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Min Deng
,
Gerald. G. Mace
, and
Zhien Wang

Abstract

The anvil productivities of tropical deep convection are investigated and compared among eight climatological regions using 4 yr of collocated and combined CloudSat and CALIPSO data. For all regions, the convective clusters become deeper while they become wider and tend to be composed of multiple rainy cores. Two strong detrainment layers from deep convection are observed at 6–8 km and above 10 km, which is consistent with the trimodal characteristics of tropical convection that are associated with different divergence, cloud detrainment, and fractional cloudiness. The anvil productivity of tropical deep convection depends on the convection scale, convective life stage or intensity, and large-scale environment. Anvil ice mass ratio related to the whole cluster starts to level off or decrease when the cluster effective scales W eff (the dimension of an equivalent rectangular with the same volume and height as the original cluster) increase to about 200 km wide, while the ratios of anvil scale and volume keep increasing from 0.4 to 0.6 and 0.15 to 0.4, respectively. The anvil clouds above 12 km can count for more than 20% of cluster volume, or more than 50% of total anvil volume, but they only count less than about 2% of total ice mass in the cluster. Anvil production of younger convection of the same W eff is higher than that of the decaying convection. The regional difference in the composite anvil productivities of tropical convective clusters sorted by W eff is subtle, while the occurrence frequencies of different scales of convection vary substantially.

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Jefferson R. Snider
,
David Leon
, and
Zhien Wang

Abstract

Several airborne field experiments have been conducted to verify model descriptions of cloud droplet activation. Measurements of cloud condensation nuclei and updraft are inputs to a parcel model that predicts droplet concentration and droplet size distributions (spectra). Experiments conducted within cumulus clouds have yielded the most robust agreement between model and observation. Investigations of stratocumulus clouds are more varied, in part because of the difficulty of gauging the effects of entrainment and drizzle on droplet concentration and spectra. Airborne lidar is used here to supplement the approach used in prior studies of droplet activation in stratocumulus clouds.

A model verification study was conducted using data acquired during the Southern Hemispheric VAMOS Ocean–Cloud–Aerosol–Land Study Regional Experiment. Consistency between observed and modeled droplet concentrations is achieved, but only after accounting for the effects of entrainment and drizzle on concentrations produced by droplet activation. In addition, predicted spectral dispersions are 74% of the measured dispersions following correction for instrument broadening. This result is consistent with the conjecture that differential activation (at cloud base) and internal mixing (i.e., mixing without entrainment) are important drivers of true spectral broadening.

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Damao Zhang
,
Zhien Wang
,
Andrew Heymsfield
,
Jiwen Fan
, and
Tao Luo

Abstract

Measurements of ice number concentration in clouds are important but still pose problems. The pattern of ice development in stratiform mixed-phase clouds (SMCs) offers an opportunity to use cloud radar reflectivity (Z e ) measurements and other cloud properties to retrieve ice number concentrations. To quantify the strong temperature dependencies of ice crystal habits and growth rates, a one-dimensional (1D) ice growth model has been developed to calculate ice diffusional growth and riming growth along ice particle fallout trajectories in SMCs. The radar reflectivity and fallout velocity profiles of ice crystals calculated from the 1D ice growth model are evaluated with the Atmospheric Radiation Measurements (ARM) Climate Research Facility (ACRF) ground-based high-vertical-resolution radar measurements. A method has been developed to retrieve ice number concentrations in SMCs at a specific cloud-top temperature (CTT) and liquid water path (LWP) by combining Z e measurements and 1D ice growth model simulations. The retrieved ice number concentrations in SMCs are evaluated using integrated airborne in situ and remote sensing measurements and three-dimensional cloud-resolving model simulations with a bin microphysical scheme. The statistical evaluations show that the retrieved ice number concentrations in the SMCs are within an uncertainty of a factor of 2.

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Tristan S. L’Ecuyer
,
Yun Hang
,
Alexander V. Matus
, and
Zhien Wang

Abstract

This study revisits the classical problem of quantifying the radiative effects of unique cloud types in the era of spaceborne active observations. The radiative effects of nine cloud types, distinguished based on their vertical structure defined by CloudSat and CALIPSO observations, are assessed at both the top of the atmosphere and the surface. The contributions from single- and multilayered clouds are explicitly diagnosed. The global, annual mean net cloud radiative effect at the top of the atmosphere is found to be −17.1 ± 4.2 W m−2 owing to −44.2 ± 2 W m−2 of shortwave cooling and 27.1 ± 3.7 W m−2 of longwave heating. Leveraging explicit cloud base and vertical structure information, we further estimate the annual mean net cloud radiative effect at the surface to be −24.8 ± 8.7 W m−2 (−51.1 ± 7.8 W m−2 in the shortwave and 26.3 ± 3.8 W m−2 in the longwave). Multilayered clouds are found to exert the strongest influence on the top-of-atmosphere energy balance. However, a strong asymmetry in net cloud radiative cooling between the hemispheres (8.6 W m−2) is dominated by enhanced cooling from stratocumulus over the southern oceans. It is found that there is no corresponding asymmetry at the surface owing to enhanced longwave emission by southern ocean clouds in winter, which offsets a substantial fraction of their impact on solar absorption in summer. Thus the asymmetry in cloud radiative effects is entirely realized as an atmosphere heating imbalance between the hemispheres.

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Min Deng
,
Gerald G. Mace
,
Zhien Wang
, and
R. Paul Lawson

Abstract

In this study several ice cloud retrieval products that utilize active and passive A-Train measurements are evaluated using in situ data collected during the Small Particles in Cirrus (SPARTICUS) field campaign. The retrieval datasets include ice water content (IWC), effective radius re , and visible extinction σ from CloudSat level-2C ice cloud property product (2C-ICE), CloudSat level-2B radar-visible optical depth cloud water content product (2B-CWC-RVOD), radar–lidar (DARDAR), and σ from Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). When the discrepancies between the radar reflectivity Ze derived from 2D stereo probe (2D-S) in situ measurements and Ze measured by the CloudSat radar are less than 10 dBZe , the flight mean ratios of the retrieved IWC to the IWC estimated from in situ data are 1.12, 1.59, and 1.02, respectively for 2C-ICE, DARDAR, and 2B-CWC-RVOD. For re , the flight mean ratios are 1.05, 1.18, and 1.61, respectively. For σ, the flight mean ratios for 2C-ICE, DARDAR, and CALIPSO are 1.03, 1.42, and 0.97, respectively. The CloudSat 2C-ICE and DARDAR retrieval products are typically in close agreement. However, the use of parameterized radar signals in ice cloud volumes that are below the detection threshold of the CloudSat radar in the 2C-ICE algorithm provides an extra constraint that leads to slightly better agreement with in situ data. The differences in assumed mass–size and area–size relations between CloudSat 2C-ICE and DARDAR also contribute to some subtle difference between the datasets: re from the 2B-CWC-RVOD dataset is biased more than the other retrieval products and in situ measurements by about 40%. A slight low (negative) bias in CALIPSO σ may be due to 5-km averaging in situations in which the cirrus layers have significant horizontal gradients in σ.

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Zhien Wang
,
Kenneth Sassen
,
David N. Whiteman
, and
Belay B. Demoz

Abstract

Mixed-phase clouds are still poorly understood, though studies have indicated that their parameterization in general circulation models is critical for climate studies. Most of the knowledge of mixed-phase clouds has been gained from in situ measurements, but reliable remote sensing algorithms to study mixed-phase clouds extensively are lacking. A combined active and passive remote sensing approach for studying supercooled altocumulus with ice virga, using multiple remote sensor observations, is presented. Precipitating altocumulus clouds are a common type of mixed-phase clouds, and their easily identifiable structure provides a simple scenario to study mixed-phase clouds. First, ice virga is treated as an independent ice cloud, and an existing lidar–radar algorithm to retrieve ice water content and general effective size profiles is applied. Then, a new iterative approach is used to retrieve supercooled water cloud properties by minimizing the difference between atmospheric emitted radiance interferometer (AERI)–observed radiances and radiances, calculated using the discrete-ordinate radiative transfer model at 12 selected wavelengths. Case studies demonstrate the capabilities of this approach in retrieving radiatively important microphysical properties to characterize this type of mixed-phase cloud. The good agreement between visible optical depths derived from lidar measurement and those estimated from retrieved liquid water path and effective radius provides a closure test for the accuracy of mainly AERI-based supercooled water cloud retrieval.

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Kenneth Sassen
,
Jennifer M. Comstock
,
Zhien Wang
, and
Gerald G. Mace

Since October 1987, the University of Utah Facility for Atmospheric Remote Sensing (FARS) has been applied to the probing of the atmosphere, concentrating on the study of high-level clouds. Regular FARS measurements, which currently total ~3000 h of ruby lidar polarization data, have been directed toward basic cloud research, remote sensing techniques development, and to improving satellite cloud property retrieval methods and GCM predictions by providing climatologically representative cloud datasets and parameterizations. Although the initial studies involved mainly the ruby lidar, the facility has steadily evolved to include a range of visible, infrared, and microwave passive remote sensors, and state-of-the-art, high-resolution dual-wavelength scanning lidar and W-band Doppler radar systems. All three active systems display polarization diversity. In this paper are reviewed the specifications of FARS instrumentation and the research programs to which they have been applied. Four multiple remote sensor case studies of various cloud systems are presented to illustrate the research capabilities. Like a handful of similar sites elsewhere, such research centers dedicated to extended time observation programs have great potential for contributing to atmospheric monitoring and climate research.

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Dana Mueller
,
Bart Geerts
,
Zhien Wang
,
Min Deng
, and
Coltin Grasmick

Abstract

This study documents the evolution of an impressive, largely undular bore triggered by an MCS-generated density current on 20 June 2015, observed as part of the Plains Elevated Convection at Night (PECAN) experiment. The University of Wyoming King Air with profiling nadir- and zenith-viewing lidars sampled the south-bound bore from the time the first bore wave emerged from the nocturnal convective cold pool and where updrafts over 10 m s−1 and turbulence in the wave’s wake were encountered, through the early dissipative stage in which the leading wave began to lose amplitude and speed. Through most of the bore’s life cycle, its second wave had a higher or equal amplitude relative to the leading wave. Striking roll clouds formed in wave crests and wave energy was detected to about 5 km AGL. The upstream environment indicates a negative Scorer parameter region due to flow reversal at midlevels, providing a wave trapping mechanism. The observed bore strength of 2.4–2.9 and speed of 15–16 m s−1 agree well with values predicted from hydraulic theory. Surface and profiling measurements collected later in the bore’s life cycle, just after sunrise, indicate a transition to a soliton.

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Guo Lin
,
Coltin Grasmick
,
Bart Geerts
,
Zhien Wang
, and
Min Deng

Abstract

This observational study documents the consequences of a collision between two converging shallow atmospheric boundaries over the central Great Plains on the evening of 7 June 2015. This study uses data from a profiling airborne Raman lidar [the compact Raman lidar (CRL)] and other airborne and ground-based data collected during the Plains Elevated Convection at Night (PECAN) field campaign to investigate the collision between a weak cold front and the outflow from an MCS. The collision between these boundaries led to the lofting of high-CAPE, low-CIN air, resulting in deep convection, as well as an undular bore. Both boundaries behaved as density currents prior to collision. Because the MCS outflow boundary was denser and less deep than the cold-frontal air mass, the bore propagated over the latter. This bore was tracked by the CRL for about 3 h as it traveled north over the shallow cold-frontal surface and evolved into a soliton. This case study is unique by using the high temporal and spatial resolution of airborne Raman lidar measurements to describe the thermodynamic structure of interacting boundaries and a resulting bore.

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Kenneth Sassen
,
Zhien Wang
,
Vitaly I. Khvorostyanov
,
Graeme L. Stephens
, and
Angela Bennedetti

Abstract

A series of cirrus cloud simulations performed using a model with explicit cloud microphysics is applied to testing ice water content retrieval algorithms based on millimeter-wave radar reflectivity measurements. The simulated ice particle size spectra over a 12-h growth/dissipation life cycle are converted to equivalent radar reflectivity factors Z e and visible optical extinction coefficients σ, which are used as a test dataset to intercompare the results of various algorithms. This approach shows that radar Z e -only approaches suffer from significant problems related to basic temperature-dependent cirrus cloud processes, although most algorithms work well under limited conditions (presumably similar to those of the empirical datasets from which each was derived). However, when lidar or radiometric measurements of σ or cloud optical depth are used to constrain the radar data, excellent agreement with the modeled contents can be achieved under the conditions simulated. Implications for the satellite-based active remote sensing of cirrus clouds are discussed. In addition to showing the utility of sophisticated cloud-resolving models for testing remote sensing algorithms, the results of the simulations for cloud-top temperatures of −50°, −60°, and −70°C illustrate some fundamental properties of cirrus clouds that are regulated by the adiabatic process.

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