
Proceedings Paper
Results from recent vacuum testing of an on-orbit absolute radiance standard (OARS) intended for the next generation of infrared remote sensing instrumentsFormat | Member Price | Non-Member Price |
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Paper Abstract
Future NASA infrared remote sensing missions will require better absolute measurement accuracies than now available,
and will most certainly rely on the emerging capability to fly SI traceable standards that provide irrefutable absolute
measurement accuracy. To establish a CLARRREO-type climate benchmark, instrumentation will need to measure
spectrally resolved infrared radiances with an absolute brightness temperature error of better than 0.1 K, verified onorbit.
This will require an independent high-emissivity (<0.999) verification blackbody with an emissivity uncertainty of
better than 0.06%, an absolute temperature uncertainty of better than 0.045K (3 sigma), and the capability of operation
over a wide range of (Earth scene) temperatures. Key elements of an On-Orbit Absolute Radiance Standard (OARS)
meeting these stringent requirements have been demonstrated in the laboratory at the University of Wisconsin and have
undergone further refinement under funding from NASA’s Earth Science and Technology Office, culminating in an end-to-end demonstration under vacuum with a prototype climate benchmark instrument. We present the new technologies that underlie the OARS, and the results of testing that demonstrate the required accuracy is being met in a vacuum
environment. The underlying technologies include: on-orbit absolute temperature calibration using the transient melt
signatures of small quantities (<1g) of reference materials (gallium, water, and mercury) imbedded in the blackbody
cavity; and on-orbit cavity spectral emissivity measurement using a carefully baffled heated halo placed in front of the
OARS blackbody viewed by the infrared spectrometer system. Emissivity is calculated from the radiance measured
from the blackbody combined with the knowledge of key temperatures and radiometric view factors.
Paper Details
Date Published: 18 November 2014
PDF: 10 pages
Proc. SPIE 9263, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications V, 926314 (18 November 2014); doi: 10.1117/12.2069338
Published in SPIE Proceedings Vol. 9263:
Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications V
Allen M. Larar; Makoto Suzuki; Jianyu Wang, Editor(s)
PDF: 10 pages
Proc. SPIE 9263, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications V, 926314 (18 November 2014); doi: 10.1117/12.2069338
Show Author Affiliations
Fred A. Best, Univ. of Wisconsin-Madison (United States)
Douglas P. Adler, Univ. of Wisconsin-Madison (United States)
Claire Pettersen, Univ. of Wisconsin-Madison (United States)
Henry E. Revercomb, Univ. of Wisconsin-Madison (United States)
Douglas P. Adler, Univ. of Wisconsin-Madison (United States)
Claire Pettersen, Univ. of Wisconsin-Madison (United States)
Henry E. Revercomb, Univ. of Wisconsin-Madison (United States)
P. Jonathan Gero, Univ. of Wisconsin-Madison (United States)
Joseph K. Taylor, Univ. of Wisconsin-Madison (United States)
Robert O. Knuteson, Univ. of Wisconsin-Madison (United States)
Joseph K. Taylor, Univ. of Wisconsin-Madison (United States)
Robert O. Knuteson, Univ. of Wisconsin-Madison (United States)
Published in SPIE Proceedings Vol. 9263:
Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques and Applications V
Allen M. Larar; Makoto Suzuki; Jianyu Wang, Editor(s)
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