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NASA NTRS2011

The NASA Lightning Nitrogen Oxides Model (LNOM): Application to Air Quality Modeling

Recent improvements to the NASA Marshall Space Flight Center Lightning Nitrogen Oxides Model (LNOM) and its application to the Community Multiscale Air Quality (CMAQ) modeling system are discussed. The LNOM analyzes Lightning Mapping Array (LMA) and National Lightning Detection Network(TradeMark)(NLDN) data to estimate the raw (i.e., unmixed and otherwise environmentally unmodified) vertical profile of lightning NO(x) (= NO + NO2). The latest LNOM estimates of lightning channel length distributions, lightning 1-m segment altitude distributions, and the vertical profile of lightning NO(x) are presented. The primary improvement to the LNOM is the inclusion of non-return stroke lightning NOx production due to: (1) hot core stepped and dart leaders, (2) stepped leader corona sheath, K-changes, continuing currents, and M-components. The impact of including LNOM-estimates of lightning NO(x) for an August 2006 run of CMAQ is discussed.

Koshak, William↗

NASA NTRS2010

Developing Collective Training for Small Unmanned Aerial Systems Employment

The projected use of small unmanned aerial systems (SUAS) in military operations will produce training requirements which go beyond current capabilities. The paper describes the development of prototype training procedures and accompanying research simulations to address this need. We initially constructed a testbed to develop simulation-based training for an SUAS operator equipped with a simulated vertical-lift and land SUAS. However, the required training will go beyond merely training an operator how to pilot an SUAS. In addition to tactics, techniques, and procedures for employment of SUASs, collective training methods must be trained. Moreover, the leader of a unit equipped with SUAS will need to learn how to plan missions which incorporate the SUAS, and take into account air space and frequency management considerations. The demands of the task require the leader to allocate personnel to the SUAS mission, communicate and coordinate with those personnel during the mission, and make use of the information provided. To help address these training issues, we expanded our research testbed to include a command and control node (C2 node), to enable communications between a leader and the SUAS operator. In addition, we added a virtual environment in which dismounted infantry missions can be conducted. This virtual environment provides the opportunity for interactions among human-controlled avatars and non-player characters (NPCs), plus authoring tools to construct scenarios. Using these NPCs, a collective exercise involving friendly, enemy, and civilian personnel can be conducted without the need for a human role-player for every entity. We will describe the results of our first experiment, which examined the ability of players to negotiate use of the C2 node and the virtual environment at the same time, in order to see if this is a feasible combination of tools for training development.

Durlach, Paula J.↗

NASA NTRS2010

Assessment of Aerosol Distributions from GEOS-5 Using the CALIPSO Feature Mask

A-train sensors such as MODIS, MISR, and CALIPSO are used to determine aerosol properties, and in the process a means of estimating aerosol type (e.g. smoke vs. dust). Correct classification of aerosol type is important for climate assessment, air quality applications, and for comparisons and analysis with aerosol transport models. The Aerosols-Clouds-Ecosystems (ACE) satellite mission proposed in the NRC Decadal Survey describes a next generation aerosol and cloud suite similar to the current A-train, including a lidar. The future ACE lidar must be able to determine aerosol type effectively in conjunction with modeling activities to achieve ACE objectives. Here we examine the current capabilities of CALIPSO and the NASA Goddard Earth Observing System general circulation model and data assimilation system (GEOS-5), to place future ACE needs in context. The CALIPSO level 2 feature mask includes vertical profiles of aerosol layers classified by type. GEOS-5 provides global 3D aerosol mass for sulfate, sea salt, dust, and black and organic carbon. A GEOS aerosol scene classification algorithm has been developed to provide estimates of aerosol mixtures and extinction profiles along the CALIPSO orbit track. In previous work, initial comparisons between GEOS-5 derived aerosol mixtures and CALIPSO derived aerosol types were presented for July 2007. In general, the results showed that model and lidar derived aerosol types did not agree well in the boundary layer. Agreement was poor over Europe, where CALIPSO indicated the presence of dust and pollution mixtures yet GEOS-5 was dominated by pollution with little dust. Over the ocean in the tropics, the model appeared to contain less sea salt than detected by CALIPSO, yet at high latitudes the situation was reserved. Agreement between CALIPSO and GEOS-5, aerosol types improved above the boundary layer, primarily in dust and smoke dominated regions. At higher altitudes (> 5 km), the model contained aerosol layers not detected by CALIPSO. Here we present new results for a full year study using the new Version 3 CALIPSO data and most recent GEOS-5 model results.

Welton, Ellsworth↗

DOE OSTI2021

Electrically Pumped Epitaxially Regrown GaSb-Based Type-I Quantum-Well Surface-Emitting Lasers with Buried High-Index-Contrast Photonic Crystal Layer

Epitaxially regrown electrically pumped photonic crystal surface-emitting lasers (PCSELs) emitting near 2 and 2.6 μm are designed, fabricated, and characterized. A high-index-contrast photonic crystal layer is incorporated into the GaSb-based laser heterostructure by air-hole-retaining epitaxial regrowth. A square lattice of triangular holes is etched in the top waveguide core layer of the incomplete laser heterostructure. The nanopatterned surface is subsequently cleaned and regrown with AlGaAsSb p-cladding material. Transmission electron microscopy studies demonstrate uniform regrowth over the nanopatterned GaSb surface. The selected regrowth regimes yield a buried 2D array of elongated air-holes. The diode PCSELs based on moderately etched nanopatterns demonstrate band-edge lasing near 2 μm up to room temperatures. The cascade diode PCSELs operate near 2.6 μm with minimum threshold current densities of about 500 A cm -2 achieved at 180 K. The devices generate mW level output in narrow divergence beam emitted from the window in substrate contact. The angle-resolved electroluminescence measurements reveal a four-sub-band band structure with an apparent photonic bandgap corresponding to the buried high-index-contrast square photonic crystal layer. Finally, the PCSELs made of heterostructures supporting two modes in the vertical direction demonstrate two sets of sub-bands showing anti-crossing-like interaction.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

NASA NTRS1994

Report on the comparison of the scan strategies employed by the Patrick Air Force Base WSR-74C/McGill radar and the NWS Melbourne WSR-88D radar

The objective of this investigation is to determine whether the current standard WSR-88D radar (NEXRAD) scan strategies permit the use of the Melbourne WSR-88D to perform the essential functions now performed by the Patrick Air Force Base (PAFB) WSR-74C/McGill radar for evaluating shuttle weather flight rules (FR) and launch commit criteria (LCC). To meet this objective, the investigation compared the beam coverage patterns of the WSR-74C/McGill radar located at PAFB and the WSR-88D radar located at the Melbourne National Weather Service (NWS) Office over the area of concern for weather FR and LCC evaluations. The analysis focused on beam coverage within four vertical 74 km radius cylinders (1 to 4 km above ground level (AGL), 4 to 8 km AGL, 8 to 12 km AGL, and 1 to 12 km AGL) centered on Kennedy Space Center (KSC) Launch Complex 39A. The PAFB WSR-74C/McGill radar is approximately 17 km north-northeast of the Melbourne WSR-88D radar. The beam coverage of the WSR-88D using VCP 11 located at the Melbourne NWS Office is comparable (difference in percent of the atmosphere sampled between the two radars is 10 percent or less) within the area of concern to the beam coverage of the WSR-74C/McGill radar located at PAFB. Both radars provide good beam coverage over much of the atmospheric region of concern. In addition, both radars provide poor beam coverage (coverage less than 50 percent) over limited regions near the radars due to the radars' cone of silence and gaps in coverage within the higher elevation scans. Based on scan strategy alone, the WSR-88D radar could be used to perform the essential functions now performed by the PAFB WSR-74C/McGill radar for evaluating shuttle weather FR and LCC. Other radar characteristics may, however, affect the decision as to which radar to use in a given case.

Taylor, Gregory↗

NASA NTRS2004

Preliminary Analysis of X-Band and Ka-Band Radar for Use in the Detection of Icing Conditions Aloft

NASA and the U.S. Army Cold Regions Research and Engineering Laboratory (CRREL) have an on-going activity to develop remote sensing technologies for the detection and measurement of icing conditions aloft. Radar has been identified as a strong tool for this work. However, since the remote detection of icing conditions with the intent to identify areas of icing hazard is a new and evolving capability, there are no set requirements for radar sensitivity. This work is an initial attempt to quantify, through analysis, the sensitivity requirements for an icing remote sensing radar. The primary radar of interest for cloud measurements is Ka-band, however, since NASA is currently using an X-band unit, this frequency is also examined. Several aspects of radar signal analysis were examined. Cloud reflectivity was calculated for several forms of cloud using two different techniques. The Air Force Geophysical Laboratory (AFGL) cloud models, with different drop spectra represented by a modified gamma distribution, were utilized to examine several categories of cloud formation. Also a fundamental methods approach was used to allow manipulation of the cloud droplet size spectra. And an analytical icing radar simulator was developed to examine the complete radar system response to a configurable multi-layer cloud environment. Also discussed is the NASA vertical pointing X-band radar. The radar and its data system are described, and several summer weather events are reviewed.

Reehorst, Andrew L.↗

NASA NTRSDate not supplied

The ACCP Inclined Orbit Project: Enabling New and Synergistic Aerosol Remote Sensing Inversions

Atmospheric aerosols have high spatiotemporal variations due to their diverse sources including windblown dust, wildfires, volcanic eruptions, and anthropogenic emissions. These aerosols also have strong diurnal emission characteristics that influence long-range transport, air quality, Earth’s radiation budget, biogeochemical cycles, and weather forecasting. While current sensors can measure the steady-state of global 3D cloud and aerosol properties, we lack the observational datasets to discover the diurnal variability of aerosols, even at seasonal and regional scales, because these missions utilize sun synchronous orbits. An Aerosols and Clouds, Convection and Precipitation (ACCP) observing system has been established as part of NASA’s new Earth System Observatory (ESO) to fulfill the science needs presented in the 2017 Earth Science Decadal Survey. The selected ACCP architecture encompasses sensors in two orbit planes, one of which utilizes an inclined orbit (nominally ~55 degrees at a 407 km altitude) to advance our understanding of aerosol and cloud properties and target the dynamics of the cloud and aerosol processes on sub-daily time scales. The anticipated instrumentation suite for the ACCP Inclined Orbit Project is a Stereo Camera System, Polarimeter, Microwave Radiometer, Two-Frequency Radar, and Backscatter Lidar. The polarimeter is expected to have multiple wavelength bands and viewing angles to enable accurate retrievals of aerosol microphysical and optical properties. The backscatter lidar will provide vertical profiles of attenuated backscatter and depolarization ratio at two wavelengths, with better daytime signal-to-noise ratio than previous space-based lidar systems to improve aerosol detection/typing and estimates of aerosol optical properties. The stereo camera system, while designed primarily for clouds, will also provide aerosol plume heights and air motions at the plume heights. This invited presentation will provide (1) an overview of the ACCP Inclined Orbit Project, (2) a description of the new sensor capabilities and orbital characteristics, and (3) a preview of the potential for new synergistic aerosol inversion techniques.

John E Yorks↗

NASA NTRS1982

A numerical simulation of an atmospheric vortex street

A simplified mesoscale mixed-layer model is utilized to study the flow past an ocean island during a case of cold air outbreak over the Kuroshio Current. Using data taken during AMTEX '75, the governing equations are integrated in time to simulate the development of a Karman vortex street downstream of the island of Cheju-do. The surface layer, inversion layer, and overlying stable layer are all parametrized in the model. Very weak sinusoidal waviness but no vortex street was found in the case of the island. For a mixed layer barely deep enough to allow no part of the mountain on the island to protrude, there was more pronounced waviness but still no vortices. This result may not hold for boundary layers with poor vertical mixing. A numerical simulation of the vortex street yielded good results in comparison. The speed ratio, spacing ratio, and Strouhal number agreed rather closely with observations.

Ruscher, P. H.↗

NASA NTRS2008

Interpolating Fields of Carbon Monoxide Data Using a Hybrid Statistical-Physical Model

Atmospheric Carbon Monoxide (CO) is a pollutant gas of which the US congress has mandated regular monitoring, and satellite sensors can be used to retrieve regional concentrations of CO over several vertical layers. However, CO at cloudy locations cannot be observed and have to be estimated from the observed data set, resulting in an interpolation problem. The current state-of-the-art solution is to combine prior information, computed by a deterministic physical model, with observations. However, the deterministic model may introduce uncertainties that do not derive from the data. While sharing certain features with the physical model, this paper presents a Bayesian hierarchical model for interpolating CO on a 3-dimensional spatial grid, across time. To our knowledge such a model has not been considered before. The model is applied to a hypothetical air-quality monitoring scenario, and is compared to existing interpolation methods. The results provide motivation for the use of the statistical model for regional to local applications.

Arellano, A. A.↗

NASA NTRSDate not supplied

Adaptive Stress Testing of Collision Avoidance Systems for Small UASs with Deep Reinforcement Learning

The next-generation Airborne Collision Avoidance System for smaller UASs (ACAS sXu) is currently being developed and tested by the Federal Aviation Administration (FAA) to provide detect-and-avoid capability for small unmanned aircraft operating beyond line-of-sight. Due to the complexity and safety-critical nature of the system, safety validation is important not only for the certification of the final system, but also for informing changes during the iterative development process. In this paper, we analyze a prototype of ACAS sXu in simulated aircraft encounters to discover scenarios of small near mid-air collisions (sNMACs), an important safety event in which two aircraft come closer than 50 feet horizontally and 15 feet vertically. Due to the size and complexity of the system as well as rarity of sNMAC events, traditional methods such as Monte Carlo testing often require informed setup and targeting to elicit failures. However, such a dependence on domain knowledge can be incompatible with the independent verification and validation (IV&V) process, the aim of which is to discover unforeseen issues. To address these challenges, we apply an accelerated validation method called adaptive stress testing (AST) to find the most likely sNMAC scenarios without reliance on system introspection. AST uses reinforcement learning to adapt the search towards the most promising areas of the search space as it progresses. We use a state-of-the-art deep reinforcement learning algorithm, proximate policy optimization, to more efficiently search the large and continuous state space. We find that this approach significantly improves the performance of AST compared to a prior approach based on Monte Carlo tree search. We perform experiments using AST to find sNMAC events under various encounter configurations, varying parameters pertaining to dynamics and coordination. Our experiments show AST to be very effective at finding sNMAC scenarios. We summarize our findings, presenting high-level categories of discovered sNMACs and specific examples of encounters in each category.

aircraft collision avoidance↗

NASA NTRSDate not supplied

Generic Urban Air Mobility Simulation

This research presents a simulation framework for autonomous research for a UAM vehicle using the NASA Revolutionary Vertical Lift Technology Lift+Cruise concept vehicle. Our research results were produced using the open-source, six degree of freedom, rigid-body, nonlinear generic urban air mobility (GUAM) simulation. The intent of this paper is to demonstrate the GUAM simulation and a series of Challenge Problems that our researchers have posed to the broader autonomous vehicle research community. Our team has developed the GUAM simulation for the express purpose of providing a high-fidelity transition vehicle dynamics model to foster collaboration and algorithm performance comparison across research teams. In this paper, we demonstrate some of the autonomous flight research challenges and some of our current approaches to tackling basic autonomous flight tasks (e.g., trajectory following, stationary and moving obstacle avoidance). Additionally, we propose some flight metrics to assess autonomous algorithm performance while accomplishing these basic autonomous tasks.

autonomous flight↗

NASA NTRSDate not supplied

Helicopter Pilot Assessments of the Airborne Collision Avoidance System XR With Automated Maneuvering

The Airborne Collision Avoidance System X (ACAS X) is a next-generation collision avoidance tool developed to support different aircraft types and operations. The rotorcraft variant – referred to as ACAS XR – is designed to accommodate existing helicopter platforms as well as in-development, electric vertical takeoff and landing concepts, which are critical to the emerging concept of operations referred to as Advanced Air Mobility. The fundamental role of ACAS XR is to provide Detect and Avoid (DAA) and/or Collision Avoidance (CA) protection against airborne traffic. DAA alerting and guidance in the context of ACAS XR is caution-level and “suggestive,” and is to be used by the pilot if, and when, they decide to maneuver against an identified threat to DAA “well clear.” The CA alerting, by contrast, is warning-level and “directive,” with the pilot required to comply with the associated guidance to prevent a predicted Near Midair Collision (NMAC). The CA alerts generated by ACAS XR are referred to as Resolution Advisories (RAs) consistent with previous CA systems. Unlike earlier CA systems, ACAS XR issues RAs in the horizontal and vertical dimensions as well as multi-axis RAs (referred to as “Blended” RAs). According to the Minimal Operational Performance Standards of DAA systems for Unmanned Aircraft Systems, maneuvers to comply with RAs may be automated, whereas maneuvers based on DAA alerting assume a manual response. The current study was a human-in-the-loop simulation that presented rotorcraft pilots with ACAS XR alerts and guidance in a fixed-base eVTOL simulator with varying levels of automation. Objective results showed that pilots complied with all RAs within the expected 5-second time window and responded to DAA alerts quicker than in earlier studies with ACAS XU. Pilots often made larger horizontal deviations during Manual RAs, but often favored vertical and blended maneuvers. No NMACs occurred, and losses of well clear were mainly attributed to the obligation of the pilots and system to maneuver only after the CA phase of the encounter had begun. Other losses were due to pilots’ noncompliance or disregard for ACAS XR’s alerting and guidance. Noncompliance with RAs most frequently occurred when pilots determined they were too close to the terrain to continue to follow Descend RAs, performing vertical maneuvers instead of following Horizontal RAs, or rejecting Horizontal RA updates because they felt that enough maneuvering had been performed. Subjectively, pilots found the DAA and RA alerting and guidance intuitive and useful for VFR helicopter operations. Slightly more pilots preferred the Automated RA condition to the Manual RA condition. Lastly, they also felt that ACAS led to occasional unsafe Descend RAs. Caveats and future implications are discussed.

eVTOL↗

NASA NTRSDate not supplied

Helicopter Pilot Assessments of the Airborne Collision Avoidance System XR With Automated Maneuvering

eVTOL↗

NASA NTRS2005

Giovanni: A System for Rapid Access, Visualization and Analysis of Earth Science Data Online

Collecting data and understanding data structures traditionally are the first steps that a user must take, before the core investigation can begin. This is a time-consuming and challenging task, especially when science objectives require users to deal with large multi-sensor data that are usually in different formats and internal structures. The Goddard Earth Sciences Data and Information Services Center (GES DISC) has created the GES DISC Interactive Online Visualization and ANalysis Infrastructure, Giovanni, to enable Web-based visualization and analysis of satellite remotely sensed meteorological, oceanographic, and hydrologic data sets, without users having to download data. The current operational Giovanni interfaces provide the capability to process a number of important satellite measurements, such as (1) ozone and other trace gases from TOMS, OMI, HALOE, and MLS; (2) air temperature, water vapor, and geopotential height from AIRS; (3) aerosols from MODIS TerrdAqua, and GOCART model; (4) precipitation from TRMM and ground measurements; (5) chlorophyll and other ocean color products from SeaWiFS and MODIS Aqua; and (6) sea surface temperature from MODIS Aqua. Depending on the input data structure, the system provides simple statistical analysis and creates time-averaged area plot, area-averaged time series, animations, Hovmoller latitude vs. time and longitude vs. time plots, as well as vertical profiles. The inter-comparison interfaces allow a user to compare observations from different instruments, to conduct anomaly analysis, and to study basic relationships between physical parameters. Giovanni handles data with different temporal and spatial resolutions and, thus, enables both regional and global long-term climate research and short-term special events investigation, as well as data validations and assessments. Because of its simplicity of usage, Giovanni is powerful and versatile, able to assist a wide range of users, from the discipline scientists conducting preliminary research in various fields, to students in the classroom learning about weather, climate, and other natural phenomena. Giovanni can be accessed from: http://disc. esfc.nasa.gov/techlab/giovanni/index.shtml

Shen, S.↗

NASA NTRS2018

The Ozone Water-Land Environmental Transition Study: An Innovative Strategy for Understanding Chesapeake Bay Pollution Events

Coastal regions have historically represented a significant challenge for air quality investigations because of water-land boundary transition characteristics and a paucity of measurements available over water. Prior studies have identified the formation of high levels of ozone over water bodies, such as the Chesapeake Bay, that can potentially recirculate back over land to significantly impact populated areas. Earth-observing satellites and forecast models face challenges in capturing the coastal transition zone where small-scale meteorological dynamics are complex and large changes in pollutants can occur on very short spatial and temporal scales. An observation strategy is presented to synchronously measure pollutants “over land” and “over water” to provide a more complete picture of chemical gradients across coastal boundaries for both the needs of state and local environmental management and new remote sensing platforms. Intensive vertical profile information from ozone lidar systems and ozonesondes, obtained at two main sites, one over land and the other over water, are complemented by remote sensing and in situ observations of air quality from ground-based, airborne (both personned and unpersonned), and shipborne platforms. These observations, coupled with reliable chemical transport simulations, such as the National Oceanic and Atmospheric Administration (NOAA) National Air Quality Forecast Capability (NAQFC), are expected to lead to a more fully characterized and complete land–water interaction observing system that can be used to assess future geostationary air quality instruments, such as the National Aeronautics and Space Administration (NASA) Tropospheric Emissions: Monitoring of Pollution (TEMPO), and current low-Earth-orbiting satellites, such as the European Space Agency’s Sentinel-5 Precursor (S5-P) with its Tropospheric Monitoring Instrument (TROPOMI).

Forecast Models↗

NASA NTRS2023

Characterization of Errors in Satellite-Based HCHO/NO 2 Tropospheric Column Ratios With Respect to Chemistry, Column-to-PBL Translation, Spatial Representation, and Retrieval Uncertainties

The availability of formaldehyde (HCHO) (a proxy for volatile organic compound reactivity) and nitrogen dioxide (NO 2 ) (a proxy for nitrogen oxides) tropospheric columns from ultraviolet–visible (UV–Vis) satellites has motivated many to use their ratios to gain some insights into the near-surface ozone sensitivity. Strong emphasis has been placed on the challenges that come with transforming what is being observed in the tropospheric column to what is actually in the planetary boundary layer (PBL) and near the surface; however, little attention has been paid to other sources of error such as chemistry, spatial representation, and retrieval uncertainties. Here we leverage a wide spectrum of tools and data to quantify those errors carefully. Concerning the chemistry error, a well-characterized box model constrained by more than 500 h of aircraft data from NASA's air quality campaigns is used to simulate the ratio of the chemical loss of HO 2 + RO 2 (LRO x ) to the chemical loss of NO x (LNO x ). Subsequently, we challenge the predictive power of HCHO/NO 2 ratios (FNRs), which are commonly applied in current research, in detecting the underlying ozone regimes by comparing them to LRO x /LNO x . FNRs show a strongly linear (R 2 =0.94) relationship with LRO x /LNO x , but only on the logarithmic scale. Following the baseline (i.e., ln(LRO x /LNO x ) = −1.0 ± 0.2) with the model and mechanism (CB06, r2) used for segregating NO x -sensitive from VOC-sensitive regimes, we observe a broad range of FNR thresholds ranging from 1 to 4. The transitioning ratios strictly follow a Gaussian distribution with a mean and standard deviation of 1.8 and 0.4, respectively. This implies that the FNR has an inherent 20 % standard error (1σ) resulting from not accurately describing the RO x –HO x cycle. We calculate high ozone production rates (PO 3 ) dominated by large HCHO × NO 2 concentration levels, a new proxy for the abundance of ozone precursors. The relationship between PO 3 and HCHO × NO 2 becomes more pronounced when moving towards NO x -sensitive regions due to nonlinear chemistry; our results indicate that there is fruitful information in the HCHO × NO 2 metric that has not been utilized in ozone studies. The vast amount of vertical information on HCHO and NO 2 concentrations from the air quality campaigns enables us to parameterize the vertical shapes of FNRs using a second-order rational function permitting an analytical solution for an altitude adjustment factor to partition the tropospheric columns into the PBL region. We propose a mathematical solution to the spatial representation error based on modeling isotropic semivariograms. Based on summertime-averaged data, the Ozone Monitoring Instrument (OMI) loses 12 % of its spatial information at its native resolution with respect to a high-resolution sensor like the TROPOspheric Monitoring Instrument (TROPOMI) (> 5.5 × 3.5 km 2 ). A pixel with a grid size of 216 km 2 fails at capturing ∼ 65 % of the spatial information in FNRs at a 50 km length scale comparable to the size of a large urban center (e.g., Los Angeles). We ultimately leverage a large suite of in situ and ground-based remote sensing measurements to draw the error distributions of daily TROPOMI and OMI tropospheric NO 2 and HCHO columns. At a 68 % confidence interval (1σ), errors pertaining to daily TROPOMI observations, either HCHO or tropospheric NO 2 columns, should be above 1.2–1.5 × 10 16 molec. cm −2 to attain a 20 %–30 % standard error in the ratio. This level of error is almost non-achievable with the OMI given its large error in HCHO. The satellite column retrieval error is the largest contributor to the total error (40 %–90 %) in the FNRs. Due to a stronger signal in cities, the total relative error (< 50 %) tends to be mild, whereas areas with low vegetation and anthropogenic sources (e.g., the Rocky Mountains) are markedly uncertain (> 100 %). Our study suggests that continuing development in the retrieval algorithm and sensor design and calibration is essential to be able to advance the application of FNRs beyond a qualitative metric.

Amir H. Souri↗

NASA NTRSDate not supplied

Solid-state Architecture Batteries for Enhanced Rechargeability and Safety (SABERS) Beyond Li-Ion: Technology to Enable Sustainable Electric Aviation

All-electric vertical take-off and landing vehicles (eVTOL) for urban air mobility (UAM) concepts face numerous challenging technical barriers before their introduction into the consumer marketplace. The primary barrier to overcome is developing an energy storage system capable of meeting the rigorous aerospace safety and performance criteria. The performance metrics for eVTOL vehicles are at least two times greater than those of electric ground vehicles. Furthermore, inherently non-flammable batteries are essential for safe operation of commercial electric aerovehicles. The SABERS concept proposes a battery that meets the key performance criteria through development of a solid-state architecture battery utilizing high-capacity sulfur-selenium cathode and lithium metal anode. The combination of sulfur and selenium offers a balanced energy-to-power density ratio, which can be tailored to the specific application by altering the stoichiometric ratios of sulfur to selenium. This hybrid cathode will be developed by implementing NASA patented holey graphene technology as a highly conductive, ultra-lightweight electrode scaffold. A solid-state electrolyte will be used as a safe, non-flammable replacement to the highly flammable liquid organic electrolytes currently used in SOA lithium-ion batteries. This solid-state lithium-sulfur/selenium cell will be designed into a serial stacking configuration to enable dense packaging of the battery cells. The serial stacking configuration is termed a bipolar stack, which has the advantages of reducing overall cell weight, simplifying the interfaced connections for the cell, and minimizing the cooling requirements. Lastly, optimization of battery components will occur through a robust and rigorous combination of various computational modeling techniques covering multiple length scales. The expected result will be a fully solid-state battery with operational temperatures up to 150 °C which provides the required energy density, discharge rates, and inherent safety to meet the strict aerospace mission performance criteria. This presentation will demonstrate a feasible path for solid-state cells that possess a specific energy of greater than 400 Wh/kg to enable electric aircraft.

Urban Air Mobility (UAM) Vehicles↗

NASA NTRS1984

Numerical simulations of the Ross Sea tides

Tidal currents below the floating Ross Ice shelf are reconstructed by using a numerical tidal model. They are predominantly diurnal, achieve maximum strength in regions near where the ice shelf runs aground, and are significantly enhanced by topographic Rossby wave propagation along the ice front. A comparison with observations of the vertical motion of the ice shelf surface indicates that the model reproduces the diurnal tidal characteristics within 20 percent. Similar agreement for the relatively weak semidiurnal tides was not obtained, and this calls attention to possible errors of the open boundary forcing obtained from global-ocean tidal simulations and to possible errors in mapping zones of ice shelf grounding. Air-sea contact below the ice shelf is eliminated by the thick ice cover. The dominant sub-ice-shelf circulation may thus be tidally induced. A preliminary assessment of sub-ice-shelf conditions based on the numerical tidal simulations suggests that (1) strong barotropic circulation is driven along the ice front and (2) tidal fronts may form in the sub-ice-shelf cavity where the water column is thin and where the buoyancy input is weak.

Macayeal, D. R.↗