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NASA NTRS2018

The Challenges of Measuring Methane from Space with a Lidar

The global and regional quantification of methane fluxes and identification of its sources and sinks has been highlighted as one of the goals of the NASA 2017 Earth Science Decadal Survey. Detecting methane from space and airborne platforms with an active (laser) remote sensing instrument presents several unique technology and measurement challenges. The instrument must have a single frequency, narrow-linewidth light source, and photon-sensitive detector at the right spectral region to make continuous measurements from orbit, day and night, all seasons and at all latitudes. It must have a high signal to noise ratio and must be relatively immune to biases from aerosol/cloud scattering, spectroscopic and meteorological data uncertainties, and instrument systematic errors. At Goddard Space Flight Center (GSFC), in collaboration with industry, we have developed an airborne instrument to measure methane. Our instrument is a nadir-viewing lidar that uses Integrated Path Differential Absorption (IPDA), to measure methane near 1.65 µm. We sample the absorption line using multiple wavelengths from a narrow linewidth laser source and a sensitive photodetector. This measurement approach provides maximum information content about the CH4 column, and minimizes biases in the XCH4 retrieval. In this paper, we will review our progress to date and discuss the technology challenges, options and tradeoffs to measure methane from space and airborne platforms.

airborne instruments↗

DOE OSTI2021

Carbonyl Identification and Quantification Uncertainties for Oxidative Polymer Degradation

The most revealing indicator for oxidative processes or state of degraded plastics is usually carbonyl formation, a key step in materials degradation as part of the carbon cycle for man-made materials. Hence, the identification and quantification of carbonyl species with infrared spectroscopy have been the method of choice for generations, thanks to their strong absorbance and being an essential intermediate in carbon oxidation pathways. Despite their importance, precise identification and quantification can be challenging and rigorous fully traceable data are surprisingly rare in the existing literature. An overview of the complexity of carbonyl quantification is presented by the screening of reference compounds in solution with transmission and polymer films with ATR IR spectroscopy, and systematic data analyses. Significant variances in existing data and their past use have been recognized. Guidance is offered how better measurements and data reporting could be accomplished. Experimental variances depend on the combination of uncertainty in exact carbonyl species, extinction coefficient, contributions from neighboring convoluting peaks, matrix interaction phenomena and instrumental variations in primary IR spectral acquisition (refractive index and penetration depth for ATR measurements). In addition, diverging sources for relevant extinction coefficients may exist, based on original spectral acquisition. For common polymer degradation challenges, a relative comparison of carbonyl yields for a material is easily accessible, but quantification for other purposes, such as degradation rates and spatially dependent interpretation, requires thorough experimental validation. All variables featured in this overview demonstrate the significant error margins in carbonyl quantification, with exact carbonyl species and extinction coefficients already being major contributors on their own.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Dark Energy Survey Identification of A Low-Mass Active Galactic Nucleus at Redshift 0.823 from Optical Variability

We report the identification of a low-mass active galactic nucleus (AGN), DES J0218−0430, in a redshift z = 0.823 galaxy in the Dark Energy Survey (DES) Supernova field. We select DES J0218−0430 as an AGN candidate by characterizing its long-term optical variability alone based on DES optical broad-band light curves spanning over 6 yr. An archival optical spectrum from the fourth phase of the Sloan Digital Sky Survey shows both broad Mg ii and broad H β lines, confirming its nature as a broad-line AGN. Archival XMM–Newton X-ray observations suggest an intrinsic hard X-ray luminosity of |$L_{{\rm 2-12\, keV}}\approx 7.6\pm 0.4\times 10^{43}$| erg s^−1, which exceeds those of the most X-ray luminous starburst galaxies, in support of an AGN driving the optical variability. Based on the broad H β from SDSS spectrum, we estimate a virial black hole (BH) mass of M_• ≈ 10^6.43–10^6.72 M_⊙ (with the error denoting the systematic uncertainty from different calibrations), consistent with the estimation from OzDES, making it the lowest mass AGN with redshift > 0.4 detected in optical. We estimate the host galaxy stellar mass to be M_* ≈ 10^10.5 ± 0.3 M_⊙ based on modelling the multiwavelength spectral energy distribution. DES J0218−0430 extends the M_•–M_* relation observed in luminous AGNs at z ∼ 1 to masses lower than being probed by previous work. Our work demonstrates the feasibility of using optical variability to identify low-mass AGNs at higher redshift in deeper synoptic surveys with direct implications for the upcoming Legacy Survey of Space and Time at Vera C. Rubin Observatory.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1975

A comparison of Skylab S-193 and aircraft views of surface roughness and a look toward SEASAT

An extensive aircraft underflight program was conducted along the Skylab groundpath for the purpose of documenting wind, wave, and atmospheric conditions affecting the amplitude of the active and passive microwave signatures. The S-193 microwave system senses a roughness parameter at the ocean surface that is proportional to the surface windspeed. The aircraft program is described, and some comparisons of satellite and aircraft results are presented. The principal result of the comparison of active radar is that direct inferences of the surface windspeed are possible, but subject to considerable scatter, and that this scatter appears to be due to interaction between long gravity and short Bragg waves and backscatter due to rain as well as errors in correcting for azimuth dependence. An unforeseen opportunity to observe a Pacific hurricane by both Skylab and NOAA aircraft has contributed to the development of a simplified wave forecasting scheme applicable to hurricanes, and more general conditions, which combines the better qualities of both spectral and height/period forecasting techniques. Horizontal polarization data obtained by the aircraft in Hurricane Ava, and in other experiments, which led to this development are presented.

Ross, D.↗

NASA NTRS1992

Runge-Kutta methods combined with compact difference schemes for the unsteady Euler equations

Recent development using compact difference schemes to solve the Navier-Stokes equations show spectral-like accuracy. A study was made of the numerical characteristics of various combinations of the Runge-Kutta (RK) methods and compact difference schemes to calculate the unsteady Euler equations. The accuracy of finite difference schemes is assessed based on the evaluations of dissipative error. The objectives are reducing the numerical damping and, at the same time, preserving numerical stability. While this approach has tremendous success solving steady flows, numerical characteristics of unsteady calculations remain largely unclear. For unsteady flows, in addition to the dissipative errors, phase velocity and harmonic content of the numerical results are of concern. As a result of the discretization procedure, the simulated unsteady flow motions actually propagate in a dispersive numerical medium. Consequently, the dispersion characteristics of the numerical schemes which relate the phase velocity and wave number may greatly impact the numerical accuracy. The aim is to assess the numerical accuracy of the simulated results. To this end, the Fourier analysis is to provide the dispersive correlations of various numerical schemes. First, a detailed investigation of the existing RK methods is carried out. A generalized form of an N-step RK method is derived. With this generalized form, the criteria are derived for the three and four-step RK methods to be third and fourth-order time accurate for the non-linear equations, e.g., flow equations. These criteria are then applied to commonly used RK methods such as Jameson's 3-step and 4-step schemes and Wray's algorithm to identify the accuracy of the methods. For the spatial discretization, compact difference schemes are presented. The schemes are formulated in the operator-type to render themselves suitable for the Fourier analyses. The performance of the numerical methods is shown by numerical examples. These examples are detailed. described. The third case is a two-dimensional simulation of a Lamb vortex in an uniform flow. This calculation provides a realistic assessment of various finite difference schemes in terms of the conservation of the vortex strength and the harmonic content after travelling a substantial distance. The numerical implementation of Giles' non-refelctive equations coupled with the characteristic equations as the boundary condition is discussed in detail. Finally, the single vortex calculation is extended to simulate vortex pairing. For the distance between two vortices less than a threshold value, numerical results show crisp resolution of the vortex merging.

Yu, Sheng-Tao↗

NASA NTRS2000

Evaluation of the Applicability of Solar and Lamp Radiometric Calibrations of a Precision Sun Photometer Operating Between 300 and 1025 nm

Over a period of 3 year a precision Sun photometer (SPM) operating between 300 and 1025 nm was calibrated four times at three different high-mountain sites in Switzerland, Germany, and the United States by means of the Langley-plot technique. We found that for atmospheric window wavelengths the total error (2 sigma-statistical plus systematic errors) of the calibration constants V(sub 0)(lambda), the SPM voltage in the absence of any attenuating atmosphere, can be kept below 1.60% in the UV-A and blue, 0.9% in the mid-visible, and 0.6% in the near-infra red spectral region. For SPM channels within strong water-vapor or ozone absorption bands a modified Langley-plot technique was used to determine V(sub 0)(lambda) with a lower accuracy. Within the same period of time, we calibrated the SPM five times using irradiance standard lamps in the optical labs of the Physikalisch-Meteorologisches Observatorium Davos and World Radiation Center, Switzerland, and of the Remote Sensing Group of the Optical Sciences Center, University of Arizona, Tucson, Arizona. The lab calibration method requires knowledge of the extraterrestrial spectral irradiance. When we refer the standard lamp results to the World Radiation Center extraterrestrial solar irradiance spectrum, they agree with the Langley results within 2% at 6 or 13 SPM wavelengths. The largest disagreement (4.4%) is found for the channel centered at 610 nm. The results of these intercomparisons change significantly when the lamp results are referred to two different extraterrestrial solar irradiance spectra that have become recently available.

Schmid, Beat↗

NASA NTRS2016

Derivation and Validation of Supraglacial Lake Volumes on the Greenland Ice Sheet from High-Resolution Satellite Imagery

Supraglacial meltwater lakes on the western Greenland Ice Sheet (GrIS) are critical components of its surface hydrology and surface mass balance, and they also affect its ice dynamics. Estimates of lake volume, however, are limited by the availability of in situ measurements of water depth,which in turn also limits the assessment of remotely sensed lake depths. Given the logistical difficulty of collecting physical bathymetric measurements, methods relying upon in situ data are generally restricted to small areas and thus their application to largescale studies is difficult to validate. Here, we produce and validate spaceborne estimates of supraglacial lake volumes across a relatively large area (1250 km(exp 2) of west Greenland's ablation region using data acquired by the WorldView-2 (WV-2) sensor, making use of both its stereo-imaging capability and its meter-scale resolution. We employ spectrally-derived depth retrieval models, which are either based on absolute reflectance (single-channel model) or a ratio of spectral reflectances in two bands (dual-channel model). These models are calibrated by usingWV-2multispectral imagery acquired early in the melt season and depth measurements from a high resolutionWV-2 DEM over the same lake basins when devoid of water. The calibrated models are then validated with different lakes in the area, for which we determined depths. Lake depth estimates based on measurements recorded in WV-2's blue (450-510 nm), green (510-580 nm), and red (630-690 nm) bands and dual-channel modes (blue/green, blue/red, and green/red band combinations) had near-zero bias, an average root-mean-squared deviation of 0.4 m (relative to post-drainage DEMs), and an average volumetric error of b1%. The approach outlined in this study - image-based calibration of depth-retrieval models - significantly improves spaceborne supraglacial bathymetry retrievals, which are completely independent from in situ measurements.

Spectrally-based depth-retrieval models↗

DOE OSTI2022

Harmonizing solar induced fluorescence across spatial scales, instruments, and extraction methods using proximal and airborne remote sensing: A multi-scale study in a soybean field

Solar-induced chlorophyll fluorescence (SIF) has been widely used to track vegetation photosynthesis at different scales ranging from in-situ measurements to satellite products. Airborne platforms sample SIF data at a spatial scale intermediate between in-situ and satellite, matching that of ground measurement (e.g. flux tower footprints and other field sampling), enabling us to explore causes of SIF variation and validate satellite-based SIF products. However, harmonizing SIF across sensors and platforms (correcting for systematic errors to yield a consistent, comparable SIF product) is challenging because SIF can be retrieved in different absorption windows, with different instruments and methods complicating the comparison between different observational levels (i.e., ground, airborne, satellites) and between sites equipped with different instruments with varying optical properties (spectral resolution and sampling intervals, spatial resolution). Additionally, the spatial and temporal variability of atmospheric properties can influence the retrieval of the weak SIF signal. Because of these complications, direct comparisons of airborne and ground SIF across scales are rarely attempted. Here, in this study, we combined airborne SIF data with simultaneous ‘ground truth’ data collected by stationary and mobile platforms in a soybean field in Nebraska, USA. In this effort, we tested several SIF extraction methods, including Fraunhofer Line Discrimination (FLD), improved Fraunhofer Line Discrimination (iFLD), Spectral Fitting Method (SFM), SpecFit, and a Singular Vector Decomposition (SVD) method. The SpecFit method was sensitive to the 715–740 nm water bands and removing the water bands in the fitting process yielded better agreement between the airborne and ground SIF spectra. Accurate estimation of the ground level downwelling irradiance obtained by ground measurements over a calibration target improved agreement between airborne and ground SIF retrievals at the O 2 A band, and allowed us to derive a SIF dataset with improved agreement across platforms and sampling scales. This experimental approach provided a method for generating comparable SIF signals across instruments, methods and platforms, which is critical to understanding the SIF-GPP relationship at different scales and to cross-validate the diversity of platforms used for satellite products calibration and validation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Implementation of stacked ensemble machine learning for the detection of surrogate plutonium contamination in soil via LIBS

Supervised machine learning methods have demonstrated increased utility for the quantification of lanthanide and actinide elements in atomic spectroscopy applications. This study implements laser-induced breakdown spectroscopy (LIBS) for the identification of plutonium surrogate material (CeO 2 ) in soil matrices by training supervised machine learning methods on the recorded spectral data. A bagged ensemble using Random Forest yields the highest sensitivity predictions with a detection limit of 0.015 wt.% CeO 2 . However, high precision in Ce content prediction required the use of a stacked ensemble regression, which provided the superlative Ce quantification model with an error of 0.107% and a detection limit of 0.022 wt.%. Furthermore, the high performance of the stacked ensemble demonstrates its potential to enhance the accuracy and sensitivity of nuclear contaminant detection using field-deployable spectroscopic analyzers in real-world scenarios.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Near-optimal ground state preparation

Preparing the ground state of a given Hamiltonian and estimating its ground energy are important but computationally hard tasks. However, given some additional information, these problems can be solved efficiently on a quantum computer. We assume that an initial state with non-trivial overlap with the ground state can be efficiently prepared, and the spectral gap between the ground energy and the first excited energy is bounded from below. With these assumptions we design an algorithm that prepares the ground state when an upper bound of the ground energy is known, whose runtime has a logarithmic dependence on the inverse error. When such an upper bound is not known, we propose a hybrid quantum-classical algorithm to estimate the ground energy, where the dependence of the number of queries to the initial state on the desired precision is exponentially improved compared to the current state-of-the-art algorithm proposed in [Ge et al. 2019]. These two algorithms can then be combined to prepare a ground state without knowing an upper bound of the ground energy. We also prove that our algorithms reach the complexity lower bounds by applying it to the unstructured search problem and the quantum approximate counting problem.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1978

The simultaneous inference of stratospheric trace gases with overlapping spectral signatures using limb sounding radiometry

An inversion algorithm has been developed to simultaneously infer the concentrations of two gases with overlapping spectral signatures using limb emission measurements. The algorithm is efficient and provides a solution in two or three iterations. It has been applied in a simulation study to the inference of stratospheric NO2-H2O and HNO3-CF2Cl2. Existing satellite instrumentation was the basis for errors used in the calculations. It is estimated that concentrations of all four gases can be determined with errors of about 20 percent. This assumes an estimated 1980 CF2Cl2 level. Also, other error sources due to contaminant gas, aerosol emission, and the temperature profile must be included to obtain a better estimate of experimental accuracies.

Russell, J. M., III↗

NASA NTRS1981

A high precision Solar Ultraviolet Spectral Irradiance Monitor for the wavelength region 120-400 nm

There exists a growing need to improve the accuracy of measurement of the absolute solar flux within the wavelength range 120-400 nm. Although full-disk solar fluxes and variations thereof in the 120-400 nm region are required to model the solar atmosphere, current increased interest in the measurements arises from their importance in modeling the terrestrial atmosphere. The Solar Ultraviolet Spectral Irradiance Monitor (SUSIM) experiment under development for flight aboard the Space Shuttle and the Upper Atmospheric Research Satellite is described. SUSIM will monitor the solar flux in the 120-144 nm region with high precision, using an in-flight calibration system to reduce absolute error to less than 10%, and error relative to the 400 nm continuum to less than 1%.

Vanhoosier, M. E.↗

NASA NTRS1990

Calibration of long term satellite ozone data sets using the space shuttle

Trends in atmospheric ozone continue to be an environmental concern. Drifts in satellite observations are the major obstacle in the detection of changes in global ozone over the long term. Careful re-analysis of satellite ozone data along with groundbased observations have more or less corroborated photochemical models which predict ozone depletion. However, there remains the margin of error in the observations that is as large as the trend itself. The National Plan for Stratospheric Monitoring calls for monitoring global ozone for at lease the next ten years employing the NOAA polar orbiting satellites. Ozone observations will be made with the Solar Backscatter Ultraviolet Spectral Radiometer Mod 2 (SBUV/2) which ia a refinement of the SBUV instrument flying on NASA's Nimbus-7 satellite. The first instrument in the operational series began taking data from the NOAA-9 spacecraft in February 1985. A second instrument was launched on NOAA-11 in September 1988. Both continue to operate. Earlier attempts to calibrate satellite data relied on comparisons with ground based observations. However, differences in instrumental techniques severely complicated these efforts. This problem will be over come by regular flights, about once per year, of the Shuttle Solar Backscatter Ultraviolet radiometer (SSBUV). The data from the SSBUV instrument will be compared with nearly coincident data taken by the NOAA satellite instruments. This procedure will permit a direct calibration transfer in space, since the two instruments observe the same qualities thereby bypassing the inversion algorithm which converts the observations to ozone amounts.

Hilsenrath, Ernest↗

NASA NTRS1999

Sensitivity Analysis of Aerosol Retrieval Algorithms Using Two-Channel Satellite Radiance Data

We discuss the methodology of interpreting channel 1 and 2 AVHRR radiance data to retrieve tropospheric aerosol properties over the ocean and describe a detailed analysis of the sensitivity of monthly average retrievals to the assumed aerosol models. We use real AVHRR data and accurate numerical techniques for computing single and multiple scattering and spectral absorption of light in the vertically inhomogeneous atmosphere-ocean system. Our analysis shows that two-channel algorithms can provide significantly more accurate retrievals of the aerosol optical thickness than one-channel algorithms and that imperfect cloud screening is the largest source of errors in the retrieved optical thickness. Both underestimating and overestimating aerosol absorption as well as strong variability of the aerosol refractive index may lead to regional and/or seasonal biases in optical thickness retrievals. The Angstrom exponent appears to be the most invariant aerosol size characteristic and should be retrieved along with optical thickness as the second aerosol parameter.

Geogdzhayev, Igor V.↗

NASA NTRS2003

Unstructured Adaptive Meshes: Bad for Your Memory?

This viewgraph presentation explores the need for a NASA Advanced Supercomputing (NAS) parallel benchmark for problems with irregular dynamical memory access. This benchmark is important and necessary because: 1) Problems with localized error source benefit from adaptive nonuniform meshes; 2) Certain machines perform poorly on such problems; 3) Parallel implementation may provide further performance improvement but is difficult. Some examples of problems which use irregular dynamical memory access include: 1) Heat transfer problem; 2) Heat source term; 3) Spectral element method; 4) Base functions; 5) Elemental discrete equations; 6) Global discrete equations. Nonconforming Mesh and Mortar Element Method are covered in greater detail in this presentation.

Biswas, Rupak↗

NASA NTRS2022

Estimating Species-Specific Leaf Area Index and Basal Area Using Optical and SAR Remote Sensing Data in Acadian Mixed Spruce-Fir Forests, USA

This study combined Sentinel-1 synthetic aperture radar (SAR), Sentinel-2 multispectral, and site variable datasets to model leaf area index (LAI) and basal area per ha (BAPH) of two economically important tree species in Northeast, USA; red spruce (Picea rubens Sarg.; RS), and balsam fir (Abies balsamea (L.) Mill.; BF). We used Random Forest (RF), and Multi-Layer Perceptron (MLP) algorithms for LAI and BAPH modeling. The results showed that RF outperformed MLP by reducing the normalized root mean square error (nRMSE) by 0.01 and 0.06 for LAI and BAPH, respectively. The final variables selected for modeling of both LAI and BAPH indicated the superiority of Sentinel-2 variables over the Sentinel-1 SAR with minor contributions of site variables (mainly elevation). The red-edge spectral vegetation indices played a significant role in both LAI and BAPH estimation. We attained the lowest nRMSEs of 0.12, and 0.16 for the final LAI model of RS, and BF, respectively using Sentinel-2 and site variables. The lowest nRMSE for both RS and BF BAPH models was 0.12. As RS and BF are the primary host species for a cyclically occurring and most destructive pest of the region, eastern spruce budworm (Choristoneura fumiferana; SBW), these estimations will be useful to evaluate SBW dynamics in the region.

Forest inventory↗

DOE OSTI2022

Impact of time-correlated noise on zero-noise extrapolation

Zero-noise extrapolation is a quantum error mitigation technique that has typically been studied under the ideal approximation that the noise acting on a quantum device is not time correlated. In this paper, we investigate the feasibility and performance of zero-noise extrapolation in the presence of time-correlated noise. We show that, in contrast to white noise, time-correlated noise is harder to mitigate via zero-noise extrapolation because it is difficult to scale the noise level without also modifying its spectral distribution. This limitation is particularly strong if “local” gate-level methods are applied for noise scaling. Furthermore, we find that “global” noise-scaling methods, e.g., global unitary folding, can be sufficiently reliable even in the presence of time-correlated noise.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS2008

Current Sounding Capability From Satellite Meteorological Observation With Ultraspectral Infrared Instruments

Ultraspectral resolution infrared spectral radiance obtained from near nadir observations provide atmospheric, surface, and cloud property information. The intent of the measurement of tropospheric thermodynamic state and trace abundances is the initialization of climate models and the monitoring of air quality. The NPOESS Airborne Sounder Testbed-Interferometer (NAST-I), designed to support the development of future satellite temperature and moisture sounders, aboard high altitude aircraft has been collecting data throughout many field campaigns. An advanced retrieval algorithm developed with NAST-I is now applied to satellite data collected with the Atmospheric InfraRed Sounder (AIRS) on the Aqua satellite launched on 4 May 2002 and the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp satellite launched on October 19, 2006. These instruments possess an ultra-spectral resolution, for example, both IASI and NAST-I have ~0.25 cm-1 and a spectral coverage from 645 to 2760 cm-1. The retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. The physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with relatively high accuracy (i.e., error less than 1 km). Retrievals of atmospheric soundings, surface properties, and cloud microphysical properties with the AIRS and IASI observations are obtained and presented. These retrievals are further inter-compared with those obtained from airborne FTS system, such as the NPOESS Airborne Sounder Testbed? Interferometer (NAST I), dedicated dropsondes, radiosondes, and ground based Raman Lidar. The capabilities of satellite ultra-spectral sounder such as the AIRS and IASI are investigated. These advanced satellite ultraspectral infrared instruments are now playing an important role in satellite meteorological observation for numerical weather prediction.

Zhou, Daniel K.↗