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At least 307 records · Page 17

Transport processes in the middle atmosphere: Reflections after MAP

The Middle Atmosphere Program (MAP) has provided a focus for considerable research on atmospherical radiative, chemical, and dynamical processes and the mutual coupling among these processes. In particular, major advances have occurred in the understanding of constituent transport as a result of near-global measurements obtained during MAP from several satellite based instruments (e.g., LIMS, SAMS, SAGE, and SSU among others). Using selected portions of these data, the development is reviewed of progress in understanding transport processes with special emphasis on dynamically active periods. Examples are presented which demonstrate coupling between chemistry and dynamics. In addition to the constituent data, the use is reviewed of Ertel's potential vorticity, inferred from satellite temperature data, as a diagnostic for interpreting transport phenomena. Finally, the use is briefly illustrated of 3-D model simulations, in conjunction with the satellite data, for providing additional insight into fundamental transport mechanisms.

Grose, W. L.↗

Digital Lunar Exploration Sites (DLES) Terrain Crafting

Humans will soon be returning to the surface of the Moon with NASA’s Artemis program. The Artemis program is an international collaboration that will consist of a complex series of space systems and missions to explore the lunar surface and pave the way for the future exploration of Mars. NASA and its partners rely heavily on simulation for lighting and navigation studies as well as training astronauts, flight controllers, and mission support staff. The NASA Exploration Systems Simulations (NExSyS) team in the Simulation and Graphics Branch (ER7) in the Engineering Directorate at NASA’s Johnson Space Center has built up many simulation products to support this effort, one of which is the Digital Lunar Exploration Sites (DLES). DLES is a collection of products used to simulate and render the lunar surface in a digital environment. We discussed and presented an overview of the DLES products at the 2022 IEEE Aerospace Conference in Big Sky, MT with a paper titled "Digital Lunar Exploration Sites". This “DLES Terrain Crafting” paper will expand on the information previously provided in “DLES” paper and dive deeper into the details of the terrain crafting process and the toolsets used to support this task. The best digital data currently available of the lunar surface is provided by the Lunar Reconnaissance Orbiter (LRO). Its Lunar Orbiter Laser Altimeter (LOLA) achieves an impressive resolution of 5m per pixel at the Lunar South Pole (LSP) and can generate datasets covering a large continuous region near the LSP. There are a few additional methods, such as Shape from Shading which can infer higher resolution data (up to 1m per pixel) from the LRO Narrow Angle Camera (NAC) images. However, surface-based simulations require higher-resolution data, and this paper will discuss the process of enhancing the terrain to meet that need. The process begins with capturing statistical data of craters in the regions of interest using images provided by the LRO NAC. This data is then used to scatter artificial features which are not captured in the truth data, resulting in an enhanced DEM with a much higher resolution of 20cm per pixel. Many tools were built up to assist in the creation of these artificial Digital Elevation Models (DEM), which this paper will discuss in detail. DEMs themselves are a very powerful representation of a planetary surface, and many operations and tools can utilize the data they contain. This paper includes a description of the rendering of the lunar surface in a graphics engine, generation of contact patches to simulate tire to ground interaction, and ray tracing utilities to model Line of Sight (LOS) interactions with the terrain. This paper will also explore some new tool sets currently under development which aim to utilize Machine Learning (ML) to assist in the identification of craters from LRO NAC imagery. While this is not a novel idea, the NExSyS team is developing a unique approach which may result in more robust identification of crater characteristics.

Artemis↗

An Approach to Dynamic Human Reliability Analysis and Its Data Collection Framework

Human reliability analysis (HRA) is a method for evaluating human errors in a variety of complex systems such as nuclear power plants, military systems, aircraft, and chemical plants. Most HRA methods currently used by regulatory institutes or utilities are called static HRA and are carried out by simple worksheets or simple calculators. To date, there are many unsolved or intrinsic challenges in static HRA. For example, existing static HRA does not realistically model and evaluate human actions as they would be performed at actual systems. There is no method with HRA to objectively estimate the time required for human actions despite being essential to HRA processes. In addition, many HRA methods still rely on a dataset generated prior to the 1980s, from unrelated industry experience or simply from expert judgment. Accordingly, this study attempted to research how to overcome the challenges of existing HRA via dynamic risk assessment (a.k.a., simulation-based or computation-based risk assessment) techniques. First, this study developed a dynamic HRA method, named as PRocedure-based Investigation Method of EMRALD Risk Assessment – HRA (PRIMERA-HRA). The PRIMERA-HRA mainly concentrates on providing HRA analysts with specific guidelines on how to reasonably model human actions, assign human reliability data and evaluate output of simulation within a dynamic probabilistic risk assessment tool, called as Event Modeling Risk Assessment using Linked Diagrams (EMRALD). Second, this study also developed a module for performance shaping factors (i.e., the key concept in HRA quantification) applicable to dynamic HRA, then implemented it based on PRIMERA-HRA within the EMRALD tool. Third, this study developed an HRA data collection framework to support dynamic HRA, called as Simplified Human Error Experimental Program (SHEEP). Originally, the SHEEP study aimed to support static HRA and its data collection, but recently extended the scope to the new technologies such as dynamic HRA or HRA for advanced reactors. SHEEP focuses on the use of data collected from simplified simulators to complement—but not replace—data collection studies using full-scope simulators and actual operators. To date, many experiments were conducted under the SHEEP framework. Multiple analyses, such as human performance analysis, human error analysis, task complexity analysis, learning effect analysis and time distribution analysis, were also carried out using the collected data. Then, based on the major insights, an approach to inferring full-scope data based on simplified simulator data was proposed. The PRIMERA-HRA and SHEEP research are expected to evaluate human actions more realistically than existing static HRA, provide an opportunity to collect more HRA data with reasonable cost and labor, then contribute to enhance the quality of HRA.

99 - GENERAL AND MISCELLANEOUS↗

TPSAS-NF1676L-13040-DND

We examine the feasibility of using airborne lidar data to: 1) infer CRC Convair-580 profiles of submicrometer fraction (SMF) over land (which is the fraction of aerosols with diameters less than 1 micrometer and is closely related to FMF) and 2) provide a proxy for CCN. If these initial Aerosol Extinction Aerosol Effective Radius feasibility studies prove successful, we will then apply these methodologies in subsequent studies to examine the feasibility of using CALIPSO data in a similar manner. We use data acquired by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) during several recent field missions conducted by NASA, the Department of Energy, and NOAA. The airborne HSRL, which has acquired over 300 hours of data coincident with CALIPSO overpasses, measures aerosol extinction (532 nm), backscatter (532 and 1064 nm), and depolarization (532 and 1064 nm) profiles and thereby provides a dataset directly applicable to the CALIPSO measurements. During several of these field campaigns, airborne in situ measurements were acquired simultaneously within the HSRL “curtains” thereby facilitating direct correlations of the lidar observables to in situ measurements of particle size and composition, including SMF and CCN concentration. Previous studies have used simultaneous in situ measurements of SMF and Angström exponents derived from in situ scattering (Anderson et al., 2005) and remote sensing extinction (Redemann et al. 2009) measurements to build empirical relationships between these parameters. We adopt a similar approach and investigate relationships between the lidar observables, such as backscatter and extinction Angström exponents, with the coincident airborne in situ measurements of SMF and CCN concentration.

Richard Ferrare↗

Zonally averaged thermal balance and stability models for nitrogen polar caps on Triton

Voyager four-color imaging data of Triton are analyzed to calculate the bolometric hemispheric albedo as a function of latitude and longitude. Zonal averages of these data have been incorporated into a thermal balance model involving insolation, reradiation, and latent heat of sublimation of N2 ice for the surface. The current average bolometric albedo of Triton's polar caps is 0.8, implying an effective temperature of 34.2 K and a surface pressure of N2 of 1.6 microbar for unit emissivity. This pressure is an order of magnitude lower than the surface pressure of 18 microbar inferred from Voyager data (Broadfoot et al., 1989; Conrath et al., 1989), a discrepancy that can be reconciled if the emissivity of the N2 on Triton's surface is 0.66. The model predicts that Triton's surface north of 15 deg N latitude is experiencing deposition of N2 frosts, as are the bright portions of the south polar cap near the equator. This result explains why the south cap covers nearly the entire southern hemisphere of Triton.

Stansberry, John A.↗

Characterization of Response Times based on Voice Communication and Traffic Surveillance Data

A barrier to the integration of remotely piloted aircraft operations in the U.S. National Airspace System is the latency of voice communications between the air traffic controller and the remote pilot, and the latency of communication between the aircraft and the remote pilot. The latency can be substantial especially when satellite-based beyond-radio-line-of-sight communication and relay through the aircraft are employed. This study uses voice recordings of controller-pilot communications and aircraft track data to establish a baseline of pilot readback latencies and maneuver detection delays in the current piloted operations. A machine learning pipeline was developed to parse the contents of the air traffic control clearances including the callsigns using natural language processing. After manually validating the results obtained using the pipeline, the average pilot readback latency was found to be about 0.6 seconds. The average latency between the end of maneuver (inferred from track data), initiated by the pilot in response to the clearance, and the end of clearance was found to be about 176 seconds for altitude change commands, 69 seconds for heading change commands, and 182 seconds for speed change commands. The average latency between the beginning of maneuver and the end of clearance was found to be about 17 seconds for altitude change commands, 17seconds for heading change commands, and 25 seconds for speed change commands.

controller-pilot communication, communication late↗

Characterization of Response Times Based on Voice Communication and Traffic Surveillance Data

A barrier to the integration of remotely piloted aircraft operations in the U.S. National Airspace System is the latency of voice communications between the air traffic controller and the remote pilot, and the latency of communication between the aircraft and the remote pilot. The latency can be substantial especially when satellite-based beyond-radio-line-of-sight communication and relay through the aircraft are employed. This study uses voice recordings of controller-pilot communications and aircraft track data to establish a baseline of pilot readback latencies and maneuver detection delays in the current piloted operations. A machine learning pipeline was developed to parse the contents of the air traffic control clearances including the callsigns using natural language processing. After manually validating the results obtained using the pipeline, the average pilot readback latency was found to be about 0.6 seconds. The average latency between the end of maneuver (inferred from track data), initiated by the pilot in response to the clearance, and the end of clearance was found to be about 176 seconds for altitude change commands, 69 seconds for heading change commands, and 182 seconds for speed change commands. The average latency between the beginning of maneuver and the end of clearance was found to be about 17 seconds for altitude change commands, 17seconds for heading change commands, and 25 seconds for speed change commands.

controller-pilot communication↗

Data-Driven Radiative Hydrodynamic Modeling of the 2014 March 29 X1.0 Solar Flare

Spectroscopic observations of solar flares provide critical diagnostics of the physical conditions in the flaring atmosphere. Some key features in observed spectra have not yet been accounted for in existing flare models. Here we report a data-driven simulation of the well-observed X1.0 flare on 2014 March 29 that can reconcile some well-known spectral discrepancies. We analyzed spectra of the flaring region from the Interface Region Imaging Spectrograph (IRIS) in Mg II hk, the Interferometric BIdimensional Spectropolarimeter at the Dunn Solar Telescope (DSTIBIS) in H(alpha) 6563A and Ca II 8542A, and the Reuven Ramaty High Energy Solar Spectroscope Imager (RHESSI) in hard X-rays. We constructed a multithreaded flare loop model and used the electron flux inferred from RHESSI data as the input to the radiative hydrodynamic code RADYN to simulate the atmospheric response. We then synthesized various chromospheric emission lines and compared them with the IRIS and IBIS observations. In general, the synthetic intensities agree with the observed ones, especially near the northern footpoint of the flare. The simulated Mg II line profile has narrower wings than the observed one. This discrepancy can be reduced by using a higher microturbulent velocity (27 km/s) in a narrow chromospheric layer. In addition, we found that an increase of electron density in the upper chromosphere within a narrow height range of approx. 800 km below the transition region can turn the simulated Mg II line core into emission and thus reproduce the single peaked profile, which is a common feature in all IRIS flares.

Da Costa, Fatima Rubio↗

Reconciling the MOLA, TES, and Neutron Observations of the North Polar CO2 Mass Budget on Mars

There are now three independent observations of the CO2 polar cap mass budget of Mars' north polar cap. The first is based elevation changes detected by the Mars Orbiter Laser Altimeter (MOLA) on the Mars Global Surveyor (MGS). The second is based on MGS Thermal Emission Spectrometer (TES) broadband observations of the solar and infrared radiation fields at the top of the atmosphere. The third is based on neutron counts measured by the neutron spectrometer (NS) on Odyssey. If one assumes a cap density of 910 kg/cu m, then the peak mass loading poleward of 85 N inferred from the MOLA data is approx. 1090 kg/sq m, which compares to approx. 1150 kg/sq m inferred from TES for the same region, and 700 kg/sq m from the NS data. TES and MOLA are in good agreement, but are about 60% higher than the NS data. Is there a way to reconcile these discrepancies?

Haberle, Robert M.↗

Role of the interfacial thermal barrier in the effective thermal diffusivity/conductivity of SiC-fiber-reinforced reaction-bonded silicon nitride

Experimental thermal diffusivity data transverse to the fiber direction for composites composed of a reaction bonded silicon nitride matrix reinforced with uniaxially aligned carbon-coated silicon carbide fibers indicate the existence of a significant thermal barrier at the matrix-fiber interface. Calculations of the interfacial thermal conductances indicate that at 300 C and 1-atm N2, more than 90 percent of the heat conduction across the interface occurs by gaseous conduction. Good agreement is obtained between thermal conductance values for the oxidized composite at 1 atm calculated from the thermal conductivity of the N2 gas and those inferred from the data for the effective composite thermal conductivity.

Bhatt, Hemanshu↗

Comparability of Liquid Chromatography Tandem Mass Spectrometry Analysis of Dissolved Organic Matter across Laboratories

Non-targeted liquid chromatography tandem highresolution mass spectrometry (LC−MS/MS) is increasingly applied for the structure-resolved chemical analysis of dissolved organic matter (DOM). With new developments in MS instrumentation and analysis software, the approach has gained substantial momentum over the past decade. However, achieving high-quality analytical data that is reproducible and comparable across laboratories can be a bottleneck in non-targeted metabolomics and organic matter chemical analysis, especially for data reuse in repository-scale analyses. Understanding the capabilities as well as challenges of comparing LC−MS/MS data from different laboratories is necessary for inferring global trends from public data sets. To illuminate instrumentation factors that drive differences and variability, we used a standardized data analysis pipeline, including classical (CMN) and featurebased molecular networking (FBMN), to analyze data from a ring trial by 24 laboratories on identical sample sets of algal and DOM extracts that were mixed in predefined concentrations and spiked with standards. Our results showed that data sets from similar mass spectrometer types with unified instrument parameters were qualitatively comparable, resolving the same general trends and shared mass spectral features. Interlaboratory comparability was best for high-intensity features, while low-intensity features showed greater detection variability. Our analysis also highlights challenges when comparing data from instruments with different acquisition rates or operating with less standardized methods. Lastly, we provide recommendations for data integration, public data sharing, standardization, and best practices for standardized LC−MS/MS data acquisition, which will be critical for long-term time series and intercomparability of DOM chemical analyses.

DOM↗

Global Seasonal Climatologies of Ocean Chlorophyll: Blending In situ and Satellite Data for the CZCS Era

The historical archives of in situ (National Oceanographic Data Center) and satellite (Coastal Zone Color Scanner) chlorophyll data were combined using the blended analysis method of Reynolds [1988] in an attempt to construct an improved climatological seasonal representation of global chlorophyll distributions. The results of the blended analysis differed dramatically from the CZCS representation: global chlorophyll estimates increased 8-35% in the blended analysis depending upon season. Regional differences were even larger, up to 140% in the equatorial Indian Ocean in summer (during the southwest monsoon). Tropical Pacific chlorophyll values increased 25-41%. The results suggested that the CZCS generally underestimates chlorophyll. Regional and seasonal differences in the blended analysis were sufficiently large as to produce a different representation of global chlorophyll distributions than otherwise inferred from CZCS data alone. Analyses of primary production and biogeochemical cycles may be substantially impacted by these results.

Gregg, Watson W.↗

Geostatistical evaluation of satellite radar altimetry for high-resolution mapping of Lambert Glacier, Antarctica

The potential of satellite radar altimetry for high-resolution mapping of Antarctic ice streams is evaluated, using retracked and slope-corrected data from the Lambert Glacier and Amery Ice Shelf area, East Antarctica, acquired by Geosat during the Exact Repeat Mission (ERM), 1986-89. The map area includes lower Lambert Glacier north of 72.18 deg S, the southern Amery Ice Shelf, and the grounded inland ice sheet on both sides. The Geosat ERM altimetry is found to provide substantially more complete coverage than the 1978 Seasat altimetry, due to improved tracking. Variogram methods are used to estimate the noise levels in the data as a function of position throughout the map area. The spatial structure in the data is quantified by constructing experimental variograms using altimetry from the area of the grounding zone of Lambert Glacier, which is the area chiefly of interest in this topographically complex region. Kriging is employed to invert the along-track height measurements onto a fine-scale 3 km grid. The unsmoothed along-track Geosat ERM altimetry yields spatially continuous maps showing the main topographic features of lower Lambert Glacier, upper Amery Ice Shelf and the adjacent inland ice sheet. The probable position of the grounding line of Lambert Glacier is identified from a break in slope at the grounded ice/floating ice transition. The approximate standard error of the kriged map is inferred from the data noise levels.

Herzfeld, Ute C.↗

Conservative force model performance for TOPEX/Poseidon precision orbit determination

The TOPEX/Poseidon spacecraft was launched on August 10, 1992 to study the Earth's oceans. To achieve maximum benefit from the altimetric data collected, mission requirements dictate that TOPEX/Poseidon's orbit must be computed at an unprecedented level of accuracy. In order to satisfy these requirements, a model which accounts for the satellite's complex geometry, attitude, and surface properties has been developed. This `box-wing' representation treats the spacecraft as the combination of flat plates arranged in the shape of a box and a connecetd solar array. The nonconservative forces acting on each of the eight surfaces are computed independently, yielding vector accelerations which are summed to compute the total aggregate effect on the satellite center-of-mass. Parameters associated with each flat plate were derived from a finite element analysis of the spacecraft. Certain parameters can be inferred from tracking data and have been adjusted to obtain a better representation of the satellite acceleration history. Changes in the nominal mission profile and the presence of an `anomalistic' force have complicated this tuning process. Model performance, parameter sensitivities, and the `anomalistic' force will be discussed.

Marshall, J. Andrew↗

On the rms anisotropy at 7 deg and 10 deg observed in the COBE-DMR two year sky maps

The frequency-independent rms temperature fluctuations determined from the Cosmic Background Explorer-Differential Microwave Radiometer (COBE-DMR) two-year sky maps are used to infer the parameter Q(sub rms-PS), which characterizes the normalization of power-law models of primordial cosmological temperature anisotropy, for a forced fit to a scale-invariant Harrison-Zel'dovich (n = 1) spectral model. Using a joint analysis of the 7 deg and 10 deg 'cross'-rms derived from both the 53 and 90 GHz sky maps, we find Q(sub rms-PS) = 17.0(sub -2.1 sup +2.5) micro Kelvin when the low quadrupole is included, and Q(sub rms-PS) = 19.4(sub -2.1 sup +2.3) micro Kelvin excluding the quadrupole. These results are consistent with the n = 1 fits from more sensitive methods. The effect of the low quadrupole derived from the COBE-DMR data on the inferred Q(sub rms-PS) normalization is investigated. A bias to lower Q(sub rms-PS) is found when the quadrupole is included. The higher normalization for a forced n = 1 fit is then favored by the cross-rms technique.

Banday, A. J.↗

Comparison of satellite-derived dynamical quantities for the stratosphere of the Southern Hemisphere

As part of the international Middle Atmosphere Program (MAP), a project was instituted to study the dynamics of the Middle Atmosphere in the Southern Hemisphere (MASH). A pre-MASH workshop was held with two aims: comparison of Southern Hemisphere dynamical quantities derived from various archives of satellite data; and assessing the impact of different base-level height information on such derived quantities. The dynamical quantities examined included geopotential height, zonal wind, potential vorticity, eddy heat and momentum fluxes, and Eliassen-Palm fluxes. It was found that while there was usually qualitative agreement between the different sets of fields, substantial quantitative differences were evident, particularly in high latitudes. The fidelity of the base-level analysis was found to be of prime importance in calculating derived quantities - especially the Eliassen-Palm flux divergence and potential vorticity. Improvements in base-level analyses are recommended. In particular, quality controls should be introduced to remove spurious localized features from analyses, and information from all Antarctic radiosondes should be utilized where possible. Caution in drawing quantitative inferences from satellite data for the middle atmosphere of the Southern Hemisphere is advised.

Miles, Thomas↗

A GPU‐Accelerated Generative Adversarial Model for Causal Inference

We develop a GPU-accelerated machine learning generative adversarial model designed to facilitate causal inferences from observational data. Our model's theoretical framework is conceptualized in a manner that is amenable to being operable and scalable for high-performance computing platforms. We leverage GPU acceleration to develop a parallel evolutionary algorithm to achieve large-scale parallel computation of the model within a now widely accessible computing platform. This capability both enhances computational speedup and efficiency and also extends the use of the model to a broader range of substantive research domains while maintaining the underlying theoretical properties of the model.

GPU↗

The effect of local advection on the inference of soil moisture from thermal infrared radiances

The degree to which the GOES-VISSR infrared data can be used to infer area-averaged soil moisture is explored for a five-day case study period. Chosen variables are transformed and incorporated into a multiple linear regression. The actual observations, rather than a simplified model, are used to determine the relationship between soil moisture and GOES-IR radiance. It is shown that a depletion coefficient of 0.92 produces an index of ground truth which is best correlated with soil moisture as inferred from GOES thermal infrared data. When all individual daily soil estimates during the case study period are averaged at each point and compared to the average observed soil moisture, the data correlate at 0.85. This implies that the algorithm can distinguish at least four categories of soil moisture.

Wetzel, Peter J.↗