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The ultimate remote sensing benefits of the high resolution Infrared radiance spectrometers will be realized with
their geostationary satellite implementation in the form of imaging spectrometers. This will enable dynamic
features of the atmosphere's thermodynamic fields and pollutant and greenhouse gas constituents to be observed
for revolutionary improvements in weather forecasts and more accurate air quality and climate predictions. As
an important step toward realizing this application objective, the Geostationary Imaging Fourier Transform
Spectrometer (GIFTS) Engineering Demonstration Unit (EDU) was successfully developed under the NASA
New Millennium Program, 2000-2006. The GIFTS-EDU instrument employs three focal plane arrays (FPAs),
which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral
bands. The GIFTS calibration is achieved using internal blackbody calibration references at ambient (260
K) and hot (286 K) temperatures. In this paper, we introduce a refined calibration technique that utilizes
Principle Component (PC) analysis to compensate for instrument distortions and artifacts, therefore, enhancing
the absolute calibration accuracy. This method is applied to data collected during the GIFTS Ground Based
Measurement (GBM) experiment, together with simultaneous observations by the accurately calibrated AERI
(Atmospheric Emitted Radiance Interferometer), both simultaneously zenith viewing the sky through the same
external scene mirror at ten-minute intervals throughout a cloudless day at Logan Utah on September 13, 2006.
The accurately calibrated GIFTS radiances are produced using the first four PC scores in the GIFTS-AERI
regression model. Temperature and moisture profiles retrieved from the PC-calibrated GIFTS radiances are
verified against radiosonde measurements collected throughout the GIFTS sky measurement period. Using the
GIFTS GBM calibration model, we compute the calibrated radiances from data collected during the moon
tracking and viewing experiment events. From which, we derive the lunar surface temperature and emissivity
associated with the moon viewing measurements.
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