Accessibility navigation


An improved algorithm for generating global window brightness temperatures from multiple satellite infrared imagery

Hodges, K. I., Chappell, D. W., Robinson, G. J. and Yang, G. ORCID: https://orcid.org/0000-0001-7450-3477 (2000) An improved algorithm for generating global window brightness temperatures from multiple satellite infrared imagery. Journal of Atmospheric and Oceanic Technology, 17 (10). pp. 1296-1312. ISSN 1520-0426

[img]
Preview
Text - Published Version
· Please see our End User Agreement before downloading.

2MB

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1175/1520-0426(2000)017<1296:AIAFGG>2.0.CO;2

Abstract/Summary

An improved algorithm for the generation of gridded window brightness temperatures is presented. The primary data source is the International Satellite Cloud Climatology Project, level B3 data, covering the period from July 1983 to the present. The algorithm rakes window brightness, temperatures from multiple satellites, both geostationary and polar orbiting, which have already been navigated and normalized radiometrically to the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiometer, and generates 3-hourly global images on a 0.5 degrees by 0.5 degrees latitude-longitude grid. The gridding uses a hierarchical scheme based on spherical kernel estimators. As part of the gridding procedure, the geostationary data are corrected for limb effects using a simple empirical correction to the radiances, from which the corrected temperatures are computed. This is in addition to the application of satellite zenith angle weighting to downweight limb pixels in preference to nearer-nadir pixels. The polar orbiter data are windowed on the target time with temporal weighting to account for the noncontemporaneous nature of the data. Large regions of missing data are interpolated from adjacent processed images using a form of motion compensated interpolation based on the estimation of motion vectors using an hierarchical block matching scheme. Examples are shown of the various stages in the process. Also shown are examples of the usefulness of this type of data in GCM validation.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:169
Publisher:American Meteorological Society

Downloads

Downloads per month over past year

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation