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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Explore Information Content Efficiently from Current and Future Hyperspectral Satellite Missions using a Spectral Fingerprinting Method

Hyperspectral remote sensors from current and future missions provide measurements of the Top of Atmosphere (TOA) radiance or reflectance spectra with high information content. For example, the Atmospheric Infrared Sounder (AIRS), together with the Cross-track Infrared Sounder (CrIS), and the Infrared Atmospheric Sounding Interferometer (IASI) have provided more than 20 years radiance measurements with thousands of spectral channels. These measurements will be continued for the next two decades with the same or more advanced hyperspectral sensors. The upcoming missions such as NASA’s CLARREO Pathfinder (CPF) and ESA’s TRUTHS will provide unprecedented accurate TOA hyperspectral radiance measurements in solar spectral region. Traditional ways to derive Climate Data Records (CDRs) from these measurements are performing spatial and temporal averages of the retrieved Level-2 products. However, it is a time-consuming process to generate decades of Level-2 data from Level-1 data. Furthermore, the differences in Level-2 algorithms used for different satellite sensors will introduce errors in derived CDRs. In this presentation, we will describe a spectral fingerprinting method to generate high-quality CDRs directly from spatiotemporally averaged Level-1 data. By using consistent radiative kernels which contain the spectral information of various atmospheric and surface CDRs, we can reduce the errors due to algorithm inconsistency. Additionally, the spectral fingerprinting method reduces the time needed to generate CDRs by more than three orders of magnitude. This makes it easy to reprocess CDRs once the Level-1 data from different satellites have been improved via either re-calibrations or inter-satellite calibrations. We will present results of applying spectral fingerprinting method to 20-years of AIRS and CrIS data. The resulting CDRs include: 1) vertical profiles of atmospheric temperature and water vapor, 2) cloud properties such as optical depth, effective size, and height, 3) vertical profiles or column amounts for atmospheric trace gases such as O3 and CO, and 4) surface emissivity spectra and skin temperatures. These CDRs will be publicly available at NASA GES DISC in late 2024. The same fingerprinting method is planned to be applied to future CPF and TRUTHS data for solar spectral region.

hyperspectral remote sensing↗
NASA NTRSDate not supplied

Fusion of Hyperspectral Sounder Products Via Spectral Fingerprinting Methodology

Satellite based measurements of top-of-atmosphere (TOA) spectral radiances in the infrared (IR) region have been in existence for almost two decades and are expected to be continued in the following decades. The data from multiple hyper-spectral IR sounders can therefore be combined to build a long-term data record to further global scale climate trend research. Challenges associated with the fusion of data from different sensors come from the stability and consistency requirement on the climate record. The direct radiance observations from different sounders need to be homogenized by reconciling the differences in calibration, spectral response function (SRF), and spatial-temporal sampling. When geophysical variables derived from radiances measured by different sounders are combined to form long-term climate records, the impacts of any inconsistencies between overlapping measurements on the retrieval must be carefully assessed in order to estimate the uncertainty of the corresponding climate anomalies/trends derived. This paper presents a novel climate fingerprinting methodology and establishes a rigorously-defined inverse relationship that allows us to efficiently evaluate the change in essential climate variables from the change in spectral radiances measured in prescribed spatial and temporal averaging scales. The inverse spectral fingerprinting relationship is constructed based on a unified spectral kernel scheme, providing a direct means for quantifying the potential discontinuity in the derived climate anomalies due to inconsistencies between overlapping measurements. We show in this paper a sample application of using the spectral fingerprinting scheme to derive long-term, global-scale surface temperatures from the Climate Hyperspectral Infrared Radiance Product (CHIRP) and quantify the inter-satellite biases.

Wan Wu↗
NASA NTRSDate not supplied

A Spectral Fingerprinting Method for Deriving Consistent Climate Data Records from Multiple Satellite IR Sounders

Deriving Climate Data Records (CDRs) from multiple IR sounders such AIRS on Aqua, CrIS on S-NPP, NOAA20 and JPSS-2, IASI on Metop A, B, and C requires from current operational products are challenging due to different radiative transfer models and retireavl algorithms used for processing level 2 data. We developed a Climate Fingerprinting Sounder Product (ClimFiSP) algorithm, which uses a single set of radiative kernels a robust spectral fingerprinting method to performs retrievals using spatiotemporally averaged L1 hyperspectral radiances directly. The ClimFiSP algorithm provides accurate data fusion CDR 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. We plan to add IASI to the CDR data set in the future. The ClimFiSP is being transitioned to NASA GES DISC data center for public access.

Xu Liu↗
NASA NTRSDate not supplied

Deriving Climate Change Signal from Hyperspectral Sounders Using Spectral Fingerprinting Method

Hyperspectral observations from satellite-based sensors provide high information content for the Earth’s atmospheric temperature, water vapor and trace gas vertical profiles. We have developed a radiometrically consistent spectral fingerprinting method to derive climate change signals from Aqua AIRS/AMSU and S-NPP CrIS/ATMS data. The climate variables include temperature and water vapor profiles, cloud, trace gases, and surface skin temperature. The radiative kernels obtained via a single field of view physical retrieval algorithm under all-sky conditions. A key component to this work is a Principal Component-based Radiative Transfer Model (PCRTM). It is 4 orders of magnitude faster than a line-by-line radiative transfer model while keeping a similar accuracy (0.03 K RMS errors with close to zero bias). The PCRTM includes multiple scattering of clouds and non-thermodynamics equilibrium of CO2 in the RT calculations. Instead of quantifying the radiometric differences between AIRS/AMSU and CrIS/ATMS measurements directly using Simultaneous Nadir Overpass (SNO) or Double Difference Technique (DDT), we use the radiometric consistent fingerprinting scheme to derive two sets of space-time averaged anomalies from the Level 1 data of AIRS/AMSU and CrIS/ATMS. The derived anomalies in geophysical space will form a long-term, stable, and continuous climate data record. We can further infer the causes of any offset or drift by studying the differences between two overlapping data sets. For example, the offset in surface skin temperature anomaly time series will most likely caused by the Blackbody temperature calibration errors of the sounder instruments.

climate↗
NASA NTRSDate not supplied

A Radiometric Consistent Spectral Fingerprinting Algorithm for Continuity Products of Hyperspectral Sounders

A radiometric consistent climate fingerprinting methodology has been developed to derive long-term temperature, water vapor, cloud, trace gases, and surface skin temperature anomaly time series from the hyper-spectral sounder measurements of multiple platforms. The spectral fingerprinting methodology requires the use of radiative kernels that are radiometrically consistent with observations. Radiative kernels are built using space-time averaged Jacobians that are physically retrieved from observations under all sky conditions. The physical retrieval algorithm uses the Principal Component based Radiative Transfer Model (PCRTM) for the forward simulation. The incorporation of multiple scattering simulation in PCRTM allows the direct radiative relationship between single field-of-view (FOV) radiance observations and corresponding thermal dynamic variables including cloud properties to be established. Therefore, radiance ?closure? can be achieved under all-sky conditions by the fingerprinting scheme. This methodology has been used to derive climate anomalies from the space-time averaged spectra of AIRS/AMSU and CrIS/ATMS. The use of a consistent fingerprinting scheme provides an effective mean of generating continuity product by merging observations from different platforms and therefore facilitating the long-term climate trend study.

Wan Wu↗
NASA NTRSDate not supplied

Hyperspectral Sounder Spectral Fingerprinting: Using Machine Learning Techniques to Enhance Model-Based Physical Inversion

Different retrieval algorithms have been developed to process top-of-atmosphere (TOA) spectral radiance data provided by hyperspectral infrared sounder missions. Those algorithms are either optimal estimation method (OEM) based schemes with radiative transfer calculation involved in the retrieval process, or machine learning based methods that allow ultra-efficient data procession but lack of radiometric consistency validation based on the directly measured information. Combining both approaches leverages their respective technical advantages, leading to more accurate results. This study introduces a hyperspectral sounder fingerprinting algorithm to explore this hybrid approach. This approach involves the use of a spectral information-based classification method to identify an reference geophysical state and the corresponding radiative kernel. This enables the efficient retrieval of geophysical variables of interest through a radiative kernel-based linear inversion procedure. The fingerprinting method has been applied to analyze a decade-long hyperspectral sounder data record.

Wan Wu↗
DOE OSTI2024

Nanoscale visualization and spectral fingerprints of the charge order in ScV 6 Sn 6 distinct from other kagome metals

Charge density waves (CDWs) in kagome metals have been tied to many exotic phenomena. Here, using spectroscopic-imaging scanning tunneling microscopy and angle-resolved photoemission spectroscopy, we study the charge order in kagome metal ScV 6 Sn 6 . The similarity of electronic band structures of ScV 6 Sn 6 and TbV 6 Sn6 (where charge ordering is absent) suggests that charge ordering in ScV 6 Sn 6 is unlikely to be primarily driven by Fermi surface nesting of the Van Hove singularities. In contrast to the CDW state of cousin kagome metals, we find no evidence supporting rotation symmetry breaking. Differential conductance dI/dV spectra show a partial gap Δ 1 CO ≈ 20 meV at the Fermi level. Interestingly, dI/dV maps reveal that charge modulations exhibit an abrupt phase shift as a function of energy at energy much higher than Δ 1 CO , which we attribute to another spectral gap. Our experiments reveal a distinctive nature of the charge order in ScV 6 Sn 6 with fundamental differences compared to other kagome metals.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Deriving Essential Climate Variable Data from Multiple Satellite Remote Sensors Using a Consistent Fingerprinting Method

Hyperspectral observations from satellite-based sensors provide high information content for the Earth’s atmospheric and surface properties. Traditionally, long-term climate products are derived by performing spatial and temporal averaging of level-2 satellite 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 can lead to errors in the climate products when fusing data from different satellite sensors. We have developed a radiometrically consistent spectral fingerprinting method, which overcomes the above-mentioned shortcomings, to derive climate change signals from multiple satellite sensors using spatiotemporally averaged level-1 data. We have applied this method to Atmospheric Infrared Sounder (AIRS) and Cross-track Infrared Sounder (CrIS) data and generated decade-long climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. A key component to this work is a set of observational-based radiative kernels produced from CrIS level-1 data using a single field of view (SFOV) optimal estimation retrieval algorithm. Only limited CrIS level-1 data (e.g., 1-2 years of data) are needed to the derive radiative kernels. Our Principal Component-based Radiative Model (PCRTM) enables us to perform SFOV retrievals under all sky conditions and provides radiative kernels (including those for clouds) needed by the spectral fingerprinting method. In this presentation, we will describe the basic methodology, the details of the algorithm, and results from NASA Aqua AIRS and Suomi-NPP CrIS data. The method can be applied to study future hyperspectral remote sensors such as CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF), Tropospheric Emissions: Monitoring of Pollution (TEMPO), Surface Biology and Geology (SBG), Aerosol and Cloud, Convection and Precipitation (ACCP).

Xu Liu↗
DOE OSTI2025

Soft X-ray Emission Spectroscopy of Phosphorus Compounds for Energy Conversion and Storage

Phosphorus (P) is a ubiquitous component of materials for energy conversion and storage. Despite the effectiveness of soft X-ray emission spectroscopy (XES) to characterize these complex materials, XES studies of P-containing compounds are still largely missing. In this investigation, the electronic structure and XES signatures from the P L 2,3 -edge are probed for nine solid-state P-containing compounds characterized by various oxidation states and chemical environments: GaP (3−) , InP (3−) , red-P (0) , H 3 P (3+) O 3 , Na 2 H 2 P 2 (4+) O 6 , H 3 P (5+) O 4 , KH 2 P (5+) O 4 , Na 2 HP (5+) O 4 , and InP (5+) O 4 . The XES spectrum of each material exhibits distinct spectral fingerprints, which provide a robust basis for the speciation of complex P-containing samples. Density functional theory calculations shed light on the electronic structure of selected materials and particularly on the effect of phosphorus-oxygen hybridization. This study provides a comprehensive understanding of P L 2,3 XES spectral fingerprints across a wide range of oxidation states and chemical environments. These data sets and insights pave the way for dedicated future work, such as in situ and operando investigations of P-containing compounds in energy-related applications, where speciation of P compounds is needed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Generating Essential Climate Variables from Multiple Satellite Hyperspectral Remote Sensors

Hyperspectral observations from satellite-based sensors provide high information content for the Earth’s atmospheric and surface properties. Traditionally, long-term climate products are derived by performing spatial and temporal averaging of level-2 satellite products. There are two shortcomings of this approach. First, 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. Secondly, differences in level-2 retrieval algorithms can lead to errors in the fused multi-satellite data. We have developed a radiometrically consistent spectral fingerprinting method, which overcomes the above-mentioned shortcomings, to derive climate change signals from multiple satellite sensors using spatiotemporally averaged level-1 data. We have applied this method to data collected from Atmospheric Infrared Sounder (AIRS) on Aqua satellite and Cross-track Infrared Sounder (CrIS) on SNPP and NOAA20 and generated decade-long climate data records for atmospheric temperature, water vapor, cloud, trace gases, and surface skin temperature. A key component to this work is a set of observational-based radiative kernels produced from CrIS level-1 data using a single field of view (SFOV) optimal estimation retrieval algorithm. Only limited CrIS level-1 data (e.g., 1-2 years of data) are needed to the derive radiative kernels. Our Principal Component-based Radiative Model (PCRTM) enables us to perform SFOV retrievals under all sky conditions and provides radiative kernels (including those for clouds) needed by the spectral fingerprinting method. In this presentation, we will describe the basic methodology, the details of the algorithm, and results from NASA Aqua AIRS and Suomi-NPP CrIS data. The method can be applied to study future hyperspectral remote sensors such as CLARREO (Climate Absolute Radiance and Refractivity Observatory) Pathfinder (CPF), Tropospheric Emissions: Monitoring of Pollution (TEMPO), Surface Biology and Geology (SBG), Atmosphere Observing System (AOS).

Xu Liu↗
NASA NTRSDate not supplied

Homogenization of Satellite Based Hyperspectral Infrared Sounder Data To Build Long Term Climate Record

Building long term climate record using data from multiple hyperspectral Infrared (IR)sounders requires the homogenization of different data record to ensure the consistency andcontinuity. Such a requirement comes from two perspectives: 1) the need to adjust theoverlapping measurements of different sounders to ensure the radiometric consistency in thespectral radiance domain; 2) the need for a rigorously defined scheme to ensure the radiometricconsistency being transferred to the essential climate variables derived from the radiance record.We develop a solution that uses a spectral fingerprinting scheme to derive anomalies of keyclimate variables from long term spectral radiance data record constructed using both AIRS andCrIS observations aboard AQUA, SNPP and JPSS satellites. The fingerprinting scheme usescommon radiative kernels for all sounder measurements and therefore effectively avoids thealgorithm introduced inconsistency in retrieved geophysical variables. Our approach uses aunified sampling scheme to match AIRS and CrIS observations in both spectral and spatial-temporal domain, facilitating the intercomparison of spectral radiances from different sensors(platforms). The optimized liner inversion scheme allows the direct quantification and thereforethe adjustment for the impact on the derived climate anomalies imposed by potential radiometricinconsistency between the overlapping measurements. Such a scheme also enables the low-latency data processing of long term hyperspectral sounder data records. This paper provides a detailed introduction of the spectral fingerprinting methodology.Also introduced here is the climate fingerprinting Sounder Product (ClimFiSP) developed basedon the fingerprinting methodology. ClimFiSP products include the space-time averagedproperties of key climate variables that are derived from the long-term, space-time averagedradiances from AQUA-AIRS, SNPP-CrIS, and JPSS1-CrIS. ClimFiSP will be available to usersthrough NASA'sGoddard Earth Sciences Data and Information Services Center (GES DISC).

Wan Wu↗
DOE OSTI2023

Hyperfine structure and isotope shifts of xenon measured for near-infrared transitions with Doppler-free saturated absorption spectroscopy

Hyperfine structure and isotope shifts of Xe were investigated with Doppler-free saturated absorption spectroscopy for all transitions in the 820-841 nm spectral interval. The Xe samples were commercial gases of natural isotopic abundances. The measurements were performed by employing a widely tunable narrow line Ti:sapphire laser. The hyperfine structures for 129 Xe and 131 Xe were well resolved. For the transitions with the wavelengths in vacuum near 820.860 nm and 841.150 nm also isotope shifts of the even isotopes were clearly observed. The modeling of the shapes of the observed absorption lines qualitatively reproduces experimental spectral profiles. The measured absorption peaks of the hyperfine structure and isotope shifts of Xe isotopes present characteristic spectral fingerprints for their identification. Eventually, quantitative spectral analysis will provide isotopic abundances of natural, as well as radioactive Xe gas samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2000

Evidence for a Hematite Ore Body on Mars

The Mars Global Surveyor (MGS) spacecraft was launched from Cape Kennedy in November 1996. MGS was put into orbit around Mars in September of 1997 and has since been sending back data from a suite of instruments, including the Thermal Emission Spectrometer (TES). The TES instrument is an interferometric spectrometer designed to map the surface mineralogy of Mars by measuring the midinfrared emitted radiation over the spectral region of about 1600 to 200 cm(exp -1) (about 6 to 50 microns). This mineralogically sensitive technique utilizes the characteristic intra- and inter-molecular vibrations of minerals that are manifested in the midinfrared spectra. These spectral "fingerprints" are unique because they are dependent upon chemical composition, crystal structure, crystal orientation, and other factors. Midinfrared spectral data received from the MGS-TES instrument have indicated the presence of a large deposit of hematite (alpha-Fe2O3) in Sinus Meridiani, Mars. This hematite ore body, that is accompanied by basalt, is really extensive, encompassing an area about 350 by 500 km. To better understand the geologic context of this large deposit, a detailed laboratory spectroscopic investigation was conducted using more than 20 hematite samples so that their spectra could be compared to the martian spectra. The samples included red and gray polycrystaline hand samples, gray single-crystal hand samples, and red and gray fine- and coarse-grained particulates. The laboratory analyses provided thermal emissivity spectra that, when compared to the hematite emissivity spectra from Mars, suggest the Sinus Meridiani hematite is possibly an exposure of oriented hematite grains. These grains are likely coarser that 10 microns (and may be much larger) and gray in color. The characteristic of oriented grains is suggested by the apparent crystal axis-dependence of the energy emitted from the surface of Mars. The strong degree of crystal alignment exhibited in the emissivity spectra of Mars suggests that these oriented hematite crystals most likely occur as bedrock of aligned specular hematite grains (possibly schistose in texture) or as a secondary coating on bedrock, rather than as discrete particles. We are investigating the nature of this vast hematite deposit in order to understand better the geologic setting and infer past conditions and geological evolution on Mars.

Morris, Richard V.↗
NASA NTRS2000

Evidence for a Hematite Ore Body on Mars

The Mars Global Surveyor (MGS) spacecraft was launched from Cape Kennedy in November 1996. MGS was put into orbit around Mars in September of 1997 and has since been sending back data from a suite of instruments, including the Thermal Emission Spectrometer (TES). The TES instrument is an interferometric spectrometer designed to map the surface mineralogy of Mars by measuring the midinfrared emitted radiation over the spectral region of approximately 1600 to 200 per centimeter (appjroximately 6 to 50 microns). This mineralogically sensitive technique utilizes the characteristic intra- and inter-molecular vibrations of minerals that are manifested in the midinfrared spectra. These spectral "fingerprints" are unique because they are dependent upon chemical composition, crystal structure, crystal orientation, and other factors. Midinfrared spectral data received from the MGS-TES instrument have indicated the presence of a large deposit of hematite (alpha-Fe2O3) in Sinus Meridiani, Mars. This hematite ore body, that is accompanied by basalt, is areally extensive, encompassing and area approximately 350 by 500 km. To better understand the geologic context of this large deposit, a detailed laboratory spectroscopic investigation was conducted using more than 20 hematite samples so that their spectra could be compared to the martian spectra. The samples included red and gray polycrystaline hand samples, gray single-crystal hand samples, and red and gray fine- and coarse-grained particulates. The laboratory analyses provided thermal emissivity spectra that, when compared to the hematite emissivity spectra from Mars, suggest the Sinus Meridiani hematite is possibly an exposure of oriented hematite grains. These grains are likely coarser that 10 microns (and may be much larger) and gray in color The characteristic of oriented grains is suggested by the apparent crystal axis-dependence of the energy emitted from the surface of Mars. The strong degree of crystal alignment exhibited in the emissivity spectra of Mars suggests that these oriented hematite crystals most likely occur as bedrock of aligned specular hematite grains (possibly schistose in texture) or as a secondary coating on bedrock, rather than as discrete particles. We are investigating the nature of this vast hematite deposit in order to understand better the geologic setting and infer past conditions and geological evolution on Mars.

Lane, M. D.↗