Search Results

You are looking at 1 - 4 of 4 items for :

  • Author or Editor: Bryan Baum x
  • Journal of Atmospheric and Oceanic Technology x
  • Refine by Access: All Content x
Clear All Modify Search
Bryan A. Baum and Qing Trepte

Abstract

The authors propose a grouped threshold method for scene identification in Advanced Very High Resolution Radiometer imagery that may contain clouds, fire, smoke, or snow. The philosophy of the approach is to build modules that contain groups of spectral threshold tests that are applied concurrently, not sequentially, to each pixel in an image. The purpose of each group of tests is to identify uniquely a specific class in the image, such as smoke. A strength of this approach is that insight into the limits used in the threshold tests may be gained through the use of radiative transfer theory. Methodology and examples are provided for two different scenes, one containing clouds, forest fires, and smoke; and the other containing clouds over snow in the central United States. For both scenes, a limited amount of supporting information is provided by surface observers.

Full access
Shaima L. Nasiri and Bryan A. Baum

Abstract

This study reports on recent progress toward the daytime detection of multilayered clouds in satellite multispectral data, specifically for the case of optically thin cirrus overlying lower-level water clouds. The technique is applied to 200 × 200 pixel arrays of data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and is primarily based on the relationship between the near-infrared reflectance (at either 1.6 or 2.1 μm) and the 11-μm brightness temperature. Additional information used by the algorithm includes the operational MODIS cloud mask and cloud thermodynamic phase as inferred from the 8.5- and 11-μm brightness temperatures. The performance of the algorithm is evaluated for two MODIS case studies, and results are compared to coincident cloud physics lidar (CPL) data obtained from an aircraft platform. In both cases, the multilayered cloud detection algorithm results appear reasonable in comparison with the CPL data. The first case study, from 11 December 2002 during the Terra–Aqua Experiment (TX-2002), also examines the behavior of the algorithm when midlevel or mixed-phase cloud is present. The second case study, from 26 February 2003 during The Observing System Research and Predictability Experiment (THORPEX) campaign, sheds light on the sensitivity of the algorithm to optically thin cirrus. In this case, the algorithm does not detect cirrus with a visible (0.564 μm) optical thickness of less than 0.1 when it overlies a lower-level water cloud.

Full access
Anthony J. Schreiner, Steven A. Ackerman, Bryan A. Baum, and Andrew K. Heidinger

Abstract

A technique using the Geostationary Operational Environmental Satellite (GOES) sounder radiance data has been developed to improve detection of low clouds and fog just after sunrise. The technique is based on a simple difference method using the shortwave (3.7 μm) and longwave (11.0 μm) window bands in the infrared range of the spectrum. The time period just after sunrise is noted for the difficulty in being able to correctly identify low clouds and fog over land. For the GOES sounder cloud product this difficulty is a result of the visible reflectance of the low clouds falling below the “cloud” threshold over land. By requiring the difference between the 3.7- and the 11.0-μm bands to be greater than 5.0 K, successful discrimination of low clouds and fog is found 85% of the time for 21 cases from 14 September 2005 to 6 March 2006 over the GOES-12 sounder domain. For these 21 clear and cloudy cases the solar zenith angle ranged from 87° to 77°; however, the range of solar zenith angles for cloudy cases was from 85° to 77°.

The success rate further improved to 95% (20 out of 21 cases) by including a difference threshold of 5.0 K between the 3.7- and 4.0-μm bands, requiring that the 11.0-μm band be greater than 260 K, and limiting the test to fields of view where the surface elevation is below 999 m. These final three limitations were needed to more successfully deal with cases involving snow cover and dead vegetation. To ensure that only the time period immediately after sunrise is included the solar zenith angle threshold for application of these tests is between 89° and 70°.

Full access
Yongxiang Hu, David Winker, Mark Vaughan, Bing Lin, Ali Omar, Charles Trepte, David Flittner, Ping Yang, Shaima L. Nasiri, Bryan Baum, Robert Holz, Wenbo Sun, Zhaoyan Liu, Zhien Wang, Stuart Young, Knut Stamnes, Jianping Huang, and Ralph Kuehn

Abstract

The current cloud thermodynamic phase discrimination by Cloud-Aerosol Lidar Pathfinder Satellite Observations (CALIPSO) is based on the depolarization of backscattered light measured by its lidar [Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP)]. It assumes that backscattered light from ice crystals is depolarizing, whereas water clouds, being spherical, result in minimal depolarization. However, because of the relationship between the CALIOP field of view (FOV) and the large distance between the satellite and clouds and because of the frequent presence of oriented ice crystals, there is often a weak correlation between measured depolarization and phase, which thereby creates significant uncertainties in the current CALIOP phase retrieval. For water clouds, the CALIOP-measured depolarization can be large because of multiple scattering, whereas horizontally oriented ice particles depolarize only weakly and behave similarly to water clouds. Because of the nonunique depolarization–cloud phase relationship, more constraints are necessary to uniquely determine cloud phase. Based on theoretical and modeling studies, an improved cloud phase determination algorithm has been developed. Instead of depending primarily on layer-integrated depolarization ratios, this algorithm differentiates cloud phases by using the spatial correlation of layer-integrated attenuated backscatter and layer-integrated particulate depolarization ratio. This approach includes a two-step process: 1) use of a simple two-dimensional threshold method to provide a preliminary identification of ice clouds containing randomly oriented particles, ice clouds with horizontally oriented particles, and possible water clouds and 2) application of a spatial coherence analysis technique to separate water clouds from ice clouds containing horizontally oriented ice particles. Other information, such as temperature, color ratio, and vertical variation of depolarization ratio, is also considered. The algorithm works well for both the 0.3° and 3° off-nadir lidar pointing geometry. When the lidar is pointed at 0.3° off nadir, half of the opaque ice clouds and about one-third of all ice clouds have a significant lidar backscatter contribution from specular reflections from horizontally oriented particles. At 3° off nadir, the lidar backscatter signals for roughly 30% of opaque ice clouds and 20% of all observed ice clouds are contaminated by horizontally oriented crystals.

Full access