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Modeling thermal emissive bands radiometric calibration impact with application to AVHRR
Author(s) -
Chang Tiejun,
Wu Xiangqian,
Weng Fuzhong
Publication year - 2017
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2016jd025601
Subject(s) - radiance , remote sensing , calibration , radiometric calibration , brightness temperature , advanced very high resolution radiometer , weighting , radiometer , environmental science , radiometry , brightness , optics , physics , statistics , mathematics , geology , satellite , astronomy , acoustics
A novel analytical model of the calibration error impact on the Earth radiance measurement from thermal emissive bands of sensors is developed. The goal is to assess the impact of calibration errors, to evaluate those errors and to perform correction. This model is applied in the correction of bias in Advanced Very High Resolution Radiometer (AVHRR) channels 4 and 5 observed from the intercomparison with Infrared Atmospheric Sounding Interferometer measurements. A two‐step regression is used to separate the effects of calibration radiance errors from calibration coefficient errors. In the first step, the calibration radiance error, primarily due to internal calibration target (ICT) imperfections and temperature measurement error, is evaluated using the bias from selected Earth scenes with brightness temperatures close to the ICT temperature. The effects from the ICT imperfections and temperature measurement errors are analyzed collectively. The resulting estimation of the calibration radiance error is 0.30% for channel 4 and 0.33% for channel 5. After correcting the Earth scene radiance for these effects, the errors in the offset and nonlinear coefficient of instrument response are evaluated through the second step of the regression. A weighting function is used to account for the nonuniformity in the data distribution over the Earth radiance range. After the evaluation of the errors, removal of their effects can be achieved either through corrections of the calibration coefficients or correction of the measured radiance. The results are useful for the improvement of the AVHRR IR channel calibration algorithm. This model and two‐step regression approach can also be applied to other similar broadband thermal infrared radiometric sensors.