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  • Author or Editor: Steven Platnick x
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Steven Platnick and Juan M. Fontenla

Abstract

Since the launch of the first Advanced Very High Resolution Radiometer (AVHRR) instrument aboard the Television and Infrared Observational Satellite (TIROS-N), measurements in the 3.7-μm atmospheric window have been exploited for use in cloud detection and screening, cloud thermodynamic phase and surface snow/ice discrimination, and quantitative cloud particle size retrievals. The utility of the band has led to the incorporation of similar channels on a number of existing satellite imagers and future operational imagers. Daytime observations in the band include both reflected solar and thermal emission energy. Since 3.7-μm channels are calibrated to a radiance scale (via onboard blackbodies), knowledge of the top-of-atmosphere solar irradiance in the spectral region is required to infer reflectance. Despite the ubiquity of 3.7-μm channels, absolute solar spectral irradiance data come from either a single measurement campaign (Thekaekara et al.) or synthetic spectra. In the current study, the historical 3.7-μm band spectral irradiance datasets are compared with the recent semiempirical solar model of the quiet sun by Fontenla et al. The model has expected uncertainties of about 2% in the 3.7-μm spectral region. The channel-averaged spectral irradiances using the observations reported by Thekaekara et al. are found to be 3.2%–4.1% greater than those derived from the Fontenla et al. model for Moderate Resolution Imaging Spectroradiometer (MODIS) and AVHRR instrument bandpasses; the Kurucz spectrum, as included in the Moderate Spectral Resolution Atmospheric Transmittance (MODTRAN4) distribution, gives channel-averaged irradiances 1.2%–1.5% smaller than the Fontenla model. For the MODIS instrument, these solar irradiance uncertainties result in cloud microphysical retrieval uncertainties that are comparable to other fundamental reflectance error sources.

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Gerald G. Mace, Yuying Zhang, Steven Platnick, Michael D. King, Patrick Minnis, and Ping Yang

Abstract

The Moderate Resolution Imaging Spectroradiometer (MODIS) on board the NASA Terra satellite has been collecting global data since March 2000 and the one on the Aqua satellite since June 2002. In this paper, cirrus cloud properties derived from ground-based remote sensing data are compared with similar cloud properties derived from MODIS data on Terra. To improve the space–time correlation between the satellite and ground-based observations, data from a wind profiler are used to define the cloud advective streamline along which the comparisons are made. In this paper, approximately two dozen cases of cirrus are examined and a statistical approach to the comparison that relaxes the requirement that clouds occur over the ground-based instruments during the overpass instant is explored. The statistical comparison includes 168 cloudy MODIS overpasses of the Southern Great Plains (SGP) region and approximately 300 h of ground-based cirrus observations. The physical and radiative properties of cloud layers are derived from MODIS data separately by the MODIS Atmospheres Team and the Clouds and the Earth’s Radiant Energy System (CERES) Science Team using multiwavelength reflected solar and emitted thermal radiation measurements. Using two ground-based cloud property retrieval algorithms and the two MODIS algorithms, a positive correlation in the effective particle size, the optical thickness, the ice water path, and the cloud-top pressure between the various methods is shown, although sometimes there are significant biases. Classifying the clouds by optical thickness, it is demonstrated that the regionally averaged cloud properties derived from MODIS are similar to those diagnosed from the ground. Because of a conservative approach toward identifying thin cirrus pixels over this region, the area-averaged cloud properties derived from the MODIS Atmospheres MOD06 product tend to be biased slightly toward the optically thicker pixels. This bias tendency has implications for model validation and parameterization development applied to thin cirrus retrieved over SGP-like land surfaces. A persistent bias is also found in the derived cloud tops of thin cirrus with both satellite algorithms reporting cloud top several hundred meters less than that reported by the cloud radar. Overall, however, it is concluded that the MODIS retrieval algorithms characterize with reasonable accuracy the properties of thin cirrus over this region.

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Eric G. Moody, Michael D. King, Crystal B. Schaaf, and Steven Platnick

Abstract

Five years (2000–04) of spatially complete snow-free land surface albedo data have been produced using high-quality-flagged diffuse bihemispherical (white sky) and direct-beam directional hemispherical (black sky) land surface albedo data derived from observations taken by the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument aboard the NASA Terra satellite platform (MOD43B3, collection 4). In addition, a spatially complete snow-free aggregate albedo climatological product was generated. These spatially complete products were prepared using an ecosystem-dependent temporal interpolation technique that retrieves missing data within 3%–8% error. These datasets have already been integrated into research and operational projects that require snow-free land surface albedo. As such, this paper provides details regarding the spatial and temporal distribution of the filled versus the original MOD43B3 data. The paper also explores the intra- and interannual variation in the 5-yr data record and provides a qualitative comparison of zonal averages and annual cycles of the filled versus the original MOD43B3 data. The analyses emphasize the data’s inter- and intraannual variation and show that the filled data exhibit large- and small-scale phenological behavior that is qualitatively similar to that of the original MOD43B3. These analyses thereby serve to showcase the inherent spectral, spatial, and temporal variability in the MOD43B3 data as well as the ability of the fill technique to preserve these unique regional and pixel-level phenological characteristics.

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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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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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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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Galina Wind, Steven Platnick, Michael D. King, Paul A. Hubanks, Michael J. Pavolonis, Andrew K. Heidinger, Ping Yang, and Bryan A. Baum

Abstract

Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the NASA Earth Observing System (EOS) Terra and Aqua spacecraft includes an algorithm for detecting multilayered clouds in daytime. The main objective of this algorithm is to detect multilayered cloud scenes, specifically optically thin ice cloud overlying a lower-level water cloud, that present difficulties for retrieving cloud effective radius using single-layer plane-parallel cloud models. The algorithm uses the MODIS 0.94-μm water vapor band along with CO2 bands to obtain two above-cloud precipitable water retrievals, the difference of which, in conjunction with additional tests, provides a map of where multilayered clouds might potentially exist. The presence of a multilayered cloud results in a large difference in retrievals of above-cloud properties between the CO2 and the 0.94-μm methods. In this paper the MODIS multilayered cloud algorithm is described, results of using the algorithm over example scenes are shown, and global statistics for multilayered clouds as observed by MODIS are discussed. A theoretical study of the algorithm behavior for simulated multilayered clouds is also given. Results are compared to two other comparable passive imager methods. A set of standard cloudy atmospheric profiles developed during the course of this investigation is also presented. The results lead to the conclusion that the MODIS multilayer cloud detection algorithm has some skill in identifying multilayered clouds with different thermodynamic phases.

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