Satellite ultraspectral infrared sensors provide key data records essential for weather forecasting and climate change
science. The Suomi National Polar-orbiting Partnership (Soumi NPP) satellite Environmental Data Records (EDRs) are
retrieved from calibrated ultraspectral radiance or Sensor Data Records (SDRs). Understanding the accuracy of retrieved
EDRs is critical. The second Suomi NPP Calibration/Validation field campaign was conducted during March 2015 with
flights over Greenland. The NASA high-altitude ER-2 aircraft carrying ultraspectral interferometer sounders such as the
National Airborne Sounder Testbed-Interferometer (NAST-I) flew under the Suomi NPP satellite that carries the Crosstrack
Infrared Sounder (CrIS) and the Advanced Technology Microwave Sounder (ATMS). Herein we inter-compare the
EDRs produced from different retrieval algorithms employed on these satellite and aircraft campaign data. The available
radiosonde measurements together with the European Centre for Medium-Range Weather Forecasts (ECMWF) analyses
are used to assess atmospheric temperature and moisture retrievals from the aircraft and satellite platforms. Preliminary
results of this experiment under a winter, Arctic environment are presented.
The evolution of satellite measurement systems continues to improve their research and operational impact and is essential for advancing global observations of the Earth’s atmosphere, clouds, and surface. Measurement system and data product validation is required to fully exploit these data for enabling their intended enhancements in weather prediction, climate monitoring capability, and environmental change detection. Airborne field campaigns can play a vital role in such validation and contribute to assessing and improving satellite sensor measurements and associated data products. The NASA LaRC National Airborne Sounder Testbed – Interferometer (NAST-I) was part of the aircraft payload for the two field experiments conducted to address Suomi NPP (SNPP) validation since the satellite’s launch in late 2011: 1) mid-latitude flights based out of Palmdale, CA during May 2013 (SNPP-1), and 2) flights over Greenland during March 2015 while based out of Keflavik, Iceland (SNPP-2). This presentation focuses on radiance analysis from the SNPP airborne field campaigns with a particular emphasis on NAST-I inter-comparisons with the Cross-track Infrared Sounder (CrIS) for challenging cold scene conditions as observed during SNPP-2.
The NASA / JPSS Airborne Sounder Testbed - Interferometer (NAST-I) is a well-proven airborne remote sensing system, which has flown in 19 previous field campaigns aboard the high altitude NASA ER-2, Northrop Grumman / Scaled Composites Proteus, and NASA WB-57 aircraft since initially being flight qualified in 1998. While originally developed to provide experimental observations needed to finalize specifications and test proposed designs and data processing algorithms for the Cross-track Infrared Sounder (CrIS) flying aboard the Suomi National Polar-orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (SNPP) and the Joint Polar Satellite System, JPSS (formerly NPOESS, prior to program restructuring), its unprecedented data quality and system characteristics have contributed to a variety of atmospheric research and measurement validation objectives. This paper will provide a program overview and update, including a summary of measurement system capabilities, with a primary focus on postmission ground testing and characterization performed subsequent to the recently conducted Suomi NPP (SNPP) airborne field campaign.
The NPOESS / NASA Airborne Sounder Testbed - Interferometer (NAST-I) is a well-proven airborne remote sensing
system, which has flown in 18 previous field campaigns aboard the high altitude NASA ER-2, Northrop Grumman /
Scaled Composites Proteus, and NASA WB-57 aircraft since initially being flight qualified in 1998. While originally
developed to provide experimental observations needed to finalize specifications and test proposed designs and data
processing algorithms for the Cross-track Infrared Sounder (CrIS) to fly on the National Polar-orbiting Operational
Environmental Satellite System (NPOESS) Preparatory Project (NPP) and the Joint Polar Satellite System, JPSS
(formerly NPOESS, prior to recent program restructuring), its unprecedented data quality and system characteristics
have contributed to a variety of atmospheric research and measurement validation objectives. This paper will provide a
program overview and update, including a summary of measurement system capabilities, select scientific results, and
recent refurbishment activities.
The National Polar-orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Testbed-
Interferometer (NAST-I) instrument is a high-resolution scanning interferometer that measures emitted thermal radiation
between 3.3 and 18 microns. The NAST-I radiometric calibration is achieved using internal blackbody calibration
references at ambient and hot temperatures. In this paper, we introduce a refined calibration technique that utilizes a
principal component (PC) noise filter to minimize the impact of measurement noise on the calibration of Earth scene
radiance spectra. To test the procedure and estimate the PC filter noise performance, we form dependent and
independent test samples using odd and even sets of blackbody spectra. To determine the optimal number of
eigenvectors, the PC filter algorithm is applied to both dependent and independent blackbody spectra with a varying
number of eigenvectors. The optimal number of PCs is selected so that the total root-mean-square (RMS) error of the
calibrated reference scene blackbody data is minimized. To estimate the filter noise performance, we examine four
different scenarios: apply PC filtering to both dependent and independent datasets, apply PC filtering to dependent
calibration data only, apply PC filtering to independent data only, and no PC filtering. The independent blackbody
radiances are predicted for each case and comparisons are made. The results show significant reduction in noise in the
final calibrated scene radiances with the implementation of the PC filtering algorithm.
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.
Ultra-spectral atmospheric remote sounding has been under development since the late 1970's. It has evolved through a
series of aircraft experiments into the operational space-borne system that we enjoy today. In this paper the background
and evolution of the ultra-spectral remote sounding program is reviewed. Results from airborne and polar satellite ultraspectral
instruments are presented to illustrate the improved atmospheric remote sounding capability provided by these
instruments. Ground-based measurements with the Geostationary Imaging Fourier Transform Spectrometer (GIFTS) are
presented to illustrate the "state of the art" in imaging spectrometry and its potential for greatly improved ultra-spectral
remote sounding from future polar and geostationary satellites.
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 raw GIFTS interferogram measurements are radiometrically and spectrally calibrated to produce radiance
spectra, which are further processed to obtain atmospheric profiles via retrieval algorithms. The radiometric
calibration is achieved using internal blackbody calibration references at ambient (260 K) and hot (286 K)
temperatures. The absolute radiometric performance of the instrument is affected by several factors including
the FPA off-axis effect, detector/readout electronics induced nonlinearity distortions, and fore-optics offsets.
The GIFTS-EDU, being the very first imaging spectrometer to use ultra-high speed electronics to readout
its large area format focal plane array detectors, operating at wavelengths as large as 15 microns, possessed
non-linearity's not easily removable in the initial calibration process. In this paper, we introduce a refined
calibration technique that utilizes Principle Component (PC) analysis to compensate for instrument distortions
and artifacts remaining after the initial radiometric calibration process, thus, further enhance the absolute
calibration accuracy. This method is applied to data collected during an atmospheric measurement experiment
with the GIFTS, 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 PC vectors
of the calibrated radiance spectra are defined from the AERI observations and regression matrices relating the
initial GIFTS radiance PC scores to the AERI radiance PC scores are calculated using the least squares inverse
method. A new set of accurately calibrated GIFTS radiances are produced using the first four PC scores in
the 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.
The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) Sensor Module (SM) Engineering Demonstration
Unit (EDU) is a high resolution spectral imager designed to measure infrared (IR) radiances using a
Fourier transform spectrometer (FTS). The GIFTS 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 raw interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra,
which are further processed to obtain atmospheric profiles via retrieval algorithms. This paper describes the
GIFTS SM EDU Level 1B algorithms involved in the calibration. The GIFTS Level 1B calibration procedures
can be subdivided into four blocks. In the first block, the measured raw interferograms are first corrected for
the detector nonlinearity distortion, followed by the complex filtering and decimation procedure. In the second
block, a phase correction algorithm is applied to the filtered and decimated complex interferograms. The resulting
imaginary part of the spectrum contains only the noise component of the uncorrected spectrum. Additional
random noise reduction can be accomplished by applying a spectral smoothing routine to the phase-corrected
spectrum. The phase correction and spectral smoothing operations are performed on a set of interferogram
scans for both ambient and hot blackbody references. To continue with the calibration, we compute the spectral
responsivity based on the previous results, from which, the calibrated ambient blackbody (ABB), hot blackbody
(HBB), and scene spectra can be obtained. We now can estimate the noise equivalent spectral radiance (NESR)
from the calibrated ABB and HBB spectra. The correction schemes that compensate for the fore-optics offsets
and off-axis effects are also implemented. In the third block, we developed an efficient method of generating
pixel performance assessments. In addition, a random pixel selection scheme is designed based on the pixel
performance evaluation. Finally, in the fourth block, the single pixel algorithms are applied to the entire FPA.
We propose an algorithm for recovering the overlapped harmonic components of a multiplex Fabry-Pérot interferometer (MFPI) spectrum. A potential solution that utilizes the multiresolution properties of the MFPI spectrum is presented. The corrupted harmonic components are detected by comparing consecutive harmonic pairs at the same sampling rate and window length. The overlapped spectral components are adjusted with correction terms that have been determined from the detection stage.
We propose an algorithm for reconstructing nonuniformly sampled interferograms when sampling locations are unknown. An optimization problem with multiple objective and constraint functions is designed based on the spatial and spectral characteristics of the data measurement. This problem is solved using an evolutionary approach, in which potential solutions are competing to be the fittest individual in a simulated natural environment.
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