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  • Author or Editor: Zhien Wang x
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Zhien Wang
and
Kenneth Sassen

Abstract

A retrieval algorithm is described to estimate vertical profiles of cirrus-cloud ice water content (IWC) and general effective size D ge from combined lidar and radar measurements. In the algorithm, the lidar extinction coefficient σ is parameterized as σ = IWC[a 0 + (a 1/D ge)] and water equivalent radar reflectivity factor Z e is parameterized as Z e = C′(IWC/ρ i ) D b ge , where a 0, a 1, C′, and b are constants based on the assumption of a modified gamma size distribution and hexagonal ice crystals. A comparison of retrieved results from a cirrus-cloud case study with aircraft in situ measurements indicates that the algorithm can provide reliable cirrus cloud microphysical properties. A technique to estimate ice water path and layer-mean D ge is also developed using the optical depth and mean radar reflectivity factor of the cloud layer.

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Zhien Wang
and
Kenneth Sassen

Abstract

Apparent depletion of ozone in a cold (∼0°C), continental stratus cloud system was observed during in situ data collection on 30 April 1994 at the Department of Energy Clouds and Radiation Test Bed site in northern Oklahoma. Analyses of the aircraft data show a significant negative correlation between ozone concentration and liquid water content (LWC) in this cloud. Although droplets of pure water should not significantly affect ozone concentrations, water clouds can potentially perturb ozone through a number of processes, including radiative effects and aqueous-phase reactions in impure cloud droplets. A simple diagnostic model that takes account of cloud effects on the vertical ozone distribution in the boundary layer was constructed to interpret the field data. The results of multifactor regression analysis indicate that aqueous-phase chemistry contributes predominantly to the negative correlation. A depletion of ozone as a function of LWC of about −6.1 ppbv (g m−3)−1 was found in this particular stratus. In this case, the average in-cloud reduction of ozone is ∼6% for an average LWC of ∼0.3 g m−3 and ozone mixing ratio of ∼31 ppbv outside the cloud layer, which is in reasonable agreement with recent model results.

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Zhien Wang
and
Kenneth Sassen

Abstract

A cloud detection algorithm based on ground-based remote sensors has been developed that can differentiate among various atmospheric targets such as ice and water clouds, virga, precipitation, and aerosol layers. Standard cloud type and macrophysical properties are identified by combining polarization lidar, millimeter-wave radar, infrared radiometer, and dual-channel microwave radiometer measurements. These algorithms are applied to measurements collected during 1998 from the Atmospheric Radiation Measurement Program Cloud and Radiation Test Bed site in north-central Oklahoma. The statistical properties of clouds for this year are presented, illustrating how extended-time remote sensing datasets can be converted to cloud properties of concern to climate research.

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Sujan Khanal
and
Zhien Wang

Abstract

Remote sensing and in situ measurements made during the Colorado Airborne Multiphase Cloud Study, 2010–2011 (CAMPS) with instruments aboard the University of Wyoming King Air aircraft are used to evaluate lidar–radar-retrieved cloud ice water content (IWC). The collocated remote sensing and in situ measurements provide a unique dataset for evaluation studies. Near-flight-level IWC retrieval is compared with an in situ probe: the Colorado closed-path tunable diode laser hygrometer (CLH). Statistical analysis showed that the mean radar–lidar IWC is within 26% of the mean in situ measurements for pure ice clouds and within 9% for liquid-topped mixed-phase clouds. Considering their different measurement techniques and different sample volumes, the comparison shows a statistically good agreement and is close to the measurement uncertainty of the CLH, which is around 20%. It is shown that ice cloud microphysics including ice crystal shape and orientation has a significant impact on IWC retrievals. These results indicate that the vertical profile of the retrieved lidar–radar IWC can be reliably combined with the flight-level measurements made by the in situ probes to provide a more complete picture of the cloud microphysics.

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David Atlas
,
Zhien Wang
, and
David P. Duda

Abstract

This work is two pronged, discussing 1) the morphology of contrails and their transition to cirrus uncinus, and 2) their microphysical and radiative properties. It is based upon the fortuitous occurrence of an unusual set of essentially parallel contrails and the unanticipated availability of nearly simultaneous observations by photography, satellite, automated ground-based lidar, and a newly available database of aircraft flight tracks. The contrails, oriented from the northeast to southwest, are carried to the southeast with a component of the wind so that they are spread from the northwest to southeast. Convective turrets form along each contrail to form the cirrus uncinus with fallstreaks of ice crystals that are oriented essentially normal to the contrail length. Each contrail is observed sequentially by the lidar and tracked backward to the time and position of the originating aircraft track with the appropriate component of the wind. The correlation coefficient between predicted and actual time of arrival at the lidar is 0.99, so that one may identify both visually and satellite-observed contrails exactly. Contrails generated earlier in the westernmost flight corridor occasionally arrive simultaneously with those formed later closer to the lidar to produce broader cirrus fallstreaks and overlapping contrails on the satellite image. The minimum age of a contrail is >2 h and corresponds to the longest time of travel to the lidar. The lag between the initial formation of the contrail and its first detectability by Moderate-Resolution Imaging Spectroradiometer (MODIS) is ≈33 min, thus accounting for the distance between the aircraft track and the first detectable contrail by satellite. The lidar also provides particle fall speeds and estimated sizes, optical extinction coefficients, optical thickness (τ = 0.35), and ice water path (IWP = 8.1 g m−2). These values correspond to the lower range of those found for midlatitude cirrus by Heymsfield et al. The ice water per meter of length along the cloud lines is 103–104 times that released by typical jet aircraft. The synthesis of these findings with those of prior investigators provides confidence in the present results. Various authors find that contrail-generated cirrus such as reported here contribute to net regional warming.

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Andrew J. Heymsfield
,
Zhien Wang
, and
Sergey Matrosov

Abstract

Airborne radar reflectivity measurements at frequencies of 9.6 and 94 GHz, with collocated, in situ particle size distribution and ice water content measurements from the Cirrus Regional Study of Tropical Anvils and Cirrus Layers (CRYSTAL) Florida Area Cirrus Experiment (FACE) in Florida in July 2002, offer one of the first opportunities to evaluate and improve algorithms for retrieving ice water content from single-wavelength spaceborne radar measurements. Both ice water content and radar reflectivity depend on the distribution of particle mass with size. It is demonstrated that single, power-law, mass dimensional relationships are unable to adequately account for the dominating contribution of small particles at lower reflectivities and large particles at higher reflectivities. To circumvent the need for multiple, or complex, mass dimensional relationships, analytic expressions that use particle ensemble mean ice particle densities that are derived from the coincident microphysical and radar observations are developed. These expressions, together with more than 5000 CRYSTAL FACE size distributions, are used to develop radar reflectivity–ice water content relationships for the two radar wavelengths that appear to provide improvements over earlier relationships, at least for convectively generated stratiform ice clouds.

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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
,
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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Andrew J. Heymsfield
,
Alain Protat
,
Dominique Bouniol
,
Richard T. Austin
,
Robin J. Hogan
,
Julien Delanoë
,
Hajime Okamoto
,
Kaori Sato
,
Gerd-Jan van Zadelhoff
,
David P. Donovan
, and
Zhien Wang

Abstract

Vertical profiles of ice water content (IWC) can now be derived globally from spaceborne cloud satellite radar (CloudSat) data. Integrating these data with Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data may further increase accuracy. Evaluations of the accuracy of IWC retrieved from radar alone and together with other measurements are now essential. A forward model employing aircraft Lagrangian spiral descents through mid- and low-latitude ice clouds is used to estimate profiles of what a lidar and conventional and Doppler radar would sense. Radar reflectivity Ze and Doppler fall speed at multiple wavelengths and extinction in visible wavelengths were derived from particle size distributions and shape data, constrained by IWC that were measured directly in most instances. These data were provided to eight teams that together cover 10 retrieval methods. Almost 3400 vertically distributed points from 19 clouds were used. Approximate cloud optical depths ranged from below 1 to more than 50. The teams returned retrieval IWC profiles that were evaluated in seven different ways to identify the amount and sources of errors. The mean (median) ratio of the retrieved-to-measured IWC was 1.15 (1.03) ± 0.66 for all teams, 1.08 (1.00) ± 0.60 for those employing a lidar–radar approach, and 1.27 (1.12) ± 0.78 for the standard CloudSat radar–visible optical depth algorithm for Ze > −28 dBZe . The ratios for the groups employing the lidar–radar approach and the radar–visible optical depth algorithm may be lower by as much as 25% because of uncertainties in the extinction in small ice particles provided to the groups. Retrievals from future spaceborne radar using reflectivity–Doppler fall speeds show considerable promise. A lidar–radar approach, as applied to measurements from CALIPSO and CloudSat, is useful only in a narrow range of ice water paths (IWP) (40 < IWP < 100 g m−2). Because of the use of the Rayleigh approximation at high reflectivities in some of the algorithms and differences in the way nonspherical particles and Mie effects are considered, IWC retrievals in regions of radar reflectivity at 94 GHz exceeding about 5 dBZe are subject to uncertainties of ±50%.

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