scholarly journals Comparison of Observed and Simulated Drop Size Distributions from Large-Eddy Simulations with Bin Microphysics

2019 ◽  
Vol 147 (2) ◽  
pp. 477-493
Author(s):  
Mikael K. Witte ◽  
Patrick Y. Chuang ◽  
Orlando Ayala ◽  
Lian-Ping Wang ◽  
Graham Feingold
Keyword(s):  
Liquid Water ◽  
Drop Size ◽  
Potential Temperature ◽  
Liquid Water Content ◽  
Liquid Water Path ◽  
Cloud Drop ◽  
Large Eddy Simulation Model ◽  
Surface Precipitation ◽  
Large Eddy ◽  
Bin Microphysics

Abstract Two case studies of marine stratocumulus (one nocturnal and drizzling, the other daytime and nonprecipitating) are simulated by the UCLA large-eddy simulation model with bin microphysics for comparison with aircraft in situ observations. A high-bin-resolution variant of the microphysics is implemented for closer comparison with cloud drop size distribution (DSD) observations and a turbulent collision–coalescence kernel to evaluate the role of turbulence on drizzle formation. Simulations agree well with observational constraints, reproducing observed thermodynamic profiles (i.e., liquid water potential temperature and total moisture mixing ratio) as well as liquid water path. Cloud drop number concentration and liquid water content profiles also agree well insofar as the thermodynamic profiles match observations, but there are significant differences in DSD shape among simulations that cause discrepancies in higher-order moments such as sedimentation flux, especially as a function of bin resolution. Counterintuitively, high-bin-resolution simulations produce broader DSDs than standard resolution for both cases. Examination of several metrics of DSD width and percentile drop sizes shows that various discrepancies of model output with respect to the observations can be attributed to specific microphysical processes: condensation spuriously creates DSDs that are too wide as measured by standard deviation, which leads to collisional production of too many large drops. The turbulent kernel has the greatest impact on the low-bin-resolution simulation of the drizzling case, which exhibits greater surface precipitation accumulation and broader DSDs than the control (quiescent kernel) simulations. Turbulence effects on precipitation formation cannot be definitively evaluated using bin microphysics until the artificial condensation broadening issue has been addressed.

scholarly journals Large-Eddy Simulations of the Impact of Ground-Based Glaciogenic Seeding on Shallow Orographic Convection: A Case Study

2017 ◽  
Vol 56 (1) ◽  
pp. 69-84 ◽  
Author(s):  
Xia Chu ◽  
Bart Geerts ◽  
Lulin Xue ◽  
Roy Rasmussen
Keyword(s):  
Liquid Water ◽  
Supercooled Liquid ◽  
Liquid Water Content ◽  
Diffusional Growth ◽  
Large Eddy Simulation Model ◽  
Surface Precipitation ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Glaciogenic Seeding ◽  
The Impact

AbstractThis study uses the WRF large-eddy simulation model at 100-m resolution to examine the impact of ground-based glaciogenic seeding on shallow (~2 km deep), cold-based convection producing light snow showers over the Sierra Madre in southern Wyoming on 13 February 2012, as part of the AgI Seeding Cloud Impact Investigation (ASCII). Detailed observations confirm that simulation faithfully captures the orographic flow, convection, and natural snow production, especially on the upwind side. A comparison between treated and control simulations indicates that glaciogenic seeding effectively converts cloud water in convective updrafts to ice and snow in this case, resulting in increased surface precipitation. This comparison further shows that seeding enhances liquid water depletion by vapor deposition, and enhances buoyancy, updraft strength, and cloud-top height. This suggests that the dynamic seeding concept applies, notwithstanding the clouds’ low natural supercooled liquid water content. But the simulated cloud-top-height changes are benign (typically <100 m). This, combined with the fact that most natural and enhanced snow growth occurs in a temperature range in which the Bergeron diffusional growth process is effective, suggests that the modeled snowfall enhancement is largely due to static (microphysical) processes rather than dynamic ones.

scholarly journals The Spiderweb Structure of Stratocumulus Clouds

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 730
Author(s):  
Georgios Matheou ◽  
Anthony B. Davis ◽  
João Teixeira
Keyword(s):  
Liquid Water ◽  
Evaporative Cooling ◽  
Liquid Water Content ◽  
Entrainment Rate ◽  
Liquid Water Path ◽  
Integral Boundary ◽  
Water Path ◽  
Large Eddy ◽  
Stratocumulus Clouds ◽  
Distinctive Structure

Stratocumulus clouds have a distinctive structure composed of a combination of lumpy cellular structures and thin elongated regions, resembling canyons or slits. The elongated slits are referred to as “spiderweb” structure to emphasize their interconnected nature. Using very high resolution large-eddy simulations (LES), it is shown that the spiderweb structure is generated by cloud-top evaporative cooling. Analysis of liquid water path (LWP) and cloud liquid water content shows that cloud-top evaporative cooling generates relatively shallow slits near the cloud top. Most of liquid water mass is concentrated near the cloud top, thus cloud-top slits of clear air have a large impact on the entire-column LWP. When evaporative cooling is suppressed in the LES, LWP exhibits cellular lumpy structure without the elongated low-LWP regions. Even though the spiderweb signature on the LWP distribution is negligible, the cloud-top evaporative cooling process significantly affects integral boundary layer quantities, such as the vertically integrated turbulent kinetic energy, mean liquid water path, and entrainment rate. In a pair of simulations driven only by cloud-top radiative cooling, evaporative cooling nearly doubles the entrainment rate.

scholarly journals CLOUD DROP SPECTRA IN MARITIME AND INLAND REGIONS

MAUSAM ◽  
2021 ◽  
Vol 43 (4) ◽  
pp. 415-420
Author(s):  
S. K. PAUL ◽  
A. G . PILLAI
Keyword(s):  
Liquid Water ◽  
Arabian Sea ◽  
Drop Size ◽  
Total Concentration ◽  
Liquid Water Content ◽  
Systematic Change ◽  
Cumulus Clouds ◽  
Cloud Drop ◽  
Size Spectra ◽  
Cloud Drop Spectra

Measurements o f clo ud drop ..ire spectra on non-preci pitating cumulus clouds, 1·2 km thick,were made at differe nt levels o ver the Arabian Sea (maritime) and over r une (inland) regio n during the end ofthe summer monsoo n seasons of 1973, 1974 and 1979.The macimurn size of clo ud drops for the. Arabian Sea generally increased with height. while that for run eJiJ not show a systematic change with height. At bot h the local ions. the total concentration o f drops decreasedwith height. The maritime dist ributions were bimodal at all levels while those o..-er Punc were usually unimodal.The average values of liquid water content. mean vo lume diameter. dispersion and conccnt rarion of drops withdiameter > 50 «m were a lin le greater and total concentration a little smaller over the maritime region as ' om'pared to those over inland. The co ncentrations of drops with diameter < 14 ,...m and those > 78 I'm and thema ximum ~ i 7e were greater over Pune than o..er the sea. The ..'a riarions in cloud drop spectra and the clo udphysical parameters over beth the locations are discussed.Kc) words - Cloud drop size spectra, Drop co ncentration,

Reconciling and Validating the Cloud Thickness and Liquid Water Path Tendencies Proposed by R. Wood and J. J. van der Dussen et al.

2015 ◽  
Vol 72 (5) ◽  
pp. 2033-2040 ◽  
Author(s):  
Mohamed S. Ghonima ◽  
Joel R. Norris ◽  
Thijs Heus ◽  
Jan Kleissl
Keyword(s):  
Boundary Layer ◽  
Liquid Water ◽  
Mixed Boundary ◽  
Liquid Water Path ◽  
Water Path ◽  
Large Eddy ◽  
Heat And Moisture ◽  
Cloud Thickness ◽  
Detailed Derivation ◽  
Good Agreement

Abstract A detailed derivation of stratocumulus cloud thickness and liquid water path tendencies as a function of the well-mixed boundary layer mass, heat, and moisture budget equations is presented. The derivation corrects an error in the cloud thickness tendency equation derived by R. Wood to make it consistent with the liquid water path tendency equation derived by J. J. van der Dussen et al. The validity of the tendency equations is then tested against the output of large-eddy simulations of a typical stratocumulus-topped boundary layer case and is found to be in good agreement.

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

2014 ◽  
Vol 7 (9) ◽  
pp. 9917-9992 ◽  
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.

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

2011 ◽  
Vol 4 (6) ◽  
pp. 7109-7158 ◽  
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.

scholarly journals Parameterizing cloud top effective radii from satellite retrieved values, accounting for vertical photon transport: quantification and correction of the resulting bias in droplet concentration and liquid water path retrievals

2018 ◽  
Vol 11 (7) ◽  
pp. 4273-4289 ◽  
Author(s):  
Daniel P. Grosvenor ◽  
Odran Sourdeval ◽  
Robert Wood
Keyword(s):  
Penetration Depth ◽  
Optical Depth ◽  
Liquid Water ◽  
Liquid Water Content ◽  
Cloud Base ◽  
Percentage Error ◽  
Time Variability ◽  
Liquid Water Path ◽  
Water Path ◽  
Droplet Concentration

Abstract. Droplet concentration (Nd) and liquid water path (LWP) retrievals from passive satellite retrievals of cloud optical depth (τ) and effective radius (re) usually assume the model of an idealized cloud in which the liquid water content (LWC) increases linearly between cloud base and cloud top (i.e. at a fixed fraction of the adiabatic LWC). Generally it is assumed that the retrieved re value is that at the top of the cloud. In reality, barring re retrieval biases due to cloud heterogeneity, the retrieved re is representative of smaller values that occur lower down in the cloud due to the vertical penetration of photons at the shortwave-infrared wavelengths used to retrieve re. This inconsistency will cause an overestimate of Nd and an underestimate of LWP (referred to here as the “penetration depth bias”), which this paper quantifies via a parameterization of the cloud top re as a function of the retrieved re and τ. Here we estimate the relative re underestimate for a range of idealized modelled adiabatic clouds using bispectral retrievals and plane-parallel radiative transfer. We find a tight relationship between gre=recloud top/reretrieved and τ and that a 1-D relationship approximates the modelled data well. Using this relationship we find that gre values and hence Nd and LWP biases are higher for the 2.1 µm channel re retrieval (re2.1) compared to the 3.7 µm one (re3.7). The theoretical bias in the retrieved Nd is very large for optically thin clouds, but rapidly reduces as cloud thickness increases. However, it remains above 20 % for τ<19.8 and τ<7.7 for re2.1 and re3.7, respectively. We also provide a parameterization of penetration depth in terms of the optical depth below cloud top (dτ) for which the retrieved re is likely to be representative. The magnitude of the Nd and LWP biases for climatological data sets is estimated globally using 1 year of daily MODIS (MODerate Imaging Spectroradiometer) data. Screening criteria are applied that are consistent with those required to help ensure accurate Nd and LWP retrievals. The results show that the SE Atlantic, SE Pacific and Californian stratocumulus regions produce fairly large overestimates due to the penetration depth bias with mean biases of 32–35 % for re2.1 and 15–17 % for re3.7. For the other stratocumulus regions examined the errors are smaller (24–28 % for re2.1 and 10–12 % for re3.7). Significant time variability in the percentage errors is also found with regional mean standard deviations of 19–37 % of the regional mean percentage error for re2.1 and 32–56 % for re3.7. This shows that it is important to apply a daily correction to Nd for the penetration depth error rather than a time–mean correction when examining daily data. We also examine the seasonal variation of the bias and find that the biases in the SE Atlantic, SE Pacific and Californian stratocumulus regions exhibit the most seasonality, with the largest errors occurring in the December, January and February (DJF) season. LWP biases are smaller in magnitude than those for Nd (−8 to −11 % for re2.1 and −3.6 to −6.1 % for re3.7). In reality, and especially for more heterogeneous clouds, the vertical penetration error will be combined with a number of other errors that affect both the re and τ, which are potentially larger and may compensate or enhance the bias due to vertical penetration depth. Therefore caution is required when applying the bias corrections; we suggest that they are only used for more homogeneous clouds.

scholarly journals Aerosol–Cloud Interaction in Deep Convective Clouds over the Indian Peninsula Using Spectral (Bin) Microphysics

2017 ◽  
Vol 74 (10) ◽  
pp. 3145-3166 ◽  
Author(s):  
K. Gayatri ◽  
S. Patade ◽  
T. V. Prabha
Keyword(s):  
Size Distribution ◽  
Cloud Condensation Nuclei ◽  
Wrf Model ◽  
Cloud Droplet ◽  
Liquid Water Content ◽  
Cloud Microphysics ◽  
Large Area ◽  
Surface Precipitation ◽  
Aerosol Cloud ◽  
Bin Microphysics

Abstract The Weather Research and Forecasting (WRF) Model coupled with a spectral bin microphysics (SBM) scheme is used to investigate aerosol effects on cloud microphysics and precipitation over the Indian peninsular region. The main emphasis of the study is in comparing simulated cloud microphysical structure with in situ aircraft observations from the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX). Aerosol–cloud interaction over the rain-shadow region is investigated with observed and simulated size distribution spectra of cloud droplets and ice particles in monsoon clouds. It is shown that size distributions as well as other microphysical characteristics obtained from simulations such as liquid water content, cloud droplet effective radius, cloud droplet number concentration, and thermodynamic parameters are in good agreement with the observations. It is seen that in clouds with high cloud condensation nuclei (CCN) concentrations, snow and graupel size distribution spectra were broader compared to clouds with low concentrations of CCN, mainly because of enhanced riming in the presence of a large number of droplets with a diameter of 10–30 μm. The Hallett–Mossop ice multiplication process is illustrated to have an impact on snow and graupel mass. The changes in CCN concentrations have a strong effect on cloud properties over the domain, amounts of cloud water, and the glaciation of the clouds, but the effects on surface precipitation are small when averaged over a large area. Overall enhancement of cold-phase cloud processes in the high-CCN case contributed to slight enhancement (5%) in domain-averaged surface precipitation.

scholarly journals Macroscopic impacts of cloud and precipitation processes on maritime shallow convection as simulated by a large eddy simulation model with bin microphysics

2015 ◽  
Vol 15 (2) ◽  
pp. 913-926 ◽  
Author(s):  
W. W. Grabowski ◽  
L.-P. Wang ◽  
T. V. Prabha
Keyword(s):  
Remote Sensing ◽  
Cloud Condensation Nuclei ◽  
Collision Kernel ◽  
Small Scale ◽  
Shallow Convection ◽  
Large Eddy Simulation Model ◽  
Large Eddy ◽  
Precipitation Processes ◽  
Bin Microphysics ◽  
The Impact

Abstract. This paper discusses impacts of cloud and precipitation processes on macrophysical properties of shallow convective clouds as simulated by a large eddy model applying warm-rain bin microphysics. Simulations with and without collision–coalescence are considered with cloud condensation nuclei (CCN) concentrations of 30, 60, 120, and 240 mg−1. Simulations with collision–coalescence include either the standard gravitational collision kernel or a novel kernel that includes enhancements due to the small-scale cloud turbulence. Simulations with droplet collisions were discussed in Wyszogrodzki et al. (2013) focusing on the impact of the turbulent collision kernel. The current paper expands that analysis and puts model results in the context of previous studies. Despite a significant increase of the drizzle/rain with the decrease of CCN concentration, enhanced by the effects of the small-scale turbulence, impacts on the macroscopic cloud field characteristics are relatively minor. Model results show a systematic shift in the cloud-top height distributions, with an increasing contribution of deeper clouds for stronger precipitating cases. We show that this is consistent with the explanation suggested in Wyszogrodzki et al. (2013); namely, the increase of drizzle/rain leads to a more efficient condensate offloading in the upper parts of the cloud field. A second effect involves suppression of the cloud droplet evaporation near cloud edges in low-CCN simulations, as documented in previous studies (e.g., Xue and Feingold, 2006). We pose the question whether the effects of cloud turbulence on drizzle/rain formation in shallow cumuli can be corroborated by remote sensing observations, for instance, from space. Although a clear signal is extracted from model results, we argue that the answer is negative due to uncertainties caused by the temporal variability of the shallow convective cloud field, sampling and spatial resolution of the satellite data, and overall accuracy of remote sensing retrievals.

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