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At least 325 records · Page 18

LUVOIR-ECLIPS Closed-Loop Adaptive Optics Performance and Contrast Predictions

One of the primary science goals of the Large UV/Optical/Infrared Surveyor (LUVOIR) mission concept is to detect and characterize Earth-like exoplanets orbiting nearby stars with direct imaging. The success of its coronagraph instrument ECLIPS (Extreme Coronagraph for Living Planetary Systems) depends on the ability to stabilize the wavefront from a large segmented mirror such that optical path differences are limited to tens of picometers RMS during an exposure time of a few hours. In order to relax the constraints on the mechanical stability, ECLIPS will be equipped with a wavefront sensing and control (WS\&C) architecture to correct wavefront errors up to temporal frequencies $\gtrsim$1 Hz. These errors may be dominated by spacecraft structural dynamics exciting vibrations at the segmented primary mirror. In this work, we present detailed simulations of the WS\&C system within the ECLIPS instrument and the resulting contrast performance. This study assumes wavefront aberrations based on a finite element model of a simulated telescope with spacecraft structural dynamics. Wavefront residuals are then computed according to a model of the adaptive optics system that includes numerical propagation to simulate a realistic wavefront sensor and an analytical model of the temporal performance. An end-to-end numerical propagation model of ECLIPS is then used to estimate the residual starlight intensity distribution at the science detector. We show that the contrast performance depends strongly on the target star magnitude and the spatio-temporal distribution of wavefront errors from the telescope. In cases with significant vibration, we advocate for the use of laser metrology to mitigate high temporal frequency wavefront errors and increase the mission yield.

Sirbu, Dan↗

Recent Changes in Cyanobacteria Algal Bloom Magnitude in Large Lakes Across the Contiguous United States

Cyanobacterial blooms in inland lakes produce large quantities of biomass that impact drinking water systems, recreation, and tourism and may produce toxins that can adversely affect public health. This study analyzed nine years of satellite-derived bloom records and compared how the bloom magnitude has changed from 2008-2011 to 2016-2020 in 1881 of the largest lakes across the contiguous United States (CONUS). We determined bloom magnitude each year as the spatio-temporal mean cyanobacteria biomass from May to October and in concentrations of chlorophyll-a. We found that bloom magnitude decreased in 465 (25%) lakes in the 2016-2020 23 period. Conversely, there was an increase in bloom magnitude in only 81 lakes (4%). Bloom magnitude either didn’t change, or the observed change was in the uncertainty range in the majority of the lakes (n=1335, 71%). Above-normal wetness and normal or below-normal maximum temperature over the warm season may have caused the decrease in bloom magnitude in the eastern part of the CONUS in recent years. On the other hand, a hotter and dryer warm season in the western CONUS may have created an environment for increased algal biomass. While more lakes saw a decrease in bloom magnitude, the pattern was not monotonic over the CONUS. The variations in temporal changes in bloom magnitude within and across climatic regions depend on the interactions between land use land cover (LULC) and physical factors such as temperature and precipitation. Despite expectations suggested by recent global studies, bloom magnitude has not increased in larger US lakes over this time period.

remote sensing↗

Understanding and Utilizing PBL Height Data from Multiple Observing Systems in the GEOS System

The accuracy of PBL height simulation is a key issue in many applications including forecasting near surface meteorology and air quality, however, it is a very challenging problem due to the lack of not only comprehensive, global Planetary Boundary Layer (PBL) observations but also a strategy and infrastructure to utilize PBL height data from a variety of sensors. Following the designation of PBL as an incubation class observable in the 2017 Decadal Survey, the PBL Incubation Study Team Report [14] made clear that “a future global PBL observing system requires modeling and data assimilation as essential components.” There is an urgent need for global modeling development in order to utilize Program of Record (POR) observations, assess their impacts, and identify gaps to be filled by future PBL missions. Our overall objective is to develop PBL data assimilation capabilities in the NASA Global Earth Observing System (GEOS), focusing on PBL height from multiple observing systems, to support the assessment and use of future PBL observations. The NASA GEOS system is composed of the GEOS global atmospheric general circulation model (AGCM) and the atmospheric data assimilation system (ADAS). The PBL parameterizations include the “Lock” K-profile scheme driven by surface and cloud-top buoyancy fluxes ([4]), and the “Louis” local scheme for stable conditions based on the Richardson number ([5]). Above the mixed layer defined by the Lock surface plume, shallow cumulus convection is represented by the mass flux scheme of [9]. Additional parameterizations are summarized in [1]. The ADAS employs the hybrid 4D Ensemble- Variational (EnVar) configuration ([15]), with the ensemble providing flow-dependent background error covariance information. The resultant analysis increments are fed back to the forecast model through the 4D incremental analysis update (IAU) approach ([11]). In this study, PBL height data are being or have been generated from radiosondes, GNSS RO, satellite (CATS, CALIPSO and ICESat-2) and ground-based (MPLNET) lidars, and wind profiler. Investigations have been conducted to specify quality marks for PBL height retrievals for the data assimilation purpose. These PBL height data have different strengths and weaknesses ([2], [3], [6], [7], [8], [10]), and the satellite PBL height data provide better global coverage and complement in-situ PBL height data. Radiosondes offer high accuracy and in situ measurement of temperature and humidity profiles, but with poor spatio-temporal sampling. The in-situ observing systems like MPLNET and wind profiler provide long history of PBL height records at each station. The GNSS RO based PBL height is retrieved based on the sharp gradients in refractivity profile that represent the fine vertical structure of temperature and moisture changes above the PBL. However, not all RO refractivity profiles reach the surface depending on location and regime, and RO refractivity retrievals can be negatively biased below 2km. The PBL height data from satellite lidars provide high resolution along track PBL height retrievals, but over land they are affected by previous day convective PBL aerosol and strongly associated with mixing layer and retrievals cannot be made below thick, attenuating clouds. A successful assimilation of PBL height data requires a thorough understanding of the observing method and the retrieval algorithm for each observing system in order to use the PBL height data from multiple observing systems properly. Due to the sensitivity of PBL height data to the observing method and choice of algorithm, it is important to use a model definition appropriate for each observation type to compute differences between PBL height data and model PBL height (OmFs). The GEOS model currently includes two PBL height definitions suitable for direct comparison with observed PBL height, and additional definitions are being added in this study. Evaluation of different model PBL height definitions is underway. Meanwhile, efforts have been made in the GEOS data assimilation system to develop PBL height data assimilation capability. PBL height data can be assimilated using two different approaches. The traditional approach is to construct an observation operator and its tangent linear and adjoint, which link control variables to PBL height data from each observing system. This observation operator can be very complicated, e.g., the lidar-based PBL height observation operator includes the backscatter lidar forward observation operator, the algorithm to derive PBL height from attenuated total backscatter, interpolation, and calculations handling the mismatch between observed and model scales. The other approach is to augment PBL height to the control variable vector, and it is adopted in this study. The latter approach was also used in previous studies, e.g., the assimilation of PBL height data from radiosonde and aircraft in the Real Time Mesoscale Analysis (RTMA) system for a dispersion modelling study ([13]); the PBL height assimilation study using lidar PBL height data at Greensburg, Kansas for a field campaign ([12]). The PBL height assimilation from multiple observing systems in this study allows us to take advantage of the diverse PBL height data that provide much better global coverage collectively under different meteorological conditions and with different temporal and spatial scales. As all the PBL heights are tightly coupled with the PBL thermodynamic variables, the strong correlations, which are provided by the 4D ensemble forecast, enable PBL height data from various sources to interact and combine coherently and provide additional information for PBL temperature and moisture fields. The results of comparisons among PBL height data from different sources and the evaluation of the model PBL height definitions with the PBL height data will be presented, and the PBL height data synergy strategies and preliminary results will also be discussed at the conference.

Y. Zhu↗

Flood Monitoring Using Enhanced Resolution Passive Microwave Data: A Test Case Over Bangladesh

Monitoring floods is a major issue in water resources management and risk mitigation, especially in the Global South. Optical and radar observations, even providing a fine spatial resolution, are still limited by cloud cover interaction or insufficient temporal resolution. On the other hand, passive microwave (PMW) sensors collect information on a daily frequency with minor cloud cover interaction, but they have been historically limited in terms of spatial resolution. Here, we evaluate the capability of an enhanced spatial resolution PMW dataset (3.125 km) in monitoring spatio-temporal evolution of flood events, focusing on a major flood event that occurred in October 2005 in Bangladesh. We apply an algorithm aimed to remove the seasonal variability of surface temperature from the PMW timeseries, exploiting the difference in emissivity between dry and water-covered pixels. We assess the capability of the algorithm in capturing flood evolution and extension through the comparison with quantities obtained from optical data collected by the Moderate Resolution Imaging Spectroradiometer (MODIS) and water level measurements. We also compare the enhanced product with the historical coarser resolution dataset by means of a variogram-based analysis to evaluate the improvements in terms of spatial representation. Finally, we evaluate the possibility to extract the water fraction within a single pixel by using an Advanced Microwave Scanning Radiometer—Earth Observing System (AMSR-E) emissivity dataset and compare the estimates with MODIS-derived water fractions. Our results show that the enhanced PMW product outperforms the coarser one when compared to flood mapped from optical data based on information content, indicating that it is possible to integrate such a product into the mapping of floods at a global scale on a daily basis.

flood detection↗

Advancing Solar and Heliospheric Science Through the Ongoing Development and Support of Atomic and Laboratory Plasma Physics

This paper outlines the necessity for the availability, accessibility, and expansion of atomic physics data and analysis tools for the meaningful interpretation of spectroscopic and polarimetric observations. As we move towards observing the Sun at higher spatio-temporal resolutions, and near-continuously at a range of wavelengths, it becomes critical to develop the appropriate atomic data and physics tools to facilitate scientific progress. We recommend the continued improvement and expansion of current databases to support the development of optically-thick/radiative transfer models, evaluate non-thermal and non-equilibrium ionization effects, and quantify uncertainties in atomic and molecular values. A critical longterm goal will require extending and strengthening collaborations across the atomic, solar/heliospheric, and laboratory plasma physics communities through the participation and training of early career scientists. We also recommend establishing funding for a centralized atomic physics resource made up of a comprehensive and user-oriented atomic database and modeling framework.

Y J Rivera↗

FluxSat: Long-term Earth Science Data Record (ESDR) for Terrestrial Gross Primary Production (GPP) based on satellite data calibrated with eddy covariance data

Gross primary production (GPP), the amount of carbon dioxide (CO 2 ) assimilated by plants through photosynthesis, is one of the most variable and uncertain components of the global carbon cycle. Global GPP has been estimated with a number of process-based models, data-driven, and hybrid approaches. Dynamic global vegetation models (DGVMs), driven by observed environmental changes, are used for global carbon budget assessments and long-term (climate) prediction. Benchmarking these and other models globally with data-driven GPP estimates is critical for understanding the land sink and ensuring accurate forecasts of the carbon cycle. In addition, global data-driven GPP estimates are crucial for studies of interannual variability, including trends that are linked to mechanisms with large uncertainties, such as the indirect CO 2 fertilization effect related to greening. In response to a community need for a GPP data set that well captures spatio-temporal variability, we developed FluxSat, a data-driven approach that optimizes the use of satellite reflectance data from the NASA MODerate-resolution Imaging Spectroradiometer (MODIS) on the Terra and Aqua satellites, calibrated using ground-based eddy covariance (EC) data. We are enhancing (spatially, higher resolution) and extending FluxSat (in time, with additional sensors) to create a high quality long term GPP Earth System Data Record (ESDR) for use in model benchmarking, carbon cycle modeling, and studies of trends and interannual variability. Our team’s objectives are to: 1. Update and document the current MODIS FluxSat GPP (daily, 0.05o and 0.5o resolutions) products with latest available MODIS and EC data sets; 2. Extend FluxSat GPP record forward in time with the Visible Infrared Imaging Radiometer Suite (VIIRS) on operational weather satellites going forward; 3. Extend FluxSat GPP record backward in time using the Advanced Very High Resolution Radiometer (AVHRR) on weather satellites dating back to 1981; 4. Provide higher spatial resolution MODIS and VIIRS GPP (0.0083o). 5. Thoroughly evaluate all FluxSat products with independent data; and 6. Create a homogenized long-term GPP record spanning 40+ years. We will discuss plans for this long-term data set that is supported through the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program.

gross Primary Production↗

Wind Profiling With the Airborne Doppler Aerosol Wind Lidar During the 2022 Convective Processes Experiment

The 2017 Decadal Survey for Earth Science and Applications from Space (ESAS 2017) identifies a critical need for improving our understanding of Planetary Boundary Layer (PBL) processes and air-surface fluxes as well as why clouds, convection, and heavy precipitation occur when and where they do. Lidars are uniquely capable of collecting high precision and high spatio-temporal observations that have been used for atmospheric process studies from the ground, aircraft, and space. The wind lidar team at the NASA Langley Research Center (LaRC) started the development of Doppler wind lidar more than a decade ago to demonstrate technologies required for an Earth-orbiting system to globally measure wind profiles. Since then, an airborne Doppler Aerosol WiNd (DAWN) lidar system has been developed and participated in a series of field campaigns. The Doppler Aerosol WiNd (DAWN) lidar uses atmospheric aerosol motion to derive vertical profiles of horizontal wind speed and direction beneath the aircraft. In September 2022, DAWN, along with a suite of other instruments, was flown on a NASA DC-8 as part of The Convective Processes EXperiment – Cabo Verde (CPEX-CV) field campaign. A main objective of CPEX was to obtain a comprehensive set of temperature, humidity and, particularly, wind observations over tropical waters in undisturbed conditions, Saharan dust outbreaks, and in the vicinity of scattered through organized deep convection in all phases of the convective life cycle. DAWN collected data for approximately 90 hours across 13 CPEX-CV science flights. Airborne Vertical Atmospheric Profiling System (AVAPS) dropsondes were dropped throughout the flight for profiling the atmosphere and validating the DAWN instrument. DAWN had co-located data with 347 AVAPS NRD41 dropsondes, providing 32,117 vertical levels for a comprehensive validation of DAWN wind retrievals. DAWN showed very good agreement with dropsondes of ~0.2 m/s bias and ~1.8 m/s RMS. Given this agreement, DAWN is considered to be a worthy reference dataset, and its retrievals have been compared to winds derived from GOES Atmospheric Motion Vectors (AMVs), Advanced Scatterometer winds (ASCAT), and model data from GFS, GEOS, and MERRA-2 to better understand the quality of our current models and satellite wind observations. The proposed presentation will provide a brief description of the DAWN instrument, discuss the synergistic observations collected across a wide range of atmospheric conditions sampled during the CPEX-CV flights, and a summary of comparisons between DAWN, GOES AMV, ASCAT, and model analyses/predictions, with an emphasis on the PBL.

DAWN↗

Study of Coronal Heating in Solar Active Regions Using Wide-Field Imaging Spectroscopy: Hinode EIS Slot Observations

Understanding the frequency of heating events that keep the coronal plasma at several million Kelvin above the photospheric temperature of~ 6000K, is one of the most important problems in solar astrophysics. Spectroscopic observations of the Sun in the extreme ultraviolet (EUV) indicate that the coronal plasma reaches temperatures from 1 to 5 MK in active regions. It is also established that temperature in active regions can vary strongly with time and, moreover, contain sub-regions that evolve and develop separately. Tracking the spatio-temporal evolution of temperature requires continuous observation of the entire active region via imaging and spectroscopy. Traditional slit imaging spectroscopy probes plasma heating in solar active regions through observations of diagnostic emission lines and the resulting data are spectrally pure. Here, imaging is performed through rastering process, which severely limits co-temporal observations and often can be slow to miss events that evolve at other portions of the active region. In contrast, wide-field imaging spectroscopy offer simultaneous coverage of a large field of view as well as obtain spectral information in the same direction. This data suffers from spatial-spectral confusion, and are called spectroheliograms. Using the state-of-the-art inversion techniques that are developed recently, now spectroheliogram data can be unfolded to yield spectrally pure maps of large fields over long duration of observations. We use wide slit data, usually referred as ‘slot’, from the EUV Imaging Spectrometer (EIS) onboard Hinode satellite, focusing on active region observations. Here, we present our study of coronal heating in an active region using a long duration Hinode EIS slot observation.

Active region heating↗

Coronal FIP Bias: From Full-Sun X-Ray Spectroscopy to Imaging Spectroscopy

The First Ionization Potential (FIP) bias, whereby the abundances of the low FIP elements in different coronal structures vary from their photospheric values and may also vary with time, has been known for a long time, but still poorly understood. X-ray spectroscopic observations of the Sun are very crucial to study the spatio-temporal variation, and to understand the physical mechanisms giving rise to the FIP bias. Recent X-ray spectroscopic observations of the Sun in disk-integrated mode by Solar X-ray Monitor (XSM) onboard Chandrayaan-2 enhanced our knowledge of the temporal variation of FIP bias during solar flares and in hot AR cores. Here we will summarize the results from these recent studies. Also we will discuss the importance of spatially resolved spectroscopic observation to understand the FIP bias. In this context we will explore the role of upcoming X-ray imaging spectrographs.

solar corona↗

Time-Resolved OH-PLIF Assessment of Deflagrations Levels in a CH4-O2 Rotating Detonation Rocket Combustor

The parasitic loss incurred by deflagrative pre-burning is considered to be one of the key challenges to the effective implementation of rotating detonation engine (RDE) systems. Thus far, there have been relatively limited high fidelity, spatio-temporally resolved measurements of the pre-burning process as a function of the reactant conditions and composition within an RDE. In this work, simultaneous high-repetition-rate broadband OH* chemiluminescence and OH planar laser-induced fluorescence (PLIF) imaging are employed to investigate deflagrative burning dynamics in a fully optically accessible CH4-O2 RDE as compared to a H2-air systems under the same conditions. A custom-built optical parametric oscillator (OPO) is coupled with a high-repetition-rate burst-mode laser to generate the 284 nm source for the excitation of the Q1(9) transition of the OH radical. Significant deflagrative burning is observed throughout the chamber as a consequence of the oxygen-rich environment. Trailing wave systems that consume unburned reactants in the region immediately following the primary detonation wave are observed. The formation of a product gas recirculation zone that entrains and combusts incoming reactants is observed, and quantitative analysis is performed to gain valuable insight into deflagration characteristics. At an oxidizer mass flux of Gox ≈ 350kg/m2/s, it is found that the levels of pre-wave burning in CH4-O2 are a factor of ∼2-3 times higher than in H2-air in the region directly ahead of the detonation wave at a global equivalence ratio Φ ≈ 1.0. This study highlights the key roles of ignition delay and turbulent mixing of the combustion product and reactant fields on the levels of pre-burning and establishes a methodology for further investigation, such as for the effects of various RDE inlet configurations.

Propulsion↗

Oxygenation of the Baltoscandian shelf linked to Ordovician biodiversification

Marine biodiversity increased markedly during the Ordovician Period (~487–443 million years ago). Some intervals within the Ordovician were associated with unusually rapid and prominent rises in taxonomic richness, the reasons for which remain debated. Links between increased oxygenation and biodiversifcation have been proposed, although supporting marine oxygen proxy data are limited. Here we present an expansive multi-site iodine-to-calcium (I/Ca) record from Lower–Middle Ordovician marine carbonates in Baltoscandia that provides a detailed account of the spatio-temporal development of oxygen conditions across this palaeoshelf. The data document progressive oxygenation of regional seafoor environments, with well-oxygenated waters sourced from the palaeoequatorward Iapetus Ocean and peak I/Ca values (that is, dissolved oxygen concentrations) coinciding with the most pronounced biodiversity increases and ecosystem reorganizations during this time interval. This occurred while the climate cooled, global sea level dropped and carbonate deposits became regionally dominant. The results suggest that ventilation of shelves played a critical role in regulating early Palaeozoic marine biodiversity via development of ecospace and aerobic–metabolic conditions.

Anders Lindskog↗

On the Spatial and Temporal Evolution of EMIC Wave-Driven Relativistic Electron Precipitation: Magnetically Conjugate Observations From the Van Allen Probes and CALET

Electromagnetic ion cyclotron (EMIC) waves have been shown to be able to drive strong electron precipitation, particularly at MeV energies. However, the spatio-temporal evolution of both the waves and the resulting precipitation is still not well understood. Here we investigate the evolution of relativistic electron precipitation driven by EMIC waves through combined observations from the Van Allen Probes and the CALorimetric Electron Telescope experiment onboard the International Space Station. Two case studies are examined where EMIC waves near the magnetic equator and precipitation at low altitude were detected in close magnetic conjunction, both of which were confined to narrow radial regions but persisted multiple hours. These observations, combined with quasilinear calculations, confirm that long-lived EMIC waves can drive hours-long MeV electron precipitation loss. However, the magnitude of the precipitation varied significantly during one of the events, as resonance conditions, particularly plasma density, evolved.

L. W. Blum↗

Impacts of Aerosol and Cloud Variability on Satellite-Derived All-skies Direct Aerosol Radiative Effects (DARE) over the North and Southeast Atlantic

The Top-of-Atmosphere (TOA) Shortwave (SW) Direct Aerosol Radiative Effect (DARE) in all-sky conditions (i.e., aerosols in clear skies and aerosols above and below all types of clouds) is the global change in upwelling radiative flux due to aerosols. It is one of the strongest indicators of global climate change due to aerosols. SW DARE at TOA depends on the Earth’s surface albedo, cloud fraction, cloud optical properties, and aerosol optical properties, which are all challenging to accurately characterize from space. The overarching goals of our project are to provide state-of-the-art observational all-sky TOA SW DARE, along with guidance on which aerosol and/or cloud properties are the most important to measure, and at which spatio-temporal scales, for accurate DARE observations. We compute all-sky DARE based on state-of-the-art cloud and aerosol retrieval algorithms from CALIOP (Cloud–Aerosol Lidar with Orthogonal Polarization) and MODIS (Moderate Resolution Imaging spectroradiometer) satellite sensors, as well as aerosol intensive properties from MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications, version 2) simulations over three specific regions of the Atlantic Ocean from 2012 to 2016. In this symposium, we present a characterization of the cloud and aerosol optical and physical properties and the observational TOA SW DARE along three individual satellite tracks in the Southeast Atlantic region -- on September 18 and 20, 2016 and August 13, 2017. We then quantify the impact of assuming homogeneous cloud or aerosol fields in space-based TOA SW DARE calculations. And, finally, the resulting space-based all-skies aerosol vertical distribution and DARE calculations are evaluated using remote sensing observations from coincident suborbital flights from the NASA ORACLES (the ObseRvations of Aerosols above CLouds and their intEractionS, ORACLES field campaign) field campaign. The NASA Atmospheric Observing System (AOS) mission addresses the NASA Aerosol, Cloud, Convection and Precipitation (ACCP) designated observables and proposes, as one of its aerosol objectives, to reduce uncertainties in estimates of global mean all-sky SW DARE at TOA. Well characterizing clouds, aerosol vertical distributions, aerosol types and associated all-skies DARE over the Atlantic Ocean will inform the AOS community on where, when, how, and how often the satellite retrievals should be performed to estimate DARE and reduce all-skies DARE uncertainties most accurately. These comprehensive characterizations will also identify the key regions and times when the AOS (or other ACCP-related) suborbital missions should be conducted to evaluate and improve the AOS space-based observations and retrievals.

aerosol↗

Analysis and Prediction of VFR Vs IFR Traffic Behavior to Support Uncrewed Aircraft Flight Operations at Regional Airports

Uncrewed Aircraft flight operations at a regional airport will be affected by the uncertainty in the Visual Flight Rules traffic around. This paper analyzes Visual Flight Rules traffic behavior, compares it with Instrument Flight Rules traffic and develops traffic prediction methods to support uncrewed aircraft flight operations. The spatio-temporal distribution of traffic operating under Visual Flight Rules and Instrument Flight Rules was analyzed from one month of historical track data around Fort Worth Alliance airport as a representative regional airport. The traffic behavior was visualized as occupancy maps generated at different altitudes. The Instrument Flight Rules traffic was concentrated in fewer regions of the airspace along structured routes where the risk of interacting with one or more flights reached close to fifty percent in some areas. Visual Flight Rules traffic was spread over more regions, mostly segregated from the Instrument Flight Rules regions, and the risk of interaction was lower reaching up to twenty-five percent on average over the month in some regions. The interaction risk was predicted using predictive occupancy maps over multiple time horizons and conditioned on time and partial observation of traffic in the vicinity. The month-to-month predictability of Visual Flight Rules risk was lower than that of the Instrument Flight Rules traffic, consistently over all the conditions analyzed. However, the prediction and its accuracy were demonstrated to be sensitive to the conditions used. The predictive models generated can be used to support both strategic planning and in-flight decision-making by uncrewed aircraft during flight operations while maintaining an acceptable risk of interacting with other traffic.

VFR↗

Analysis and Prediction of VFR Vs IFR Traffic Behavior to Support Uncrewed Aircraft Flight Operations at Regional Airports

Uncrewed Aircraft flight operations at a regional airport will be affected by the uncertainty in the Visual Flight Rules traffic around. This paper analyzes Visual Flight Rules traffic behavior, compares it with Instrument Flight Rules traffic and develops traffic prediction methods to support uncrewed aircraft flight operations. The spatio-temporal distribution of traffic operating under Visual Flight Rules and Instrument Flight Rules was analyzed from one month of historical track data around Fort Worth Alliance airport as a representative regional airport. The traffic behavior was visualized as occupancy maps generated at different altitudes. The Instrument Flight Rules traffic was concentrated in fewer regions of the airspace along structured routes where the risk of interacting with one or more flights reached close to fifty percent in some areas. Visual Flight Rules traffic was spread over more regions, mostly segregated from the Instrument Flight Rules regions, and the risk of interaction was lower reaching up to twenty-five percent on average over the month in some regions. The interaction risk was predicted using predictive occupancy maps over multiple time horizons and conditioned on time and partial observation of traffic in the vicinity. The month-to-month predictability of Visual Flight Rules risk was lower than that of the Instrument Flight Rules traffic, consistently over all the conditions analyzed. However, the prediction and its accuracy were demonstrated to be sensitive to the conditions used. The predictive models generated can be used to support both strategic planning and in-flight decision-making by uncrewed aircraft during flight operations while maintaining an acceptable risk of interacting with other traffic.

VFR↗

Dependence of Lightning Cloud-Top Optical Emissions on Channel Characteristics Using Boltzmann Radiative Transfer Modeling

With an estimated global flash rate of 46 lightning per second, a significant amount of lightning nitrogen oxides (LNOx) are produced within the climate system. In turn, LNOx affect the concentrations of ozone (O 3 , an important greenhouse gas) as well as the very reactive hydroxyl radicals (OH, that affect all greenhouse gases). Thus, space-based estimation of LNOx is highly sought [Koshak 2017; Koshak et al. (2015)]. Total lightning channel length, L , is a proxy for the total flash energy (and hence LNOx production). Geostationary lightning mappers provide cloud-top 2D views of the diffuse (i.e., blurry) optical images of lightning, thereby making it difficult to determine L (and other channel features). Transient Boltzmann radiative transfer modeling is applied here to investigate the dependence of the spatio-temporal pattern of cloud-top lightning optical emissions on L and other channel characteristics (e.g., orientation, propagation direction, amplitude, location, ...).

William J Koshak↗

Recent Progress and Development of Self-Aligned Focusing Schlieren

A broad range of developments and applications of self-aligned focusing schlieren (SAFS)systems is presented. The replacement of the Ronchi ruling (RR) with a𝜇LCD was demonstrated with digital SAFS, which provides the ability to modulate the pattern and orientation without physical intervention. Additionally, replacement of the traditional RR with spectral-spatial filters was demonstrated to yield the ability to simultaneously image horizontal and vertical index of refraction gradients using two separate wavelengths. The application of the Scheimpflug principle to SAFS systems enables off-axis imaging and allowed for extended fields-of-view to be captured using a two-camera system. The addition of a plenoptic camera to a baseline SAFS system enables refocusing capabilities, which is demonstrated on two jets offset along the optical axis. Furthermore, application of an event-based camera to SAFS was shown to enable acquisition of sparse, spatio-temporal data. Beyond the listed developments, SAFS was applied to difficult and constraining facilities, such as the National Full-Scale Aerodynamics Complex(NFAC) 80- by 120-ft Wind Tunnel and the Thermal Acoustic Engines (TAE) rig at NASA Ames Research Center and NASA Glenn Research Center, respectively. Behavior of Ronchi rulings, Rochon prisms, and the use of quarter-wave plates versus quarter-wave films are evaluated to provide insight for future experimental design of SAFS-systems.

Self-Aligned Focusing Schlieren↗

PRODEM: An Annual Series of Summer DEMs (2019 through 2022) of the Marginal Areas of the Greenland Ice Sheet

Surface topography across the marginal zone of the Greenland Ice Sheet is constantly evolving in response to changing weather, season, climate, and ice dynamics. However, current digital elevation models (DEMs) for the ice sheet are usually based on data from a multi-year period, thus obscuring these changes over time. Here we present four 500 m resolution summer DEMs (PRODEMs) of the Greenland Ice Sheet marginal zone for 2019 through 2022. The PRODEMs cover the marginal zone from the ice edge to 50 km inland, hence capturing all Greenland outlet glaciers. Each PRODEM is based on data fusion of CryoSat-2 radar altimetry and ICESat-2 laser altimetry using regionally varying kriging of elevation anomalies relative to ArcticDEM. The PRODEMs are validated using leave-one-out cross-validation, and PRODEM19 is further validated against an external data set, showcasing their ability to correctly represent surface elevations within the associated spatially varying prediction uncertainties. We observe a general lowering of surface elevations during the 4-year PRODEM period, but the spatial pattern of change is highly complex and with annual changes superimposed. The PRODEMs enable detailed studies of the marginal ice sheet elevation changes. With their high spatio-temporal resolution, the PRODEMs will be of value to a wide range of researchers and users studying ice sheet dynamics and monitoring how the ice sheet responds to changing environmental conditions. PRODEMs from summer 2019 through 2022 are available at https://doi.org/10.22008/FK2/52WWHG (Winstrup, 2024), and we plan to annually update the product henceforth.

Digital Elevation Models↗