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All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Retrieving Atmospheric Temperature and Moisture Profiles from NPP CRIS/ATMS Sensors Using Crimss EDR Algorithm

The Joint Polar Satellite System (JPSS) is a U.S. National Oceanic and Atmospheric Administration (NOAA) mission in collaboration with the U.S. National Aeronautical Space Administration (NASA) and international partners. The NPP Cross-track Infrared Microwave Sounding Suite (CrIMSS) consists of the infrared (IR) Crosstrack Infrared Sounder (CrIS) and the microwave (MW) Advanced Technology Microwave Sounder (ATMS). The CrIS instrument is hyperspectral interferometer, which measures high spectral and spatial resolution upwelling infrared radiances. The ATMS is a 22-channel radiometer similar to Advanced Microwave Sounding Units (AMSU) A and B. It measures top of atmosphere MW upwelling radiation and provides capability of sounding below clouds. The CrIMSS Environmental Data Record (EDR) algorithm provides three EDRs, namely the atmospheric vertical temperature, moisture and pressure profiles (AVTP, AVMP and AVPP, respectively), with the lower tropospheric AVTP and the AVMP being JPSS Key Performance Parameters (KPPs). The operational CrIMSS EDR an algorithm was originally designed to run on large IBM computers with dedicated data management subsystem (DMS). We have ported the operational code to simple Linux systems by replacing DMS with appropriate interfaces. We also changed the interface of the operational code so that we can read data from both the CrIMSS science code and the operational code and be able to compare lookup tables, parameter files, and output results. The detail of the CrIMSS EDR algorithm is described in reference [1]. We will present results of testing the CrIMSS EDR operational algorithm using proxy data generated from the Infrared Atmospheric Sounding Interferometer (IASI) satellite data and from the NPP CrIS/ATMS data.

Liu, X.↗
NASA NTRS2026

Incremental Learning for Passive Microwave Precipitation Retrievals using Advanced Technology Microwave Sounder

Spaceborne passive microwave (PMW) radiometry is central to global precipitation monitoring, yet retrieval uncertainties remain substantial, particularly for cross-track sounders whose variable footprints and channel configurations are optimized for atmospheric temperature and moisture profiling rather than precipitation. Consequently, existing operational products often exhibit angular-dependent biases, limited effective swath utilization, unrealistic rainfall probability distributions, and systematic misclassification of precipitation phase. These limitations are further compounded by the scarcity of globally accurate and representative precipitation observations, as training data from the Dual-frequency Precipitation Radar (DPR) and the Cloud Profiling Radar (CPR) are spatially sparse, lack uniform global coverage, and exhibit heterogeneous error characteristics across precipitation regimes. To address these challenges, this study presents a supervised retrieval algorithm that incrementally trains an ensemble of extreme gradient-boosted decision trees by augmenting base learners with pre-training on reanalysis data and post-training on coincident DPR and CPR observations matched with the Advanced Technology Microwave Sounder (ATMS). By transferring prior information from reanalysis to posterior constraints from radar observations and adopting a sequential detection–estimation strategy for precipitation phase and rate retrieval, the proposed approach yields retrievals across the full ATMS swath that are largely free from persistent deficiencies in current Global Precipitation Measurement (GPM) passive microwave operational products. In particular, the method resolves bimodal artifacts in rainfall retrievals and mitigates systematic high-latitude snowfall biases, including overestimation across the Arctic and underestimation across the Antarctic. Validation against independent Multi-Radar Multi-Sensor (MRMS) data over the Contiguous United States (CONUS) further demonstrates improved performance in precipitation phase detection and rate estimation relative to both reanalysis and current GPM PMW products.

Mahyar Garshasbi↗
DOE OSTI2024

Repainting the colour–mass diagrams by unearthing the green mountain: dust-rich S0 galaxies in the colour–(galaxy stellar mass) diagram, and the colour–(black hole mass) relations for dust-poor versus dust-rich galaxies

ABSTRACT Lenticular galaxies are notoriously misclassified as elliptical galaxies and, as such, a (disc inclination)-dependent correction for dust is often not applied to the magnitudes of dusty lenticular galaxies. This results in overly red galaxy colours, impacting their distribution in the colour–magnitude diagram. It is revealed how this has led to an underpopulation of the ‘green valley’ by hiding a ‘green mountain’ of massive dust-rich lenticular galaxies – known to be built from gas-rich major mergers – within the ‘red sequence’ of colour–(stellar mass) diagrams. Correcting for dust, a ‘green mountain’ appears at M*,gal ∼ 1011 M⊙, along with signs of an extension to lower masses producing a ‘green range’ or ‘green ridge’ on the green side of the ‘red sequence’ and ‘blue cloud.’ The ‘red sequence’ is shown to be comprised of two components: a red plateau defined by elliptical galaxies with a near-constant colour and by lower-mass dust-poor lenticular galaxies, which are mostly a primordial population but may include faded/transformed spiral galaxies. The presence of the quasi-triangular-shaped galaxy evolution sequence, previously called the ‘Triangal’, is revealed in the galaxy colour–(stellar mass) diagram. It tracks the speciation of galaxies and their associated migration through the diagram. The connection of the ‘Triangal’ to previous galaxy morphology sequences (Fork, Trident, and Comb) is also shown herein. Finally, the colour–(black hole mass) diagram is revisited, revealing how the dust correction generates a blue–green sequence for the spiral and dust-rich lenticular galaxies that is offset from a green–red sequence defined by the dust-poor lenticular and elliptical galaxies.

Graham, Alister W. (ORCID:0000000264969414)↗
NASA NTRS2008

Measurement of Atmospheric Composition from Geostationary Platforms

Satellite instruments flown since 1970 have had great success in elucidating the processes that control stratospheric ozone. In contrast, space-based data for tropospheric constituents that affect air quality and climate have only recently become available. While these datasets highlight the rapidly advancing capabilities of spacebased tropospheric sensors, they are also pointing to the limitations of sun-synchronous, low-earth orbiting (SSO/LEO) satellite platforms for making such measurements. In our talk we will highlight the science requirements for new missions and the technological and algorithmic approaches that we are developing to meet these requirements. From these studies a clear need for advanced atmospheric composition sensors has emerged that can be put on geostationary (GEO) platforms to provide 5 km horizontal resolution with 15-60 minutes repeat cycle. Such measurements have been high priority in the recently released Decadal Survey report by the US National Research Council. The need for GEO is driven not only by the science requirements to track rapidly changing pollution events but also by the need to provide altitude-resolved information about tropospheric constituents. Currently, with the exception of aerosols, it is not possible to derive profile information about lower tropospheric constituents from satellite measurements. New algorithmic approaches are being developed to obtain this information by combining UV and IR data, by monitoring the spatial and temporal structures of the constituents, and by using low-level clouds to separate boundary layer constituents from free troposphere. All these approaches require better spatial and temporal resolution than that provided by LEO sensors.

Bhartia, P. K.↗
NASA NTRS2010

Polar Mesospheric Clouds (PMCs) Observed by the Ozone Monitoring Instrument (OMI) on Aura

Backscattered ultraviolet (BUV) instruments designed for measuring stratospheric ozone profiles have proven to be robust tools for observing polar mesospheric clouds (PMCs). These measurements are available for more than 30 years, and have been used to demonstrate the existence of long-term variations in PMC occurrence frequency and brightness. The Ozone Monitoring Instrument (OMI) on the EOS Aura satellite provides new and improved capabilities for PMC characterization. OMI uses smaller pixels than previous BUV instruments, which increases its ability to identify PMCs and discern more spatial structure, and its wide cross-track viewing swath provides full polar coverage up to 90 latitude every day in both hemispheres. This cross-track coverage allows the evolution of PMC regions to be followed over several consecutive orbits. Localized PMC variations determined from OMI measurements are consistent with coincident SBUV/2 measurements. Nine seasons of PMC observations from OMI are now available, and clearly demonstrate the advantages of these measurements for PMC analysis.

DeLand, Matthew T.↗
NASA NTRS2016

Effect of Satellite Formations and Imaging Modes on Global Albedo Estimation

We confirm the applicability of using small satellite formation flight for multi-angular earth observation to retrieve global, narrow band, narrow field-of-view albedo. The value of formation flight is assessed using a coupled systems engineering and science evaluation model, driven by Model Based Systems Engineering and Observing System Simulation Experiments. Albedo errors are calculated against bi-directional reflectance data obtained from NASA airborne campaigns made by the Cloud Absorption Radiometer for the seven major surface types, binned using MODIS' land cover map - water, forest, cropland, grassland, snow, desert and cities. A full tradespace of architectures with three to eight satellites, maintainable orbits and imaging modes (collective payload pointing strategies) are assessed. For an arbitrary 4-sat formation, changing the reference, nadir-pointing satellite dynamically reduces the average albedo error to 0.003, from 0.006 found in the static reference case. Tracking pre-selected waypoints with all the satellites reduces the average error further to 0.001, allows better polar imaging and continued operations even with a broken formation. An albedo error of 0.001 translates to 1.36 W/sq m or 0.4% in Earth's outgoing radiation error. Estimation errors are found to be independent of the satellites' altitude and inclination, if the nadir-looking is changed dynamically. The formation satellites are restricted to differ in only right ascension of planes and mean anomalies within slotted bounds. Three satellites in some specific formations show average albedo errors of less than 2% with respect to airborne, ground data and seven satellites in any slotted formation outperform the monolithic error of 3.6%. In fact, the maximum possible albedo error, purely based on angular sampling, of 12% for monoliths is outperformed by a five-satellite formation in any slotted arrangement and an eight satellite formation can bring that error down four fold to 3%. More than 70% ground spot overlap between the satellites is possible with 0.5deg of pointing accuracy, 2 Km of GPS accuracy and commands uplinked once a day. The formations can be maintained at less than 1 m/s of monthly (Delta)V per satellite.

BRDF↗
NASA NTRS2022

Cockpit Interface for Locomotion and Manipulation Control of the NASA Valkyrie Humanoid in Virtual Reality (VR)

A virtual reality (VR) interface is presented for controlling NASA’s Valkyrie humanoid robot with flexible locomotion control options and intuitive teleoperation. Locomotion modes include navigating to a specified waypoint, sending desired velocities with a joystick, or manually placing a sequence of footsteps. On the other hand, teleoperation modes include voice commands to toggle relative whole-body tracking or high-level commandeering, and key bindings for common stored poses such as power grasps. The primary novelties of the interface are in the implementation of the cockpit mode and a floating augmented reality (AR) screen fixed with respect to the robot. The former enables embodied teleoperation and increased awareness during navigation in a mixed-reality setting. The latter preserves depth perception without the disparity clutter from a stereo point cloud. The interface is demonstrated on two real humanoids performing common explosive ordnance disposal (EOD) tasks such as door opening, vehicle inspection, and disruptor placement. Notably, the interface enables a single operator to control multiple humanoids. While the interface is motivated by EOD missions, the presented ideas are usable for other robots employing VR-based control.

Virtual-reality↗
NASA NTRS1997

Analyses of 1994 Typhoons in the Taiwan Region Using Satellite Data

Taiwan is situated in the prevalent typhoon track in the northwestern Pacific. On average, about one third of the island total annual precipitation is due to typhoons, with the other two third being contributed by the summer monsoon, or Meiyu, and wintertime large scale frontal rainfall. While the typhoons bring the needed moisture for agricultural consumption and industrial utilization, heavy rainfall associated with typhoons often result in large scale flooding and land slide. The prediction of the typhoon track and its severity is therefore a high priority topic both for operation and research. The severity of a typhoon can be defined in terms of the wind strength and the moisture content. The Special Sensor Microwave/Imager (SSM/I) on board of the Defense Meteorological Satellite Program (DMSP) satellites measures microwave radiation in 19.4, 22.2, 37, and 85.5 GHz. These measurements provide an opportunity to estimate parameters such as surface wind speed, water vapor and cloud water contents, and rainfall rate over oceans. In 1994, Taiwan experienced an above normal frequency of typhoon hits, five typhoons hit the island in two months. In this report, estimates of the moisture content of these typhoons are made based on the SSM/I measurements. An assessment of the relative strength of the typhoons are made with analyzed data.

Chang, A. T. C.↗
NASA NTRS2006

International Polar Year Observations From the International Space Station

Astronauts aboard the International Space Station (ISS) have several opportunities each day to observe and document high-latitude phenomena. Although lighting conditions, ground track and other viewing parameters change with orbital precessions and season, the 51.6 degree orbital inclination and 400 km altitude of the ISS provide the crew an excellent vantage point for collecting image-based data for IPY investigators. To date, the database of imagery acquired by the Crew Earth Observations (CEO) experiment aboard the ISS (http://eol.jsc.nasa.gov) contains more than 12,000 images of high latitude (above 50 degrees) events such as aurora, mesospheric clouds, sea-ice, high-latitude plankton blooms, volcanic eruptions, and snow cover. The ISS Program will formally participate in IPY through an activity coordinated through CEO entitled Synchronized Observations of Polar Mesospheric Clouds, Aurora and Other Large-scale Polar Phenomena from the ISS and Ground Sites. The activity will augment the existing collection of Earth images taken from the ISS by focusing astronaut observations on polar phenomena. NASA s CEO experiment will solicit requests by IPY investigators for ISS observations that are coordinated with or complement ground-based polar studies. The CEO imagery website (http://eol.jsc.nasa.gov) will provide an on-line form for IPY investigators to interact with CEO scientists and define their imagery requests. This information will be integrated into daily communications with the ISS crews about their Earth Observations targets. All data collected will be cataloged and posted on the website for downloading and assimilation into IPY projects.

Pettit, Donald R.↗
DOE OSTI2023

What Sets the Star Formation Rate of Molecular Clouds? The Density Distribution as a Fingerprint of Compression and Expansion Rates

We use a suite of 3D simulations of star-forming molecular clouds, with and without stellar feedback, magnetic fields, and driven turbulence, to study the compression and expansion rates of the gas as functions of density. We show that, around the mean density, supersonic turbulence promotes rough equilibrium between the amounts of compressing and expanding gas, consistent with continuous gas cycling between high- and low-density states. We find that the inclusion of protostellar jets produces rapidly expanding and compressing low-density gas. We find that the gas mass flux peaks at the transition between the lognormal and power-law forms of the density probability distribution function (PDF). This is consistent with the transition density tracking the post-shock density, which promotes an enhancement of mass at this density (i.e., shock compression and filament formation). At high densities, the gas dynamics are dominated by self-gravity: the compression rate in all of our runs matches the rate of the run with only gravity, suggesting that processes other than self-gravity have little effect at these densities. The net gas mass flux becomes constant at a density below the sink formation threshold, where it equals the star formation rate. The density at which the net gas mass flux equals the star formation rate is one order of magnitude lower than our sink threshold density, corresponds to the formation of the second power-law tail in the density PDF, and sets the overall star formation rates of these simulations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

TRACER-Vertical Profile of Aerosol in Convective System (TRACER-VPACS) Field Campaign Report

We investigated physicochemical properties of aerosol at different altitudes during the U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) user facility Tracking Aerosol Convection Interactions Experiment (TRACER). We used ARM’s tethered balloon system (TBS) and multi-modal offline analysis techniques available at DOE’s Environmental Molecular Sciences Laboratory (EMSL) at Pacific Northwest National Laboratory (PNNL) and at the Advanced Light Source (ALS) at the Lawrence Berkley National Laboratory (LBNL). The main scientific aim of this project was to understand the influence of the vertical profile of aerosol composition on the properties of deep convective clouds. The effect of aerosol properties on convective activity is still poorly understood and debated. For example, previous studies suggested that higher concentration of hygroscopic aerosol may lead to lower collection efficiency and eventually delay in onset of precipitation and total amount of precipitation. However, some observations suggested that increased aerosol concentration may result in vigorous convection and a higher amount of precipitation. In addition, the radiative forcing of the ambient aerosol is strongly influenced by the vertical distribution of aerosols and their chemical composition, and not well constrained in climate models. The estimation of the indirect effect of aerosol also has a significant uncertainty due to the spatial variation of the aerosol, especially at the cloud base. Detailed size-resolved chemical composition studies of aerosol and their microphysical properties, along with in situ measurements from ARM’s mobile facilities, help to improve our understanding of the role of aerosol in deep convective cloud formation over a broad range of environmental thermodynamic and aerosol conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Inpainting radar missing data regions with deep learning

Abstract. Missing and low-quality data regions are a frequent problem for weather radars. They stem from a variety of sources: beam blockage, instrument failure, near-ground blind zones, and many others. Filling in missing data regions is often useful for estimating local atmospheric properties and the application of high-level data processing schemes without the need for preprocessing and error-handling steps – feature detection and tracking, for instance. Interpolation schemes are typically used for this task, though they tend to produce unrealistically spatially smoothed results that are not representative of the atmospheric turbulence and variability that are usually resolved by weather radars. Recently, generative adversarial networks (GANs) have achieved impressive results in the area of photo inpainting. Here, they are demonstrated as a tool for infilling radar missing data regions. These neural networks are capable of extending large-scale cloud and precipitation features that border missing data regions into the regions while hallucinating plausible small-scale variability. In other words, they can inpaint missing data with accurate large-scale features and plausible local small-scale features. This method is demonstrated on a scanning C-band and vertically pointing Ka-band radar that were deployed as part of the Cloud Aerosol and Complex Terrain Interactions (CACTI) field campaign. Three missing data scenarios are explored: infilling low-level blind zones and short outage periods for the Ka-band radar and infilling beam blockage areas for the C-band radar. Two deep-learning-based approaches are tested, a convolutional neural network (CNN) and a GAN that optimize pixel-level error or combined pixel-level error and adversarial loss respectively. Both deep-learning approaches significantly outperform traditional inpainting schemes under several pixel-level and perceptual quality metrics.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1995

Shuttle Laser Altimeter (SLA): A pathfinder for space-based laser altimetry and lidar

The Shuttle Laser Altimeter (SLA) is a Hitchhiker experiment now being integrated for first flight on STS-72 in November 1995. Four Shuttle flights of the SLA are planned at a rate of about a flight every 18 months. They are aimed at the transition of the Goddard Space Flight Center airborne laser altimeter and lidar technology to low Earth orbit as a pathfinder for operational space-based laser remote sensing devices. Future alser altimeter sensors such as the Geoscience Laser Altimeter System (GLAS), an Earth Observing System facility instrument, and the Multi-Beam Laser Altimeter (MBLA), the land and vegetation laser altimeter for the NASA TOPSAT (Topography Satellite) Mission, will utilize systems and approaches being tested with SLA. The SLA Instrument measures the distance from the Space Shuttle to the Earth's surface by timing the two-way propagation of short (approximately 10 na noseconds) laser pulses. laser pulses at 1064 nm wavelength are generated in a laser transmitter and are detected by a telescope equipped with a silicon avalanche photodiode detector. The SLA data system makes the pulse time interval measurement to a precision of about 10 nsec and also records the temporal shape of the laser echo from the Earth's surface for interpretation of surface height distribution within the 100 m diam. sensor footprint. For example, tree height can be determined by measuring the characteristic double-pulse signature that results from a separation in time of laser backscatter from tree canopies and the underlying ground. This is accomplished with a pulse waveform digitizer that samples the detector output with an adjustable resolution of 2 nanoseconds or wider intervals in a 100 sample window centered on the return pulse echo. The digitizer makes the SLA into a high resolution surface lidar sensor. It can also be used for cloud and atmospheric aerosol lidar measurements by lengthening the sampling window and degrading the waveform resolution. Detailed test objectives for the STS-72 mission center on the acquisition of sample data sets for land topography and vegetation height, waveform digitizer performance, and verification of data acquisition algorithms. The operational concept of SLA is illustrated in Fig. 1 where a series of 100 m footprints stretch in a profile of Earth surface topography along the nadir track of the Space Shuttle. The location of SLA as a dual canister payload on the Hitchhiker Bridge Assembly in Bay 12 of the Space Shuttle Endeavor can also be noted in this figure. Full interpretation of the SLA range measurement data set requires a 1 m knowledge of the Orbiter trajectory and better than 0.1 deg knowledge of Orbiter pointing angle. These ancillary data sets will be acquired during the STS-72 mission with an on-board Global Positioning System (GPS) receiver, K-band range and range-rate tracking of the Orbiter through TDRSS, and use of on-board inertial measurement units and star trackers. Integration and interpretation of all these different data sets as a pathfinder investigation for accurate determination of Earth surface elevation is the overall science of the SLA investigation.

Bufton, Jack↗
NASA NTRS2001

Remote Sensing of Aerosol and their Radiative Properties from the MODIS Instrument on EOS-Terra Satellite: First Results and Evaluation

The MODIS instrument was launched on the NASA Terra satellite in Dec. 1999. Since last Oct., the sensor and the aerosol algorithm reached maturity and provide global daily retrievals of aerosol optical thickness and properties. MODIS has 36 spectral channels in the visible to IR with resolution down to 250 m. This allows accurate cloud screening and multi-spectral aerosol retrievals. We derive the aerosol optical thickness over the ocean and most of the land areas, distinguishing between fine (mainly man-made aerosol) and coarse aerosol particles. The information is more precise over the ocean where we derive also the effective radius and scattering asymmetry parameter of the aerosol. New methods to derive the aerosol single scattering albedo are also being developed. These measurements are use to track different aerosol sources, transport and the radiative forcing at the top and bottom of the atmosphere. The AErosol RObotic NETwork of ground based radiometers is used for global validation of the satellite derived optical thickness, size parameters and single scattering albedo and measure additional aerosol parameters that cannot be derived from space.

Kaufman, Yoram↗
NASA NTRS2006

A-Train Data Depot: Integrating, Visualizing, and Extracting Cloudsat, CALIPSO, MODIS, and AIRS Atmospheric Measurements Along the A-Train Tracks

The succession of US and international Earth observing satellites that follow each other, seconds to minutes apart, across the local afternoon equator crossing is called the ATrain. The A-Train consists of the following satellites, in order of equator crossing: OCO, EOS Aqua, CloudSat, CALIPSO, PARASOL, and EOS Aura. Flying in such formation increases the number of observations, validates observations, and enables coordination between science observations, resulting in a more complete virtual science platform (Kelly, 2000). The goal of this project is to create the first ever A-Train virtual data portal/center, the A-Train Data Depot (ATDD), to process, archive, access, visualize, analyze and correlate distributed atmosphere measurements from various A-Train instruments along A-Train tracks. The ATDD will enable the free movement of remotely located A-Train data so that they are combined to create a consolidated vertical view of the Earth's Atmosphere along the A-Train tracks. Once the infrastructure of the ATDD is in place, it will be easily evolved to serve data from all A-Train data measurements: one stop shopping. The innovative approach of analyzing and visualizing atmospheric profiles along the platforms track (i.e., time) will be accommodated by reusing the GSFC Atmospheric Composition Data and Information Services Center (ACDISC) visualization and analysis tool, GIOVANNI, existing data reduction tools, on-line archiving for fast data access, access to remote data without unnecessary data transfers, and data retrieval by users finding data desirable for further study. Initial measurements utilized include CALIPSO lidar backscatter, CloudSat radar reflectivity, clear air relative humidity, water vapor and temperature from AIRS, and cloud properties and aerosols from both MODIS. This will be foilowed by associated measurements from TVILS, =MI, HIRDLS, sad TES. Given the independent nature of instrumentlplatform development, the ATDD project has been met with many interesting challenges that, once resolved, will provide a much greater understanding of the relative flight dynamics and data co-registration of the suite of A-Train instruments, thus greatly increasing the accuracy of A-Train data analysis. Some of these challenges will be illustrated and discussed. The project's early visualizations and analysis efforts illustrate the importance of managing data so that measurements from various missions can be combined to enhance the understanding of the atmosphere. A-Train data management coordination, as performed here, is extremely significant in facilitating the A-Train science of clouds, precipitation, aerosol and chemistry.

Kempler, Steven↗
NASA NTRS2018

Solar System Science with the Wide-Field Infrared Survey Telescope

We present a community-led assessment of the solar system investigations achievable with NASA's next-generation space telescope, the Wide Field Infrared Survey Telescope (WFIRST). WFIRST will provide imaging, spectroscopic, and coronagraphic capabilities from 0.43 to 2.0 m and will be a potential contemporary and eventual successor to the James Webb Space Telescope (JWST). Surveys of irregular satellites and minor bodies are where WFIRST will excel with its 0.28 deg2 field-of-view Wide Field Instrument. Potential ground- breaking discoveries from WFIRST could include detection of the first minor bodies orbiting in the inner Oort Cloud, identification of additional Earth Trojan asteroids, and the discovery and characterization of asteroid binary systems similar to Ida/Dactyl. Additional investigations into asteroids, giant planet satellites, Trojan asteroids, Centaurs, Kuiper belt objects, and comets are presented. Previous use of astrophysics assets for solar system science and synergies between WFIRST, Large Synoptic Survey Telescope, JWST, and the proposed Near-Earth Object Camera mission is discussed. We also present the case for implementation of moving target tracking, a feature that will benefit from the heritage of JWST and enable a broader range of solar system observations.

Holler, Bryan J.↗
NASA NTRS2017

Deep-Space Navigation Using Optical Communications Systems

Optical communication links using lasers can potentially deliver data rates much higher than those possible using radio frequencies. If optical communications equipment is going to be carried by future deep-space missions, this equipment, with some adaptations, could also be used to perform tracking for trajectory determination. A number of experiments have been performed in Earth orbit and in lunar orbit using optical data links, while other missions have demonstrated optical links over interplanetary distances. Laser ranging using corner cube retroreflectors is a well-established technique that has been used for orbit determination of Earth orbiting spacecraft, for geodesy, and for lunar research, achieving centimeter-level precisions, but it is not a practical method for deep-space distances. There are two main optical tracking types that are being considered for deep-space navigation. The first is optical astrometry of spacecraft: a telescope on the ground images the laser beam coming from a spacecraft against the star background, determining its plane-of-sky position as seen from the observatory. This type will greatly benefit from the release of the high-accuracy star catalog produced by ESA’s Gaia mission, allowing for the generation of plane-of-sky measurements with an accuracy similar to that obtained today using VLBI tracking techniques. The second is optical ranging using active optical systems at both ends of the link, requiring a more careful design of the spacecraft optical communications system. One of the advantages of using optical frequencies is that they are not affected by charged particles in the signal path the way that radio frequencies are, eliminating solar plasma and ionospheric effects from the light-time calculation and the corresponding noise. On the other hand, clouds would preclude any type of optical communication, and daytime light scattering precludes astrometric measurements. This paper presents our analysis so far of the performance that could be achieved using optical data types in a number of deep-space scenarios. One of the questions that we are trying to answer is whether spacecraft equipped with optical communications terminals would also need to carry radio-frequency equipment for navigational purposes. We also want to understand how accurately we will be able to navigate spacecraft in different mission types and phases, and what would be the constraints, advantages, and disadvantages of using optical communications systems for deep-space navigation.

Karimi, Reza↗
NASA NTRSDate not supplied

Evaluating CERES TOA Fluxes using ARISE aircraft observations

Uncertainty in observations of top-of-atmosphere (TOA) radiation fluxes are larger in the Arctic than in other regions. The magnitude of these uncertainties limit our understanding of the Arctic surface energy budget and its variability. The significant uncertainties are due to the low sun angles and wide range of highly reflecting, anisotropic, and highly heterogeneous surface conditions. Therefore, quantifying, attributing, and reducing Arctic TOA radiative flux uncertainty enables a better understanding of the rapidly changing Arctic. To advance this goal, we compare the Cloud and Earth’s Radiant Energy System (CERES) TOA radiative fluxes with measurements from the Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE) flow in September 2014. A key objective of ARISE was to evaluate and attribute uncertainty in CERES footprint and gridded TOA radiative fluxes. In this study, we first compare the CERES TOA flux with those obtained from the broadband radiometer measurements from the aircraft using instantaneously matched footprint with the flight track and as the hourly gridded fluxes. This comparison indicates an agreement within uncertainty in the longwave (2 Wm-2 ) for all five grid boxes and agreement in the shortwave (10 Wm-2) for four-out-of-five grid boxes. While not a statistically significant results given the small sample size, the hourly, gridded and the instantaneously matched footprint comparison suggest a -10 Wm-2 bias for CERES in the shortwave. To explore whether this is a robust feature or a statistical artifact, we quantify the individual sources of uncertainty in the differences (temporal and spatial sampling differences, scene evolution, accuracy, angular distribution models, and scene id) to see if any of these differences account for the shortwave bias.

CERES↗