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Nadia Smith, W. Paul Menzel, Elisabeth Weisz, Andrew K. Heidinger, and Bryan A. Baum

Abstract

To overcome the complexities associated with combining or comparing multisensor data, a statistical gridding algorithm is introduced for projecting data from their unique instrument domain to a uniform space–time domain. The algorithm has two components: 1) a spatial gridding phase in which geophysical properties are filtered on the basis of a set of criteria (e.g., time of day or viewing angle) and then aggregated into nearest-neighbor clusters as defined by equal-angle grid cells and 2) a temporal gridding phase in which daily statistics are calculated per grid cell from which longer time-aggregate statistics are derived. The sensitivity of the gridding algorithm is demonstrated using a month (1–31 August 2009) of level 2 Aqua/Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-top pressure (CTP) retrievals as an example. Algorithm sensitivity is tested for grid size, number of days in the definition of a time average, viewing angle, and minimum number of observations per grid cell per day. The average CTP for high-level clouds from a number of different polar-orbiting instruments are compared on a 1° × 1° global grid. With the data projected onto a single grid, differences in CTP retrieval algorithms are highlighted. The authors conclude that this gridding algorithm greatly facilitates the intercomparison of CTP (or any other geophysical parameter) and algorithms in a dynamic environment. Its simplicity lends transparency to understanding the behavior of a given parameter and makes it useful for both research and operational use.

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Benjamin H. Cole, Ping Yang, Bryan A. Baum, Jerome Riedi, Laurent C.-Labonnote, Francois Thieuleux, and Steven Platnick

Abstract

Insufficient knowledge of the habit distribution and the degree of surface roughness of ice crystals within ice clouds is a source of uncertainty in the forward light scattering and radiative transfer simulations of ice clouds used in downstream applications. The Moderate Resolution Imaging Spectroradiometer (MODIS) collection-5 ice microphysical model presumes a mixture of various ice crystal shapes with smooth facets, except for the compact aggregate of columns for which a severely rough condition is assumed. When compared with Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) polarized reflection data, simulations of polarized reflectance using smooth particles show a poor fit to the measurements, whereas very rough-faceted particles provide an improved fit to the polarized reflectance. In this study a new microphysical model based on a mixture of nine different ice crystal habits with severely roughened facets is developed. Simulated polarized reflectance using the new ice habit distribution is calculated using a vector adding–doubling radiative transfer model, and the simulations closely agree with the polarized reflectance observed by PARASOL. The new general habit mixture is also tested using a spherical albedo differences analysis, and surface roughening is found to improve the consistency of multiangular observations. These results are consistent with previous studies that have used polarized reflection data. It is suggested that an ice model incorporating an ensemble of different habits with severely roughened surfaces would potentially be an adequate choice for global ice cloud retrievals.

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Chenxi Wang, Ping Yang, Bryan A. Baum, Steven Platnick, Andrew K. Heidinger, Yongxiang Hu, and Robert E. Holz

Abstract

A computationally efficient radiative transfer model (RTM) is developed for the inference of ice cloud optical thickness and effective particle size from satellite-based infrared (IR) measurements and is aimed at potential use in operational cloud-property retrievals from multispectral satellite imagery. The RTM employs precomputed lookup tables to simulate the top-of-the-atmosphere (TOA) radiances (or brightness temperatures) at 8.5-, 11-, and 12-μm bands. For the clear-sky atmosphere, the optical thickness of each atmospheric layer resulting from gaseous absorption is derived from the correlated-k-distribution method. The cloud reflectance, transmittance, emissivity, and effective temperature are precomputed using the Discrete Ordinate Radiative Transfer model (DISORT). For an atmosphere containing a semitransparent ice cloud layer with a visible optical thickness τ smaller than 5, the TOA brightness temperature differences (BTDs) between the fast model and the more rigorous DISORT results are less than 0.1 K, whereas the BTDs are less than 0.01 K if τ is larger than 10. With the proposed RTM, the cloud optical and microphysical properties are retrieved from collocated observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) in conjunction with the Modern Era Retrospective-Analysis for Research and Applications (MERRA) data. Comparisons between the retrieved ice cloud properties (optical thickness and effective particle size) based on the present IR fast model and those from the Aqua/MODIS operational collection-5 cloud products indicate that the IR retrievals are smaller. A comparison between the IR-retrieved ice water path (IWP) and CALIOP-retrieved IWP shows robust agreement over most of the IWP range.

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Gang Hong, Ping Yang, Bo-Cai Gao, Bryan A. Baum, Yong X. Hu, Michael D. King, and Steven Platnick

Abstract

This study surveys the optical and microphysical properties of high (ice) clouds over the Tropics (30°S–30°N) over a 3-yr period from September 2002 through August 2005. The analyses are based on the gridded level-3 cloud products derived from the measurements acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard both the NASA Earth Observing System Terra and Aqua platforms. The present analysis is based on the MODIS collection-4 data products. The cloud products provide daily, weekly, and monthly mean cloud fraction, cloud optical thickness, cloud effective radius, cloud-top temperature, cloud-top pressure, and cloud effective emissivity, which is defined as the product of cloud emittance and cloud fraction. This study is focused on high-level ice clouds. The MODIS-derived high clouds are classified as cirriform and deep convective clouds using the International Satellite Cloud Climatology Project (ISCCP) classification scheme. Cirriform clouds make up more than 80% of the total high clouds, whereas deep convective clouds account for less than 20% of the total high clouds. High clouds are prevalent over the intertropical convergence zone (ITCZ), the South Pacific convergence zone (SPCZ), tropical Africa, the Indian Ocean, tropical America, and South America. Moreover, land–ocean, morning–afternoon, and summer–winter variations of high cloud properties are also observed.

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Shaima L. Nasiri, Bryan A. Baum, Andrew J. Heymsfield, Ping Yang, Michael R. Poellot, David P. Kratz, and Yongxiang Hu

Abstract

Detailed in situ data from cirrus clouds have been collected during dedicated field campaigns, but the use of the size and habit distribution data has been lagging in the development of more realistic cirrus scattering models. In this study, the authors examine the use of in situ cirrus data collected during three field campaigns to develop more realistic midlatitude cirrus microphysical models. Data are used from the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE)-I (1986) and FIRE-II (1991) campaigns and from a recent Atmospheric Radiation Measurement (ARM) Program campaign held in March–April of 2000. The microphysical models are based on measured vertical distributions of both particle size and particle habit and are used to develop new scattering models for a suite of moderate-resolution imaging spectoradiometer (MODIS) bands spanning visible, near-infrared, and infrared wavelengths. The sensitivity of the resulting scattering properties to the underlying assumptions of the assumed particle size and habit distributions are examined. It is found that the near-infrared bands are sensitive not only to the discretization of the size distribution but also to the assumed habit distribution. In addition, the results indicate that the effective diameter calculated from a given size distribution tends to be sensitive to the number of size bins that are used to discretize the data and also to the ice-crystal habit distribution.

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Bryan A. Baum, Ping Yang, Andrew J. Heymsfield, Steven Platnick, Michael D. King, Y-X. Hu, and Sarah T. Bedka

Abstract

This study examines the development of bulk single-scattering properties of ice clouds, including single-scattering albedo, asymmetry factor, and phase function, for a set of 1117 particle size distributions obtained from analysis of the First International Satellite Cloud Climatology Project Regional Experiment (FIRE)-I, FIRE-II, Atmospheric Radiation Measurement Program intensive observation period, Tropical Rainfall Measuring Mission Kwajalein Experiment (KWAJEX), and the Cirrus Regional Study of Tropical Anvils and Cirrus Layers (CRYSTAL) Florida Area Cirrus Experiment (FACE) data. The primary focus is to develop band-averaged models appropriate for use by the Moderate Resolution Imaging Spectroradiometer (MODIS) imager on the Earth Observing System Terra and Aqua platforms, specifically for bands located at wavelengths of 0.65, 1.64, 2.13, and 3.75 μm. The results indicate that there are substantial differences in the bulk scattering properties of ice clouds formed in areas of deep convection and those that exist in areas of much lower updraft velocities. Band-averaged bulk scattering property results obtained from a particle-size-dependent mixture of ice crystal habits are compared with those obtained assuming only solid hexagonal columns. The single-scattering albedo is lower for hexagonal columns than for a habit mixture for the 1.64-, 2.13-, and 3.75-μm bands, with the differences increasing with wavelength. In contrast, the asymmetry factors obtained from the habit mixture and only the solid hexagonal column are most different at 0.65 μm, with the differences decreasing as wavelength increases. At 3.75 μm, the asymmetry factor results from the two habit assumptions are almost indistinguishable. The asymmetry factor, single-scattering albedo, and scattering phase functions are also compared with the MODIS version-1 (V1) models. Differences between the current and V1 models can be traced to the microphysical models and specifically to the number of both the smallest and the largest particles assumed in the size distributions.

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Guanglin Tang, Ping Yang, George W. Kattawar, Xianglei Huang, Eli J. Mlawer, Bryan A. Baum, and Michael D. King

Abstract

Cloud longwave scattering is generally neglected in general circulation models (GCMs), but it plays a significant and highly uncertain role in the atmospheric energy budget as demonstrated in recent studies. To reduce the errors caused by neglecting cloud longwave scattering, two new radiance adjustment methods are developed that retain the computational efficiency of broadband radiative transfer simulations. In particular, two existing scaling methods and the two new adjustment methods are implemented in the Rapid Radiative Transfer Model (RRTM). The results are then compared with those based on the Discrete Ordinate Radiative Transfer model (DISORT) that explicitly accounts for multiple scattering by clouds. The two scaling methods are shown to improve the accuracy of radiative transfer simulations for optically thin clouds but not effectively for optically thick clouds. However, the adjustment methods reduce computational errors over a wide range, from optically thin to thick clouds. With the adjustment methods, the errors resulting from neglecting cloud longwave scattering are reduced to less than 2 W m−2 for the upward irradiance at the top of the atmosphere and less than 0.5 W m−2 for the surface downward irradiance. The adjustment schemes prove to be more accurate and efficient than a four-stream approximation that explicitly accounts for multiple scattering. The neglect of cloud longwave scattering results in an underestimate of the surface downward irradiance (cooling effect), but the errors are almost eliminated by the adjustment methods (warming effect).

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Bryan A. Baum, Ping Yang, Andrew J. Heymsfield, Carl G. Schmitt, Yu Xie, Aaron Bansemer, Yong-Xiang Hu, and Zhibo Zhang

Abstract

This study summarizes recent improvements in the development of bulk scattering/absorption models at solar wavelengths. The approach combines microphysical measurements from various field campaigns with single-scattering properties for nine habits including droxtals, plates, solid/hollow columns, solid/hollow bullet rosettes, and several types of aggregates. Microphysical measurements are incorporated from a number of recent field campaigns in both the Northern and Southern Hemisphere. A set of 12 815 particle size distributions is used for which T cld ≤ −40°C. The ice water content in the microphysical data spans six orders of magnitude. For evaluation, a library of ice-particle single-scattering properties is employed for 101 wavelengths between 0.4 and 2.24 μm. The library includes the full phase matrix as well as properties for smooth, moderately roughened, and severely roughened particles. Habit mixtures are developed for generalized cirrus, midlatitude cirrus, and deep tropical convection. The single-scattering properties are integrated over particle size and wavelength using an assumed habit mixture to develop bulk scattering and absorption properties. In comparison with global Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) data, models built with severely roughened particles compare best for all habit mixtures. The assumption of smooth particles provided the largest departure from CALIOP measurements. The use of roughened rather than smooth particles to infer optical thickness and effective diameter from satellite imagery such as the Moderate Resolution Imaging Spectroradiometer (MODIS) will result in a decrease in optical thickness and an increase in particle size.

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Chenxi Wang, Ping Yang, Steven Platnick, Andrew K. Heidinger, Bryan A. Baum, Thomas Greenwald, Zhibo Zhang, and Robert E. Holz

Abstract

A computationally efficient high-spectral-resolution cloudy-sky radiative transfer model (HRTM) in the thermal infrared region (700–1300 cm−1, 0.1 cm−1 spectral resolution) is advanced for simulating the upwelling radiance at the top of atmosphere and for retrieving cloud properties. A precomputed transmittance database is generated for simulating the absorption contributed by up to seven major atmospheric absorptive gases (H2O, CO2, O3, O2, CH4, CO, and N2O) by using a rigorous line-by-line radiative transfer model (LBLRTM). Both the line absorption of individual gases and continuum absorption are included in the database. A high-spectral-resolution ice particle bulk scattering properties database is employed to simulate the radiation transfer within a vertically nonisothermal ice cloud layer. Inherent to HRTM are sensor spectral response functions that couple with high-spectral-resolution measurements in the thermal infrared regions from instruments such as the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer. When compared with the LBLRTM and the discrete ordinates radiative transfer model (DISORT), the root-mean-square error of HRTM-simulated single-layer cloud brightness temperatures in the thermal infrared window region is generally smaller than 0.2 K. An ice cloud optical property retrieval scheme is developed using collocated AIRS and Moderate Resolution Imaging Spectroradiometer (MODIS) data. A retrieval method is proposed to take advantage of the high-spectral-resolution instrument. On the basis of the forward model and retrieval method, a case study is presented for the simultaneous retrieval of ice cloud optical thickness τ and effective particle size D eff that includes a cloud-top-altitude self-adjustment approach to improve consistency with simulations.

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Ping Yang, Lei Bi, Bryan A. Baum, Kuo-Nan Liou, George W. Kattawar, Michael I. Mishchenko, and Benjamin Cole

Abstract

A data library is developed containing the scattering, absorption, and polarization properties of ice particles in the spectral range from 0.2 to 100 μm. The properties are computed based on a combination of the Amsterdam discrete dipole approximation (ADDA), the T-matrix method, and the improved geometric optics method (IGOM). The electromagnetic edge effect is incorporated into the extinction and absorption efficiencies computed from the IGOM. A full set of single-scattering properties is provided by considering three-dimensional random orientations for 11 ice crystal habits: droxtals, prolate spheroids, oblate spheroids, solid and hollow columns, compact aggregates composed of eight solid columns, hexagonal plates, small spatial aggregates composed of 5 plates, large spatial aggregates composed of 10 plates, and solid and hollow bullet rosettes. The maximum dimension of each habit ranges from 2 to 10 000 μm in 189 discrete sizes. For each ice crystal habit, three surface roughness conditions (i.e., smooth, moderately roughened, and severely roughened) are considered to account for the surface texture of large particles in the IGOM applicable domain. The data library contains the extinction efficiency, single-scattering albedo, asymmetry parameter, six independent nonzero elements of the phase matrix (P 11, P 12, P 22, P 33, P 43, and P 44), particle projected area, and particle volume to provide the basic single-scattering properties for remote sensing applications and radiative transfer simulations involving ice clouds. Furthermore, a comparison of satellite observations and theoretical simulations for the polarization characteristics of ice clouds demonstrates that ice cloud optical models assuming severely roughened ice crystals significantly outperform their counterparts assuming smooth ice crystals.

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