Exploiting the inherent redundancy in hyperspectral observations, Principle Component Analysis (PCA) is a simple yet very powerful tool not only for noise filtering and lossy compression, but also for the characterization of sensor noise and other variable artifacts using Earth scene data. Our approach for dependent set PCA of radiance spectra from the Atmospheric Infrared Sounder (AIRS) on NASA Aqua is presented. Aspects of the analyses include 1) estimation of NEDT and comparisons to values derived from on-board blackbodies, 2) estimation of the signal dependence of NEDN, 3) estimation of the spectrally correlated component of NEDT, 4) investigation of non-Gaussian noise behavior, and 5) inspection of individual PCs. The results are generally consistent with results obtained pre-launch and on-orbit using blackbody and space view data. Specific findings include: 1) PCA estimates of AIRS spectrally random and spectrally correlated NEDN compare well with estimates computed from blackbody and space views, 2) the signal dependence of AIRS NEDN is accurately parameterized in terms of scene radiance, 3) examination of the reconstruction error allows non-Gaussian phenomenon such as popping to be characterized, and 4) inspection of the PCs and filtered spectra is a powerful technique for diagnosing variable artifacts in hyperspectral data.
The ability to accurately validate high spectral resolution infrared radiance measurements from space using comparisons
with a high altitude aircraft spectrometer has been successfully demonstrated (Tobin, et al. 2006). A comparison
technique which accounts for the different viewing geometries and spectral characteristics of the two sensors was
introduced, and accurate comparisons were made for AIRS channels throughout the infrared spectrum. Resulting
brightness temperature differences were found to be 0.2 K or less for most channels. Continuing work on additional
cases has shown some channels to have brightness temperature differences larger than 0.2 K. Atmospheric contribution
from above the aircraft is a suspected factor in producing the larger differences. The contribution of upper atmosphere
HNO3 and O3 are studied as contributors to the brightness temperature differences. Improved forward model
calculations are used to understand and compensate for the above aircraft atmospheric contribution. Results of this
effort to understand the observed temperature differences are presented. The methodology demonstrated for the NASA
AIRS instrument is expected to be used in the validation of the CrIS sensor radiances from the operational
NPP/NPOESS platforms and the IASI sensor radiances from the METOP platforms.
Exploiting the redundancy in high spectral resolution observations, dependent set Principle Component Analysis (PCA)
is a simple yet very powerful tool not only for noise filtering and lossy compression, but also for the characterization of
sensor noise and other variable artifacts using Earth scene data. Our approach for dependent set PCA of AIRS Earth
scene data is presented. Aspects of the analyses include 1) estimation of NEDT using PCA and comparisons to values
derived from on-board blackbodies, 2) estimation of the scene dependence of NEDN, 3) estimation of the spectrally
correlated component of NEDT and comparison to pre-launch analyses using blackbody views, 4) investigation of non-
Gaussian noise behavior, and 5) inspection of individual PCs. The results of the PCA analyses are generally consistent
with results obtained pre-launch and on-orbit using blackbody and/or space view data. Specific findings include: 1)
PCA estimates of AIRS spectrally random and spectrally correlated NEDN compare well with estimates computed from
on-board blackbody and space views, 2) the signal dependence of AIRS NEDN is accurately parameterized in terms of
the scene radiance, 3) examination of the reconstruction error allows non-Gaussian phenomenon such as popping to be
characterized, and 4) inspection of the PCs and individual PC filtered radiance spectra is a powerful technique for
diagnosing low level artifacts in hyperspectral data.
KEYWORDS: Interferometers, Mirrors, Calibration, Black bodies, Sensors, Satellites, Digital signal processing, Data storage, Fluctuations and noise, Acoustics
A comparison of S-HIS instrument performance on various airborne platforms, and during ground characterization is presented. Specific emphasis is placed on instrument improvements, 1998 to present day, and the engineering lessons learned. Also discussed is the ability to accurately validate high spectral resolution IR radiance measurements from space using comparisons with aircraft spectrometer observations. Aircraft comparisons of this type provide a mechanism for periodically verifying expected absolute calibration of spacecraft instruments with instrumentation for which the calibration can be carefully maintained on the ground. This capability is especially valuable for achieving the long-term consistency and accuracy of climate observations, including those from the NASA EOS spacecrafts (Terra, Aqua, Aura).
This study will present results of an effort to validate the accuracy of the cloud-cleared radiance products of the Atmospheric Infrared Sounder (AIRS) using observations from a variety of aircraft based sensors. The AIRS cloud-clear radiances are a product of the Level 2 ground processing software developed by the NASA AIRS science team. The cloud-clear radiance represents an estimate of the infrared upwelling spectrum at the top of the atmosphere for a cloud free atmosphere. This study concentrates on observations collected during the Pacific THORpex experiment, conducted in February-March 2003. NASA ER-2 aircraft based observations from the Scanning-High Resolution Interferometer Sounder (S-HIS) and the MODIS Airborne Simulator (MAS) are used in this validation effort.
Development in the mid 80s of the High-resolution Interferometer Sounder (HIS) for the high altitude NASA ER2 aircraft demonstrated the capability for advanced atmospheric temperature and water vapor sounding and set the stage for new satellite instruments that are now becoming a reality [AIRS (2002), CrIS (2006), IASI (2006), GIFTS (2005/6)]. Follow-on developments at the University of Wisconsin-Madison that employ interferometry for a wide range of Earth observations include the ground-based Atmospheric Emitted Radiance Interferometer (AERI) and the Scanning HIS aircraft instrument (S-HIS). The AERI was developed for the US DOE Atmospheric Radiation Measurement (ARM) Program, primarily to provide highly accurate radiance spectra for improving radiative transfer models. The continuously operating AERI soon demonstrated valuable new capabilities for sensing the rapidly changing state of the boundary layer and properties of the surface and clouds. The S-HIS is a smaller version of the original HIS that uses cross-track scanning to enhance spatial coverage. S-HIS and its close cousin, the NPOESS Airborne Sounder Testbed (NAST) operated by NASA Langley, are being used for satellite instrument validation and for atmospheric research. The calibration and noise performance of these and future satellite instruments is key to optimizing their remote sensing products. Recently developed techniques for improving effective radiometric performance by removing noise in post-processing is a primary subject of this paper.
This study presents a new technique for the retrieval of Carbon Monoxide and Methane effective optical depths using upwelling infrared emission spectra from high spectral resolution Fourier Transform Spectrometer (FTS) data. Also presented is a technique for deriving mean column mixing ratios from these effective optical depths. Results are presented from aircraft flights of the Scanning-High-resolution Interferometer Sounder (S-HIS) and the National Polar-orbiting Operational Environmental Satellite System Airborne Sounder Testbed - Interferometer (NAST-I). Case study results are presented from the SAFARI 2000 experiment in Southern from the CLAMS experiment on the mid-Atlantic coast of the United States.
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