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At least 325 records · Page 18

Interference effects on Space Station Freedom and space shuttle orbiter Ku-band downlinks

The space shuttle orbiter (SSO) and Ku-band single access return (KSAR) link and the Space Station Freedom (SSF) KSAR link via the tracking and data relay satellite system (TDRSS) use the same carrier frequency. The interference between spacecraft is minimized by opposite antenna polarizations and by TDRSS antenna beam pointing, but if the SSF and SSO are in close proximity, it is expected that mutual interference will be significant. Recently, Tsang and Su (1988, 1989) simulated the mutual interference effects, using a practical nonlinear bandlimited channel. The purpose of this paper is to demonstrate that a simplified (i.e., linear band-limited channel) analytical approach will yield adequate accuracy for the expected range of operating conditions. Relative degradation in bit energy-to-thermal noise power spectral density ratio to achieve a 10 exp -5 coded bit-error-probability is determined to be 4 dB for the Ku-band SSO-to-TDRS I-channel return link with a 4.5 dB effective signal-to-interference total power ratio (S/I) when the Ku-band SSF-to-TDRS return link interferes, whereas Su's simulation yields approximately 5 dB degradation. For the Ku-band SSF-to-TDRS return link, both analysis and simulation results yield a relative signal degradation of 0.4 dB at the effective S/I = 21.6 dB. In conclusion, interference on the Ku-band SSO-to-TDRS I-channel return link is significant, but on the Ku-band SSF-to-TDRS return link it is negligible.

Kwon, Hyuck M.↗

Radio observations of peculiar emission-line Algol binary stars

Twelve peculiar emission-line Algol (PELA) binaries were observed at cm wavelengths. Six of these objects, WW And (tentative), KX And, AM Aur, V644 Mon, DN Ori, and AY Per were detected at the 100 to 400 micro-Jy level, corresponding to luminosity densities of order 10 exp 17 erg/s/Hz. These luminosity densities, combined with nearly flat cm spectra and high brightness temperatures, are consistent with the nonthermal gyrosynchrotron radiation model proposed as the result of observations from the previous PELA survey. Also, the star V367 Cyg was reobserved at thirteen different orbital phases; no variability was found within the errors. V367 Cyg's lack of variability and well-determined average spectral index, however, imply the possibility of a different emission mechanism, thermal bremsstrahlung, although the nonthermal model cannot be entirely ruled out. The characteristic brightness temperature of thermal bremsstrahlung is only about 10,000 K, which means that the radius of the emission region would have to be much larger than previously assumed, about 10 AU. Suggestions for further observations of all previously observed PELAS are presented in order to determine the correct emission mechanism.

Elias, Nicholas M., II↗

Spatial spectra from a satellite scanning radiometer

A method for computing spatial spectra from measurement based on a scanning radiometer is presented which takes into account the instrument field-of-view, time response, and the scan pattern. To compute the mean of the field, measurements away from nadir are weighted more heavily than those near nadir. The proposed method is capable of defining the limits beyond which the Fourier components cannot be extracted from the data. Results show that, for the Earth Radiation Budget Experiment scanning radiometer at an altitude of 600 km, spectral features with wavelengths greater than 100 km can be measured without errors due to incorporation of unobservable portions of the spectrum into results.

Smith, G. L.↗

Application of AI techniques to infer vegetation characteristics from directional reflectance(s)

Traditionally, the remote sensing community has relied totally on spectral knowledge to extract vegetation characteristics. However, there are other knowledge bases (KB's) that can be used to significantly improve the accuracy and robustness of inference techniques. Using AI (artificial intelligence) techniques a KB system (VEG) was developed that integrates input spectral measurements with diverse KB's. These KB's consist of data sets of directional reflectance measurements, knowledge from literature, and knowledge from experts which are combined into an intelligent and efficient system for making vegetation inferences. VEG accepts spectral data of an unknown target as input, determines the best techniques for inferring the desired vegetation characteristic(s), applies the techniques to the target data, and provides a rigorous estimate of the accuracy of the inference. VEG was developed to: infer spectral hemispherical reflectance from any combination of nadir and/or off-nadir view angles; infer percent ground cover from any combination of nadir and/or off-nadir view angles; infer unknown view angle(s) from known view angle(s) (known as view angle extension); and discriminate between user defined vegetation classes using spectral and directional reflectance relationships developed from an automated learning algorithm. The errors for these techniques were generally very good ranging between 2 to 15% (proportional root mean square). The system is designed to aid scientists in developing, testing, and applying new inference techniques using directional reflectance data.

Kimes, D. S.↗

Variable extinction in HD 45677 and the evolution of dust grains in pre-main-sequence disks

Changes in the UV extinction and IR emission were sought in the Herbig Ae/Be star candidate HD 45677 (= FS CMa) by comparing UV, optical, and IR observations made approximately 10 yr apart. HD 45677 varied significantly, becoming more than 50% brighter in the UV and optical than it was a decade ago. A comparison of the observations between epochs indicates that if the variations are due to changes in dust obscuration, the dust acts as a gray absorber into the near-IR and must be depleted in grains smaller than 1 micron. This is similar to the results obtained on the circumstellar disks of stars like Vega and Beta Pic, and suggests that radiation pressure may be responsible for the small-grain depletion. In addition, the total IR flux seems to have declined, indicating a decrease in the total mass of the dust envelope that contributes to the IR emission in this part of the spectrum. Due to the anomalous nature of the extinction, the use of normal extinction curves to deredden the spectral energy distributions of stars with circumstellar dust may lead to significant errors and should be used with great caution.

Sitko, Michael L.↗

A reanalysis of the SWP-HI IUE observations of Capella

We have reanalyzed the numerous high-resolution, far-ultraviolet observations of Capella made by the International Ultraviolet Explorer (IUE) in its 16 yr lifetime. Our purpose was to search for long-term profile variations in Capella's ultraviolet emission lines and to complement the analysis of Goddard High Resolution Spectrograph (GHRS) observations of Capella, discussed in a companion paper (Linsky et al. 1995). We implemented a state-of-the-art photometric correction and spectral extraction procedure to improve S/N and control potential sources for systematic errors. Nevertheless, we were unable to find compelling evidence for any significant long-term profile variations. Previous work has shown that the G8 primary star is only a minor contributor to the high-excitation transition region lines but is a significant contributor to the low-excitation chromospheric lines. We have found exceptions to this rule, however. We find that the G8 star is responsible for a significant portion of Capella's N V lambda lambda 1239, 1243 emission, but is not a large contributor to the S I lambda 1296, Cl I lambda 1352, and O lambda 1356 lines. We suggest possible explanations for these behaviors. We also find evidence that the He II lambda 1640 emission from the G1 star is from the transition region, while the He II lambda 1640 emission from the G8 star is chromospheric, consistent with the findings of Linsky et al. (1994). The C II lambda 1336 line shows a weak central reversal. It is blueshifted by about 9 km/s with respect to the centroid of the emission from the G1 star. While the central reversal of the C II line is blueshifted by about 9 km/s with respect to the centroid of the emission from the G1 star. While the central reversal of the C II line is blueshifted, the central reversal of the Si III lambda 1207 line discussed by Linsky et al. (1994) is not.

Wood, Brian E.↗

Long-Term Trends in the Concentrations of SF6, CHClF2, and COF2 in the Lower Stratosphere from Analysis of High-Resolution Infrared Solar Occultation Spectra

Long-term trends in the concentrations of SF6, CHClF2 (CFC-22), and COF2 in the lower stratosphere have been derived from analysis of ca. 1980 and more recent infrared solar occultation spectra recorded near 32 deg N latitude at approx. 0.02/ cm resolution. Consistent sets of line parameters and spectral calibration methods have been used in the retrievals to minimize systematic error effects. Quoted error limits are 1 sigma estimated precisions. The SF6 and CHClF2 results are based on spectra recorded by balloon-borne interferometers in March 1981 and June 1988 and a comparison of these results with the Atmospheric Trace Molecule Spectroscopy (ATMOS) Experiment/Spacelab 3 measurements obtained in May 1985 near 30 deg N latitude. In the 13-18 km altitude range the mean measured SF6 mixing ratio in parts per trillion by volume (pptv) increased from 1.17 +/- 0.21 in March 1981 to 2.02 +/- 0.20 pptv in June 1988, and the CHClF2 mixing ratio below 15 km altitude increased from 51 +/- 8 pptv in March 1981 to 102 +/- 10 pptv in June 1988. The CHClF2 retrievals used new empirical CHClF2 line parameters derived from 0.03/cm resolution laboratory spectra recorded at six temperatures between 203 and 293 K; the derived mixing ratios are approx. 30% higher than obtained with earlier sets of line parameters, thereby removing a large discrepancy noted previously between IR and in situ measurements of CHClF2. Assuming an exponential growth model for fitting the trends, SF6 and CHClF2 mean increase rates of 7.4% +/- 1.9% and 9.4% +/- 1.3% /year, are obtained, respectively, which correspond to cumulative increases by factors of approx. 1.7 and -2.0 in the concentrations of these gases over the 7.2-year measurement period. Analysis of spectra recorded in October 1979 and April 1989 yields COF2 volume mixing ratios that are respectively 0.44 +/- 0.17 and 1.21 +/- 0.24 times the ATMOS/Spacelab 3 values, from which an average COF2 increase rate of 10.3 +/- 1.8%/ year over this time period has been estimated. The present results are compared with previously reported observations and trends and with one-dimensional model calculations. The model calculated trends are in reasonably good agreement with the observations.

Rinsland, C. P.↗

Integrated Path Differential Absorption Lidar Optimizations Based on Pre-Analyzed Atmospheric Data for ASCENDS Mission Applications

In this paper a modeling method based on data reductions is investigated which includes pre analyzed MERRA atmospheric fields for quantitative estimates of uncertainties introduced in the integrated path differential absorption methods for the sensing of various molecules including CO2. This approach represents the extension of our existing lidar modeling framework previously developed and allows effective on- and offline wavelength optimizations and weighting function analysis to minimize the interference effects such as those due to temperature sensitivity and water vapor absorption. The new simulation methodology is different from the previous implementation in that it allows analysis of atmospheric effects over annual spans and the entire Earth coverage which was achieved due to the data reduction methods employed. The effectiveness of the proposed simulation approach is demonstrated with application to the mixing ratio retrievals for the future ASCENDS mission. Independent analysis of multiple accuracy limiting factors including the temperature, water vapor interferences, and selected system parameters is further used to identify favorable spectral regions as well as wavelength combinations facilitating the reduction in total errors in the retrieved XCO2 values.

Pliutau, Denis↗

Radioelements on Vesta: An Update

The main-belt asteroid 4 Vesta is the putative parent body of the howardite, eucrite, and diogenite (HED) meteorites. Because these achondrites have similar petrology, geochemistry, chronology, and O-isotope compositions, it is thought that most HEDs originated from a single parent body. The connection to Vesta is supported by a close spectroscopic match between Vesta and the HEDs and a credible mechanism for their delivery to Earth. Studies of the HEDs show that Vesta underwent igneous differentiation, forming a Fe-rich core, ultramafic mantle, and basaltic crust. Here we present the results of peak analyses applied to a gamma ray difference spectrum to determine the absolute abundances of K and Th. Data are compared to meteorite whole-rock compositions and other inner solar system bodies. The results, while preliminary, represent our present best estimates for these elements. Because the element signatures are near detection limits and not fully resolved, further analysis (e.g. using spectral unmixing) will be required for improved accuracy and to characterize systematic errors.

Prettyman, T. H.↗

Hyperspectral Radiative Transfer Modeling to Explore the Combined Retrieval of Biophysical Parameters and Canopy Fluorescence from FLEX - Sentinel-3 Tandem Mission Multi-Sensor Data

The FLuorescence EXplorer (FLEX) satellite mission, selected as ESA's 8th Earth Explorer, has been designed forthe measurement of sun-induced fluorescence (F) spectra emitted by plants. This will be accomplished through amulti-sensor approach by placing it in a common orbit in tandem with the Sentinel-3 (S3) mission, which willhave two optical sensors on board, OLCI (Ocean and Land Colour Instrument) and SLSTR (Sea and Land SurfaceTemperature Radiometer) to complement FLEX. These S3 instruments will be used in combination with theimaging spectrometers on board FLEX to provide data useful for atmospheric correction of FLEX data. However,a fully synergetic approach, i.e. by exploiting the spectral and directional information from all tandem missioninstruments together, is an attractive alternative which is explored in this paper. By employing all combined topof-atmosphere (TOA) spectral radiance data, one can (i) characterize the relevant optical properties of the atmosphere,(ii) retrieve biophysical canopy properties including the associated reflectance anisotropy, and (iii)retrieve a more accurate and consistent canopy F.Regarding retrieval methods, Fraunhofer Line Depth (FLD) and Spectral Fitting (SF) are well-known techniquesapplied to hyperspectral data. Both methods depend on a high spectral resolution and assume aLambertian (isotropic) canopy reflectance. However, most vegetation canopies are non-Lambertian. This impliesthat, in particular when ignoring the anisotropic surface reflection, substantial retrieval errors can occur due tothe interaction between atmospheric absorption bands and surface reflectance anisotropy. In this paper, a novelmethod based on spectral radiative transfer (RT) modeling is proposed, in which coupled RT models are used tosimulate TOA radiance spectra. These are then matched with ‘measured' spectra in order to retrieve surfacefluorescence, along with a suite of biophysical parameters, by model inversion through optimization. By applyingcoupled RT models of the soil-leaf-canopy and the surface-atmosphere systems, TOA radiance spectra canbe simulated for all optical sensors of this tandem mission. In this way, complex effects due to surface reflectanceanisotropy and the spectral sampling by the various instruments, which are difficult to compensate for in the endproducts, are properly taken into account by their incorporation in the forward modeling. Next, by model inversionof TOA radiance data via optimization, the most accurate F retrievals can be achieved in a consistentmanner, along with important canopy level biophysical parameters that may help interpret the F spectrum, suchas chlorophyll content and leaf area index (LAI). The potential of this approach has been explored in a numericalexperiment, and the results are presented in this paper. We find that, with the assumed well-characterized andplausible FLEX/S3 instrument performances, the simultaneous retrieval of biophysical canopy parameters and Fspectra would be possible with a remarkable accuracy, provided the correct atmospheric characterization isavailable.

Verhoef, Wouter↗

Thermal Inspection of Low Emissivity Surfaces Using a Pulsed Light Emitting Diodes (PLED) Heat Source

Thermal inspections of a structure typically utilize a flash or quartz lamp heat source located on the same side of an infrared camera. The heat source provides light energy for heating while the infrared camera measures the surface transient temperature response. The inspection can be difficult for low emissivity surfaces for several reasons. First, the high intensity light can reflect off the surface and cause “burn-in” to the camera’s detector. The “burn-in” can take time for the sensors to recover and potentially damage the detector. Secondly, the heat source after pulsing, has a transient cool down component. The cool down component can be reflected and therefore superimposed over the structure’s thermal response which can cause an error (false defect indications) in the inspection. Lastly, the heat source is spectrally broad and therefore while heating, infrared components of the heat source can produce non-uniformity in the measured temperature field. Typically for the inspection of reflective surfaces, paint or other emissivity enhancing coatings are applied before inspection. In this paper, a pulsed light emitting diodes (PLED) heat source is used. The PLED heat source is spectrally narrow, contained within the visible band, and therefore not detectable by the infrared camera. The PLED heat source is configured to reduce any transient cool down components that could produce false defect indications. The PLED thermal inspections are compared to commercially available flash thermography inspections on unpainted aluminum samples with simulated corrosion and additively manufactured Ti-6AL-4V metal specimens.

thermal nondestructive evaluation↗

Thermal Inspection of Low Emissivity Surfaces Using a Pulsed Light Emitting Diodes (PLED) Heat Source

Thermal inspections of a structure typically utilize a flash or quartz lamp heat source located on the same side of an infrared camera. The heat source provides light energy for heating while the infrared camera measures the surface transient temperature response. The inspection can be difficult for low emissivity surfaces for several reasons. First, the high intensity light can reflect off the surface and cause “burn-in” to the camera’s detector. The “burn-in” can take time for the sensors to recover and potentially damage the detector. Secondly, the heat source after pulsing, has a transient cool down component. The cool down component can be reflected and therefore superimposed over the structure’s thermal response which can cause an error (false defect indications) in the inspection. Lastly, the heat source is spectrally broad and therefore while heating, infrared components of the heat source can produce non-uniformity in the measured temperature field. Typically for the inspection of reflective surfaces, paint or other emissivity enhancing coatings are applied before inspection. In this paper, a pulsed light emitting diodes (PLED) heat source is used. The PLED heat source is spectrally narrow, contained within the visible band, and therefore not detectable by the infrared camera. The PLED heat source is configured to reduce any transient cool down components that could produce false defect indications. The PLED thermal inspections are compared to commercially available flash thermography inspections on unpainted aluminum samples with simulated corrosion and additively manufactured Ti-6AL-4V metal specimens.

thermal nondestructive evaluation↗

20-Years of Atmospheric Temperature, Water Vapor, Cloud, and Surface Temperature Anomalies and Trends Derived From Operational Hyperspectral Ir Sounders

Hyperspectral IR sounders such as AIRS on Aqua, CrIS on S-NPP, NOAA20 and JPSS-2, IASI on Metop A, B, and C provide high-quality atmospheric temperature, water, vapor, and greenhouse gas vertical profiles. Additionally, they provide atmospheric cloud properties, surface emissivity, and surface skin temperatures. We have developed two algorithms which can consistently derive these products from multiple IR sounders. The first one is a Single Field-of-view Sounder Atmospheric Product (SIFSAP) algorithm and the second one is a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm. Compared to current operational AIRS and CrIS Level-2 (L2) algorithms, which perform one retrieval for each 3 by 3 field of views (FOVs) using a cloud-clearing approach, the SiFSAP algorithm, on the other hand, performs one retrieval for each FOV using an all-sky optimal estimation approach. The SiFSAP algorithm retrieves all the above-mentioned atmosphere and surface properties simultaneously including cloud properties with 3-time higher spatial resolution and 9-times more products. The core of the SiFSAP algorithm is an accurate and fast Principal Component-based Radiative Transfer Model (PCRTM), which can calculate hyperspectral radiance spectra under both clear and cloudy conditions. The PCRTM was developed in the past decade using consistent reference line-by-line radiative transfer model and spectroscopy for hyperspectral sounders such as AIRS, CrIS, IASI, NAST-I, and S-HIS. The SiFSAP retrieval algorithm also uses the same climatology a priori and associated covariances, which makes it ideal for generating high quality products for both weather and climate applications. Climate products are typically derived by performing spatial and temporal averaging of L2 products. It is a time-consuming process to generate L2 data products since AIRS, CrIS, and IASI have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in L2 retrieval algorithms for different satellite sensors can lead to errors in the climate products. Our ClimFiSP algorithm, which performs retrievals from spatiotemporally averaged L1 hyperspectral radiances directly, will be orders of magnitude faster than traditional method. he ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides accurate data climate data fusion products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. Both SiFSAP and ClimFiSP will be available at NASA GES DISC data center for public access.

Xu Liu↗

Two Decades of Atmospheric and Surface Temperature, Water Vapor, and Cloud Trends Derived from Satellite Remote Sensors

Satellite remote sensor such as Atmospheric Infrared Sounder (AIRS), Cross-track Infrared Sounder (CrIS), and Infrared Atmospheric Sounding Interferometer (IASI) provide high-quality atmospheric temperature, water, vapor, and greenhouse gas vertical profiles. Additionally, they provide atmospheric cloud properties, surface emissivity, and surface skin temperatures. We have developed two algorithms which can consistently derive these products from multiple IR sounders. The first one is a Single Field-of-view Sounder Atmospheric Product (SIFSAP) algorithm and the second one is a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm. Compared to current operational AIRS and CrIS Level-2 (L2) algorithms, which perform one retrieval for each 3 by 3 field of views (FOVs) using a cloud-clearing approach, the SiFSAP algorithm, on the other hand, performs one retrieval for each FOV using an all-sky optimal estimation approach. The SiFSAP algorithm retrieves all the above-mentioned atmosphere and surface properties simultaneously including cloud properties with 3-time higher spatial resolution and 9-times more products. Climate products are typically derived by performing spatial and temporal averaging of L2 products. It is a time-consuming process to generate L2 data products since AIRS, CrIS, and IASI have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in L2 retrieval algorithms for different satellite sensors can lead to errors in the climate products. Our ClimFiSP algorithm, which performs retrievals from spatiotemporally averaged L1 hyperspectral radiances directly, will be orders of magnitude faster than traditional method. he ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It provides accurate data climate data fusion products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. Both SiFSAP and ClimFiSP will be available at NASA GES DISC data center for public access.

remote sensing↗

The Intercalibration of Geostationary Visible Imagers Using Operational Hyperspectral SCIAMACHY Radiances

Spectral band differences between sensors can complicate the process of intercalibration of a visible sensor against a reference sensor. This can be best addressed by using a hyperspectral reference sensor whenever possible because they can be used to accurately mitigate the band differences. This paper demonstrates the feasibility of using operational Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) large-footprint hyperspectral radiances to calibrate geostationary Earth-observing (GEO) sensors. Near simultaneous nadir overpass measurements were used to compare the temporal calibration of SCIAMACHY with Aqua Moderate Resolution Imaging Spectroradiometer band radiances, which were found to be consistent to within 0.44% over seven years. An operational SCIAMACHY/GEO ray-matching technique was presented, along with enhancements to improve radiance pair sampling. These enhancements did not bias the underlying intercalibration and provided enough sampling to allow up to monthly monitoring of the GEO sensor degradation. The results of the SCIAMACHY/GEO intercalibration were compared with other operational four-year Meteosat-9 0.65-μm calibration coefficients and were found to be within 1% of the gain, and more importantly, it had one of the lowest temporal standard errors of all the methods. This is more than likely that the GEO spectral response function could be directly applied to the SCIAMACHY radiances, whereas the other operational methods inferred a spectral correction factor. This method allows the validation of the spectral corrections required by other methods.

Doelling, David R.↗

Incorporating Endmember Variability into Spectral Mixture Analysis Through Endmember Bundles

Variation in canopy structure and biochemistry induces a concomitant variation in the top-of-canopy spectral reflectance of a vegetation type. Hence, the use of a single endmember spectrum to track the fractional abundance of a given vegetation cover in a hyperspectral image may result in fractions with considerable error. One solution to the problem of endmember variability is to increase the number of endmembers used in a spectral mixture analysis of the image. For example, there could be several tree endmembers in the analysis because of differences in leaf area index (LAI) and multiple scatterings between leaves and stems. However, it is often difficult in terms of computer or human interaction time to select more than six or seven endmembers and any non-removable noise, as well as the number of uncorrelated bands in the image, limits the number of endmembers that can be discriminated. Moreover, as endmembers proliferate, their interpretation becomes increasingly difficult and often applications simply need the aerial fractions of a few land cover components which comprise most of the scene. In order to incorporate endmember variability into spectral mixture analysis, we propose representing a landscape component type not with one endmember spectrum but with a set or bundle of spectra, each of which is feasible as the spectrum of an instance of the component (e.g., in the case of a tree component, each spectrum could reasonably be the spectral reflectance of a tree canopy). These endmember bundles can be used with nonlinear optimization algorithms to find upper and lower bounds on endmember fractions. This approach to endmember variability naturally evolved from previous work in deriving endmembers from the data itself by fitting a triangle, tetrahedron or, more generally, a simplex to the data cloud reduced in dimension by a principal component analysis. Conceptually, endmember variability could make it difficult to find a simplex that both surrounds the data cloud and has vertices that are realistic endmember spectra with reflectances between 0 and 1. In this paper, we create endmember bundles and bounding fraction images for an AVIRIS subscene simulated with a plant canopy radiative transfer model. The simulated subscene is spatially patterned after a subscene from the AVIRIS image acquired August, 1993 over La Copita, Texas. In addition, for comparison, we performed a traditional unmixing with image endmembers.

Bateson, C. Ann↗

Hydrocarbons on Phoebe, Iapetus, and Hyperion: Quantitative Analysis

We present a quantitative analysis of the hydrocarbon spectral bands measured on three of Saturn's satellites, Phoebe, Iaperus, and Hyperion. These bands, measured with the Cassini Visible-Infrared Mapping Spectrometer on close fly-by's of these satellites, are the C-H stretching modes of aromatic hydrocarbons at approximately 3.28 micrometers (approximately 3050 per centimeter), and the are four blended bands of aliphatic -CH2- and -CH3 in the range approximately 3.36-3.52 micrometers (approximately 2980- 2840 per centimeter) bably indicating the presence of polycyclic aromatic hydrocarbons (PAH), is unusually strong in comparison to the aliphatic bands, resulting in a unique signarure among Solar System bodies measured so far, and as such offers a means of comparison among the three satellites. The ratio of the C-H bands in aromatic molecules to those in aliphatic molecules in the surface materials of Phoebe, NAro:NAliph approximately 24; for Hyperion the value is approximately 12, while laperus shows an intermediate value. In view of the trend of the evolution (dehydrogenation by heat and radiation) of aliphatic complexes toward more compact molecules and eventually to aromatics, the relative abundances of aliphatic -CH2- and -CH3- is an indication of the lengths of the molecular chain structures, hence the degree of modification of the original material. We derive CH2:CH3 approximately 2.2 in the spectrum of low-albedo material on laperus; this value is the same within measurement errors to the ratio in the diffuse interstellar medium. The similarity in the spectral signatures of the three satellites, plus the apparent weak trend of aromatic/aliphatic abundance from Phoebe to Hyperion, is consistent with, and effectively confirms that the source of the hydrocarbon-bearing material is Phoebe, and that the appearance of that material on the other two satellites arises from the deposition of the inward-spiraling dust that populates the Phoebe ring.

Cruikshank, Dale P.↗

A New, Efficient, and Consistent Method for Generating Climate Data Record from Operational Hyperspectral Sounder Instruments on AQUA, S-NPP and NOAA 20

Operational IR sounders such AIRS on NASA Aqua, CrIS on S-NPP and on NOAA 20 satellites provide high quality hyperspectral measurements for weather and climate applications. Climate products are typically derived by performing spatial and temporal averaging of level-2 products. It is a time-consuming process to generate level-2 data products since modern hyperspectral satellite sensors have millions of observations each day with thousands of spectral channels for each observation. Additionally, differences in level-2 retrieval algorithms for different satellite sensors can lead to errors in the climate products. We have developed a Climate Fingerprinting Sounder Product (ClimFiSP), which is derived from spatiotemporally averaged level-1 hyperspectral radiances directly. The ClimFiSP algorithm uses consistent radiative kernels and a robust spectral fingerprinting method. It can provide fast and accurate data fusion products from multiple satellite sensors. We have applied this method to both AIRS and CrIS (on SNPP and on NOAA 20) data and generated two decades climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. The ClimFiSP are being transitioned to NASA data centers for routine generations level-3 products.

Xu Liu↗