Presentation + Paper
3 October 2017 SI-traceable top-of-the-atmosphere lunar irradiance: potential tie-points to the output of the ROLO model
Author Affiliations +
Abstract
The United States Geological Survey (USGS) has developed an empirical model, known as the Robotic Lunar Observatory (ROLO) Model, that predicts the reflectance of the Moon for any Sun-sensor-Moon configuration over the spectral range from 350 nm to 2500 nm. The lunar irradiance can be predicted from the modeled lunar reflectance using a spectrum of the incident solar irradiance. While extremely successful as a relative exo-atmospheric calibration target, the ROLO Model is not SI-traceable and has estimated uncertainties too large for the Moon to be used as an absolute celestial calibration target. In this work, two recent absolute, low uncertainty, SI-traceable top-of-the-atmosphere (TOA) lunar irradiances, measured over the spectral range from 380 nm to 1040 nm, at lunar phase angles of 6.6° and 16.9° , are used as tie-points to the output of the ROLO Model. Combined with empirically derived phase and libration corrections to the output of the ROLO Model and uncertainty estimates in those corrections, the measurements enable development of a corrected TOA lunar irradiance model and its uncertainty budget for phase angles between ±80° and libration angles from 7° to 51° . The uncertainties in the empirically corrected output from the ROLO model are approximately 1 % from 440 nm to 865 nm and increase to almost 3 % at 412 nm. The dominant components in the uncertainty budget are the uncertainty in the absolute TOA lunar irradiance and the uncertainty in the fit to the phase correction from the output of the ROLO model.
Conference Presentation
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Steven W. Brown, Robert E. Eplee Jr., and Xiaoxiong Xiong "SI-traceable top-of-the-atmosphere lunar irradiance: potential tie-points to the output of the ROLO model", Proc. SPIE 10402, Earth Observing Systems XXII, 1040229 (3 October 2017); https://doi.org/10.1117/12.2274064
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Cited by 1 scholarly publication.
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KEYWORDS
Atmospheric modeling

Data modeling

Remote sensing

Satellites

Sensor calibration

Calibration

Sensors

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