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NASA NTRS2016

The Effects of High Density on the X-ray Spectrum Reflected from Accretion Discs Around Black Holes

Current models of the spectrum of X-rays reflected from accretion discs around black holes and other compact objects are commonly calculated assuming that the density of the disc atmosphere is constant within several Thomson depths from the irradiated surface. An important simplifying assumption of these models is that the ionization structure of the gas is completely specified by a single, fixed value of the ionization parameter (xi), which is the ratio of the incident flux to the gas density. The density is typically fixed at n(sub e) = 10(exp 15) per cu cm. Motivated by observations, we consider higher densities in the calculation of the reflected spectrum. We show by computing model spectra for n(sub e) approximately greater than 10(exp 17) per cu cm that high-density effects significantly modify reflection spectra. The main effect is to boost the thermal continuum at energies 2 approximately less than keV. We discuss the implications of these results for interpreting observations of both active galactic nuclei and black hole binaries. We also discuss the limitations of our models imposed by the quality of the atomic data currently available.

accretion↗
NASA NTRS2015

Role of Multiple Atmospheric Reflections in Formation of Electron Distribution Function in the Diffuse Aurora Region

The precipitation of high-energy magnetospheric electrons (E greater than 500-600 electronvolts) in the diffuse aurora contributes significant energy flux into Earth's ionosphere. In the diffuse aurora, precipitating electrons initially injected from the plasmasheet via wave-particle interaction processes degrade in the atmosphere toward lower energies and produce secondary electrons via impact ionization of the neutral atmosphere. These initially precipitating electrons of magnetospheric origin can be additionally reflected back into the magnetosphere by the two magnetically conjugated atmospheres, leading to a series of multiple reflections that can greatly influence the initially precipitating flux at the upper ionospheric boundary (700-800 kilometers) and the resultant population of secondary electrons and electrons cascading toward lower energies. We present the solution of the Boltzmann.Landau kinetic equation that uniformly describes the entire electron distribution function in the diffuse aurora, including the affiliated production of secondary electrons (E is less than or equal to 600 electronvolts) and their energy interplay in the magnetosphere and two conjugated ionospheres. This solution takes into account the role of multiple atmospheric reflections of the precipitated electrons that were initially moved into the loss cone via wave.particle interaction processes in Earth's plasmasheet.

Khazanov, George V.↗
NASA NTRS2017

First Optical Observations of Interhemispheric Electron Reflections Within Pulsating Aurora

A case study of a pulsating auroral event imaged optically at high time resolution presents direct observational evidence in agreement with the interhemispheric electron bouncing predicted by the Super Thermal Electron Transport model. Pulsation-on times are identified and subsequent equally spaced fainter pulsations are also noted and can be explained by a portion/percentage of the primary precipitating electrons reflecting upward from the ionosphere, traveling to the opposite hemisphere and reflecting upward again. The high time resolution of these data, combined with the short duration of the pulsation-on time (approx. 1 s) and the relatively long spacing between pulsations (approx. 6 to 9 s) made it possible to observe the faint optical pulses caused by the reflected electrons coming from the opposite hemisphere.

thermal↗
NASA NTRS2018

Land Surface Reflectances from Geostationary Sensors

GEONEX is a processing pipeline that produces a suite of satellite land surface products using data streams from the latest geostationary (GEO) sensors including the GOES016/ABI and the Himawari-8/AHI. The suite, created collaboratively by scientists from NASA and NOAA, includes top-of-atmosphere (TOA) reflectances, land surface reflectances (LSRs), vegetation indices, LAI/fPAR, and other downstream products. As a key component of the GEONEX product processing, we have adapted the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm to produce LSRs from the TOA data. Because the algorithm depends on building "stacks" of images, we first run internal geo-registration checks to ensure geo-spatial accuracy and consistency of the input (L1B) data before transferring them from the geostationary projection into a tile system in geographic grids. Scan-time is inferred from metadata and applied to calculate the sun-sensor angles for each grid cell. The MAIAC algorithm is run to detect clouds/shadows, estimate aerosol optical thickness (AOT), perform atmospheric corrections, and generate LSRs. We have processed 18-months (from 2016/04 onward) of AHI data over East Asia and Oceania at a 10-minute time step and 10-months (from 2018/01 onward) of ABI data over North and South Americas at a 15-minute time step. As a verification measure, we compare the GEONEX (AHI/ABI) surface reflectances with the standard MODIS products (MOD09GA) and the MODIS MAIAC products over pixels that have similar sun-view geometries. The results indicate general linear relationships between GEONEX and corresponding MODIS LSRs. In particular, the RMSEs between GEONEX and MOD09 data are comparable to those between MOD09 and MODIS MAIAC products, suggesting that the uncertainties of GEONEX LSRs fall into an acceptable range. However, direct comparisons of LSRs over pixels with different sun-view angles are not as straightforward and require more modeling efforts to correct the directional effects. Evaluation of such angular influences on the downstream products (e.g., vegetation indices) is also under investigation.

Geostationary satellite; Remote Sensing; Atmospher↗
NASA NTRS2018

Initial Assessment of Radiometric Performance of N20 VIIRS Reflective Solar Bands Using Vicarious Approaches

The newly launched (November 18, 2017) polar-orbiting satellite of the Joint Polar Satellite System (JPSS-1), now transitioned to NOAA-20, is the follow-on mission to the SNPP (Suomi National Polar-orbiting Partnership) satellite, launched six years ago. NOAA-20 leads SNPP by a half orbit or about 50 minutes. The Visible Infrared Imaging Radiometer Suite (VIIRS) is a key sensor onboard both NOAA-20 and SNPP spacecraft with nearly identical band spectral responses. Similar to the heritage sensor MODIS, VIIRS has on-board calibration components including a solar diffuser (SD) and a solar diffuser stability monitor (SDSM) for the reflective solar bands (RSB), a V-groove blackbody for the thermal emissive bands (TEB), and a space view (SV) as background reference for calibration. This study provides an initial assessment of calibration of the NOAA-20 VIIRS reflective solar bands (RSB) by inter-comparison with measurements from SNPP VIIRS using various vicarious approaches. The first approach is based on a double difference method using observations from simultaneous nadir overpasses (SNO) with Aqua MODIS. The second is from the collected reflectances over the widely used Liby-4 desert site from 16-day repeatable orbits so each data point has the same viewing geometry relative to the site. The third approach is to use the frequent overpasses over the Dome C snow site. Results of this study provide useful information on NOAA-20 VIIRS post-launch calibration assessment and preliminary analysis of its calibration stability and consistency for the first 6 months

Wu, Aisheng↗
NASA NTRS2019

3-μm Reflectance Spectroscopy of Carbonaceous Chondrites Under Asteroid-Like Conditions

We measured 3-μm reflectance spectra of 21 meteorites that represent all carbonaceous chondrite types available in terrestrial meteorite collections. The measurements were conducted at the Laboratory for Spectroscopy under Planetary Environmental Conditions (LabSPEC) at the Johns Hopkins University Applied Physics Laboratory (JHU APL) under asteroid-like conditions (vacuum at room temperature after slight overnight heating at T < 400 K). This is the most comprehensive 3-μm dataset of carbonaceous chondrites ever acquired in environments similar to the ones experienced by asteroids. The 3-μm reflectance spectra are extremely important for direct comparisons with and appropriate interpretations of reflectance data from ground-based telescopic and spacecraft observations of asteroids. We found good agreement between 3-μm spectral characteristics of carbonaceous chondrites and carbonaceous chondrite classifications. The 3-μm band is diverse, indicative of varying composition, thus suggesting that these carbonaceous chondrites experienced distinct parent body aqueous alteration and metamorphism environments. The spectra of CI chondrites, from which significant amount of water adsorbed under ambient conditions was removed, are consistent with Mg-serpentine and clay minerals. The high abundances of organics in CI chondrites is also associated with the mineralogy of these chondrites, oxyhydroxides- and complex clay minerals-rich. CM chondrites, which are cronstedtite-rich, have shallower 3-μm band than CI chondrites, suggesting they experienced less aqueous alteration. CR chondrites showed moderate aqueous alteration relative to CI and CM chondrites. CV chondrites, except for Efremovka, have a very shallow 3-μm band, consistent with their lower phyllosilicate proportions. CO chondrites, like most CVs, have a very shallow 3-μm spectra that suggest they experienced minor aqueous alteration. The 3-μm band in CH/CBb is deep and broad centered ~ 3.11 μm, possibly due the high abundance of FeNi metal and presence of heavily hydrated clasts in these chondrites. The 3-μm spectra of Essebi (C2-ung) and EET 83226 are more consistent with CM chondrites’ spectra. The 3-μm spectra of Tagish lake (C2-ung), on the other hand, are consistent with CI chondrites. None of these spectral details could have been resolved without removing the adsorbed water before acquiring spectra.

Driss Takir↗
NASA NTRS2017

The Sensitivity of Ground-Reflected GNSS Signals to Near-Surface Soil Moisture, as Recorded by Spaceborne Receivers

Spatial and temporal variations in near-surface soil moisture are important to measure for climate studies, numerical weather forecasts, and drought monitoring. Several previous studies have shown success in using ground-reflected Global Navigation Satellite System (GNSS) signals as a form of bistatic radar to sense soil moisture. However, the ability of this type of data to sense soil moisture variations from space is still a nascent field of study. In the past two years, three satellites have been launched that were either designed to capture ground-reflected GNSS signals or have been modified to record these signals. The data provided by these satellites are giving scientists an unprecedented opportunity to investigate their ability to detect changes in Earth’s land surface, including but certainly not limited to near-surface soil moisture. This paper will present spaceborne observations of ground-reflected GNSS signals and evaluate their sensitivity to near-surface soil moisture. This sensitivity will be compared to empirical and theoretical sensitivities of monostatic L-band radar measurements to soil moisture. We will also comment on possibilities for retrieval algorithm development, using techniques employed for monostatic radar as a guide.

Chew, C.↗
NASA NTRS2017

Generating Land Surface Reflectance for the New Generation of Geostationary Satellite Sensors with the MAIAC Algorithm

The latest generation of geostationary satellite sensors, including the GOES-16/ABI and the Himawari 8/AHI, provide exciting capability to monitor land surface at very high temporal resolutions (5-15 minute intervals) and with spatial and spectral characteristics that mimic the Earth Observing System flagship MODIS. However, geostationary data feature changing sun angles at constant view geometry, which is almost reciprocal to sun-synchronous observations. Such a challenge needs to be carefully addressed before one can exploit the full potential of the new sources of data. Here we take on this challenge with Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm, recently developed for accurate and globally robust applications like the MODIS Collection 6 re-processing. MAIAC first grids the top-of- atmosphere measurements to a fixed grid so that the spectral and physical signatures of each grid cell are stacked (“remembered”) over time and used to dramatically improve cloud/shadow/snow detection, which is by far the dominant error source in the remote sensing. It also exploits the changing sun-view geometry of the geostationary sensor to characterize surface BRDF with augmented angular resolution for accurate aerosol retrievals and atmospheric correction. The high temporal resolutions of the geostationary data indeed make the BRDF retrieval much simpler and more robust as compared with sun-synchronous sensors such as MODIS. As a prototype test for the geostationary-data processing pipeline on NASA Earth Exchange (GEONEX), we apply MAIAC to process 18 months of data from Himawari 8/AHI over Australia. We generate a suite of test results, including the input TOA reflectance and the output cloud mask, aerosol optical depth (AOD), and the atmospherically-corrected surface reflectance for a variety of geographic locations, terrain, and land cover types. Comparison with MODIS data indicates a general agreement between the retrieved surface reflectance products. Furthermore, the geostationary results satisfactorily capture the movement of clouds and variations in atmospheric dust/aerosol concentrations, suggesting that high quality land surface and vegetation datasets from the advanced geostationary sensors can help complement and improve the corresponding EOS products.

geostationary satellite sensors↗
NASA NTRS2019

MODIS Aqua Reflective Solar Bands Calibration for NASA's R2018 Ocean Color Products

Remote sensing ocean color products have stringent requirements on radiometric calibration stability. To address a calibration deficiency in MODIS Aqua in recent years, the NASA Ocean Biological Processing Group (OBPG) developed a new calibration for the reflective solar bands. Prior to the reprocessing of NASA's ocean color products for 2018 (R2018), the OBPG MODIS products had been based on calibration provided by the MODIS Calibration Support Team (MCST). Several modifications were made to the MCST calibration approach to improve the calibration accuracy for ocean color products. These include: 1) apply 936nm detector normalization to solar diffuser stability monitor (SDSM) data to reduce coherent noise; 2) modeling solar diffuser (SD) degradation wavelength dependency to determine SD degradation in near-infrared and shortwave infrared wavelength; 3) detector gains are computed using SD screen-closed data to better match ocean radiance levels in all bands; 4) a simple atmospheric correction is performed to reduce bidirectional reflectance distribution function (BRDF) effects in desert trends; 5) modulated relative spectral response (RSR) impact on ocean data is estimated and used to adjust the calibration coefficients. 6) smoothing is used to characterize the temporal change in calibration, and response versus scan angle (RVS) changes are characterized using 2nd order polynomials to improve spatial/temporal calibration stability. Relative to the previous R2014 ocean color products, the R2018 calibration removed the suspect late-mission global trends in blue-band water-leaving reflectance, and some anomalously large short-term variability (spikes) in the temporal trend of chlorophyll concentration. This paper will describe the OBPG calibration with a focus on the differences between the MCST and OBPG approaches.

calibration↗
NASA NTRS2019

Surface Reflectance Product from Geostationary Satellite

We have generated provisional Himawari-8 AHI surface reflectance (SR) product for land and vegetation monitoring. The Himawari-8 AHI surface reflectance product is part of our GeoNEX land products, which integrate level 2 and higher remote sensing data from a set of geostationary satellite sensors (i.e. GOES-16, -17 ABI, Himawari-8 AHI, FY4-A AGRI, and MTG-I). Adapted Multiangle Implementation of Atmospheric Correction (MAIAC) algorithm is used to process time series Himawari-8 AHI observations. Himawari-8 AHI SR provides gridded and tiled land SR in 1-km resolution with high frequency (every 10 minutes during daylight time). There are three subdatasets: 1) retrieved atmospheric properties (e.g. column water vapor at 0.86 m, aerosol optical depth at 0.47m and 0.51m); 2) spectral (AHI bands 1-6) surface reflectance, kernels of RTLS BRDF model; 3)spectral BRDF kernel weights, and extensive quality assurance flags. The evaluation results show that Himawari-8 AHI data yield much more valid pixels in a single day in the characterization of land surface, when compare to NASA flagship satellite MODIS Terra/Aqua. This observation frequency and resolution of geostationary data should allow for using continuous ecosystem monitoring in diurnal studies at continental scale. Initial evaluations indicate a stable Himawari-8 AHI land SR product.

Li, Shuang↗
NASA NTRSDate not supplied

Reflecting on Planning Models: A Challenge for Verification and Validation of Planning Systems

We discuss the opportunities for autonomous sys- tems to perform reflection on their planners by adapting the models used to build plans. We first describe model-based planning systems, a form of automated planning system driven by declarative models of the planning domain. These models include descriptions of the conditions and effects of actions on the state of the world. When planning the activities of cyber-physical systems, the command and data representation of the system must be formally abstracted to the actions and states described in the planning system model. When the execution of a plan either fails or produces unexpected outcomes, the execution trace can be abstracted and compared to the predicted state according to the planning model, producing a list of discrepancies; these discrepancies can then be used to fix the model. This provides part of a reflection capability, namely, a set of well-formed problems with the domain model, the abstractions, or both. The challenge lies in the rest of the reflection capability, namely, a set of techniques for changing the models or the abstractions. We discuss these challenges and describe some of the options for addressing them

Mission Planning↗
NASA NTRS2020

SCoBi Multilayer: A Signals of Opportunity Reflectometry Model for Multilayer Dielectric Reflections

A multilayer module is incorporated into the Signals of Opportunity (SoOp) Coherent Bistatic Scattering model (SCoBi) for determining the reflections and propagation of electric fields within a series of multilayer dielectric slabs. This module can be used in conjunction with other SCoBi components to simulate complex, bistatic simulation schemes that include features such as surface roughness, vegetation, antenna effects, and multilayer soil moisture interactions on reflected signals. This paper introduces the physics underlying the multilayer module and utilizes it to perform a simulation study of the response of SoOp-R measurements with respect to subsurface soil moisture parameters. For a frequency range of 100–2400 MHz, it is seen that the SoOp-R response to a single dielectric slab is mostly frequency insensitive; however, the SoOp-R response to multilayer dielectric slabs will vary between frequencies. The relationship between SoOp-R reflectivity and the contributing depth is visualized, and the results show that SoOp-R measurements can display sensitivity to soil moisture below the penetration depth. By simulation of simple soil moisture profiles with different wetting and drying gradients, the dielectric contrast between layers is shown to be the greatest contributing factor to subsurface soil moisture sensitivity. Overall, it is observed that different frequencies can sense different areas of a soil moisture profile, and this behavior can enable subsurface soil moisture data products from SoOp-R observations.

Dylan Boyd↗
NASA NTRS2020

Variations in color and reflectance on the surface of asteroid (101955) Bennu

Visible-wavelength color and reflectance provide information about the geologic history of planetary surfaces. Here we present multispectral images (0.44 to 0.89 micrometers) of near-Earth asteroid (101955) Bennu. The surface has variable colors overlain on a moderately blue global terrain. Two primary boulder types are distinguishable by their reflectance and texture. Space weathering of Bennu surface materials does not simply progress from red to blue (or vice versa). Instead, freshly exposed, redder surfaces initially brighten in the near-ultraviolet region (i.e., become bluer at shorter wavelengths), then brighten in the visible to near-infrared region, leading to Bennu’s moderately blue average color. Craters indicate that the time scale of these color changes is ~105 years. We attribute the reflectance and color variation to a combination of primordial heterogeneity and varying exposure ages.

D. N. DellaGiustina↗
NASA NTRSDate not supplied

MODIS Reflective Solar Band Calibration Improvements using Pseudo-Invariant Desert Targets

To provide the best science data quality, an accurate characterization of the response versus scan angle (RVS) function is critical for the MODIS reflective solar bands (RSB) on-orbit calibration. In every MODIS operational scan, the Earth’s surface, referred to here as Earth view (EV), the space view (SV) port, and the onboard calibrators are viewed via a two-sided scan mirror. The RVS is defined as the sensor’s relative response as a function the angle of incidence (AOI) to the scan mirror. Many different approaches have been developed to derive the time-dependent RVS and its look-up table (LUT) applied to MODIS Level 1B (L1B) products since calibration Collection 4. For most MODIS RSB, the on-board calibrators can reasonably track the RVS change with time. In practice, their RVS is derived using data from on-board calibrators and the EV mirror side ratio (for mirror side 2). For Terra bands 1-4, 8-10 and Aqua bands 1-4, 8-9, an enhancement has been employed in Collections 6 and 6.1 (C6/C6.1) by using Earth scene response trending from pseudo-invariant desert sites in addition to the onboard calibrators. The current C6/C6/1 RVS algorithm is focused on fitting the EV data at each AOI over time and then deriving the relative change at different AOI. The EV response trending is currently fitted with multiple segments over time. Alternatively, the EV responses can be fit first as a function of AOI before fitting temporally in order to reduce the dependence on the stability of the desert site. These pre-treatment methods on the EV data provide improvement in the derived calibration coefficients. However, evidence of insufficient calibration is still observed in the MODIS L1B reflectance data, especially in the form of differences between the mirror sides. In this paper, we review the current methodologies that utilize the EV response trends from the pseudo-invariant Libyan desert targets to supplement the gain derived from the onboard calibrators. An improvement is then proposed and investigated such that a sliding window average (SWA) is used to pre-process the raw EV data. The SWA parameters are carefully selected using trade-off studies to accurately track the Earth scene response trending in multiple cases to overcome the reflectance differences between two mirror sides. Calibration results show improvements for both Aqua and Terra MODIS RSB L1B data products. This new adjustment has been included in the recently delivered Collection 7 LUT that will be evident in the L1B products expected to be released in late 2021.

MODIS↗
NASA NTRS2021

Reflectivity, Emissivity, and Brightness from Multilayered Soil with Linearly Varying Permittivity at P- and L- bands

Passive sensing of root zone soil moisture is theoretically investigated using P and L band frequencies. The soil is considered to be a stratified medium. The reflectivity from the soil surface is found by considering the soil to be composed of a finely layered structure with layer widths that are small compared to a wavelength. A well-known transmission line algorithm is then used to compute the reflectivity at the surface. Emissivity is obtained as (1 – reflectivity). It assumed that the soil is at a constant temperature of 300o K when determining the brightness temperature. A soil moisture profile consisting of two homogeneous layers separated by a layer of linearly varying soil moisture is investigated. The study is made at an incident angle of 40O for horizontal polarization at 0.8 and 1.4 GHz. Two variations of the basic profile are considered: a transition from a layer of lesser moisture to a layer of greater moisture and the opposite. In both cases the P band signal shows greater penetration than the L band case. There is greater penetration in the transition to drier soils. In both cases the L band signals show sensitivity to only the upper surface of the soil as expected.

Ming Li↗
NASA NTRS2022

Intercalibration of the reflective solar bands of MODIS and MISR instruments on the Terra platform

As a part of NASA’s Earth Observing System (EOS), the Terra spacecraft was launched on December 18, 1999, with the goal of understanding the changes of the Earth, by examining the Earth’s hydrological, geophysical, and climatic processes. The MODIS and MISR instruments on the Terra platform, combined with their continuous operation, broad spectral coverage, and different spatial resolutions, have played an important role to achieve the goals of the EOS. Over two decades of successful operations, these multispectral imaging instruments have benefited a variety of scientific applications. Being on the same platform, the two sensors complement each other in terms of spatial coverage (and target viewing geometry) and facilitate synergistic applications using multispectral data. A consistent radiometric calibration between these sensors is a prerequisite for creating high quality science products from their observations. Both instruments underwent intensive prelaunch characterization and their on-orbit calibrations are monitored using their onboard calibrators. In this paper, we perform a calibration inter-comparison of the spectrally matching bands of the two instruments using vicarious techniques. These techniques include multiyear simultaneous views of the North African desert, North Atlantic Ocean, and Dome Concordia, therefore covering different reflectance regimes. Also included in this work are the near-simultaneous top-of-atmosphere (TOA) reflectance measurements from Railroad Valley, USA, as provided by the RadCalNet (converted to TOA), that are used as a calibration reference to compare the on-orbit observations between MODIS and MISR. Simultaneous overpasses from desert, ocean, Dome C, and RadCalNet over Railroad Valley reveal that the agreement between the four spectrally matching bands is within 3% for the time-period between 2014 and 2020. Also, observed are some long-term drifts in the TOA reflectance time-series from MISR for the red and NIR band that are expected to be corrected in a future calibration reprocess.

MODIS↗
NASA NTRSDate not supplied

Infrared Reflection Removal in Wind Tunnels using Polarization Theory

Infrared radiometry with infrared cameras allows for high spatial resolution, noncontact measurements in wind tunnel experiments and has been increasingly used to visualize flow features. Reflections from test section walls present a major challenge in collecting these measurements as it is difficult or impossible to separate them from the true model emission signal. This paper implements a method to quantitatively separate the reflections from the emission using polarization theory. Samples with a range of emissivities were tested, and in all samples the reflections were significantly reduced. This method will lead to more accurate radiometric and thermographic measurements in wind tunnel experiments.

Infrared↗
NASA NTRS2022

Southern Ocean Solar Reflection Biases in Cmip6 Models Linked to Cloud Phase and Vertical Structure Representations

Over the Southern Ocean (SO, 40˚S-70˚S), climate models have consistently underestimated solar reflection. Here we evaluate the relationship between cloud profiles, cloud phase and radiation over the SO in Coupled Model Intercomparison Project Phase 6 (CMIP6) models against Clouds and the Earth's Radiant Energy System (CERES) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). We find that the lack of solar reflection is slightly improved in CMIP6 models compared to CMIP5’s, attributable to a better representation of cloud fraction and phase. We show that clouds have a different vertical structure and radiative effect south and north of where the 0˚C isotherm meets the surface (~55˚S). Although the models capture the greater vertical extent of clouds south of 55˚S, they fail to reproduce the observed increase in solar reflection, which we pinpoint to cloud phase biases. Increasing CMIP6 supercooled liquid cloud opacity should help reduce their persistent SW biases.

Southern Ocean↗