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805 records · Page 45

Multiparametric Determination of Radiation Risk

Predicting risk of human cancer following exposure to ionizing space radiation is challenging in part because of uncertainties of low-dose distribution amongst cells, of unknown potentially synergistic effects of microgravity upon cellular protein-expression, and of processing dose-related damage within cells to produce rare and late-appearing malignant transformation, degrade the confidence of cancer risk-estimates. The NASA- specific responsibility to estimate the risks of radiogenic cancer in a limited number of astronauts is not amenable to epidemiologic study, thereby increasing this challenge. Developing adequately sensitive cellular biodosimeters that simultaneously report 1) the quantity of absorbed close after exposure to ionizing radiation, 2) the quality of radiation delivering that dose, and 3) the risk of developing malignant transformation by the cells absorbing that dose could be useful for resolving these challenges. Use of a multiparametric cellular biodosimeter is suggested using analyses of gene-expression and protein-expression whereby large datasets of cellular response to radiation-induced damage are obtained and analyzed for expression-profiles correlated with established end points and molecular markers predictive for cancer-risk. Analytical techniques of genomics and proteomics may be used to establish dose-dependency of multiple gene- and protein- expressions resulting from radiation-induced cellular damage. Furthermore, gene- and protein-expression from cells in microgravity are known to be altered relative to cells grown on the ground at 1g. Therefore, hypotheses are proposed that 1) macromolecular expression caused by radiation-induced damage in cells in microgravity may be different than on the ground, and 2) different patterns of macromolecular expression in microgravity may alter human radiogenic cancer risk relative to radiation exposure on Earth. A new paradigm is accordingly suggested as a national database wherein genomic and proteomic datasets are registered and interrogated in order to provide statistically significant dose-dependent risk estimation of radiogenic cancer in astronauts.

Richmond, Robert C.↗

Project Integration Architecture

The Project Integration Architecture (PIA) is a distributed, object-oriented, conceptual, software framework for the generation, organization, publication, integration, and consumption of all information involved in any complex technological process in a manner that is intelligible to both computers and humans. In the development of PIA, it was recognized that in order to provide a single computational environment in which all information associated with any given complex technological process could be viewed, reviewed, manipulated, and shared, it is necessary to formulate all the elements of such a process on the most fundamental level. In this formulation, any such element is regarded as being composed of any or all of three parts: input information, some transformation of that input information, and some useful output information. Another fundamental principle of PIA is the assumption that no consumer of information, whether human or computer, can be assumed to have any useful foreknowledge of an element presented to it. Consequently, a PIA-compliant computing system is required to be ready to respond to any questions, posed by the consumer, concerning the nature of the proffered element. In colloquial terms, a PIA-compliant system must be prepared to provide all the information needed to place the element in context. To satisfy this requirement, PIA extends the previously established object-oriented- programming concept of self-revelation and applies it on a grand scale. To enable pervasive use of self-revelation, PIA exploits another previously established object-oriented-programming concept - that of semantic infusion through class derivation. By means of self-revelation and semantic infusion through class derivation, a consumer of information can inquire about the contents of all information entities (e.g., databases and software) and can interact appropriately with those entities. Other key features of PIA are listed.

Jones, William Henry↗

Simultaneous Retrieval of Selected Optical Water Quality Indicators From Landsat-8, Sentinel-2, and Sentinel-3

Constructing multi-source satellite-derived water quality (WQ) products in inland and nearshore coastal waters from the past, present, and future missions is a long-standing challenge. Despite inherent differences in sensors’ spectral capability, spatial sampling, and radiometric performance, research efforts focused on formulating, implementing, and validating universal WQ algorithms continue to evolve. This research extends a recently developed machine-learning (ML) model, i.e., Mixture Density Networks (MDNs) (Pahlevan et al., 2020; Smith et al., 2021), to the inverse problem of simultaneously retrieving WQ indicators, including chlorophyll-a (Chla), Total Suspended Solids (TSS), and the absorption by Colored Dissolved Organic Matter at 440 nm (a cdom (440)), across a wide array of aquatic ecosystems. We use a database of in situ measurements to train and optimize MDN models developed for the relevant spectral measurements (400–800 nm) of the Operational Land Imager (OLI), MultiSpectral Instrument (MSI), and Ocean and Land Color Instrument (OLCI) aboard the Landsat-8, Sentinel-2, and Sentinel-3 missions, respectively. Our two performance assessment approaches, namely hold-out and leave-one-out, suggest significant, albeit varying degrees of improvements with respect to second-best algorithms, depending on the sensor and WQ indicator (e.g., 68%, 75%, 117% improvements based on the hold-out method for Chla, TSS, and a cdom (440), respectively from MSI-like spectra). Using these two assessment methods, we provide theoretical upper and lower bounds on model performance when evaluating similar and/or out-of-sample datasets. To evaluate multi-mission product consistency across broad spatial scales, map products are demonstrated for three near-concurrent OLI, MSI, and OLCI acquisitions. Overall, estimated TSS and a cdom (440) from these three missions are consistent within the uncertainty of the model, but Chla maps from MSI and OLCI achieve greater accuracy than those from OLI. By applying two different atmospheric correction processors to OLI and MSI images, we also conduct matchup analyses to quantify the sensitivity of the MDN model and best-practice algorithms to uncertainties in reflectance products. Our model is less or equally sensitive to these uncertainties compared to other algorithms. Recognizing their uncertainties, MDN models can be applied as a global algorithm to enable harmonized retrievals of Chla, TSS, and a cdom (440) in various aquatic ecosystems from multi-source satellite imagery. Local and/or regional ML models tuned with an apt data distribution (e.g., a subset of our dataset) should nevertheless be expected to outperform our global model.

Machine learning↗

Nozzle Plume/Shock Interaction Experimental and Computational Sonic Boom Analyses from the NASA Ames 9- by 7-Foot Supersonic Wind Tunnel

A wind tunnel test and a computational study were conducted to investigate the complex interactions between a supersonic nozzle plume and shock waves of differing strengths generated from various aft surfaces typical of supersonic aircraft. These analytically-defined aft surfaces were representative of horizontal tails of various sizes, and an aft deck. CFD simulations of many proposed model configurations allowed for assessments of the detailed flow interactions of components in close proximity to the nozzle, as well as assessments of the nozzle jet flow itself. The evaluation of the computational results for many candidate configurations guided the design of model components. The interactions of the waveforms from these surfaces with the jet exhaust plume can have significant adverse effects on the loudness of the sonic boom if the surfaces are not carefully integrated into an aircraft design. The greatest discrepancy in estimating sonic boom loudness for low-boom flight vehicles is currently in predicting the signatures from the aft part of an aircraft, including the interactions with the plume flow. The objectives of this test were to gain a better understanding of these interactions, and to provide a detailed experimental database from multiple sources for use as validation cases for CFD tool development. The subject test was run in the NASA Ames 9- by 7-Ft Supersonic Wind Tunnel in February 2016 at Mach numbers of 1.6 and 2.0, and was funded by the NASA Commercial Supersonics Technology (CST) Project. The nozzle flow was provided by high-pressure air (HPA) pumped through the model, and pressure signature data were acquired with the NASA 14-inch sonic boom pressure rail. The rail measured the locations of the shocks and expansions at various distances and off-track angles from the model. This enabled the impact of the nozzle plume/shock interactions on the near- and mid-field sonic boom pressure waveforms to be quantified. Schlieren images of the flow field around and behind the model were obtained with an RBOS (Retroreflective Background-Oriented Schlieren) technique to determine the origins of the shock and expansion waves, to identify the shape and boundaries of the plume, and to determine the changes in incoming and exiting waveforms within the plume. A total pressure rake was positioned closely behind the model nozzle in order to measure the total pressure profiles of the flow above, within, and below the nozzle exhaust. Model angles and positions in the tunnel were measured by photogrammetry using two cameras since the lack of a model force balance prevented the measurement of model deflections under load.Navier-Stokes computations using two different CFD codes were compared to the experimental sonic boom pressure signature data, and the rake total pressure data in the plume. A computational schlieren technique was used to compare the computed flow field with the RBOS images. The computational results were also used to complement the test data with flow field quantities that could not be measured, such as Mach number and pressure distributions to distinguish shock waves and expansion waves.

sonic boom↗

Alpha, beta, or gamma: where does all the diversity go?

Global taxonomic richness is affected by variation in three components: within-community, or alpha, diversity, between-community, or beta, diversity; and between-region, or gamma, diversity. A data set consisting of 505 faunal lists distributed among 40 stratigraphic intervals and six environmental zones was used to investigate how variation of alpha and beta diversity influenced global diversity through the Paleozoic, and especially during the Ordovician radiations. As first shown by Bambach (1977), alpha diversity increased by 50 to 70 percent in offshore marine environments during the Ordovician and then remained essentially constant of the remainder of the Paleozoic. The increase is insufficient, however, to account for the 300 percent rise observed in global generic diversity. It is shown that beta diversity among level, soft-bottom communities also increased significantly during the early Paleozoic. This change is related to enhanced habitat selection, and presumably increased overall specialization, among diversifying taxa during the Ordovician radiations. Combined with alpha diversity, the measured change in beta diversity still accounts for only about half of the increase in global diversity. Other sources of increase are probably not related to variation in gamma diversity but rather to appearance and/or expansion of organic reefs, hardground communities, bryozoan thickets, and crinoid gardens during the Ordovician.

NASA Discipline Exobiology↗

Methodology and Results of the Near-Earth Object (NEO) Human Space Flight (HSF) Accessible Targets Study (NHATS)

Near-Earth Asteroids (NEAs) have been identified by the current administration as potential destinations for human explorers during the mid-2020s. While the close proximity of these objects' orbits to Earth's orbit creates a risk of highly damaging or catastrophic impacts, it also makes some of these objects particularly accessible to spacecraft departing Earth, and this presents unique opportunities for solar system science and humanity's first ventures beyond cislunar space. Planning such ambitious missions first requires the selection of potentially accessible targets from the growing population of nearly 7,800 NEAs. To accomplish this, NASA is conducting the Near-Earth Object (NEO) Human Space Flight (HSF) Accessible Targets Study (NHATS). Phase I of the NHATS was executed during September of 2010, and Phase II was completed by early March of 2011. The study is ongoing because previously undetected NEAs are being discovered constantly, which has motivated an effort to automate the analysis algorithms in order to provide continuous monitoring of NEA accessibility. The NHATS analysis process consists of a trajectory filter and a minimum maximum estimated size criterion. The trajectory filter employs the method of embedded trajectory grids to compute all possible ballistic round-trip mission trajectories to every NEA in the Jet Propulsion Laboratory (JPL) Small-Body Database (SBDB) and stores all solutions that satisfy the trajectory filter criteria. An NEA must offer at least one qualifying trajectory solution to pass the trajectory filter. The Phase II NHATS filter criteria were purposely chosen to be highly inclusive, requiring Earth departure date between January 1st, 2015 and December 31st, 2040, total round-trip flight time <= 450 days, stay time at the NEA >= 8 days, Earth departure C(sub 3) energy <= 60 km(exp 2)/s(exp 2), total mission delta-v <= 12 km/s (including an Earth departure maneuver from a 400 km altitude circular parking orbit), and a maximum atmospheric re-entry speed of 12 km/s. After determining which NEAs offer at least one trajectory solution meeting the criteria, the estimated size constraint is then imposed whereby those NEAs may only be considered NHATS- qualifying NEAs if their maximum estimated size is >= 30 m. This corresponds to an absolute magnitude H <= 26.5 with an assumed albedo p = 0:05. The following is a brief high-level summary of the Phase II study results. Of the 7,665 NEAs in the SBDB as of February 3rd, 2011, 765 NEAs passed the trajectory filter and yielded a total of 79,157,604 trajectory solutions. The trajectory solutions for each NEA are post-processed into Pork Chop Contour (PCC) plots which show total mission delta-v as a function of Earth departure date and total mission duration. Although the PCC plots necessarily compress a very multi-dimensional design space into a two-dimensional plot, they permit rapid assessment of the breadth and quality of an NEA's available Earth departure season and clearly indicate the regions of the trajectory design space which warrant further analysis and optimization. The PCC plot for the NEA with the greatest number of NHATS-qualifying trajectory solutions, 2000 SG-344, is shown. Of the 765 NEAs which passed the Phase II trajectory filter, a total of 590 NEAs also satisfied the further constraint of maximum estimated size >= 30 m. The distributions of osculating heliocentric orbital semi-major axis (a), eccentricity (e), and inclination (i), for those 590 NEAs are shown. Note that the semi-latus rectum used is equal to alpha (1-e(exp 2)). To further our understanding of round-trip trajectory accessibility dynamics, it is instructive to examine the distribution of the NHATS-Qualifying NEAs according to orbit classification. NEAs are grouped into four orbit families: Atiras (aphelion < 0.983 AU), Atens (aphelion > 0.983 AU, alpha < 1.0 AU), Apollos (perihelion < 1.017 AU, alpha > 1.0 AU), and Amors (1.017 < perihelion < 1.3 AU). Of the 765 NEAhich satisfied the NHATS trajectory criteria, none are Atiras, 193 are Atens (31% of known Atens), 456 are Apollos (11% of known Apollos), and 116 are Amors (4% of known Amors). While Apollos comprise 60% of the NEAs which pass the NHATS trajectory filter and Atens comprise only 25%, the percentages according to orbit family are perhaps more relevant. Note that only 11% of known Apollos passed the trajectory filter while 31% of known Atens passed. These simple statistics alone strongly suggest that Aten orbits possess features which tend to enhance their round-trip trajectory accessibility as compared to Apollos or Amors. This is significant because Atens' orbits cause them to spend considerable time in Earth's daytime sky, making them difficult to discover and track using ground-based observing assets. In this paper we will detail the NHATS analysis algorithms, present and analyze all NHATS results to date, and discuss aspects of HSF mission architecture design for future NEA missions.

Barbee, Brent↗

ARES Biennial Report 2012 Final

Since the return of the first lunar samples, what is now the Astromaterials Research and Exploration Science (ARES) Directorate has had curatorial responsibility for all NASA-held extraterrestrial materials. Originating during the Apollo Program (1960s), this capability at Johnson Space Center (JSC) included scientists who were responsible for the science planning and training of astronauts for lunar surface activities as well as experts in the analysis and preservation of the precious returned samples. Today, ARES conducts research in basic and applied space and planetary science, and its scientific staff represents a broad diversity of expertise in the physical sciences (physics, chemistry, geology, astronomy), mathematics, and engineering organized into three offices (figure 1): Astromaterials Research (KR), Astromaterials Acquisition and Curation (KT), and Human Exploration Science (KX). Scientists within the Astromaterials Acquisition and Curation Office preserve, protect, document, and distribute samples of the current astromaterials collections. Since the return of the first lunar samples, ARES has been assigned curatorial responsibility for all NASA-held extraterrestrial materials (Apollo lunar samples, Antarctic meteorites - some of which have been confirmed to have originated on the Moon and on Mars - cosmic dust, solar wind samples, comet and interstellar dust particles, and space-exposed hardware). The responsibilities of curation consist not only of the longterm care of the samples, but also the support and planning for future sample collection missions and research and technology to enable new sample types. Curation provides the foundation for research into the samples. The Lunar Sample Facility and other curation clean rooms, the data center, laboratories, and associated instrumentation are unique NASA resources that, together with our staff's fundamental understanding of the entire collection, provide a service to the external research community, which relies on access to the samples. The curation efforts are greatly enhanced by a strong group of planetary scientists who conduct peerreviewed astromaterials research. Astromaterials Research Office scientists conduct peer-reviewed research as Principal or Co-Investigators in planetary science (e. g., cosmochemistry, origins of solar systems, Mars fundamental research, planetary geology and geophysics) and participate as Co-Investigators or Participating Scientists in many of NASA's robotic planetary missions. Since the last report, ARES has achieved several noteworthy milestones, some of which are documented in detail in the sections that follow. Within the Human Exploration Science Office, ARES is a world leader in orbital debris research, modeling and monitoring the debris environment, designing debris shielding, and developing policy to control and mitigate the orbital debris population. ARES has aggressively pursued refinements in knowledge of the debris environment and the hazard it presents to spacecraft. Additionally, the ARES Image Science and Analysis Group has been recognized as world class as a result of the high quality of near-real-time analysis of ascent and on-orbit inspection imagery to identify debris shedding, anomalies, and associated potential damage during Space Shuttle missions. ARES Earth scientists manage and continuously update the database of astronaut photography that is predominantly from Shuttle and ISS missions, but also includes the results of 40 years of human spaceflight. The Crew Earth Observations Web site (http://eol.jsc.nasa.gov/Education/ESS/crew.htm) continues to receive several million hits per month. ARES scientists are also influencing decisions in the development of the next generation of human and robotic spacecraft and missions through laboratory tests on the optical qualities of materials for windows, micrometeoroid/orbital debris shielding technology, and analog activities to assess surface science operations. ARES serves as host to numerous students and visiting scientists as part of the services provided to the research community and conducts a robust education and outreach program. ARES scientists are recognized nationally and internationally by virtue of their success in publishing in peer-reviewed journals and winning competitive research proposals. ARES scientists have won every major award presented by the Meteoritical Society, including the Leonard Medal, the most prestigious award in planetary science and cosmochemistry; the Barringer Medal, recognizing outstanding work in the field of impact cratering; the Nier Prize for outstanding research by a young scientist; and several recipients of the Nininger Meteorite Award. One of our scientists received the Department of Defense (DoD) Joint Meritorious Civilian Service Award (the highest civilian honor given by the DoD). ARES has established numerous partnerships with other NASA Centers, universities, and national laboratories. ARES scientists serve as journal editors, members of advisory panels and review committees, and society officers, and several scientists have been elected as Fellows in their professional societies. This biennial report summarizes a subset of the accomplishments made by each of the ARES offices and highlights participation in ongoing human and robotic missions, development of new missions, and planning for future human and robotic exploration of the solar system beyond low Earth orbit.

Stansbery, Eileen↗

Understanding Effective Diameter and Its Application to Terrestrial Radiation in Ice Clouds

The cloud property known as "effective diameter" or "effective radius", which in essence is the cloud particle size distribution (PSD) volume at bulk density divided by its projected area, is used extensively in atmospheric radiation transfer, climate modeling and remote sensing. This derives from the assumption that PSD optical properties can be uniquely described in terms of their effective diameter, D(sub e), and their cloud water content (CWC), henceforth referred to as the D(sub e)-CWC assumption. This study challenges this assumption, showing that while the D(sub e)-CWC assumption appears generally valid for liquid water clouds, it appears less valid for ice clouds in regions where (1) absorption is not primarily a function of either the PSD ice water content (IWC) or the PSD projected area, and (2) where wave resonance (i.e. photon tunneling) contributes significantly to absorption. These two regions often strongly coincide at terrestrial wavelengths when De less than ~60 m, which is where this D(sub e)-CWC assumption appears poorest. Treating optical properties solely in terms of D(sub e) and IWC may lead to errors up to 24%, 26% and 20% for terrestrial radiation in the window region regarding the absorption and extinction coefficients and the single scattering albedo, respectively. Outside the window region, errors may reach 33% and 42% regarding absorption and extinction. The magnitude and sign of these errors can change rapidly with wavelength, which may produce significant errors in climate modeling, remote sensing and other applications concerned with the wavelength dependence of radiation. Where the D(sub e)-CWC assumption breaks down, ice cloud optical properties appear to depend on D(sub e), IWC and the PSD shape. Optical property parameterizations in climate models and remote sensing algorithms based on historical PSD measurements may exhibit errors due to previously unknown PSD errors (i.e. the presence of ice artifacts due to the shattering of larger ice particles on the probe inlet tube during sampling). More recently developed cloud probes are designed to mitigate this shattering problem. Using realistic PSD shapes for a given temperature (and/or IWC) and cloud type may minimize errors associated with PSD shape in ice optics parameterizations and remote sensing algorithms. While this topic was investigated using two ice optics schemes (the Yang et al., 2005 database and the modified anomalous diffraction approximation, or MADA), a physical understanding of the limitations of the D(sub e)-IWC assumption was made possible by using MADA. MADA allows one to approximate the contribution of photon tunneling to absorption relative to other optical processes, which reveals that part of the error regarding the D(sub e)-IWC assumption can be associated with tunneling. By relating the remaining error to the radiation penetration depth in bulk ice (DELTA L) due to absorption, the domain where the D(sub e)-IWC assumption is weakest was described in terms of D(sub e) and DELTA L.

Mitchell, D. L.↗

4-D Cloud Water Content Fields Derived from Operational Satellite Data

In order to improve operational safety and efficiency, the transportation industry, including aviation, has an urgent need for accurate diagnoses and predictions of clouds and associated weather conditions. Adverse weather accounts for 70% of all air traffic delays within the U.S. National Airspace System. The Federal Aviation Administration has determined that as much as two thirds of weather-related delays are potentially avoidable with better weather information and roughly 20% of all aviation accidents are weather related. Thus, it is recognized that an important factor in meeting the goals of the Next Generation Transportation System (NexGen) vision is the improved integration of weather information. The concept of a 4-D weather cube is being developed to address that need by integrating observed and forecasted weather information into a shared 4-D database, providing an integrated and nationally consistent weather picture for a variety of users and to support operational decision support systems. Weather analyses and forecasts derived using Numerical Weather Prediction (NWP) models are a critical tool that forecasters rely on for guidance and also an important element in current and future decision support systems. For example, the Rapid Update Cycle (RUC) and the recently implemented Rapid Refresh (RR) Weather Research and Forecast (WRF) models provide high frequency forecasts and are key elements of the FAA Aviation Weather Research Program. Because clouds play a crucial role in the dynamics and thermodynamics of the atmosphere, they must be adequately accounted for in NWP models. The RUC, for example, cycles at full resolution five cloud microphysical species (cloud water, cloud ice, rain, snow, and graupel) and has the capability of updating these fields from observations. In order to improve the models initial state and subsequent forecasts, cloud top altitude (or temperature, T(sub c)) derived from operational satellite data, surface observations of cloud base altitude, radar reflectivity, and lightning data are used to help build and remove clouds in the models assimilation system. Despite this advance and the many recent advances made in our understanding of cloud physical processes and radiative effects, many problems remain in adequately representing clouds in models. While the assimilation of cloud top information derived from operational satellite data has merit, other information is available that has not yet been exploited. For example, the vertically integrated cloud water content (CWC) or cloud water path (CWP) and cloud geometric thickness (delta Z) are standard products being derived routinely from operational satellite data. These and other cloud products have been validated under a variety of conditions. Since the uncertainties have generally been found to be less than those found in model analyses and forecasts, the satellite products should be suitable for data assimilation, provided an appropriate strategy can be developed that links the satellite-derived cloud parameters with cloud parameters specified in the model. In this paper, we briefly outline such a strategy and describe a methodology to retrieve cloud water content profiles from operational satellite data. Initial results and future plans are presented. It is expected that the direct assimilation of this new product will provide the most accurate depiction of the vertical distribution of cloud water ever produced at the high spatial and temporal resolution needed for short term weather analyses and forecasts.

Smith, William L., Jr.↗

The AERONET Version 3 Aerosol Retrieval Algorithm, Associated Uncertainties and Comparisons to Version 2

The Aerosol Robotic Network (AERONET) Version 3 (V3) aerosol retrieval algorithm is described, which is based on the Version 2 (V2) algorithm with numerous updates. Comparisons of V3 aerosol retrievals to those of V2 are presented, along with a new approach to estimate uncertainties in many of the retrieved aerosol parameters. Changes in the V3 aerosol retrieval algorithm include (1) a new polarized radiative transfer code (RTC), which replaced the scalar RTC of V2, (2) detailed characterization of gas absorption by adding NO2 and H2O to specify total gas absorption in the atmospheric column, specification of vertical profiles of all the atmospheric species, (3) new bidirectional reflectance distribution function (BRDF) parameters for land sites adopted from the MODIS BRDF/Albedo product, (4) a new version of the extraterrestrial solar flux spectrum, and (5) a new temperature correction procedure of both direct Sun and sky radiance measurements. The potential effect of each change in V3 on single scattering albedo (SSA) retrievals was analyzed. The operational almucantar retrievals of V2 versus V3 were compared for four AERONET sites: GSFC, Mezaira, Mongu, and Kanpur. Analysis showed very good agreement in retrieved parameters of the size distributions. Comparisons of SSA retrievals for dust aerosols (Mezaira) showed a good agreement in 440 nm SSA, while for longer wavelengths V3 SSAs are systematically higher than those of V2, with the largest mean difference at 675 nm due to cumulative effects of both extraterrestrial solar flux and BRDF changes. For non-dust aerosols, the largest SSA deviation is at 675 nm due to differences in extraterrestrial solar flux spectrums used in each version. Further, the SSA 675 nm mean differences are very different for weakly (GSFC) and strongly (Mongu) absorbing aerosols, which is explained by the lower sensitivity to a bias in aerosol scattering optical depth by less absorbing aerosols. A new hybrid (HYB) sky radiance measurement scan is introduced and discussed. The HYB combines features of scans in two different planes to maximize the range of scattering angles and achieve scan symmetry, thereby allowing for cloud screening and spatial averaging, which is an advantage over the principal plane scan that lacks robust symmetry. We show that due to an extended range of scattering angles, HYB SSA retrievals for dust aerosols exhibit smaller variability with solar zenith angles (SZAs) than those of almucantar (ALM), which allows extension of HYB SSA retrievals to SZAs less than 50∘ to as small as 25∘. The comparison of SSA retrievals from closely time-matched HYB and ALM scans in the 50 to 75∘ SZA range showed good agreement with the differences below ∼0.005. We also present an approach to estimate retrieval uncertainties which utilizes the variability in retrieved parameters generated by perturbing both measurements and auxiliary input parameters as a proxy for retrieval uncertainty. The perturbations in measurements and auxiliary inputs are assumed as estimated biases in aerosol optical depth (AOD), radiometric calibration of sky radiances combined with solar spectral irradiance, and surface reflectance. For each set of Level 2 Sun/sky radiometer observations, 27 inputs corresponding to 27 combinations of biases were produced and separately inverted to generate the following statistics of the inversion results: average, standard deviation, minimum and maximum values. From these statistics, standard deviation (labeled U27) is used as a proxy for estimated uncertainty, and a lookup table (LUT) approach was implemented to reduce the computational time. The U27 climatological LUT was generated from the entire AERONET almucantar (1993–2018) and hybrid (2014–2018) scan databases by binning U27s in AOD (440 nm), Angström exponent (AE, 440–870 nm), and SSA (440, 675, 870, 1020 nm). Using this LUT approach, the uncertainty estimates U27 for each individual V3 Level 2 retrieval can be obtained by interpolation using the corresponding measured and inverted combination of AOD, AE, and SSA.

Aliaksandr Siniuk↗

Diode laser absorption sensors for gas-dynamic and combustion flows

Recent advances in room-temperature, near-IR and visible diode laser sources for tele-communication, high-speed computer networks, and optical data storage applications are enabling a new generation of gas-dynamic and combustion-flow sensors based on laser absorption spectroscopy. In addition to conventional species concentration and density measurements, spectroscopic techniques for temperature, velocity, pressure and mass flux have been demonstrated in laboratory, industrial and technical flows. Combined with fibreoptic distribution networks and ultrasensitive detection strategies, compact and portable sensors are now appearing for a variety of applications. In many cases, the superior spectroscopic quality of the new laser sources compared with earlier cryogenic, mid-IR devices is allowing increased sensitivity of trace species measurements, high-precision spectroscopy of major gas constituents, and stable, autonomous measurement systems. The purpose of this article is to review recent progress in this field and suggest likely directions for future research and development. The various laser-source technologies are briefly reviewed as they relate to sensor applications. Basic theory for laser absorption measurements of gas-dynamic properties is reviewed and special detection strategies for the weak near-IR and visible absorption spectra are described. Typical sensor configurations are described and compared for various application scenarios, ranging from laboratory research to automated field and airborne packages. Recent applications of gas-dynamic sensors for air flows and fluxes of trace atmospheric species are presented. Applications of gas-dynamic and combustion sensors to research and development of high-speed flows aeropropulsion engines, and combustion emissions monitoring are presented in detail, along with emerging flow control systems based on these new sensors. Finally, technology in nonlinear frequency conversion, UV laser materials, room-temperature mid-IR materials and broadly tunable multisection devices is reviewed to suggest new sensor possibilities.

Non-NASA Center↗

A Historical Overview of the NASA Orbital Debris Program Office’s Laboratory Optical Measurements

The NASA Orbital Debris Program Office (ODPO) has used laboratory measurements to help bring ground-based measurements together with models to ascertain Earth-orbiting target parameters of interest to support various orbital debris models. In 2005, the Optical Measurement Center (OMC) was established to simulate space-based illumination conditions using equipment and techniques that recreate telescopic observations, particularly source-target-sensor orientations. The intent was to recreate light curves using known aspect angles of known targets and phase angles (angle is defined by the vertex between illumination source-object-detector) to complement telescopic observations that could be used to update the current optical size estimation model (OSEM) – a model that converts object brightness into size for orbital debris models. To support the above goals, the laboratory has undergone several equipment upgrades to increase capabilities over almost 20 years of operation. The primary instrumentation acquires reflectance measurements and includes a solar-like light source, CCD camera with astrometric filters, and robotic arm. A rotary arm was added approximately five years after full operation to allow acquisition through a full 360° range of phase angles. Another part of the OMC instrumentation is a field spectrometer, predominately used for field operations to acquire pre- and post-flight spacecraft material spectral measurements. Additionally, reflectance spectroscopy of various materials is also of interest resulting from hypervelocity impact tests, pristine spacecraft materials, or samples of materials that are used in spacecraft design. These measurements are stored in NASA’s Spectral Material Database, a resource that is still being populated today. The study of spectral measurements also enabled the development of spectral unmixing routines to support the identification of spacecraft materials from spectral data gathered by ground based telescopes. Preliminary OMC investigations focused on feasibility studies to acquire 360° rotation light curves of simple shapes at a single-phase angle and extended to measurements of representative fragments from ground-based explosion tests. To correlate the light curves with ground-based optical measurements, a focused study on high area to mass materials was conducted in support of a newly identified population (at the time) in geosynchronous orbit (GEO) consisting of multi-layered insulation. To further characterize orbital debris, a larger selection of materials was analyzed using laboratory photometric measurements that included representative targets from pristine spacecraft materials and ground-based impact tests. Around 2012, an initiative was requested to understand the feasibility of active debris removal (ADR) of larger targets using grappling methods for spent rocket bodies. Using a priori information on selected targets, scaled-down versions of rocket bodies were generated thanks to improvements in 3D printing technology and machining. These targets were studied in the OMC to understand rotation characteristics. These were compared with telescopic data to determine if the tumble and rotation angles would allow ADR. In 2013, the OMC focused on combining spectral measurements with photometric data to characterize GEO orbital debris. Several years later, NASA acquired a Titan III Transtage test article from “The Boneyard” with a high-resemblance to on-orbit Titan III Transtage rocket bodies, allowing physical access to a representative rocket body that suffered fragmentations in GEO. This prompted the creation of 3D models using lidar technology and spectral measurements of the materials. Focused research also transitioned to specific materials (i.e., solar cells) when telescopic surveys requested characterization of specific GEO targets. In the different research products presented, the focus has been to understand the various parameters that influence optical size estimation, including albedo, phase functions, and brightness variations. Work in this area continues with newer sources of data, including DebriSat, a high-fidelity 56-kg spacecraft replica representative of a modern low Earth orbit (LEO) satellite subjected to a laboratory hypervelocity impact test to understand fragmentation events and to support updates to satellite breakup models and size estimation models. Utilizing the vast population of fragments from DebriSat and prior laboratory impact experiments, the ODPO has focused on acquiring bidirectional reflectance distribution function (BRDF) data to characterize targets in the laboratory, thus removing aspect angle dependencies. Additionally, the DebriSat project has provided improved processes for measuring size via image acquisition, such that a true fragment size can be directly compared to the derived size using the OSEM. The team continues to assess BRDFs and use spectral measurement data to investigate the parameters used in the OSEM, specifically magnitudes, albedo, and phase functions.

Heather Cowardin↗

Influence of Nucleation Mechanisms on the Radiative Properties of Deep Convective Clouds and Subvisible Cirrus in CRYSTAL/FACE

During the past few years we have conducted work on several different topics, as reflected by our publications. As one of the Co-Project scientists for The Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment (CRYSTAL FACE) we worked to help design the mission and then conduct it in the field. Another major activity during the past two years has been to pull together various groups to formulate plans for follow on missions to CRYSTAL FACE. We organized a workshop at the University of Colorado during the summer of 2003 to assess the best locations for future missions. Working with a group of about 10 scientists from around the country we prepared a science-planning document (Tropical Composition, Cloud and Climate Coupling Experiment (TC(sup 4)) that outlined the rationale, locations, strategy to accomplish the goals, and possible payloads for a set of three tropical missions. We also prepared background materials for various NRAs being prepared at NASA Headquarters for missions in Costa Rica, Darwin and Guam. In conjunction with the group at NASA Ames we have helped build a new numerical model for deep convection and have applied that model to simulate the CRYSTAL data. Our goal in particular has been to better understand how convection distributes water vapor isotopes. CRYSTAL observations of water isotopes are very different from those suggested by previous workers who assumed the isotopes would obey Rayleigh fractionation. The water isotope study has several implications. First it is a check on the realism of the deep convection model. Second, the isotopes are a measure of the precipitation removal in the atmosphere. Hence they provide a constraint on a parameter that is difficult to otherwise measure. Finally it has been suggested that isotopes may be the key to unraveling the water transport into the stratosphere and upper troposphere. Such transport is critical both for the radiation balance and for stratospheric chemistry. Ours is the first model that is able to treat this transport. Our initial results have just been submitted to Geophys. Res. Lett (Smith et al., 2005). Essentially we are able to explain the vertical profiles of isotopes in the tropical tropopause transition layer. We are also able to account for stratospheric humidity and isotope abundances with this model. We have also been heavily involved in trying to improve our understanding of nitric acid condensation on ice. Gao et al (2004) have shown that water supersaturations above ice occur when the atmosphere is supersaturated with respect to nitric acid trihydrate. As one of the co-authors of that work, we suggested the mechanism that may explain why this is occurring. Essentially, ice does not like to grow near unit supersaturation, but does so because the water molecules can find sites on the ice surface to attach themselves to before they fly off the ice surface. This phenomena was well known in the 1960s when it was a source of debate about whether condensation and evaporation coefficients for ice would be the same. Evaporation does not require any molecular orientation, while condensation does, so it was possible that the coefficients would differ. They don't differ because the water molecules rapidly move across the surface and find places to attach. Nitric acid may be occupying these preferred sites and therefore the water molecules can't find a desirable place to attach. We anticipate that this research will be the subject of laboratory work during the coming few years. Another possibility that has been suggested is that cubic ice is forming in clouds. We have measured the vapor pressure of cubic ice, and plan to publish that result in the next few months. We have also been working on additional aspects of the condensation of nitric acid on ice. With Y. Kondo we studied the condensation of NOy on ice using the SOLVE data. Gamblin et al. have continued this work. The CRYSTAL NOy and HNO, groups have shown th their data can be fit using standard Langmuir isotherms as suggested in some, but not all, laboratory studies. We have found in the SOLVE data set that this is not the case. Moreover some laboratory studies show there are important kinetic effects that may be occurring in the atmosphere limiting the transfer of nitric acid to the ice. The SOLVE data seem consistent with these studies. We are currently re-analyzing the CRYSTAL data to look for these kinetic effects. There are a number of implications of these studies. One of the more interesting is that the nitric acid coating on ice can be used as a cloud clock to determine how long the cloud parcel has been in existence. We have also been involved with several laboratory studies. We have worked to improve the database on ice optical constants, which are critical for remote sensing. We have also studied the ways in which ice nucleates on clays. We suspect now that the standard theories used for depositional ice nucleation are completely incorrect. Further work will be needed to develop a new theory.

Toon, Owen B.↗