Relationships between cloud droplet effective radius, liquid water content, and droplet concentration for warm clouds in Brazil embedded in biomass smoke

Abstract The radar reflectivity and liquid water content of stratocumulus clouds have been computed from cloud droplet spectra recorded during more than 4000 km of cloud penetrations by an aircraft, and the probability of detecting various values of liquid water content as a function of the radar sensitivity threshold has been derived. The goal of the study is to specify the sensitivity required for any future spaceborne cloud radar. In extensive marine stratocumulus deeper than about 200 m, occasional but ubiquitous drizzle-sized droplets of up to 200 μm dominate the radar return and increase it by between 10 and 20 dB above the cloud droplet contribution to the return, making radar detection easier, although the concentration of the drizzle drops is so low that they have no effect on the liquid water content or effective radius. These occasional drizzle-sized droplets are present throughout the vertical and horizontal extent of such clouds but should evaporate within 200 m of cloud base. On occasion, the drizzle can fall farther and may yield a false measurement of cloud-base altitude, but such cases can be recognized by examining the vertical profile of reflectivity. A radar sensitivity threshold of −30 dBZ would detect 80%, 85%, and 90% of the marine stratocumulus, with a liquid water content above 0.025, 0.05, and 0.075 g m−3, respectively. Because nonprecipitating drizzle droplets are rare in continental stratocumulus, the equivalent figures are reduced to 38%, 33%, and 25%. Improving the sensitivity to −40 dBZ increases detection probability to nearly 100% for both types of cloud. These figures are based on the assumption that the cloud is deep enough to fill the radar pulse volume.

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Parameterization of Vertical Profiles of Governing Microphysical Parameters of Shallow Cumulus Cloud Ensembles Using LES with Bin Microphysics

Journal of the Atmospheric Sciences ◽

10.1175/jas-d-18-0046.1 ◽

2019 ◽

Vol 76 (2) ◽

pp. 533-560 ◽

Cited By ~ 8

Author(s):

Pavel Khain ◽

Reuven Heiblum ◽

Ulrich Blahak ◽

Yoav Levi ◽

Harel Muskatel ◽

...

Keyword(s):

Water Content ◽

Liquid Water ◽

Liquid Water Content ◽

Effective Radius ◽

Cloud Base ◽

Vertical Profiles ◽

Droplet Concentration ◽

Radiation Properties ◽

Microphysical Parameters ◽

Bin Microphysics

Abstract Shallow convection is a subgrid process in cloud-resolving models for which their grid box is larger than the size of small cumulus clouds (Cu). At the same time such Cu substantially affect radiation properties and thermodynamic parameters of the low atmosphere. The main microphysical parameters used for calculation of radiative properties of Cu in cloud-resolving models are liquid water content (LWC), effective droplet radius, and cloud fraction (CF). In this study, these parameters of fields of small, warm Cu are calculated using large-eddy simulations (LESs) performed using the System for Atmospheric Modeling (SAM) with spectral bin microphysics. Despite the complexity of microphysical processes, several fundamental properties of Cu were found. First, despite the high variability of LWC and droplet concentration within clouds and between different clouds, the volume mean and effective radii per specific level vary only slightly. Second, the values of effective radius are close to those forming during adiabatic ascent of air parcels from cloud base. These findings allow for characterization of a cloud field by specific vertical profiles of effective radius and of mean liquid water content, which can be calculated using the theoretical profile of adiabatic liquid water content and the droplet concentration at cloud base. Using the results of these LESs, a simple parameterization of cloud-field-averaged vertical profiles of effective radius and of liquid water content is proposed for different aerosol and thermodynamic conditions. These profiles can be used for calculation of radiation properties of Cu fields in large-scale models. The role of adiabatic processes in the formation of microstructure of Cu is discussed.

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Measuring cloud droplet effective radius and liquid water content using changes in degree of linear polarization along cloud depth

Optics Letters ◽

10.1364/ol.39.003378 ◽

2014 ◽

Vol 39 (12) ◽

pp. 3378 ◽

Cited By ~ 6

Author(s):

Dukhyeon Kim ◽

Jeongsoon Lee

Keyword(s):

Water Content ◽

Liquid Water ◽

Linear Polarization ◽

Cloud Droplet ◽

Liquid Water Content ◽

Effective Radius

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A depolarisation lidar based method for the determination of liquid-cloud microphysical properties

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-7-9917-2014 ◽

2014 ◽

Vol 7 (9) ◽

pp. 9917-9992 ◽

Cited By ~ 1

Author(s):

D. P. Donovan ◽

H. Klein Baltink ◽

J. S. Henzing ◽

S. R. de Roode ◽

A. P. Siebesma

Keyword(s):

Water Content ◽

Multiple Scattering ◽

Liquid Water ◽

Cloud Droplet ◽

Optimal Estimation ◽

Liquid Water Content ◽

Cloud Base ◽

Base Region ◽

Large Eddy Simulation Model ◽

Inversion Procedure

Abstract. The fact that polarisation lidars measure a depolarisation signal in liquid clouds due to the occurrence of multiple-scattering is well-known. The degree of measured depolarisation depends on the lidar characteristics (e.g. wavelength and receiver field-of-view) as well as the cloud macrophysical (e.g. liquid water content) and microphysical (e.g. effective radius) properties. Efforts seeking to use depolarisation information in a quantitative manner to retrieve cloud properties have been undertaken with, arguably, limited practical success. In this work we present a retrieval procedure applicable to clouds with (quasi-)linear liquid water content (LWC) profiles and (quasi-)constant cloud droplet number density in the cloud base region. Thus limiting the applicability of the procedure allows us to reduce the cloud variables to two parameters (namely the derivative of the liquid water content with height and the extinction at a fixed distance above cloud-base). This simplification, in turn, allows us to employ a fast and robust optimal-estimation inversion using pre-computed look-up-tables produced using extensive lidar Monte-Carlo multiple-scattering simulations. In this paper, we describe the theory behind the inversion procedure and successfully apply it to simulated observations based on large-eddy simulation model output. The inversion procedure is then applied to actual depolarisation lidar data corresponding to a range of cases taken from the Cabauw measurement site in the central Netherlands. The lidar results were then used to predict the corresponding cloud-base region radar reflectivities. In non-drizzling condition, it was found that the lidar inversion results can be used to predict the observed radar reflectivities with an accuracy within the radar calibration uncertainty (2–3 dBZ). This result strongly supports the accuracy of the lidar inversion results. Results of a comparison between ground-based aerosol number concentration and lidar-derived cloud droplet number densities are also presented and discussed. The observed relationship between the two quantities is seen to be consistent with the results of previous studies based on aircraft-based in situ measurements.

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An intercomparison of radar-based liquid cloud microphysics retrievals and implication for model evaluation studies

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-4-7109-2011 ◽

2011 ◽

Vol 4 (6) ◽

pp. 7109-7158 ◽

Cited By ~ 1

Author(s):

D. Huang ◽

C. Zhao ◽

M. Dunn ◽

X. Dong ◽

G. G. Mace ◽

...

Keyword(s):

Great Plains ◽

Liquid Water ◽

Model Evaluation ◽

Evaluation Studies ◽

Cloud Droplet ◽

Liquid Water Content ◽

Cloud Microphysics ◽

Effective Radius ◽

High Altitudes ◽

Liquid Water Path

Abstract. To assess if current radar-based liquid cloud microphysical retrievals of the Atmospheric Radiation Measurement (ARM) program can provide useful constraints for modeling studies, this paper presents intercomparison results of three cloud products at the Southern Great Plains (SGP) site: the ARM MICROBASE, University of Utah (UU), and University of North Dakota (UND) products over the nine-year period from 1998 to 2006. The probability density and spatial autocorrelation functions of the three cloud Liquid Water Content (LWC) retrievals appear to be consistent with each other, while large differences are found in the droplet effective radius retrievals. The differences in the vertical distribution of both cloud LWC and droplet effective radius retrievals are found to be alarmingly large, with the relative difference between nine-year mean cloud LWC retrievals ranging from 20% at low altitudes to 100% at high altitudes. Nevertheless, the spread in LWC retrievals is much smaller than that in cloud simulations by climate and cloud resolving models. The MICROBASE effective radius ranges from 2.0 at high altitudes to 6.0 μm at low altitudes and the UU and UND droplet effective radius is 6 μm larger. Further analysis through a suite of retrieval experiments shows that the difference between MICROBASE and UU LWC retrievals stems primarily from the partition total Liquid Water path (LWP) into supercooled and warm liquid, and from the input cloud boundaries and LWP. The large differences between MICROBASE and UU droplet effective radius retrievals are mainly due to rain/drizzle contamination and the assumptions of cloud droplet concentration used in the retrieval algorithms. The large discrepancy between different products suggests caution in model evaluation with these observational products, and calls for improved retrievals in general.

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Modelling the relationship between liquid water content and cloud droplet number concentration observed in low clouds in the summer Arctic and its radiative effects

Atmospheric Chemistry and Physics ◽

10.5194/acp-20-29-2020 ◽

2020 ◽

Vol 20 (1) ◽

pp. 29-43

Author(s):

Joelle Dionne ◽

Knut von Salzen ◽

Jason Cole ◽

Rashed Mahmood ◽

W. Richard Leaitch ◽

...

Keyword(s):

Linear Relationship ◽

Water Content ◽

Liquid Water ◽

Cloud Droplet ◽

Liquid Water Content ◽

Number Concentration ◽

Radiative Effect ◽

Low Clouds ◽

Cloud Radiative Effect ◽

Cloud Droplet Number Concentration

Abstract. Low clouds persist in the summer Arctic with important consequences for the radiation budget. In this study, we simulate the linear relationship between liquid water content (LWC) and cloud droplet number concentration (CDNC) observed during an aircraft campaign based out of Resolute Bay, Canada, conducted as part of the Network on Climate and Aerosols: Addressing Key Uncertainties in Remote Canadian Environments study in July 2014. Using a single-column model, we find that autoconversion can explain the observed linear relationship between LWC and CDNC. Of the three autoconversion schemes we examined, the scheme using continuous drizzle (Khairoutdinov and Kogan, 2000) appears to best reproduce the observed linearity in the tenuous cloud regime (Mauritsen et al., 2011), while a scheme with a threshold for rain (Liu and Daum, 2004) best reproduces the linearity at higher CDNC. An offline version of the radiative transfer model used in the Canadian Atmospheric Model version 4.3 is used to compare the radiative effects of the modelled and observed clouds. We find that there is no significant difference in the upward longwave cloud radiative effect at the top of the atmosphere from the three autoconversion schemes (p=0.05) but that all three schemes differ at p=0.05 from the calculations based on observations. In contrast, the downward longwave and shortwave cloud radiative effect at the surface for the Wood (2005b) and Khairoutdinov and Kogan (2000) schemes do not differ significantly (p=0.05) from the observation-based radiative calculations, while the Liu and Daum (2004) scheme differs significantly from the observation-based calculation for the downward shortwave but not the downward longwave fluxes.

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Drizzle in Stratiform Boundary Layer Clouds. Part I: Vertical and Horizontal Structure

Journal of the Atmospheric Sciences ◽

10.1175/jas3529.1 ◽

2005 ◽

Vol 62 (9) ◽

pp. 3011-3033 ◽

Cited By ~ 121

Author(s):

R. Wood

Keyword(s):

Boundary Layer ◽

Water Content ◽

Liquid Water ◽

Liquid Water Content ◽

Precipitation Rate ◽

Cloud Base ◽

Specific Reference ◽

Horizontal Structure ◽

Boundary Layer Clouds ◽

Droplet Concentration

Abstract Detailed observations of stratiform boundary layer clouds on 12 days are examined with specific reference to drizzle formation processes. The clouds differ considerably in mean thickness, liquid water path (LWP), and droplet concentration. Cloud-base precipitation rates differ by a factor of 20 between cases. The lowest precipitation rate is found in the case with the highest droplet concentration even though this case had by far the highest LWP, suggesting that drizzle can be severely suppressed in polluted clouds. The vertical and horizontal structure of cloud and drizzle liquid water and bulk microphysical parameters are examined in detail. In general, the highest concentration of r > 20 μm drizzle drops is found toward the top of the cloud, and the mean volume radius of the drizzle drops increases monotonically from cloud top to base. The resulting precipitation rates are largest at the cloud base but decrease markedly only in the upper third of the cloud. Below cloud, precipitation rates decrease markedly with distance below base due to evaporation, and are broadly consistent in most cases with the results from a simple sedimentation–evaporation model. Evidence is presented that suggests evaporating drizzle is cooling regions of the subcloud layer, which could result in dynamical feedbacks. A composite power spectrum of the horizontal spatial series of precipitation rate is found to exhibit a power-law scaling from the smallest observable scales to close to the maximum observable scale (∼30 km). The exponent is considerably lower (1.1–1.2) than corresponding exponents for LWP variability obtained in other studies (∼1.5–2), demonstrating that there is relatively more variability of drizzle on small scales. Singular measures analysis shows that drizzle fields are much more intermittent than the cloud liquid water content fields, consistent with a drizzle production process that depends strongly upon liquid water content. The adiabaticity of the clouds, which can be modeled as a simple balance between drizzle loss and turbulent replenishment, is found to decrease if the time scale for drizzle loss is shorter than roughly 5–10 eddy turnover time scales. Finally, the data are compared with three simple scalings derived from recent observations of drizzle in subtropical stratocumulus clouds.

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Understanding aerosol–cloud interactions through modeling the development of orographic cumulus congestus during IPHEx

Atmospheric Chemistry and Physics ◽

10.5194/acp-19-1413-2019 ◽

2019 ◽

Vol 19 (3) ◽

pp. 1413-1437 ◽

Cited By ~ 2

Author(s):

Yajuan Duan ◽

Markus D. Petters ◽

Ana P. Barros

Keyword(s):

Water Content ◽

Liquid Water ◽

Cloud Droplet ◽

Liquid Water Content ◽

Cloud Microphysics ◽

Turbulent Dispersion ◽

Cloud Base ◽

Droplet Growth ◽

Aerosol Cloud ◽

Aerosol Cloud Interactions

Abstract. A new cloud parcel model (CPM) including activation, condensation, collision–coalescence, and lateral entrainment processes is used to investigate aerosol–cloud interactions (ACIs) in cumulus development prior to rainfall onset. The CPM was applied with surface aerosol measurements to predict the vertical structure of cloud development at early stages, and the model results were evaluated against airborne observations of cloud microphysics and thermodynamic conditions collected during the Integrated Precipitation and Hydrology Experiment (IPHEx) in the inner region of the southern Appalachian Mountains (SAM). Sensitivity analysis was conducted to examine the model response to variations in key ACI physiochemical parameters and initial conditions. The CPM sensitivities mirror those found in parcel models without entrainment and collision–coalescence, except for the evolution of the droplet spectrum and liquid water content with height. Simulated cloud droplet number concentrations (CDNCs) exhibit high sensitivity to variations in the initial aerosol concentration at cloud base, but weak sensitivity to bulk aerosol hygroscopicity. The condensation coefficient ac plays a governing role in determining the evolution of CDNC, liquid water content (LWC), and cloud droplet spectra (CDS) in time and with height. Lower values of ac lead to higher CDNCs and broader CDS above cloud base, and higher maximum supersaturation near cloud base. Analysis of model simulations reveals that competitive interference among turbulent dispersion, activation, and droplet growth processes modulates spectral width and explains the emergence of bimodal CDS and CDNC heterogeneity in aircraft measurements from different cloud regions and at different heights. Parameterization of nonlinear interactions among entrainment, condensational growth, and collision–coalescence processes is therefore necessary to simulate the vertical structures of CDNCs and CDSs in convective clouds. Comparisons of model predictions with data suggest that the representation of lateral entrainment remains challenging due to the spatial heterogeneity of the convective boundary layer and the intricate 3-D circulations in mountainous regions.

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