrium values” of concentration of the soluble trace gas in a gaseous phase and for concentration of the dissolved gas in a liquid phase for the case of hydrogen peroxide and nitric acid absorption by cloud droplets.

Retrieval of liquid cloud microphysical properties from spaceborne active and passive sensor data based on optimal estimation theory

In order to meet the urgent requirement for accurate retrieval of liquid cloud microphysical properties, integrating the detecting advantages of active and passive sensors and combining radar reflectivity and optical depth information from CloudSat and Aqua, a new retrieval algorithm of liquid cloud microphysical parameters is proposed according to the optimal estimation theory. By assuming the lognormal size distribution of cloud droplets and establishing functional relationships between measurement and retrieval variables based on forward physical model, with the prior information about spectral distribution parameters, the optimal solutions of spectral parameters are obtained after iteratively calculating, then the microphysical parameters of liquid cloud could be retrieved based on forward physical model, and the uncertainty can be calculated according to error propagation theory. By designing retrieval scheme and using measured case data, the retrieval results are compared with the data published by CloudSat official institutions and those retrieved using empirical algorithms, showing that retrievals of liqiud cloud microphysical parameters based on optimal estimation theory by using combined active and passive sensor data are well consistent with official released data, which makes up for the disadvantages of empirical algorithms that have large error and poor expansibility and gives some important references for retrieval research of liquid cloud microphysical parameters based on domestic spaceborne and airborne W-band millimeter-wave radar data.

Observed impacts of vertical velocity on cloud microphysics and implications for aerosol indirect effects

The simultaneous measurements of vertical velocity and cloud droplet size distributions in cumuli collected during the RACORO field campaign over the Atmospheric Radiation Measurement Program's Southern Great Plains site near Lamont, Oklahoma, US, are analyzed to determine the effects of vertical velocity on droplet number concentration, relative dispersion (the ratio of standard deviation to mean radius), and their relationship. The results show that with increasing vertical velocity the droplet number concentration increases while the relative dispersion decreases. The data also exhibit a negative correlation between relative dispersion and droplet number concentration. These empirical relationships can be fitted well with power law functions. This observational study confirms the theoretical and numerical expectations of the effects of vertical velocity on cloud microphysics by analyzing the data of vertical velocity directly. The effects of vertical velocity on relative dispersion and its relationship with droplet number concentration are opposite to that associated with aerosol loading, posing a confounding challenge for separating aerosol indirect effects from dynamical effects.

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

We present an algorithm for the retrieval of cloud droplet size distribution parameters (effective radius and variance) from the Research Scanning Polarimeter (RSP) measurements. The RSP is an airborne prototype for the Aerosol Polarimetery Sensor (APS), which was on-board of the NASA Glory satellite. This instrument measures both polarized and total reflectance in 9 spectral channels with central wavelengths ranging from 410 to 2260nm. The cloud droplet size retrievals use the polarized reflectance in the scattering angle range between 135° and 165°, where they exhibit the sharply defined structure known as the rain- or cloud-bow. The shape of the rainbow is determined mainly by the single scattering properties of cloud particles. This significantly simplifies both forward modeling and inversions, while also substantially reducing uncertainties caused by the aerosol loading and possible presence of undetected clouds nearby. In this study we present the accuracy evaluation of our algorithm based on the results of sensitivity tests performed using realistic simulated cloud radiation fields.

On the sensitivity of droplet size relative dispersion to warm cumulus cloud evolution

Relative dispersion (ε), defined as the ratio between cloud droplet size distribution width (σ) and cloud droplet average radius (〈r〉), is a key factor used to parameterize various cloud processes in global circulation models (GCMs) and bulk microphysical scheme models (BSMs). Recent studies indicate that the impact of aerosol loading (N) and atmospheric thermodynamic conditions on ε are far from fully understood. Currently, a fixed value per hydrometeor type is used in most BSMs and GCMs, which imposes significant limitations on our ability to model and predict cloud processes and their impact on the environment, on regional to global scales. In this study, we use a detailed bin microphysics single cloud model to investigate the combined impact of atmospheric thermodynamic conditions and N on ε, in warm cumulus clouds. As initial conditions, we used different lapse‐rates combined with 8 scenarios of aerosol loading, representing very clean (N = 25 cm−3) to heavily polluted (N = 1600 cm−3) conditions. Moreover, the results are analyzed per cloud evolutionary stage according to the dominance of microphysical processes. The use of this method indicated a different pattern of ε at each stage. Specifically, during the mature stage fitting of ε to rv is relatively resilient to changes in the environmental conditions. Such findings suggest a new view of the effect of aerosols on clouds, via changes in the cloud evolution patterns and a new approach to parameterization of ε based on rv, which can significantly improve the prediction of cloud processes by GCMs and BSMs.

The production of warm rain in shallow maritime cumulus clouds

AbstractThe problem of the production of warm rain by collision and coalescence has been studied for over half a century and several processes have been suggested to explain the observed production, which is more rapid than generally possible with models. A straightforward scenario in relatively shallow maritime cumulus clouds is one where cloud drops simply grow by condensation and coalescence, with no appeal to enhancement due to entrainment or turbulence or indeed the presence of giant and ultragiant aerosols that may exist in the boundary layer. However, it is difficult in a field experiment to measure the concentrations of aerosols and the time evolution of the droplet size distribution or reflectivity in individual clouds. The Rain in Cumulus Over the Ocean (RICO) field experiment overcame some of these difficulties due to the abundance of clouds and the statistical sampling strategy at all significant altitudes. In this article, we present the results of the rate of increase in the radar reflectivity in a couple of cases. Comparisons with a cloud model strongly suggest that the development of warm rain can be explained using the observed aerosol distribution alone. Sensitivity studies suggested that giant and ultragiant aerosols were unimportant for the production of rain in these clouds. Copyright © 2012 Royal Meteorological Society

Aerosol and cloud characteristics analysis methods using multiple kinds of Raman lidar signals

In this paper, we introduce three kinds of methods for the analysis of aerosol and cloud droplet characteristics: backscattering color ratio at two wavelengths (color ratio), aerosol liquid-water content, and cloud droplet size distribution using the liquid water and aerosol extinction coefficients. Based on theoretical perspective as well as our experimental results, we find that the liquid-water Raman scattering efficiency does not depend on four orders of particle size, but rather, depends on less than four orders, particularly in a smaller effective size distribution than Mie scattering efficiency. Therefore, we conclude that the color ratio method can be applied to aerosols, while the ratio between the liquid water Raman and extinction coefficients can be applied to cloud droplet size measurements.

Rainbow Fourier transform

We present a novel technique for remote sensing of cloud droplet size distributions. Polarized reflectances in the scattering angle range between 135° and 165° exhibit a sharply defined rainbow structure, the shape of which is determined mostly by single scattering properties of cloud particles, and therefore, can be modeled using the Mie theory. Fitting the observed rainbow with such a model (computed for a parameterized family of particle size distributions) has been used for cloud droplet size retrievals. We discovered that the relationship between the rainbow structures and the corresponding particle size distributions is deeper than it had been commonly understood. In fact, the Mie theory-derived polarized reflectance as a function of reduced scattering angle (in the rainbow angular range) and the (monodisperse) particle radius appears to be a proxy to a kernel of an integral transform (similar to the sine Fourier transform on the positive semi-axis). This approach, called the rainbow Fourier transform (RFT), allows us to accurately retrieve the shape of the droplet size distribution by the application of the corresponding inverse transform to the observed polarized rainbow. While the basis functions of the proxy-transform are not exactly orthogonal in the finite angular range, this procedure needs to be complemented by a simple regression technique, which removes the retrieval artifacts. This non-parametric approach does not require any a priori knowledge of the droplet size distribution functional shape and is computationally fast (no look-up tables, no fitting, computations are the same as for the forward modeling).

Retrieval of cloud droplet size distribution parameters from polarized reflectance measurements

We present an algorithm for retrieval of cloud droplet size distribution parameters (effective radius and variance) from the Research Scanning Polarimeter (RSP) measurements. The RSP is an airborne prototype for the Aerosol Polarimetery Sensor (APS), which is due to be launched as part of the NASA Glory Project. This instrument measures both polarized and total reflectances in 9 spectral channels with center wavelengths ranging from 410 to 2250 nm. For cloud droplet size retrievals we utilize the polarized reflectances in the scattering angle range between 140 and 170 degrees where they exhibit rainbow. The shape of the rainbow is determined mainly by single scattering properties of the cloud particles, that simplifies the inversions and reduces retrieval uncertainties. The retrieval algorithm was tested using realistically simulated cloud radiation fields. Our retrievals of cloud droplet sizes from actual RSP measurements made during two recent field campaigns were compared with the correlative in situ observations.

Vapour density field of a population of cloud droplets

The idea that a cluster of droplets evaporates in times longer than a single droplet and that the droplets near the edge of the cluster evaporate most rapidly is based on observational evidence. In this work, we use a theoretical model based on the electrostatic-image-charge method to calculate the vapour density field for a cloud of monodisperse cloud droplet size distribution immersed in an undersaturated environment. Calculations are performed for variations of droplet size, droplet number, droplet separation, relative humidity and temperature of the environment. The results show the screening effect produced by the outermost droplets of the cluster, which reduces the effect of the vapour density at infinity within the cluster. Additionally, this model allows us to observe that each droplet within the cluster evaporates with a different evaporation rate according to the position that it occupies within the cluster. Droplets near the edge of the cluster are shown to evaporate faster than droplets within the cluster. The treatment uses a highly simplified description of a droplet cluster, but it nevertheless allows us to build a good theoretical understanding of the microphysical properties of the evaporation process in real cloud systems.

Inverse modeling of cloud-aerosol interactions – Part 1: Detailed response surface analysis

Abstract. New methodologies are required to probe the sensitivity of parameters describing cloud droplet activation. This paper presents an inverse modeling-based method for exploring cloud-aerosol interactions via response surfaces. The objective function, containing the difference between the measured and model predicted cloud droplet size distribution is studied in a two-dimensional framework, and presented for pseudo-adiabatic cloud parcel model parameters that are pair-wise selected. From this response surface analysis it is shown that the susceptibility of cloud droplet size distribution to variations in different aerosol physiochemical parameters is highly dependent on the aerosol environment and meteorological conditions. In general the cloud droplet size distribution is most susceptible to changes in the updraft velocity. A shift towards an increase in the importance of chemistry for the cloud nucleating ability of particles is shown to exist somewhere between marine average and rural continental aerosol regimes. We also use these response surfaces to explore the feasibility of inverse modeling to determine cloud-aerosol interactions. It is shown that the "cloud-aerosol" inverse problem is particularly difficult to solve due to significant parameter interaction, presence of multiple regions of attraction, numerous local optima, and considerable parameter insensitivity. The identifiability of the model parameters will be dependent on the choice of the objective function. Sensitivity analysis is performed to investigate the location of the information content within the calibration data to confirm that our choice of objective function maximizes information retrieval from the cloud droplet size distribution. Cloud parcel models that employ a moving-centre based calculation of the cloud droplet size distribution pose additional difficulties when applying automatic search algorithms for studying cloud-aerosol interactions. To aid future studies, an increased resolution of the region of the size spectrum associated with droplet activation within cloud parcel models, or further development of fixed-sectional cloud models would be beneficial. Despite these improvements, it is demonstrated that powerful search algorithms remain necessary to efficiently explore the parameter space and successfully solve the cloud-aerosol inverse problem.

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

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).

Spectral dispersion of cloud droplet size distributions and radar threshold reflectivity for drizzle

From first principles, we find that the radar threshold reflectivity between nonprecipitating clouds and precipitating clouds is strongly related to not only the cloud droplet number concentration but also the spectral dispersion of cloud droplet size distributions. The further investigation indicates that the threshold value is an increasing function of spectral dispersion and cloud droplet number concentration. These results may improve our understanding of the cloud-precipitation interaction and the aerosol indirect effect.

Strong air pollution causes widespread haze‐clouds over China

North China (Huabei in Chinese) is a geographical region located between 32°N and 42°N latitude in eastern China, including several provinces and large municipalities (e.g., Beijing and Tianjin). In the past decades the region has experienced dramatic changes in air quality and climate. Among the multiple causes aerosol pollution is expected to play a particularly important role. To investigate this, a field measurement campaign was performed in April–May 2006 as part of the project Influence of Pollution on Aerosols and Cloud Microphysics in North China. Here we report the first aircraft measurements of atmospheric trace gases, aerosols, and clouds over this part of China, a region strongly affected by both natural desert dust and pollution smog. We observed very high concentrations of gaseous air pollutants and haze particles, partly together with nonprecipitating stratiform clouds. The clouds were characterized by numerous droplets, much smaller than in a less‐polluted atmosphere. Our data reveal that the highly efficient coating of dust particles by pollution acids provides the predominant source of cloud condensation nuclei. The pollution‐enhanced activation of dust particles into droplets is shown to be remarkably efficient so that clouds even form below 100% relative humidity. Contrary to previous analyses, we find that the haze particles influence the spectral shape of the cloud droplet size distribution such that the indirect climate cooling effect of aerosols on clouds is increased. The widespread haze, combined with low clouds, diminishes air quality and exerts an unusually strong cooling forcing on climate.