A two-habit model for the microphysical and optical properties of ice clouds

Abstract. To provide a better representation of natural ice clouds, a novel ice cloud model is developed by assuming an ice cloud to consist of an ensemble of hexagonal columns and 20-element aggregates with specific habit fractions at each particle size bin. The microphysical and optical properties of this two-habit model (THM) are compared with both laboratory and in situ measurements, and its performance in downstream satellite remote sensing applications is assessed. The ice water contents and median mass diameters calculated based on the THM closely agree with in situ measurements made during 11 field campaigns. In this study, the scattering, absorption, and polarization properties of ice crystals are calculated with a combination of the invariant imbedding T matrix, pseudo-spectral time domain, and improved geometric-optics methods over an entire practical range of particle sizes. The phase functions, calculated based on the THM, show close agreement with counterparts from laboratory and in situ measurements and from satellite-based retrievals. When the THM is applied to the retrievals of cloud microphysical and optical properties from MODIS (the Moderate Resolution Imaging Spectroradiometer) observations, excellent spectral consistency is achieved; specifically, the retrieved cloud optical thicknesses based on the visible/near infrared bands and the thermal infrared bands agree quite well. Furthermore, a comparison between the polarized reflectivities observed by the PARASOL satellite and from theoretical simulations illustrates that the THM can be used to represent ice cloud polarization properties.

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A two-habit model for the microphysical and optical properties of ice clouds

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-14-19545-2014 ◽

2014 ◽

Vol 14 (13) ◽

pp. 19545-19586 ◽

Cited By ~ 2

Author(s):

C. Liu ◽

P. Yang ◽

P. Minnis ◽

N. Loeb ◽

S. Kato ◽

...

Keyword(s):

Optical Properties ◽

Near Infrared ◽

Cloud Model ◽

In Situ Measurements ◽

Ice Clouds ◽

Ice Cloud ◽

Sensing Applications ◽

Phase Functions ◽

Ice Water

Abstract. To provide a better representation of natural ice clouds, a novel ice cloud model containing two particle habits is developed. The microphysical and optical properties of the two-habit model (THM) are compared with both laboratory and in situ measurements, and its performance in downstream satellite remote sensing applications is tested. The THM assumes an ice cloud to be an ensemble of hexagonal columns and twenty-element aggregates, and to have specific habit fractions at each particle size. The ice water contents and median mass diameters calculated based on the THM closely agree with in situ measurements made during 11 field campaigns. In this study, the scattering, absorption, and polarization properties of ice crystals are calculated with a combination of the invariant imbedding T-matrix, pseudo-spectral time domain, and improved geometric-optics methods over an entire range of particle sizes. The phase functions, calculated based on the THM, show excellent agreement with counterparts from laboratory and in situ measurements and from satellite retrievals. For downstream applications in the retrieval of cloud microphysical and optical properties from MODIS observations, the THM presents excellent spectral consistency; specifically, the retrieved cloud optical thicknesses based on the visible/near infrared bands and the thermal infrared bands agree quite well. Furthermore, a comparison between the polarized reflectivities observed by the PARASOL satellite and from theoretical simulations illustrates that the THM can be used to represent ice cloud polarization properties.

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An Inverse Problem Approach for the Retrieval of Ice Particle Mass from In Situ Measurements

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-17-0013.1 ◽

2017 ◽

Vol 34 (11) ◽

pp. 2457-2473 ◽

Cited By ~ 2

Author(s):

Pierre Coutris ◽

Delphine Leroy ◽

Emmanuel Fontaine ◽

Alfons Schwarzenboeck

Keyword(s):

Inverse Problem ◽

Particle Size ◽

Power Law ◽

In Situ Measurements ◽

Ice Cloud ◽

Size Dependent ◽

Microphysical Properties ◽

Ice Water Content ◽

Ice Water

AbstractMass–dimensional relationships have been published for decades to characterize the microphysical properties of ice cloud particles. Classical retrieval methods employ a simplifying assumption that restricts the form of the mass–dimensional relationship to a power law, an assumption that was proved inaccurate in recent studies. In this paper, a nonstandard approach that leverages optimal use of in situ measurements to remove the power-law constraint is presented. A model formulated as a linear system of equations relating ice particle mass to particle size distribution (PSD) and ice water content (IWC) is established, and the mass retrieval process consists of solving the inverse problem with numerical optimization algorithms. First, the method is applied to a synthetic crystal dataset in order to validate the selected algorithms and to tune the regularization strategy. Subsequently, the method is applied to in situ measurements collected during the High Altitude Ice Crystal–High Ice Water Content field campaigns. Preliminary results confirm the method is efficient at retrieving size-dependent masses from real data despite a significant amount of noise: the IWC values calculated from the retrieved masses are in good agreement with reference IWC measurements (errors on the order of 10%–15%). The possibility to retrieve ice particle size–dependent masses combined with the flexibility left for sorting datasets as a function of parameters such as cloud temperature, cloud type, or convective index makes this approach well suited for studying ice cloud microphysical properties.

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Glint Removal Assessment to Estimate the Remote Sensing Reflectance in Inland Waters with Widely Differing Optical Properties

Remote Sensing ◽

10.3390/rs10101655 ◽

2018 ◽

Vol 10 (10) ◽

pp. 1655 ◽

Cited By ~ 4

Author(s):

Nariane Bernardo ◽

Enner Alcântara ◽

Fernanda Watanabe ◽

Thanan Rodrigues ◽

Alisson Carmo ◽

...

Keyword(s):

Remote Sensing ◽

Optical Properties ◽

Wind Speed ◽

In Situ Measurements ◽

Colored Dissolved Organic Matter ◽

The Third ◽

Sensing Applications ◽

Remote Sensing Reflectance ◽

Remote Sensing Applications

The quality control of remote sensing reflectance (Rrs) is a challenging task in remote sensing applications, mainly in the retrieval of accurate in situ measurements carried out in optically complex aquatic systems. One of the main challenges is related to glint effect into the in situ measurements. Our study evaluates four different methods to reduce the glint effect from the Rrs spectra collected in cascade reservoirs with widely differing optical properties. The first (i) method adopts a constant coefficient for skylight correction (ρ) for any geometry viewing of in situ measurements and wind speed lower than 5 m·s−1; (ii) the second uses a look-up-table with variable ρ values accordingly to viewing geometry acquisition and wind speed; (iii) the third method is based on hyperspectral optimization to produce a spectral glint correction, and (iv) computes ρ as a function of wind speed. The glint effect corrected Rrs spectra were assessed using HydroLight simulations. The results showed that using the glint correction with spectral ρ achieved the lowest errors, however, in a Colored Dissolved Organic Matter (CDOM) dominated environment with no remarkable chlorophyll-a concentrations, the best method was the second. Besides, the results with spectral glint correction reduced almost 30% of errors.

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Evaluation of Several A-Train Ice Cloud Retrieval Products with In Situ Measurements Collected during the SPARTICUS Campaign

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-12-054.1 ◽

2013 ◽

Vol 52 (4) ◽

pp. 1014-1030 ◽

Cited By ~ 89

Author(s):

Min Deng ◽

Gerald G. Mace ◽

Zhien Wang ◽

R. Paul Lawson

Keyword(s):

Water Content ◽

Detection Threshold ◽

In Situ Measurements ◽

Subtle Difference ◽

Ice Cloud ◽

In Situ Data ◽

Cloud Water Content ◽

Mass Size ◽

Ice Water

AbstractIn 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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Bulk Scattering Properties for the Remote Sensing of Ice Clouds. Part I: Microphysical Data and Models

Journal of Applied Meteorology ◽

10.1175/jam2308.1 ◽

2005 ◽

Vol 44 (12) ◽

pp. 1885-1895 ◽

Cited By ~ 196

Author(s):

Bryan A. Baum ◽

Andrew J. Heymsfield ◽

Ping Yang ◽

Sarah T. Bedka

Keyword(s):

Remote Sensing ◽

Particle Size ◽

In Situ Measurements ◽

Two Dimensional ◽

Cloud Particle ◽

Ice Clouds ◽

Sensing Applications ◽

Airborne Sampling ◽

Bulk Scattering

Abstract This study reports on the use of in situ data obtained in midlatitude and tropical ice clouds from airborne sampling probes and balloon-borne replicators as the basis for the development of bulk scattering models for use in satellite remote sensing applications. Airborne sampling instrumentation includes the two-dimensional cloud (2D-C), two-dimensional precipitation (2D-P), high-volume precipitation spectrometer (HVPS), cloud particle imager (CPI), and NCAR video ice particle sampler (VIPS) probes. Herein the development of a comprehensive set of microphysical models based on in situ measurements of particle size distributions (PSDs) is discussed. Two parameters are developed and examined: ice water content (IWC) and median mass diameter Dm. Comparisons are provided between the IWC and Dm values derived from in situ measurements obtained during a series of field campaigns held in the midlatitude and tropical regions and those calculated from a set of modeled ice particles used for light-scattering calculations. The ice particle types considered in this study include droxtals, hexagonal plates, solid columns, hollow columns, aggregates, and 3D bullet rosettes. It is shown that no single habit accurately replicates the derived IWC and Dm values, but a mixture of habits can significantly improve the comparison of these bulk microphysical properties. In addition, the relationship between Dm and the effective particle size Deff, defined as 1.5 times the ratio of ice particle volume to projected area for a given PSD, is investigated. Based on these results, a subset of microphysical models is chosen as the basis for the development of ice cloud bulk scattering models in Part II of this study.

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Objective Assessment of the Information Content of Visible and Infrared Radiance Measurements for Cloud Microphysical Property Retrievals over the Global Oceans. Part II: Ice Clouds

Journal of Applied Meteorology and Climatology ◽

10.1175/jam2327.1 ◽

2006 ◽

Vol 45 (1) ◽

pp. 42-62 ◽

Cited By ~ 44

Author(s):

Steven J. Cooper ◽

Tristan S. L’Ecuyer ◽

Philip Gabriel ◽

Anthony J. Baran ◽

Graeme L. Stephens

Keyword(s):

Information Content ◽

Near Infrared ◽

Objective Assessment ◽

Ice Clouds ◽

Ice Cloud ◽

Cloud Properties ◽

Microphysical Property ◽

Retrieval Scheme ◽

Retrieval Problem ◽

Moderate Resolution Imaging Spectroradiometer

Abstract Cirrus clouds play an important yet poorly determined role in the earth’s climate system and its various feedback mechanisms. As such, a significant amount of work has been accomplished both in understanding the physics of the ice clouds and in using this knowledge to estimate global distributions of ice cloud properties from satellite-based instruments. This work seeks to build on these past efforts by offering a reexamination of the ice cloud retrieval problem in context of recent advancements in the understanding of optical properties for a variety of realistic ice crystal shapes. In this work, the formal information content analysis outlined in Part I is used to objectively select the optimal combination of measurements for an ice cloud microphysical property retrieval scheme given a realistic assessment of the uncertainties that govern the ice cloud retrieval problem. Although this analysis is for a theoretical retrieval combining simulated measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS) with the CloudSat Cloud Profiling Radar (CPR) above an ocean surface, the general methodology is applicable to any instrument package. Channel selection via information content is determined through a realistic characterization of not only the sensitivity of top-of-the-atmosphere radiances to desired retrieval parameters but also to the uncertainties resulting from both the measurements themselves and from the forward model assumptions used in relating observational and retrieval space. Results suggest that the channels that maximize retrieval information are strongly dependent upon the state of the atmosphere, meaning that no combination of two or three channels will always ensure an accurate retrieval. Because of the complexities of this state-dependent nature and the need for a consistent retrieval scheme for an operational retrieval, a five-channel retrieval approach consisting of a combination of error-weighted visible, near-infrared, and infrared channels is suggested. Such an approach ensures high information content regardless of cloud and atmospheric properties through use of the inherent sensitivities in each of these spectral regions.

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