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Si-traceable top-of-the-atmosphere lunar irradiance: Potential tie-points to the output of the ROLO Model

Published

Author(s)

Steven W. Brown, Robert E. Eplee, Xiaoxiong Xiong

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 6.6o and 16.9o, 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 ±80o and libration angles from 7o to 51o. 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.
Proceedings Title
Proceedings of SPIE
Volume
10402
Conference Dates
August 6-11, 2017
Conference Location
San Diego, CA

Keywords

calibration, radiometry, spectrograph, Moon, ROLO

Citation

Brown, S. , Eplee, R. and Xiong, X. (2017), Si-traceable top-of-the-atmosphere lunar irradiance: Potential tie-points to the output of the ROLO Model, Proceedings of SPIE, San Diego, CA, [online], https://doi.org/10.1117/12.2274064 (Accessed July 6, 2022)
Created October 3, 2017, Updated January 27, 2020