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Development of multi-sensor global cloud and radiance composites for earth radiation budget monitoring from DSCOVR
Author(s): Konstantin Khlopenkov; David Duda; Mandana Thieman; Patrick Minnis; Wenying Su; Kristopher Bedka
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Paper Abstract

The Deep Space Climate Observatory (DSCOVR) enables analysis of the daytime Earth radiation budget via the onboard Earth Polychromatic Imaging Camera (EPIC) and National Institute of Standards and Technology Advanced Radiometer (NISTAR). Radiance observations and cloud property retrievals from low earth orbit and geostationary satellite imagers have to be co-located with EPIC pixels to provide scene identification in order to select anisotropic directional models needed to calculate shortwave and longwave fluxes. A new algorithm is proposed for optimal merging of selected radiances and cloud properties derived from multiple satellite imagers to obtain seamless global hourly composites at 5-km resolution. An aggregated rating is employed to incorporate several factors and to select the best observation at the time nearest to the EPIC measurement. Spatial accuracy is improved using inverse mapping with gradient search during reprojection and bicubic interpolation for pixel resampling. The composite data are subsequently remapped into EPIC-view domain by convolving composite pixels with the EPIC point spread function defined with a half-pixel accuracy. PSF-weighted average radiances and cloud properties are computed separately for each cloud phase. The algorithm has demonstrated contiguous global coverage for any requested time of day with a temporal lag of under 2 hours in over 95% of the globe.

Paper Details

Date Published: 2 October 2017
PDF: 13 pages
Proc. SPIE 10424, Remote Sensing of Clouds and the Atmosphere XXII, 104240K (2 October 2017); doi: 10.1117/12.2278645
Show Author Affiliations
Konstantin Khlopenkov, Science Systems and Applications, Inc. (United States)
David Duda, Science Systems and Applications, Inc. (United States)
Mandana Thieman, Science Systems and Applications, Inc. (United States)
Patrick Minnis, Science Systems and Applications, Inc. (United States)
Wenying Su, NASA Langley Research Ctr. (United States)
Kristopher Bedka, NASA Langley Research Ctr. (United States)


Published in SPIE Proceedings Vol. 10424:
Remote Sensing of Clouds and the Atmosphere XXII
Adolfo Comerón; Evgueni I. Kassianov; Klaus Schäfer, Editor(s)

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