Paolo Antonelli

Application of Principal Component Analysis to High-Resolution Infrared Measurement Compression and Retrieval

Abstract A simulation study is used to demonstrate the application of principal component analysis to both the compression of, and meteorological parameter retrieval from, high-resolution infrared spectra. The study discusses the fundamental aspects of spectral correlation, distributions, and noise; the correlation between principal components (PCs) and atmospheric-level temperature and water vapor; and how an optimal subset of PCs is selected so a good compression ratio and high retrieval accuracy are obtained. Principal component analysis, principal component compression, and principal component regression under certain conditions are shown to provide 1) nearly full spectral information with little degradation, 2) noise reduction, 3) data compression with a compression ratio of approximately 15, and 4) tolerable loss of accuracy in temperature and water vapor retrieval. The techniques will therefore be valuable tools for data compression and the accurate retrieval of meteorological parameters from new-g...

Inference of ice cloud properties from high spectral resolution infrared observations

The theoretical basis is explored for inferring the microphysical properties of ice clouds from high spectral resolution infrared (IR) observations. Extensive radiative transfer simulations are carried out to address relevant issues. The single-scattering properties of individual ice crystals are computed from state-of-the-art light scattering computational methods and are subsequently averaged for 30 in situ particle size distributions and for four additional analytical Gamma size distributions. The nonsphericity of ice crystals is shown to have a significant impact on the radiative signatures in the IR spectrum. Furthermore, the errors associated with the use of the Henyey-Greenstein phase function can be larger than 1 K in terms of brightness temperature for large particle effective sizes (/spl sim/80 /spl mu/m) at wavenumbers where the scattering of the IR radiation by ice crystals is not negligible. The simulations undertaken in this paper show that the slope of the IR brightness temperature spectrum between 790-960 cm/sup -1/ is sensitive to the effective particle size. Furthermore, a strong sensitivity of the IR brightness temperature to cloud optical thickness is noted within the 1050-1250-cm/sup -1/ region. Based on these spectral features, a technique is presented for the simultaneous retrieval of the visible optical thickness and effective particle size from high spectral resolution IR data for ice clouds. An error analysis shows that the uncertainties of the retrieved optical thickness and effective particle size have a small range of variation. The error for retrieving particle size in conjunction with an uncertainty of 5 K in cloud temperature, or a surface temperature uncertainty of 2.5 K, is less than 15%. The corresponding errors in the uncertainty of optical thickness are within 5% to 20%, depending on the value of cloud optical thickness. The applicability of the present retrieval technique is demonstrated using airborne high-resolution IR measurements obtained during two field campaigns.

An Improvement to the High-Spectral-Resolution CO2-Slicing Cloud-Top Altitude Retrieval

Abstract An improvement to high-spectral-resolution infrared cloud-top altitude retrievals is compared to existing retrieval methods and cloud lidar measurements. The new method, CO2 sorting, determines optimal channel pairs to which the CO2 slicing retrieval will be applied. The new retrieval is applied to aircraft Scanning High-Resolution Interferometer Sounder (S-HIS) measurements. The results are compared to existing passive retrieval methods and coincident Cloud Physics Lidar (CPL) measurements. It is demonstrated that when CO2 sorting is used to select channel pairs for CO2 slicing there is an improvement in the retrieved cloud heights when compared to the CPL for the optically thin clouds (total optical depths less than 1.0). For geometrically thick but tenuous clouds, the infrared retrieved cloud tops underestimated the cloud height, when compared to those of the CPL, by greater than 2.5 km. For these cases the cloud heights retrieved by the S-HIS correlated closely with the level at which the CPL...

EAQUATE: An International Experiment For Hyperspectral Atmospheric Sounding Validation

The international experiment called the European Aqua Thermodynamic Experiment (EAQUATE) was held in September 2004 in Italy and the United Kingdom to validate Aqua satellite Atmospheric Infrared Sounder (AIRS) radiance measurements and derived products with certain groundbased and airborne systems useful for validating hyperspectral satellite sounding observations. A range of flights over land and marine surfaces were conducted to coincide with overpasses of the AIRS instrument on the Earth Observing System Aqua platform. Direct radiance evaluation of AIRS using National Polar-Orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Testbed-Interferometer (NAST-I) and the Scanning High-Resolution Infrared Sounder has shown excellent agreement. Comparisons of level-2 retrievals of temperature and water vapor from AIRS and NAST-I validated against high-quality lidar and dropsonde data show that the 1-K/l-km and 10%/1-km requirements for temperature and water vapor (respectively) are ge...

Minimum Local Emissivity Variance Retrieval of Cloud Altitude and Effective Spectral Emissivity—Simulation and Initial Verification

Abstract This paper describes the theory and application of the minimum local emissivity variance (MLEV) technique for simultaneous retrieval of cloud pressure level and effective spectral emissivity from high-spectral-resolution radiances, for the case of single-layer clouds. This technique, which has become feasible only with the recent development of high-spectral-resolution satellite and airborne instruments, is shown to provide reliable cloud spectral emissivity and pressure level under a wide range of atmospheric conditions. The MLEV algorithm uses a physical approach in which the local variances of spectral cloud emissivity are calculated for a number of assumed or first-guess cloud pressure levels. The optimal solution for the single-layer cloud emissivity spectrum is that having the “minimum local emissivity variance” among the retrieved emissivity spectra associated with different first-guess cloud pressure levels. This is due to the fact that the absorption, reflection, and scattering processes...

Hyperspectral data noise characterization using principle component analysis: application to the atmospheric infrared sounder

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.

Infrared atmospheric sounder interferometer radiometric noise assessment from spectral residuals

The problem of characterizing and estimating the radiometric noise of satellite high spectral resolution infrared spectrometers from Earth views is addressed in this paper. A methodology has been devised which is based on the common concept of spectral residuals (Observations-Calculations) obtained after spectral radiance inversion for atmospheric and surface parameters. An in-depth analytical assessment of the statistical covariance matrix of the spectral residuals has been performed which is based on the optimal estimation theory. It has been mathematically demonstrated that the use of spectral residuals to assess instrument noise leads to an effective estimator, which is largely independent of possible departures of the observational covariance matrix from the true covariances. Application to the Infrared Atmospheric Sounder Interferometer has been considered. It is shown that Earth-view-derived observation errors agree with blackbody in-flight calibration. The spectral residuals approach also proved to be effective in characterizing noise features due to mechanical microvibrations of the beam splitter of the IASI instrument.

Destriping MODIS data using IFOV overlapping

In this paper, we present a new destriping algorithm for MODIS images. The algorithm takes advantage of the observation redundancy due to the bow-tie effect. It estimates the equalization curve from single fields of view observed by multiple detectors. Results show that the strategy is correct in those regions where equalization curve is estimated in the low to moderate range of radiance

Applications of high spectral resolution FTIR observations demonstrated by the radiometrically accurate ground-based AERI and the scanning HIS aircraft instruments

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.

Principal Component Analysis of IASI Spectra with a Focus on Non‐Uniform Scene Effects on the ILS

Exploiting the redundancy of spectrally correlated information in high spectral resolution infrared radiance observations, Principal Component Analysis (PCA) is useful for extracting signals from the observations, noise filtering, and for characterization of variable artifacts within the data. Here, PCA is used to investigate the spectral nature of observations from the Infrared Atmospheric Sounding Interferometer (IASI) with a focus on the effects of non‐uniform scenes on the Instrument Line Shape (ILS). For IASI and other similar FTS systems, non‐uniform scenes produce a non‐uniform weighting of angles through the interferometer that can produce subtle distortions in the ILS from that of uniform scenes. For the PCA approach used here, it is found that the spectral signature due to the non‐uniform scene effects are contained primarily within a single principal component, and that reconstruction of the radiance spectra with this component excluded provides an accurate and robust correction algorithm. Furt...