Snow/cloud Discrimination

Snow/cloud Discrimination PDF

Author: Francis R. Valovcin

Publisher:

Published: 1976

Total Pages: 24

ISBN-13:

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The main objective of this investigation was to evaluate the usefulness of the data from the S192 Multispectral Scanner aboard Skylab in snow-cloud discrimination. From the available S192 screening films and digital tape data, the reflectance characteristics of snow, ice, and water clouds in different spectral bands from the visible into the near infrared spectral region can be determined. In the visible part of the spectrum, snow, ice, and water clouds appear white. In the near infrared, Band 11 (1.55 to 1.75 micrometers), water clouds are white, ice clouds are gray and snow is black. The ratio of the radiance values in Band 6 (0.68 to 0.76 micrometers to Band 11 (1.55 to 1.75 micrometers appears to provide a method for discriminating between snow cover, ice, and water clouds. (Author).

Snow/cloud Discrimination

Snow/cloud Discrimination PDF

Author: Francis R. Valovcin

Publisher:

Published: 1976

Total Pages: 20

ISBN-13:

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The main objective of this investigation was to evaluate the usefulness of the data from the S192 Multispectral Scanner aboard Skylab in snow-cloud discrimination. From the available S192 screening films and digital tape data, the reflectance characteristics of snow, ice, and water clouds in different spectral bands from the visible into the near infrared spectral region can be determined. In the visible part of the spectrum, snow, ice, and water clouds appear white. In the near infrared, Band 11 (1.55 to 1.75 micrometers), water clouds are white, ice clouds are gray and snow is black. The ratio of the radiance values in Band 6 (0.68 to 0.76 micrometers to Band 11 (1.55 to 1.75 micrometers appears to provide a method for discriminating between snow cover, ice, and water clouds. (Author).

Spectral Radiance of Snow and Clouds in the Near Infrared Spectral Region

Spectral Radiance of Snow and Clouds in the Near Infrared Spectral Region PDF

Author: Francis R. Valovcin

Publisher:

Published: 1978

Total Pages: 56

ISBN-13:

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The near infrared spectral radiance measurements of snow and cirrus and cumulus cloud backgrounds taken by the Air Force Geophysics Laboratory's flying laboratory are evaluated. From the analysis of the 124 specra obtained, the spectral radiances or reflectance characteristics of snow and cirrus and cumulus clouds between 5500 and 7000/cm (1.82-1.43 micrometers were determined. Snow/cloud discrimination can be made by utilizing a sensor in the 5500 to 7000/ cm spectral region. Based on the analysis of these data, certain snow/cloud design parameters were identified; that is, slope of the spectral radiance, absolute spectral and/or total radiance, and the location and value of the maximum spectral radiance for the snow and cirrus and cumulus cloud backgrounds. Finally, specific recommendations are made for an optimal operational snow/cloud discrimination radiometer. (Author).

Automated Satellite Cloud Analysis

Automated Satellite Cloud Analysis PDF

Author: Robert C. Allen (Jr.)

Publisher:

Published: 1987

Total Pages: 114

ISBN-13:

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An algorithm is developed and evaluated for discriminating among clouds, snow cover and clear land. The multispectral technique uses daytime images of AVHRR channels 1 (0.63 microns, 3 (3.7 microns) and 4 (11.0 microns). Reflectance is derived for channel 3 by using the channel 4 emission temperature to estimate and remove the channel 3 thermal emission. Separation of clouds from snow and land is based primarily on this derived channel 3 reflectance. Using this technique, observed reflectance in channel 3 is 2 to 4% for snow, 3 to 10 % for land, 2 to 27 % for ice clouds and 8 to 36 % for liquid clouds. These values overlap for thin cirrus and snow, so the routine than attempts analysis of cirrus based on its different transmissive properties between channels 3 and 4. Six images were analyzed and the total cloud cover was verified against a total of 110 conventional surface observations using the standard categories of clear, scattered, broken and overcast. The routine was quite successful, with the analyzed sky cover being within category for 55% of the stations, one category different for 33%, 2 categories different for 9% and 3 categories for 3% of the stations. A major remaining problem is discrimination between ice clouds and snow cover due to the great similarity of reflective properties of there two surfaces.