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At least 307 records · Page 17

Major Pathways to Electron Distribution Function Formation in Regions of Diffuse Aurora

This paper discusses the major pathways of electron distribution function formation in the region of diffuse aurora. The diffuse aurora accounts for about of 75% of the auroral energy precipitating into the upper atmosphere, and its origin has been the subject of much discussion. We show that an earthward stream of precipitating electrons initially injected from the Earth's plasma sheet via wave-particle interactions degrades in the atmosphere toward lower energies and produces secondary electrons via impact ionization of the neutral atmosphere. These electrons of magnetospheric origin are then reflected back into the magnetosphere along closed dipolar magnetic field lines, leading to a series of reflections and consequent magnetospheric interactions that greatly augment the initially precipitating flux at the upper ionospheric boundary (700-800 km). To date this, systematic magnetosphere-ionosphere coupling element has not been included in auroral research models, and, as we demonstrate in this article, has a dramatic effect (200-300%) on the formation of the precipitating fluxes that result in the diffuse aurora. It is shown that wave-particle interaction processes that drive precipitating fluxes in the region of diffuse aurora from the magnetospheric altitudes are only the first step in the formation of electron precipitation at ionospheric altitudes, and they cannot be separated from the atmospheric collisional machine that redistributes and transfers their energy inside the magnetosphere-ionosphere-atmosphere coupling system.

magnetospheric↗

Transforming Satellite Data into Weather Forecasts

A NASA project spans the gap between research and operations, introducing new composites of satellite imagery to weather forecasters to prepare for the next generation of satellites. Satellite imagery has been an immense benefit to weather forecasters. With it, they can assess aviation hazards such as low clouds, monitor thunderstorms, and track the evolution of dust plumes. Satellite sensors are continually evolving to provide ever greater imaging capabilities, and researchers continue to develop advanced techniques to identify hazards in satellite imagery. However, barriers can prevent experimental products from reaching forecasters in the operational environment. A NASA project has developed an interactive process whereby weather forecasters learn to interpret the latest satellite imagery and apply it to their operations. Forecasters then provide feedback to the researchers who are developing algorithms and products to further improve future products. This effort has taken on greater importance with the anticipated launch of a new series of satellites that will provide substantially greater amounts of data than are currently available.

Emily Berndt↗

Herschel Observations of the Debris Disc Around HIP 92043

Context: Typical debris discs are composed of particles ranging from several micron sized dust grains to kilometer-sized asteroidal bodies, and their infrared emission peaks at wavelengths 60-100 microns. Recent Herschel DUNES (Dust Around Nearby Stars) observations have identified several debris discs around nearby Sun-like stars (F, G and K spectral type) with significant excess emission only at 160 microns. Aims: We observed HIP 92043 (110 Her, HD 173667) at far-infrared and sub-millimetre wavelengths with Herschel PACS (Photodetector Array Camera and Spectrometer) and SPIRE (Spectral and Photometric Imaging Receiver).Identification of the presence of excess emission from HIP 92043 and the origin and physical properties of any excess was undertaken through analysis of its spectral energy distribution (SED) and the PACS images. Methods: The PACS and SPIRE images were produced using the HIPE (Herschel Interactive Processing Environment) photProject map maker routine. Fluxes were measured using aperture photometry. A stellar photosphere model was scaled to optical and near infrared photometry and subtracted from the far-infared and sub-mm fluxes to determine the presence of excess emission. Source radial profiles were fitted using a 2D Gaussian and compared to a PSF (Point Spread Function) model based on Herschel observations of alpha Boo to check for extended emission. Results: Clear excess emission from HIP 92043 was observed at 70 and 100 microns. Marginal excess was observed at 160 and 250 microns.Analysis of the images reveals that the source is extended at 160 microns. A fit to the source SED is inconsistent with a photosphere and single temperature black body. Conclusions: The excess emission from HIP 92043 is consistent with the presence of an unresolved circumstellar debris disc at 70and 100 microns, with low probability of background contamination. The extended 160 micron emission may be interpreted as an additional cold component to the debris disc or as the result of background contamination along the line of sight. The nature of the 160 micron excess cannot be determined absolutely from the available data, but we favour a debris disc interpretation, drawing parallels with previously identified cold disc sources in the DUNES sample.

debris discs↗

Examining Sub-Flash Properties of Lightning from GLM for Tracking and Intensification Characterization of Thunderstorms

Current methodologies for operational use of lightning are developed using ground-based networks. Lightning detectors measure different characteristics of the flash, thus they don't observe the same lightning event in the same manner: i.e., flash rates from NDLN (National Lightning Detection Network (R)) will typically not match flash rates from GLM (Geostationary Lightning Mapper) because each sensor is measuring different characteristics (EM (Electromagnetic) radiation vs. optical). Resolution/timeliness of space-based sensor data will change our "rules of thumb" for operational use: Lightning safety - how does the 2D mapping of lightning enhance lightning safety metrics; Is the super-fast input of data (20s) useful for decision-makers, including (non-AWIPS (Advanced Weather Interactive Processing System) -users) non-mets?

lightning jump↗

New York City Panel on Climate Change 2019 Report Chapter 1: Introduction

While urban areas like New York City and its surrounding metropolitan region are key drivers of climate change through emissions of greenhouse gases, cities are also significantly impacted by climate shifts, both chronic changes and extreme events. These are already affecting the New York metropolitan region, including the five boroughs of New York City through higher temperatures, more intense precipitation, and higher sea levels, and will increasingly do so in the coming decades. The City of New York has embarked on a flexible adaptation pathway (i.e., strategies that can evolve through time as climate risk assessment, evaluation of adaptation strategies, and monitoring continues) to respond to climate change challenges. This entails significant programs to develop resilience in communities and critical infrastructure to observed and projected changes in temperature, precipitation, and sea level. The first NPCC Report laid out the risk management framing for the city and region via flexible adaptation pathways. The second New York City Panel on Climate Change Report (NPCC2) developed the “climate projections of record” that are currently being used by the City of New York in its resilience programs . The NPCC3 2019 Report co-generates new tools and methods for the next generation of climate risk assessments and implementation of region-wide resilience. Co-generation is an interactive process by which stakeholders and scientists work together to produce climate change information that is targeted to decision-making needs. These tools and methods can be used to observe, project, and map climate extremes; monitor risks and responses; and engage with communities to develop effective programs. They are especially important at “transformation points” in the adaptation process when large changes in the structure and function of physical, ecological, and social systems of the city and region are undertaken.

Rosenzweig, Cynthia↗

Development of a Silicon Tracker for the All-Sky Medium Energy Gamma-ray Observatory Prototype

The gamma-ray sky from several hundred keV to a hundred MeV has remained largely unexplored due to the challenging nature of detecting gamma rays in this regime. At lower energies, Compton scattering is the dominant interaction process whereas at higher energies pair production dominates, with a crossover at a few MeV. Thus, an instrument designed to work in this energy range must be optimized for both Compton and pair-production events. AMEGO, the All-sky Medium Energy Gamma-ray Observatory, a Probe-class mission in consideration for the 2020 decadal survey, is designed to operate at energies from 200 keV to > 10 GeV with over an order of magnitude increase in sensitivity and with superior angular and energy resolution compared to previous instruments. AMEGO comprises four major subsystems: a plastic anticoincidence detector for rejecting cosmic-ray events, a silicon tracker for tracking pair-production products and tracking and measuring the energies of Compton-scattered electrons, a cadmium-zinc-telluride (CZT) calorimeter for measuring the energy and location of Compton scattered photons, and a CsI calorimeter for measuring the energy of the pair-production products at high energies. A prototype instrument, known as ComPair, is under development at NASA’s Goddard Space Flight Center and the US Naval Research Laboratory. In this contribution, we provide details on the development of the silicon tracker subsystem.

Griffin, Sean↗

Geometry Modeling for Unstructured Mesh Adaptation

The quantification and control of discretization error is critical to obtaining reliable simulation results. Adaptive mesh techniques have the potential to automate discretization error control, but have made limited impact on production analysis workflow. Recent progress has matured a number of independent implementations of flow solvers, error estimation methods, and anisotropic mesh adaptation mechanics. However, the poor integration of initial mesh generation and adaptive mesh mechanics to typical sources of geometry has hindered adoption of adaptive mesh techniques, where these geometries are often created in Mechanical Computer- Aided Design (MCAD) systems. The difficulty of this coupling is compounded by two factors: the inherent complexity of the model (e.g., large range of scales, bodies in proximity, details not required for analysis) and unintended geometry construction artifacts (e.g., translation, uneven parameterization, degeneracy, self-intersection, sliver faces, gaps, large tolerances be- tween topological elements, local high curvature to enforce continuity). Manual preparation of geometry is commonly employed to enable fixed-grid and adaptive-grid workflows by reducing the severity and negative impacts of these construction artifacts, but manual process interaction inhibits workflow automation. Techniques to permit the use of complex geometry models and reduce the impact of geometry construction artifacts on unstructured grid workflows are models from the AIAA Sonic Boom and High Lift Prediction are shown to demonstrate the utility of the current approach.

Park, Michael A.↗

Use of Climate Change Projections for Resilience Planning in Rio de Janeiro, Brazil

In this study we use three different methodologies to document and compare temperature and precipitation projections for the city of Rio de Janeiro (RJ) over the 21st century. It aims to explore in what way the differences and similarities of those methodologies and their outcomes support the incorporation of climate risks in urban planning and improve effective urban climate change governance. We compared the projections for RJ from the Eta Regional Climate Model from the Brazilian National Institute for Space Research nested in two Hadley Center Global Climate Models (GCMs) (Eta-HadCM3 method and Eta-HadGEM2-ES method) and 33 GCMs from the Coupled Model Intercomparison Project Phase 5 multi-model dataset (Urban Climate Change Research Network - UCCRN method). The three methods showed increasing temperatures for RJ at the end of the century. Precipitation projections span a 13% decrease to a 12% increase when using the UCCRN method or are reduced between 0.4 and 0.5%, when using the Eta-HadGEM2-ES method. However, the middle range of the projections from UCCRN and Eta-HadGEM2-ES is similar. The three methods project an increase of warm days and nights and a decrease of cold days and nights. Nevertheless, although the directions of change are the same applying the three methods, the magnitude differs when considering warm and cold nights. Hence, city stakeholders are better informed when we apply different projection methods as it gives them the opportunity to consider the level of risk they are willing to bear in the future. We observed that defining climate change projections on the city scale based on clear communication and an interactive process between scientists and stakeholders can be used to inform citywide adaptation strategies and sector-specific uses, as well as promote urban climate risk governance.

urban governance and management↗

LaRC SmartLab Apps For Instrument Control And Data Processing: Optical Micrometer Data Visualizer

The LaRC Smart Lab applications are a series of software tools to greatly enhance researcher efficiency by streamlining and automating workflows. Python scripts and applications are increasingly being used in scientific workflows, including for instrument control and data processing. Interactive Python scripting environments such as Jupyter Lab provide powerful tools for using Python. In some use cases, the development of standalone applications with dedicated graphical user interfaces (GUIs) can enhance the utility of the code and open it up to more users, including non-programmers. Here, we describe a GUI based optical micrometer data visualization application developed as part of the LaRC SmartLab project. We highlight its use in visualizing experimental data and briefly discuss its implementation to give pointers to programmers who wish develop work based on this application's or similar co de.

LaRC SmartLab↗

LaRC SmartLab Apps For Instrument Control and Data Processing: Laboratory Environment Monitor

The LaRC SmartLab applications are a series of software tools to greatly enhance researcher efficiency by streamlining and automating workflows. Python scripts and applications are increasingly being used in scientific workflows, including for instrument control and data processing. Interactive Python scripting environments such as JupyterLab provide powerful tools for using Python. In some use cases, the development of standalone applications with dedicated graphical user interfaces can enhance the utility of the code and open it up to more users, including non-programmers. Here, we describe a Python based application for communicating with, and displaying data from, iTHX Temperature, Humidity, and Dew Point probes. We discuss the set up and use of the application as well as its implementation. We also highlight the use of Simulated probes to enable users and developers to familiarize with or debug the application, even when they do not have access to the physical hardware in the laboratory.

LaRC SmartLab↗

Variation of Ice Microphysical Properties With Temperature and Humidity at Tops of Convective Clouds

A better understanding of the many interacting processes governing the evaluation of ice in natural clouds is required to improve the representation of ice clouds in global circulation models. Recent studies suggest a dominant role of vapor growth processes in determining the temperature dependence of cloud top ice sizes and shapes. Using airborne cloud remote sensing along with reanalysis data, here we show that observed cloud top ice effective radii and estimated normalized growth rates at cloud top highly correlate with an approximately linear relationship, which is consistent with a conceptual model also presented. Furthermore, significant differences in crystal shape characteristics and scattering asymmetry parameters are found between sub- and super-saturated cloud tops over ocean, although not over land. These results provide valuable observational targets for studying ice formation and evolution processes using models, while also helping interpretation of satellite observations of ice microphysical properties at cloud tops.

ice↗

Arctic Amplification: Process Drivers and Sources of Uncertainty

Arctic amplification (AA) is a coupled atmosphere-sea ice-ocean process. This understanding has evolved from the early concept of AA, as a consequence of snow ice line progressions, through more than a century of research that has clarified the relevant processes and driving mechanisms of AA. The predictions made by early modeling studies, namely the fall/winter maximum, bottom-heavy structure, the prominence of surface albedo feedback, and the importance of stable stratification have withstood the scrutiny of multi-decadal observations and more complex models. Yet, the uncertainty in Arctic climate projections is larger than in any other region of the planet, making the assessment of high-impact, near-term regional changes difficult or impossible. Reducing this large spread in Arctic climate projections requires a quantitative process understanding. This presentation synthesizes current knowledge of AA and describes a set of recommendations to guide future research. It briefly reviews the history of AA science, summarizes observed Arctic changes, discusses modeling approaches and feedback diagnostics, and assesses the current understanding of the most relevant feedbacks to AA. These sections culminate in a conceptual model of the fundamental physical mechanisms causing AA and a collection of recommendations to accelerate progress towards reduced uncertainty in Arctic climate projections. Our conceptual model highlights the need to account for local feedback and remote process interactions within the context of the annual cycle to constrain projected AA.

Patrick C Taylor↗

Expanding the Time Dimension of Hyperspectral Infrared Sounding Observations: Designing the NUCAPS-Forecast System

Low Earth orbit (LEO) hyper-spectral infrared (IR) sounders have significant yet untapped potential for characterizing thermodynamic environments of convective initiation and ongoing convection. While LEO soundings are of enormous value to weather forecasters, they cannot provide the temporal resolution needed to resolve the rapidly evolving thermodynamics of the convective environment. A novel methodology was developed to extend snapshots of LEO soundings forward in time up to six hours into the future and has been made available within the NOAA National Weather Service Advanced Weather Interactive Processing System (AWIPS) for testing in a quasi-operational setting. This methodology is based on parcel forward-trajectory calculations from the satellite observing time to recreate future soundings of temperature and moisture at regularly gridded intervals in space and time. The soundings are based on NOAA-Unique Combined Atmospheric Processing System (NUCAPS) retrievals from the Suomi NPP and NOAA-20 satellite platforms to allow for rapid near-real time product processing. Science code was transitioned to operational production in 2019 and the product, NUCAPS-Forecast, was tested at the NOAA Hazardous Weather Testbed Spring Experiment in 2019 and 2021. Forecaster feedback has led to improving the product and processing system to address product limitations and improve its applicability for pre-convective forecasting. This presentation highlights the design of the NUCAPS-Forecast system. Solutions were tested and implemented to remove excess moisture and conjoin forward-trajected parcels into vertical profiles for calculating grids of stability indices. Additionally, use cases that explore the tendencies of derived convective available potential energy (CAPE) and convective inhibition (CIN) were investigated. When evaluated against gridded, hourly accumulated rainfall obtained from the Multi-Radar Multi-Sensor (MRMS) observational data set areas with elevated CAPE (reduced CIN) are shown to be associated with areas of precipitation and increase confidence the LEO soundings advected forward in time physically represent atmospheric processes. These results suggest that adiabatic parcel advection of LEO satellite sounding snapshots forward in time exhibits skill in discriminating locations and times that are more likely to lead to convective initiation. Leveraging trajectory modeling to increase the spatial and temporal resolution of LEO IR sounding observations today demonstrates the value of these observations from the future constellation of JPSS satellites and GeoXO mission.

weather↗

Theoretical Study of Interhemispheric Electron Bouncing Within Pulsating Aurora

Wave-particle interaction processes in the equatorial magnetosphere initiate time-dependent electron precipitation in the pulsating aurora. These electrons enter loss-cone and bounce between the two magnetically conjugate hemispheres, collide with the atmospheric constituents, and introduce additional time scales in electron precipitation dynamics. In this letter we present preliminary results of pulsating aurora formation using the time-dependent SuperThermal Electron Transport code, which considers the magnetosphere-ionosphere-atmosphere energy coupling between the two magnetically conjugate regions and discuss their contribution to the peculiarities of electron distribution function formation within the pulsating aurora.

Pulsating Aurora↗

NASA GPM Status and Future Activities

The joint U.S.-Japan Global Precipitation Measurement (GPM) mission is approaching a decade of operations, and continues to pursue research, dataset production, and outreach related to precipitation. Key activities over the last year were the release of an improved “Version 07” of all GPM precipitation and latent heating products, boosting the orbit of the GPM Core Observatory (GPM CO) to 435 km, and improving quality control on precipitation retrievals from the GPM constellation of passive microwave satellites. This presentation summarizes key improvements to the GPM products and provides some examples of the changes between Versions 06 and 07 in algorithm performance. One important operational change that affected Version 07 is that the scanning strategy for the Ka-band radar channel changed in May 2018; all products that depend on Ka were revised to accommodate this change. For example, in Version 07 the Goddard Profiling (GPROF) algorithm has implemented improvements in regions where orographic enhancement and suppression take place and where the surface is snowy/icy, and again covers radiometers reaching back to 1987. The Combined Radar Radiometer Algorithm (CORRA) now incorporates modified drop-size distribution constraints that substantially reduce bias. Revisions to the Convective-Stratiform Heating (CSH) algorithm employ new radiative transfer retrievals as well as accounting for terrain in the vertical coordinates. Each algorithm was adjusted to ensure continuity for each product across the boundary in 2014 between the predecessor Tropical Rainfall Measuring Mission (TRMM) and the GPM CO. The U.S. Science Team’s Integrated Multi-satellitE Retrievals for GPM (IMERG) was upgraded to account for distortions in the probability density function of regional precipitation rates due to weighted averaging in the Kalman filter used for “morphing” the passive microwave data. Maintaining the GPM CO orbital altitude in the the current very active solar cycle has been forcing the use of more fuel than planned and consequently shortening the forecasted life of the mission from the early 2030's to the late 2020's. It was considered vital to regain some of this lifetime to ensure overlap with the upcoming Atmosphere Observing System mission to provide crosscalibration of instruments. To accomplish this, the orbital altitude was raised from 400 to 435 km on 7-8 November 2023. Thereafter, the primary GPM CO algorithms had to be revised to account for the change in observing parameters. By meeting time this action should be complete. Recently, a screening algorithm based on auto-encoding was developed that uncovered 162 orbits (out of the many thousands of orbits across all years and all satellites) of passive microwave retrievals that had highly anomalous values. Removing these defective retrievals has improved the integrity of both the GPROF and IMERG records. However, the nature of the IMERG processing interacted sufficiently badly with the now-discovered anomalous orbits that it was necessary to completely reprocess the IMERG Final Run record, now labeled Version 07B. The presentation also considers major issues that require continued attention, including the use of machine learning algorithms and the operational challenge of swarms of “small”, perhaps short-lived satellites.

GPM↗

Radiation Effects Considerations for Instrumentation and Control in Space Nuclear Systems

Radiation effects in electrical, electronic, electro-motive, and electro-optical (EEEE) hardware encompass a complex variety of interactions, processes, environments, and an evolving landscape of relevant hardware. Appropriately mitigating the effects of radiation in sensors, data acquisition, and control hardware is among the most significant challenges associated with deploying space nuclear power and propulsion systems. The expertise within EEEE radiation effects disciplines require working knowledge that is at least as complex and diverse as the problem itself, but that should not dissuade stakeholders and engineers in adjacent disciplines from attempting to understand the general principles associated with the problem at hand. This brief overview seeks to bring to the foreground a set of relevant topics that are of special importance for space nuclear propulsion applications that involve high rates of neutron and gamma radiation. The unique set of environments and design requirements for space nuclear systems mean that the experience and utility for methods applied to typical spaceflight hardware or terrestrial nuclear systems must not be applied naively. Forward consideration on the applicability of testing methods applied to either existing or bespoke hardware is likely to drive early decisions on system-wide radiation effects mitigation strategies, and will influence procurement requirements for providers of radiation tolerant hardware who are unlikely to have experience in this unique set of environments. Radiation hardness assurance (RHA) guidance should be adapted and emphasize the importance of hardware testing in the relevant environment. These must consider the combined effects of temperature, total ionizing dose (TID), non-ionizing/displacement damage (TNID/DD), and single event effects (SEE), and should consider the impacts of flux (rate) in addition to cumulative effects.

Radiation↗

SUPIN: A Tool for the Aerodynamic Design and Analysis of Supersonic Inlets

The Supersonic Inlet Design and Analysis Tool (SUPIN) is a computational program that performs geometric modeling and aerodynamic design and analysis of a set of supersonic inlets whose types include the axisymmetric pitot, three-dimensional pitot, axisymmetric, two-dimensional, two-dimensional bifurcated-duct, and streamline-traced inlets. The inlets are modeled by dividing the inlet flowpath into components that start at the freestream and ends at the engine face. The primary components of the inlet include the external supersonic diffuser, throat section, and subsonic diffuser. Each component is characterized by a set of inputs that include geometric and aerodynamic factors. Examples of the geometric factors are angles, lengths, area ratios, and coordinates that describe the geometry of the components. Examples of the aerodynamic factors are Mach numbers, flow ratios, and pressure ratios that set constraints or desired aerodynamic properties of the component. These input factors are specified within a text-based input data file that is read into SUPIN. SUPIN is a Fortran 95 program that performs the inlet design and analysis as a batch or non-interactive process. SUPIN writes output data files describing the inlet geometry and aerodynamic performance. SUPIN uses analytic, empirical, and numerical methods to perform the inlet design and analysis. The inlet geometry is constructed using planar and three-dimensional geometry constructs and is represented by coordinates, angles, areas, profiles, and surfaces. Surfaces are output in the form of a Plot3D surface grid file. SUPIN does have some capability to automatically generate planar and three-dimensional, multi-block, structured grids for computational fluid dynamics (CFD) analysis. The aerodynamic analysis performed by SUPIN computes quasi-one-dimensional properties, such as Mach numbers, pressures, and temperatures, through the inlet flowpath. Planar aerodynamic properties, such as those for shock and Mach waves, are computed for the supersonic compression of the external supersonic diffuser and throat section. The inlet performance is characterized by the inlet flow rates, total pressure recovery, and inlet drag. The primary intent of this document is to describe the usage of SUPIN. The methods used within SUPIN are documented and may serve as a useful reference for understanding the aerodynamic design and analysis of supersonic inlets.

supersonic inlets↗

Improved Air Quality Forecasts using NASA’s Pandora and GEOS CF at International and Domestic Sites for SNWG Stakeholders

Air pollution prediction is complex due to the dynamic nature of atmospheric processes and the variability in data resolutions and availability. This project addresses these challenges by integrating and analyzing high-resolution ground-based measurements with global air quality models. Through this integration, we have gained a deeper understanding of how these processes interact under various conditions, which we then use to model and enhance the accuracy of forecasts.

Noussair Lazrak↗