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Investigating the Impacts of a Separation Standard for UAS Operations in Enroute and Transition Airspace

Unmanned aircraft systems will be required to equip with a detect and avoid system in order to satisfy the federal aviation regulations to remain well clear of other aircraft. To comply with regulations in today’s operations manned aircraft must “see and avoid” other aircraft and use subjective judgment to determine whether those aircraft are well clear. For a detect-and- avoid (DAA) system to satisfy the requirement to stay well clear, a quantitative definition of well clear needs to be defined and evaluated. Definitions for the boundary of well clear have been proposed by the Unmanned Aircraft System (UAS) Executive Committee Science and Research Panel (SaRP) and the Radio Technical Commission for Aeronautics (RTCA) Special Committee 228 on Detect and Avoid Systems. This study investigates the interoperability implications of UAS using proposed well clear definitions as a separation standard for conducting operations in the national airspace system. The first analysis in the study focuses on the effect of variations in well clear definition parameters on the rate of losses of well clear per flight hour. The second analysis considers three well clear definitions and presents the relative state conditions of intruder aircraft as they encroach upon the well clear boundary. The third analysis focuses on the definition of the alerting criteria needed to inform the UAS operator of a potential loss of well clear. All three analyses are conducted in a NAS-wide fast-time simulation environment using UAS aircraft models, proposed UAS missions, and historical air defense radar data to populate the background traffic operating under visual flight rules. The results from the three analyses presented in this study inform the safety case, requirements development, and the operational environment for the DAA minimum operational performance standards.

UAS Seperation Standard↗

NASADEM Global Elevation Model: Methods and Progress

NASADEM (NASA Digital Elevation Model) is a near-global elevation model that is being produced primarily by completely reprocessing the Shuttle Radar Topography Mission (SRTM) radar data and then merging it with refined ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) GDEM (Global Digital Elevation Model) elevations. The new and improved SRTM elevations in NASADEM result from better vertical control of each SRTM data swath via reference to ICESat (Ice, Cloud, and land Elevation Satellite) elevations and from SRTM void reductions using advanced interferometric unwrapping algorithms. Remnant voids will be filled primarily by GDEM3, but with reduction of GDEM glitches (mostly related to clouds) and therefore with only minor need for secondary sources of fill.

GDEM↗

Characteristics of a Well Clear Definition and Alerting Criteria for Encounters Between UAS and Manned Aircraft in Class E Airspace

Unmanned aircraft systems (UAS) will be required to equip with a detect-and-avoid (DAA) system in order to satisfy the federal aviation regulations to remain well clear of other aircraft. For a DAA system to satisfy the requirement to stay well clear of other airborne traffic, a quantitative definition of well clear needs to be defined and evaluated. This study investigates the implications of UAS using proposed well clear definitions as a separation standard for conducting operations in the National Airspace System (NAS). The first analysis considers three well clear definitions and presents the relative state conditions of intruder aircraft as they encroach upon the well clear boundary. The second analysis focuses on the definition of the alerting criteria needed to inform the UAS operator of a potential loss of well clear. All analyses are conducted in a NAS-wide fast-time simulation environment using UAS aircraft models, proposed UAS missions, and historical air defense radar data to populate the background traffic operating under visual flight rules. The results presented in this study inform the safety case, requirements development, and the operational environment for DAA minimum operational performance standards.

Safety↗

Path Attenuation Estimates for the DPR

The algorithm for the Surface Reference Technique (SRT) has been updated from version V6A to version V6X. The modified algorithm is designed to process dual-frequency radar data which are now available over the full swath. Comparisons between V6A and V6X show that the dual-wavelength version of the SRT (DSRT) eliminates some of the overestimates of path attenuation in the outer swath that occurred in the earlier version of the algorithm when dual-frequency data was unavailable in the outer swath. However, the DSRT is not reliable in cases of light rain rates where only the Ku-band channel detects rain, nor is it reliable in high rain rate cases where the Ka-band surface signal is lost through attenuation. A modified hybrid algorithm is planned for version 7 that can combine the best features of single- and dual-frequency path attenuation methods.

Meneghini, Robert↗

The Evolution of Lidar Networks: A US Perspective

Atmospheric aerosols and clouds play an important role in climate by directly scattering and absorbing sunlight. Aerosol-cloud interactions modify the particle properties causing indirect effects, alter aerosol deposition and rainfall, and contribute substantially to the uncertainties in predicting climate effects. Aerosols also affect air quality and both constituents modulate boundary layer dynamics to a certain extent, in turn impacting aerosol transport and aerosol-cloud interactions. The spatiotemporal distribution of aerosol and cloud layers is thus important, and lidar remains the primary instrument for determining the vertical distribution of aerosols and thin clouds. Lidar still provides important information for opaque cloud layers by determining base heights. Combined lidar and radar data provide a comprehensive coverage of aerosol and cloud vertical distributions, and thus locations where and when they interact. Lidar data provide a means of constraining column aerosol loading observations (e.g. AOD) to vertical extents. In addition, lidar has proven effective at determining a proxy for boundary layer height by examining aerosol gradients and/or cloud base heights in lidar profiles. Polarized lidars provide additional information on particle shape, allowing estimates of cloud phase and separation of dust or smoke from sulfate and sea salt aerosols. Given the importance of lidar observations and a critical maturation in technology and retrieval techniques, several organizations began to build operational lidar networks around 2000. The European Aerosol Research Lidar Network (EARLINET) was started as a research focused network of advanced lidars across Europe. The Asian Dust Lidar Network (ADNET) was also developed as a regional network providing lidar profiles of dust and pollution across Eastern Asia. In the US, the NASA Micro Pulse Lidar Network (MPLNET) was created to provide global lidar profiling at key sites in the NASA Aerosol Robotic Network (AERONET). The Network for the Detection of Atmospheric Composition Change (NDACC) pre-dates these networks and many sites have lidar, but it is not strictly a lidar network and at the time focused less on the lower troposphere. Finally, there were already existing ceilometer networks operated by various meteorological agencies, but in particular here in the US the profile data has not been available. The ceilometer networks were used to provide only clouds base heights and estimates of PBL height. Thus, the distinguishing feature between lidar and ceilometer networks was historically the ability to actually provide profile information (in addition to differences in wavelength, and advanced retrievals such as the raman technique). As time progressed, each lidar network matured and developed more operational capabilities and data sets, coupled with viable data centers providing DAAC services and access to near-real-time (NRT) data. In 2008 under WMO guidance, the Global Atmospheric Watch (GAW) Aerosol Lidar Observation Network (GALION) was formed as a global network made up of the existing lidar networks. The goal was to share information, best practices, and develop frameworks and techniques for quality data. GALION grew to include several other regional lidar networks and this has led to a vast increase in quality lidar sites worldwide.

Welton, Ellsworth J.↗

Gusev Meridiani will look different : radar scattering properties of the Mars Exploration Rover landing sites

Analysis of all existing radar data for the two Mars Exploration Rover (MER) landing sites at Meridiani Planum and Gusev Crater suggest that their meter-scale morphological appearance will be noticeably different than previous Mars landing sites; their "human-scale", decimeter- to meter-scal roughness is not the same as for previous Mars landing sites. We make this prediction based on the comparison of the MER landing sites.

Harmon, J. K.↗

Enhanced Firn Densification in High‐Accumulation Shear Margins of the NE Greenland Ice Stream

Firn thickness across the NE Greenland Ice Stream is a function of accumulated strain, with thinner firn in the high‐strain margins of the ice stream. We present a novel technique for extracting firn density from previously collected seismic reflection profiles and apply this technique across both shear margins of NE Greenland Ice Stream. Firn is up to 30 m thinner in the vicinity of the ice stream shear margins. Snow accumulation rates across the ice stream were calculated from airborne ice‐penetrating radar data, calibrated with ground‐based firn density measurements from a shallow core. We find that accumulation is ~20% higher in the shear margins compared to the surroundings. The higher density firn adjacent to shear margins is due to high along‐flow stresses that accelerate firn densification and develops despite the higher accumulation rate favoring lower density. These firn density variations influence subglacial hydropotential by changing the ice surface slope and overburden pressure and may influence subglacial water flow. These results demonstrate the importance of high‐resolution firn surveys in studies of shear‐margin dynamics.

ice stream↗

Evolution of Drop Size Distributions during Hurricane Harvey and Their Effects on Rain Intensity

Hurricane Harvey hit the Texas Gulf Coast as a major hurricane on August 25, 2017, before exiting the state as a tropical storm on August 29, 2017. Left in its wake was historic flooding over southeast Texas with some locations measuring more than 60 inches of rain. The Houston NEXRAD radar (KHGX) maintained operations for the entirety of the event and is utilized in this study to better understand the evolution of the drop size distribution (DSD) in the lower (liquid) portions of the storm and how changes in the DSD were tied to observed and measured changes in rain intensities. From the KHGX dual-polarimetric radar data several DSD parameters were retrieved, including three different rain rate retrievals, as well as the mass-weighted mean-drop diameter Dm, and the normalized intercept parameter NW of the gamma distribution. Two of the rain retrievals are popular hybrid approaches, where reflectivity, differential and specific differential phase are used. The other is an attenuation-based retrieval. In a previous study, it was found that both hybrid retrievals significantly underestimated the rainfall during the heaviest rain periods, while the attenuation-based retrieval, with proper adjustment, agreed quite well with a large network of gauges from the Harris County Flood Warning System. Using Dm and NW as proxies for drop size and concentration, respectively, we will show that the heaviest rain intensities were associated in areas of the storm where there was a large concentration of large drops present. It is envisaged that results of this study can be used to develop a near-real-time tuning of the attenuation-based retrieval, thus providing timely, and possibly life-saving warnings during inundating rainfall.

David B. Wolff↗

Pre-Tropical Cyclone Squall Lines and the Connection to the Diurnal Cycle during Hurricane Laura (2020)

Previous studies on the tropical cyclone (TC) diurnal cycle have shown in observations and modeling the presence of outward propagating squall lines. These squall lines were observed in several TCs during the 2020 Atlantic hurricane season. Of these squall lines, one observed in Hurricane Laura made landfall over 14 hours prior to the hurricane’s eye. This squall was responsible for numerous tornado warnings, which disrupted preparations and evacuations ahead of the storm’s landfall. This study seeks to characterize these squall lines and their environmental and thermodynamic characteristics, determine whether they behave more like midlatitude squall lines or tropical cyclone rain bands, and assess the performance of the convection-allowing High Resolution Rapid Refresh model in forecasting them over the ocean and over land. By using a combination of operational radar data, a network of surface weather observations from land and sea, satellite data, and HRRR model output, this case will undergo an extensive evaluation based on criteria from past literature in order to better understand these features as a whole and in relation to the diurnal cycle.

Vivian L Brasfield↗

Pre-Tropical Cyclone Squall Lines and the Connection to the Diurnal Cycle in Hurricane Laura (2020)

Previous studies on the tropical cyclone (TC) diurnal cycle have shown in observations and modeling the presence of outward propagating squall lines. These squall lines were observed in several TCs during the 2020 Atlantic hurricane season. Of these squall lines, one observed in Hurricane Laura made landfall over 13 hours prior to the hurricane’s eye. This squall was responsible for numerous tornado warnings, which disrupted preparations and evacuations ahead of the storm’s landfall. This study seeks to characterize these squall lines and their environmental and thermodynamic characteristics, determine whether they behave more like midlatitude squall lines or tropical cyclone rain bands, and assess the performance of the convection-allowing High Resolution Rapid Refresh model in forecasting them over the ocean and over land. By using a combination of operational radar data, a network of surface weather observations from land and sea, satellite data, and HRRR model output, this case will undergo an extensive evaluation based on criteria from past literature in order to better understand these features as a whole and in relation to the diurnal cycle.

Vivian L Brasfield↗

2020 Innovation Fair Project: Is Midlatitude Ground Ice on Mars Habitable for Life?

The objective of this project was to perform a modeling study to evaluate whether midlatitude ground ice on Mars that could support life in geologically recent times. Recent studies from Mars orbital imaging, ground penetrating radar data, and infrared thermal data have revealed that large areas of Mars at latitudes higher than 40o N host near surface ground ice. Past climate cycles driven by orbital oscillations are expected to result in the distribution of ground ice changing over geologically recent history. The insolation at any location on Mars varies over time due to quasi-periodic changes in its orbital parameters (obliquity, eccentricity, perihelion longitude). The last 2 MY Mars obliquity varied between 15o and 35o but 5 MY ago varied between 24o and 48o with the average obliquity being 36o. The current low obliquity Mars atmosphere is dryer than average conditions. Recent work (Mellon and Sizemore Icarus (2022) 371;114667) has shown that repeatedly over the last 2 MY ground ice was present even at low Northern latitudes. The ice table depth is controlled by diffusive equilibrium with water vapor in the atmosphere, which also varies with orbital parameters. Determining the surface temperature and water vapor abundance requires a sophisticated climate model that was developed at NASA Ames, and results of high obliquity climate simulations will be used in the study. Work is underway to evaluate the subsurface thermal conditions in ice-rich areas of Mars during high obliquity periods to determine whether, where, and when the subsurface ice becomes warm enough to support metabolic processes or growth of terrestrial organisms.

Carol R Stoker↗

Observational Analysis of Atlantic Basin Tropical Cyclone Squall Lines and Relationship to the Diurnal Cycle

Previous studies on the tropical cyclone (TC) diurnal cycle have shown in observations and modeling the presence of outward propagating squall lines. These squall lines were observed in several TCs during recent Atlantic hurricane seasons. Of these squall lines, one observed in Hurricane Laura made landfall over 14 hours prior to the hurricane’s eye. This squall was responsible for 40 tornado warnings, which disrupted preparations and evacuations ahead of the storm’s landfall. This study seeks to characterize these squall lines and their environmental and thermodynamic characteristics, determine whether they behave more like midlatitude squall lines or tropical cyclone rain bands, and assess the performance of the convection-allowing High Resolution Rapid Refresh model in forecasting them over the ocean and over land. By using a combination of operational radar data, a network of surface weather observations from land and sea, satellite data, and HRRR model output, this case will undergo an extensive evaluation based on criteria from past literature in order to better understand these features as a whole and in relation to the diurnal cycle.

Vivian Brasfield↗

Predicting Antarctic Net Snow Accumulation at the Kilometer Scale and Its Impact on Observed Height Changes

Sub-grid-scale processes occurring at or near the surface of an ice sheet have a potentially large impact on local and integrated net accumulation of snow via redistribution and sublimation. Given observational complexity, they are either ignored or parameterized over large-length scales. Here, we train random forest (RF) models to predict variability in net accumulation over the Antarctic Ice Sheet using atmospheric variables and topographic characteristics as predictors at 1 km resolution. Observations of net snow accumulation from both in situ and airborne radar data provide the input observable targets needed to train the RF models. We find that local net accumulation deviates by as much as 172% of the atmospheric model mean. The correlation in space between the predicted net accumulation variability and satellite-derived surface-height change indicates that surface processes operate differently through time, driven largely by the seasonal anomalies in snow accumulation.

Antarctic↗

Observations of Ion Upflow and 630.0 Nm Emission During Pulsating Aurora

In this study, we report observations made by filtered (557.7 and 630.0 nm) All-Sky Imagers located at Poker Flat, Alaska alongside Poker Flat Incoherent Scatter Radar data for an event observed on 5 February 2017. Together, the data indicate ion upflow in the vicinity of pulsating aurora. Additionally, the data show a strong 630.0 nm (red-line) auroral emission. Observations of pulsating aurora are typically reported at 557.7 and 427.8 nm, as these wavelengths are more sensitive to high-energy (∼ tens of keV) electron precipitation. In contrast, 630.0 nm emission is generated preferentially by low-energy soft electron precipitation (∼ hundreds of eV), and is less commonly observed. The All-Sky Imager data discussed here are unusual in that they suggest regions of enhanced soft electron precipitation in conjunction with enhanced ambipolar electric fields, which are a known factor contributing to ion outflow.

ion upflow↗

An Overview of NASA’s Newest Engineering Model, ORDEM 4.0

Since the mid-1990s, one of the most important products produced by the NASA Orbital Debris Program Office (ODPO) has been the Orbital Debris Engineering Model (ORDEM). This series of models distills down our knowledge of the orbital debris environment to compute debris fluxes on satellites in a given orbit. This information can be used by spacecraft and upper stage designers and operators to design missions for better protection against the debris environment. The current version of the model is ORDEM 3.2, but the ODPO is working on the next generation of ORDEM, to be designated ORDEM 4.0. ORDEM 4.0 will include many known features from previous models, such as the ability to input a spacecraft orbit and time and to compute the flux as a function of debris size, impact speed, impact direction, and debris material densities, as well as uncertainty information on the flux. ORDEM 4.0 will update debris populations using the most recent measurements, including radar observations by the Haystack Ultrawideband Satellite Imaging Radar (HUSIR), NASA’s Goldstone radar, data from the new Space Surveillance Network Space Fence, and observations of Geosynchronous Earth Orbits (GEO) using the Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT). The latest in situ impact data from returned hardware surfaces will be used. In addition, ORDEM 4.0 will introduce a parameterized debris shape model based on laboratory hypervelocity impact tests, such as DebriSat. This will allow analysts to implement shape characteristics in their damage equations and more accurately predict impact damage risk by debris of different shapes and orientations. This paper provides an overview of some of the new features forthcoming in ORDEM 4.0 and a status report on its development.

Mark Matney↗

Understanding the Vertical Slope of Mesoscale Snow Band Reflectivity Signatures

Mesoscale snow bands are frequently responsible for dumping large amounts of snow over a relatively small region and pose a considerable forecasting challenge. The ongoing NASA Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign observed several instances of mesoscale snow bands during January and February of 2020 and 2022. These snow bands were sampled by a combination of airborne (NASA ER-2 and P-3) and ground-based remote sensing and in-situ instruments. Along-band cross sections of these snow bands reveal that many of them are vertically sloped. Our preliminary analysis into one of these snow bands suggests that the vertical slope is not maintained by isentropic lift and does not appear to be tied to horizontal deformation. A combined analysis of the reflectivity and wind retrievals from the ER-2 radars raises the possibility that these features could be produced by vertical wind shear layers deforming fall streaks into bands that extend hundreds of kilometers. The present study will focus on extending our preliminary analysis to additional cases and understanding the mechanisms that support these features using a combination of radar data, in-situ aircraft measurements, and numerical modeling.

Charles Helms↗

An Overview of NASA’s Newest Engineering Model, ORDEM 4.0

Since the mid-1990s, one of the most important products produced by the NASA Orbital Debris Program Office (ODPO) has been the Orbital Debris Engineering Model (ORDEM). This series of models distills down our knowledge of the orbital debris environment to compute debris fluxes on satellites in a given orbit. This information can be used by spacecraft and upper stage designers and operators to design missions for better protection against the debris environment. The current version of the model is ORDEM 3.2, but the ODPO is working on the next generation of ORDEM, to be designated ORDEM 4.0. ORDEM 4.0 will include many known features from previous models, such as the ability to input a spacecraft orbit and time and to compute the flux as a function of debris size, impact speed, impact direction, and debris material densities, as well as uncertainty information on the flux. ORDEM 4.0 will update debris populations using the most recent measurements, including radar observations by the Haystack Ultrawideband Satellite Imaging Radar (HUSIR), NASA’s Goldstone radar, data from the new Space Surveillance Network Space Fence, and observations of Geosynchronous Earth Orbits (GEO) using the Eugene Stansbery-Meter Class Autonomous Telescope (ES-MCAT). The latest in situ impact data from returned hardware surfaces will be used. In addition, ORDEM 4.0 will introduce a parameterized debris shape model based on laboratory hypervelocity impact tests, such as DebriSat. This will allow analysts to implement shape characteristics in their damage equations and more accurately predict impact damage risk by debris of different shapes and orientations. This paper provides an overview of some of the new features forthcoming in ORDEM 4.0 and a status report on its development.

Mark Matney↗