Hanna Pawlowska

Radiative Properties of Boundary Layer Clouds: Droplet Effective Radius versus Number Concentration

The plane-parallel model for the parameterization of clouds in global climate models is examined in order to estimate the effects of the vertical profile of the microphysical parameters on radiative transfer calculations for extended boundary layer clouds. The vertically uniform model is thus compared to the adiabatic stratified one. The validation of the adiabatic model is based on simultaneous measurements of cloud microphysical parameters in situ and cloud radiative properties from above the cloud layer with a multispectral radiometer. In particular, the observations demonstrate that the dependency of cloud optical thickness on cloud geometrical thickness is larger than predicted with the vertically uniform model and that it is in agreement with the prediction of the adiabatic one. Numerical simulations of the radiative transfer have been performed to establish the equivalence between the two models in terms of the effective radius. They show that the equivalent effective radius of a vertically uniform model is between 80% and 100% of the effective radius at the top of an adiabatic stratified model. The relationship depends, in fact, upon the cloud geometrical thickness and droplet concentration. Remote sensing measurements of cloud radiances in the visible and near infrared are then examined at the scale of a cloud system for a marine case and the most polluted case sampled during the second Aerosol Characterization Experiment. The distributions of the measured values are significantly different between the two cases. This constitutes observational evidence of the aerosol indirect effect at the scale of a cloud system. Finally, the adiabatic stratified model is used to develop a procedure for the retrieval of cloud geometrical thickness and cloud droplet number concentration from the measurements of cloud radiances. It is applied to the marine and to the polluted cases. The retrieved values of droplet concentration are significantly underestimated with respect to the values measured in situ. Despite this discrepancy the procedure is efficient at distinguishing the difference between the two cases.

CCN measurements during ACE-2 and their relationship to cloud microphysical properties

Measurements of cloud condensation nuclei (CCN) concentration at 0.1% supersaturation were made onboard the CIRPAS Pelican over the northeast Atlantic during June and July, 1997, in the vicinity of Tenerife, Spain, as part of the second Aerosol Characterization Experiment (ACE-2). The average CCN concentration (N ccn ) in the marine boundary layer for clean air masses was 27±8 and 42±14 cm’3 for cloudy and clear conditions, respectively, consistent with measurements made near the British Isles and close to Tasmania, Australia, during ACE-1 for similar conditions. A local CCN closure experiment was conducted. Measured N ccn is compared with predictions based on aerosol number size distributions and size-resolved chemical composition profiles determined from measurements and the literature. A sublinear relationship between measured and predicted N ccn ,N ccn ~N0.51 , was found. This result is consistent with some previous studies, but others have obtained results much closer to the expected 1 : 1 relationship between measured and predicted N ccn . A large variability between measured and predicted N ccn was also observed, leading to the conclusion that, for 95% of the data, the predictions agree with measurements to within a factor of 11. Relationships between belowcloud N ccn and aerosol accumulation mode concentration, and in-cloud cloud droplet number

Microphysical properties of stratocumulus clouds

Data collected in situ with the Meteo-France Merlin-IV instrumented aircraft during the EUCREX mission 206 are analyzed to document cloud properties that are relevant to the calculation of cloud radiative properties. Ascents and descents through the cloud layer reveal that most of the vertical profiles of liquid water content (LWC) and droplet sizes are close to adiabatic profiles. Analysis of horizontal legs shows that sub-adiabatic regions are characterized by reduced droplet concentrations, while droplet sizes remain close to their adiabatic values at that level. Statistics of LWC, droplet concentration and droplet mean volume radius normalized by their adiabatic values are presented for four distinct regions of the cloud layer. This information is provided for tests of a parameterization of optical thickness based on the adiabatic model.

Droplet Activation and Mixing in Large-Eddy Simulation of a Shallow Cumulus Field

AbstractThis paper presents the application of a double-moment bulk warm-rain microphysics scheme to the simulation of a field of shallow convective clouds based on Barbados Oceanographic and Meteorological Experiment (BOMEX) observations. The scheme predicts the supersaturation field and allows secondary in-cloud activation of cloud droplets above the cloud base. Pristine and polluted cloud condensation nuclei (CCN) environments, as well as opposing subgrid-scale mixing scenarios, are contrasted. Numerical simulations show that about 40% of cloud droplets originate from CCN activated above the cloud base. Significant in-cloud activation leads to the mean cloud droplet concentration that is approximately constant with height, in agreement with aircraft observations. The in-cloud activation affects the spatial distribution of the effective radius and the mean albedo of the cloud field. Differences between pristine and polluted conditions are consistent with the authors’ previous study, but the impact of th...

Effective radius and droplet spectral width from in‐situ aircraft observations in trade‐wind cumuli during RICO

Received 19 March 2009; accepted 28 April 2009; published 3 June 2009. [1] This paper presents statistics of cloud microphysical properties of shallow tropical cumuli observed by a research aircraft during RICO field campaign. Cloud properties are derived from 10 Hz (about 10 m spatial distance) Fast-FSSP data in four different flights. The motivation comes from similar analyses of either aircraft data from stratocumulus clouds or remote-sensing data of tropical cumuli. In the lowest few hundred meters, the standard deviation of the droplet size distribution sr and the relative dispersion, the ratio of sr and the mean radius, are similar to stratocumulus clouds, but they are significantly larger in the upper half of the cloud field depth. The frequency distribution of the effective radius is significantly narrower than in the remote-sensing observations in the middle and upper third of the cloud field. These results can be used in parameterizations and validations of cloud microphysics in numerical models of various complexity. Citation: Arabas, S., H. Pawlowska, and W. W. Grabowski (2009), Effective radius and droplet spectral width from insitu aircraft observations in trade-wind cumuli during RICO, Geophys. Res. Lett., 36, L11803, doi:10.1029/2009GL038257.

Optimal Nonlinear Estimation for Cloud Particle Measurements

Abstract Particle concentration is generally derived from measurements by cumulating particle counts on a given sampling period and dividing this particle number by the corresponding sampled volume. Such a procedure is a poor estimation of the concentration when the number of counts per sample is too low. It is shown that counting particles in a cloud is a conditionally Poisson random process given its intensity, which is proportional to the local average concentration of particles. Because of turbulence and mixing processes, the particle concentration in clouds fluctuates and so does the intensity of the counting process, which is referred to as an inhomogeneous Poisson process. The series of counts during a cloud traverse is a unique realization of the process. The estimation of the expected number of particles is thus a Bayesian procedure that consists in the estimation of the intensity of an a priori random inhomogeneous Poisson process from a unique realization of the process. This implies, of course...

Optical Properties of Shallow Convective Clouds Diagnosed from a Bulk-Microphysics Large-Eddy Simulation

Large-eddy simulation (LES) models provide an indispensable tool to study processes within cloudtopped subtropical and trade wind boundary layers (e.g., Siebesma et al. 2003; Stevens et al. 2005, and references therein). Typically, LES models use bulk representation of cloud microphysics. Bulk approach assumes that warm (ice free) clouds are exactly at water saturation and that a cloud cannot exist in undersaturated conditions. It is well established from cloud observations (e.g., Stommel 1947; Warner 1955; Blyth 1993; Wang and Albrecht 1994) and cloud modeling (e.g., Brenguier and Grabowski 1993; Carpenter et al. 1998; Siebesma et al. 2003; Chosson et al. 2007) that shallow cumulus and stratocumulus clouds are strongly diluted by entrainment and that such dilution affects not only bulk thermodynamic properties [e.g., the liquid water content (LWC)] but also cloud microphysics (i.e., the spectrum of cloud droplets). For nonprecipitating clouds, conservation of total water (vapor plus liquid) and moist static energy determines bulk thermodynamic properties of cloud volumes diluted by entrainment of environmental air. Predicting changes of the cloud droplet spectra resulting from entrainment, on the other hand, requires additional constraints because situations where cloud water after homogenization is distributed over either the same number of smaller droplets (i.e., the homogeneous mixing scenario) or smaller number of droplets with the initial size (i.e., the extremely inhomogeneous mixing scenario; Baker and Latham 1979; Baker et al. 1980) are equally possible (see discussion in Andrejczuk et al. 2006). The impact of entrainment and mixing on cloud droplet spectra has been shown to significantly affect mean radiative properties of a field of stratocumulus and cumulus clouds. Chosson et al. (2004) were first to show this for the case of stratocumulus. They examined the impact of microphysical transformation following entrainment and mixing by considering separately the homogeneous and extremely inhomogeneous mixing scenarios and showed that the mean cloud optical thickness derived by applying the homogeneous scheme was about 35% larger than for the extremely inhomogeneous mixing (see Chosson et al. 2007 for further discussion). This result prompted an investigation reported in Grabowski (2006, hereafter G06), where a similar issue was investigated in the context of Corresponding author address: Wojciech W. Grabowski, NCAR/MMM, P.O. Box 3000, Boulder, CO 80307-3000. E-mail: grabow@ncar.ucar.edu

Homogeneity of the Subgrid-Scale Turbulent Mixing in Large-Eddy Simulation of Shallow Convection

AbstractThis paper presents an approach to locally predict homogeneity of the subgrid-scale turbulent mixing in large-eddy simulation of shallow clouds applying double-moment warm-rain microphysics. The homogeneity of subgrid-scale mixing refers to the partitioning of the cloud water evaporation due to parameterized entrainment between changes of the mean droplet radius and changes of the mean droplet concentration. Homogeneous and extremely inhomogeneous mixing represent two limits of possible scenarios, where the droplet concentration and the mean droplet radius remains unchanged during the microphysical adjustment, respectively. To predict the subgrid-scale mixing scenario, the double-moment microphysics scheme is merged with the approach to delay droplet evaporation resulting from entrainment. Details of the new scheme and its application in the Barbados Oceanographic and Meteorological Experiment (BOMEX) shallow convection case are discussed. The simulated homogeneity of mixing varies significantly i...

Modeling of Subgrid-Scale Mixing in Large-Eddy Simulation of Shallow Convection

Abstract This paper discusses an extension of the approach proposed previously to represent the delay of cloud water evaporation and buoyancy reversal due to the cloud–environment mixing in bulk microphysics large-eddy simulation of clouds. In the original approach, an additional equation for the mean spatial scale of cloudy filaments was introduced to represent the progress toward microscale homogenization of a volume undergoing turbulent cloud–environment mixing, with the evaporation of cloud water allowed only when the filament scale approached the Kolmogorov microscale. Here, it is shown through a posteriori analysis of model simulations that one should also predict the volume fraction of the cloudy air that was diagnosed in the original approach. The resulting model of turbulent mixing and homogenization, referred to as the λ–β model, is applied in a series of shallow convection simulations using various spatial resolutions and compared to the traditional bulk model. This work represents an intermedi...

libcloudph++ 1.0: a single-moment bulk, double-moment bulk, and particle-based warm-rain microphysics library in C++

Abstract. This paper introduces a library of algorithms for representing cloud microphysics in numerical models. The library is written in C++, hence the name libcloudph++. In the current release, the library covers three warm-rain schemes: the single- and double-moment bulk schemes, and the particle-based scheme with Monte Carlo coalescence. The three schemes are intended for modelling frameworks of different dimensionalities and complexities ranging from parcel models to multi-dimensional cloud-resolving (e.g. large-eddy) simulations. A two-dimensional (2-D) prescribed-flow framework is used in the paper to illustrate the library features. The libcloudph++ and all its mandatory dependencies are free and open-source software. The Boost.units library is used for zero-overhead dimensional analysis of the code at compile time. The particle-based scheme is implemented using the Thrust library that allows one to leverage the power of graphics processing units (GPU), retaining the possibility of compiling the unchanged code for execution on single or multiple standard processors (CPUs). The paper includes a complete description of the programming interface (API) of the library and a performance analysis including comparison of GPU and CPU set-ups.