NASA Logo

NTRS

NTRS - NASA Technical Reports Server

Back to Results
Development of Multi-Sensor Global Cloud and Radiance Composites for DSCOVR EPIC Imager with Subpixel DefinitionThe 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). EPIC delivers adequate spatial resolution imagery but only in shortwave bands (317-780 nm), while NISTAR measures the top-of-atmosphere (TOA) whole-disk radiance in shortwave and longwave broadband windows. Accurate calculation of albedo and outgoing longwave flux requires a high-resolution scene identification such as the radiance observations and cloud properties retrievals from low earth orbit (LEO, including NASA Terra and Aqua MODIS, Suomi-NPP VIIRS, and NOAA AVHRR) and geosynchronous (GEO, including GOES east and west, METEOSAT, INSAT-3D, MTSAT-2, and Himawari-8) satellite imagers. The cloud properties are derived using the Clouds and the Earth's Radiant Energy System (CERES) mission Cloud Subsystem group algorithms. These properties have to be co-located with EPIC pixels to provide the scene identification and to select anisotropic directional models (ADMs), which are then used to adjust the NISTAR-measured radiance and subsequently obtain the global daytime shortwave and longwave fluxes. This work presents an algorithm for optimal merging of selected radiance and cloud property parameters derived from multiple satellite imagers to obtain seamless global hourly composites at 5-km resolution. Selection of satellite data for each 5-km pixel is based on an aggregated rating that incorporates five parameters: nominal satellite resolution, pixel time relative to the EPIC time, viewing zenith angle, distance from day/night terminator, and probability of sun glint. To provide a smoother transition in the merged output, in regions where candidate pixel data from two satellite sources have comparable aggregated rating, the selection decision is defined by the cumulative function of the normal distribution so that abrupt changes in the visual appearance of the composite data are avoided. Higher spatial accuracy in the composite product is achieved by using the inverse mapping with gradient search during reprojection and bicubic interpolation for pixel resampling.
Document ID
20180000855
Acquisition Source
Langley Research Center
Document Type
Presentation
Authors
Khlopenkov, Konstantin V.
(Science Systems and Applications, Inc. Hampton, VA, United States)
Duda, David
(Science Systems and Applications, Inc. Hampton, VA, United States)
Thieman, Mandana
(Science Systems and Applications, Inc. Hampton, VA, United States)
Sun-mack, Szedung
(Science Systems and Applications, Inc. Hampton, VA, United States)
Su, Wenying
(NASA Langley Research Center Hampton, VA, United States)
Minnis, Patrick
(NASA Langley Research Center Hampton, VA, United States)
Bedka, Kristopher
(NASA Langley Research Center Hampton, VA, United States)
Date Acquired
January 31, 2018
Publication Date
December 11, 2017
Subject Category
Meteorology And Climatology
Optics
Report/Patent Number
NF1676L-27843
Meeting Information
Meeting: Fall American Geophysical Union (AGU) Meeting
Location: New Orleans, LA
Country: United States
Start Date: December 11, 2017
End Date: December 15, 2017
Sponsors: American Geophysical Union
Funding Number(s)
WBS: WBS 239702.04.32.01.06
Distribution Limits
Public
Copyright
Public Use Permitted.
No Preview Available