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At least 271 records · Page 15

Multi-wavelength Radio Continuum Emission Studies of Dust-free Red Giants

Multi-wavelength centimeter continuum observations of non-dusty, non-pulsating K spectral-type red giants directly sample their chromospheres and wind acceleration zones. Such stars are feeble emitters at these wavelengths, however, and previous observations have provided only a small number of modest signal-to-noise measurements slowly accumulated over three decades. We present multi-wavelength Karl G. Jansky Very Large Array thermal continuum observations of the wind acceleration zones of two dust-free red giants, Arcturus (alpha Boo: K2 III) and Aldebaran (alpha Tau: K5 III). Importantly, most of our observations of each star were carried out over just a few days, so that we obtained a snapshot of the different stellar atmospheric layers sampled at different wavelengths, independent of any long-term variability. We report the first detections at several wavelengths for each star including a detection at 10 cm (3.0 GHz: S band) for both stars and a 20 cm (1.5 GHz: L band) detection for alpha Boo. This is the first time single (non-binary) luminosity class III red giants have been detected at these continuum wavelengths. Our long-wavelength data sample the outer layers of alpha Boo's atmosphere where its wind velocity is approaching (or possibly has reached) its terminal value and the ionization balance is becoming frozen-in. For alpha Tau, however, our long-wavelength data are still sampling its inner atmosphere, where the wind is still accelerating probably due to its lower mass-loss rate. We compare our data with published semi-empirical models based on ultraviolet data, and the marked deviations highlight the need for new atmospheric models to be developed. Spectral indices are used to discuss the possible properties of the stellar atmospheres, and we find evidence for a rapidly cooling wind in the case of alpha Boo. Finally, we develop a simple analytical wind model for alpha Boo based on our new long-wavelength flux measurements.

chromospheres↗

Soil organic matter diagenetic state informs boreal forest ecosystem feedbacks to climate change

The fate of soil organic carbon (SOC) in boreal forests is dependent on the integrative ecosystem response to climate change. For example, boreal forest productivity is often nitrogen (N) limited, and climate warming can enhance N cycling and primary productivity. However, the net effect of this feedback on the SOC reservoir and its longevity with climate change remain unclear due to difficulty in detecting small differences between large and variable carbon (C) fluxes needed to determine net changes in soil reservoirs. The diagenetic state of SOC – resulting from the physicochemical and biological transformations that alter the original biomolecular composition of detrital inputs to soil over time – is useful for tracing the net response of SOC at the timescales relevant to climate change not usually discernible from fluxes and stocks alone. Here, we test two hypotheses using a mesic boreal forest climate transect: (1) the SOC diagenetic state is maintained across this climosequence, and (2) the maintenance of the SOC diagenetic state is a consequence of coupled soil C and N cycling, signifying the role of enhanced N cycling supporting SOC inputs that maintain SOC stocks within the warmer-climate forests. Shifts in nonvascular to vascular plant inputs with climate observed in these and other boreal forests highlighted the need to carefully separate biogeochemical indicators of SOC source from those signifying diagenetic alteration. We thus evaluated and applied lignin biomarkers to assess the diagenetic alteration of SOC in these boreal forest organic soils and directly compared the lignin diagenetic state with that of soil organic nitrogen (SON) assessed through amino acid composition. The lignin diagenetic state remained constant across the climate transect, indicating a balance between the input and removal of lignin in these mesic boreal forests. When combined with previous knowledge of these forest ecosystems, including the diagenetic state of SON and direct measures of C fluxes and stocks, the results indicate a coupled increase in C and N cycling with climate warming that supports forest productivity and maintains SOC stocks. This balance could markedly shift as other factors begin to limit forest productivity (e.g., trace nutrients, water) with further climate change or affect forest nutrient allocation (e.g., forest age or compositional change). Further application of the approach presented here could be used to detect the limits of this and other ecosystem–climate feedbacks, by providing a tractable and parameterizable index of the lignin state across large spatial scales, necessary for ecosystem-scale parameterizations.

54 ENVIRONMENTAL SCIENCES↗

Increased Occurrence of Large–Scale Windthrows Across the Amazon Basin

Convective storms with strong downdrafts create windthrows: snapped and uprooted trees that locally alter the structure, composition, and carbon balance of forests. Comparing Landsat imagery from subsequent years, we documented temporal and spatial variation in the occurrence of large (≥30 ha) windthrows across the Amazon basin from 1985 to 2020. Over 33 individual years, we detected 3179 large windthrows. Windthrow density was greatest in the central and western Amazon regions, with ~33% of all events occurring in ~3% of the monitored area. Return intervals for large windthrows in the same location of these “hotspot” regions are centuries to millennia, while over the rest of the Amazon they are >10,000 years. Our data demonstrate a nearly 4–fold increase in windthrow number and affected area between 1985 (78 windthrows and 6,900 ha) and 2020 (264 events and 32,170 ha), with more events of >500 ha size since 1990. Such extremely large events (>500 ha up to 2,543 ha) are responsible for interannual variation in the overall median (84 ± 5.2 ha; ±95% CI) and mean (147 ± 13 ha) windthrow area, but we did not find significant temporal trends in the size distribution of windthrows with time. Our results document increased damage from convective storms over the past 40 years in the Amazon, filling a gap in temporal records for tropical regions. Our publicly accessible large windthrow database provides a valuable tool for exploring dynamic conditions leading to damaging storms and their ecological impact on Amazon forests.

54 ENVIRONMENTAL SCIENCES↗

The Relationship between Precipitation and Precipitable Water in CMIP6 Simulations and Implications for Tropical Climatology and Change

It is well documented that over the tropical oceans, column-integrated precipitable water (pw) and precipitation (P) have a nonlinear relationship. In this study moisture budget analysis is used to examine this P–pw relationship in a normalized precipitable water framework. It is shown that the parameters of the nonlinear relationship depend on the vertical structure of moisture convergence. Specifically, the precipitable water values at which precipitation is balanced independently by evaporation versus by moisture convergence define a critical normalized precipitable water, pw nc . This is a measure of convective inhibition that separates tropical precipitation into two regimes: a local evaporation-controlled regime with widespread drizzle and a precipitable water–controlled regime. Most of the 17 CMIP6 historical simulations examined here have higher pw nc compared to ERA5, and more frequently they operate in the drizzle regime. When compared to observations, they overestimate precipitation over the high-evaporation oceanic regions off the equator, thereby producing a ‘‘double ITCZ’’ feature, while underestimating precipitation over the large tropical landmasses and over the climatologically moist oceanic regions near the equator. The responses to warming under the SSP585 scenario are also examined using the normalized precipitable water framework. It is shown that the critical normalized precipitable water value at which evaporation versus moisture convergence balance precipitation decreases as a result of the competing dynamic and thermodynamic responses to warming, resulting in an increase in drizzle and total precipitation. Statistically significant historical trends corresponding to the thermodynamic and dynamic changes are detected in ERA5 and in lowintensity drizzle precipitation in the PERSIANN precipitation dataset.

54 ENVIRONMENTAL SCIENCES↗

Modulator for tone and binary signals

Tones and binary information are transmitted as phase variations on a carrier wave of constant amplitude and frequency. The carrier and tones are applied to a balanced modulator for deriving an output signal including a pair of sidebands relative to the carrier. The carrier is phase modulated by a digital signal so that it is + or - 90 deg out of phase with the predetermined phase of the carrier. The carrier is combined in an algebraic summing device with the phase modulated signal and the balanced modulator output signal. The output of the algebraic summing device is hard limited to derive a constant amplitude and frequency signal having very narrow bandwidth requirements. At a receiver, the tones and binary data are detected with a phase locked loop having a voltage controlled oscillator driving a pair of orthogonal detection channels.

Mcchesney, J. R.↗

Evaluate ERTS imagery for mapping and detection of changes of snowcover on land and on glaciers

The author has identified the following significant results. A new procedure to determine snowcovered areas has been devised. Aside from problems in heavily forested areas this method shows promise in predicting snowmelt runoff from mountain areas and will also assist in energy balance modeling of large snowfields. Snowcover results compare favorably with measurements made by high altitude aircraft photography. Changes in snowcover in areas as small as 3 x 5 km can be determined from ERTS-1 images by both optical and electronic methods. Snowcover changes determined by these two methods in the experimental South Cascade Glacier Basin were verified by field mapping. Image enahancement techniques on ERTS-1 images of large Alaskan glaciers (the Hubbard, Yentna, and Kahiltna) have given new insights into the large-scale structures and flow dynamics of these potentially hazardous glaciers. The Hubbard Glacier, in particular, is one which poses a threat to man and should be monitored for future changes.

Meier, M. F.↗

On the detectability of key-MeV solar protons through their nonthermal Lyman-alpha emission

The intensity and timescale of nonthermal Doppler-shifted hydrogen L alpha photon emission as diagnostics of 10 keV to 10 MeV protons bombarding the solar chromosphere during flares are investigated. The steady-state excitation and ionization balance of the proton beam are determined, taking into account all important atomic interactions with the ambient chromosphere. For a proton energy flux comparable to the electron energy flux commonly inferred for large flares, L alpha wing intensities orders of magnitude larger than observed nonflaring values were found. Investigation of timescales for ionization and charge exchange leads researchers to conclude that over a wide range of values of mean proton energy and beam parameters, Doppler-shifted nonthermal L alpha emission is a useful observational diagnostic of the presence of 10 keV to 10 MeV superthermal proton beams in the solar flare chromosphere.

Canfield, R. C.↗

Thermographic Leak Detection of the Space Shuttle Main Engine Nozzle

The Space Shuttle Main Engines Nozzles consist of over one thousand tapered Inconel coolant tubes brazed to a stainless steel structural jacket. Liquid Hydrogen flows through the tubing, from the aft to forward end of the nozzle, under high pressure to maintain a thermal balance between the rocket exhaust and the nozzle wall. Three potential problems occur within the SSME nozzle coolant tubes as a result of manufacturing anomalies and the highly volatile service environment including poor or incomplete bonding of the tubes to the structural jacket, cold wall leaks and hot wall leaks. Of these conditions the identification of cold wall leaks has been the most problematic. The methods and results presented in this summary addresses the thermographic identification of cold wall "interstitial" leaks between the structural jacket and coolant tubes of the Space Shuttle Main Engines Nozzles.

Walker, James L.↗

Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1

Abstract. Atmospheric rivers (ARs) are extreme weather events that can alleviate drought or cause billions of US dollars in flood damage. By transporting significant amounts of latent energy towards the poles, they are crucial to maintaining the climate system's energy balance. Since there is no first-principle definition of an AR grounded in geophysical fluid mechanics, AR identification is currently performed by a multitude of expert-defined, threshold-based algorithms. The variety of AR detection algorithms has introduced uncertainty into the study of ARs, and the thresholds of the algorithms may not generalize to new climate datasets and resolutions. We train convolutional neural networks (CNNs) to detect ARs while representing this uncertainty; we name these models ARCNNs. To detect ARs without requiring new labeled data and labor-intensive AR detection campaigns, we present a semi-supervised learning framework based on image style transfer. This framework generalizes ARCNNs across climate datasets and input fields. Using idealized and realistic numerical models, together with observations, we assess the performance of the ARCNNs. We test the ARCNNs in an idealized simulation of a shallow-water fluid in which nearly all the tracer transport can be attributed to AR-like filamentary structures. In reanalysis and a high-resolution climate model, we use ARCNNs to calculate the contribution of ARs to meridional latent heat transport, and we demonstrate that this quantity varies considerably due to AR detection uncertainty.

54 ENVIRONMENTAL SCIENCES↗

Provider of Services for Urban Air Mobility (PSU) Prototype Simulation (X5) Final Report

Urban Air Mobility (UAM) is a new air transportation service concept to carry passengers or cargo in metropolitan areas, leveraged by innovative aircraft and air traffic automation technologies. NASA has conducted a series of simulations, called the X-series simulation, to evaluate the UAM concept of operations and support the development of airspace procedures and services for UAM operations. The simulation called “X5” was conducted in 2023 to test a Provider of Services for UAM (PSU) prototype developed by NASA for UAM flight planning, strategic conflict management support, and data exchange between UAM operators. In this simulation, two strategic conflict management capabilities, Demand-Capacity Balancing and Sequencing and Scheduling, were further investigated. This document describes the UAM system architecture modeled, the X5 simulation environment to be executed (e.g., traffic scenario and UAM airspace construct), and the strategic conflict management processes developed and evaluated in this study. Then, the simulation results are provided using several system performance metrics, such as the number of operations planned and activated, demand-capacity imbalances detected and resolved, and pre-departure delays. Based on these metrics, the test findings and lessons learned from this simulation are discussed. NASA developed a PSU prototype as part of a reference implementation of UAM system architecture and evolved strategic conflict management capabilities for UAM operations from the previous collaborative simulations with industry partners. Below is the summary of the achievements: - Aligned NASA’s UAM reference architecture with the FAA’s UAM ConOps notional architecture - Extended UAM airspace management capabilities to include 1) Demand-Capacity Balancing (DCB) to ensure operators coordinate planned usage of shared vertiports, and 2) Sequencing and Scheduling (S&S) at UAM corridor entry and exit points to help facilitate an orderly flow of traffic - Defined the PSU information exchange APIs and requirements towards informing industry standards - Developed and tested a NASA PSU prototype as reference implementation to validate the requirements and APIs - Developed a prototype service connecting NASA’s PSU and the FAA system for testing future PSU-ATM interface requirements - Tested NASA-developed assumptions for UAM operations such as airspace design, procedures, vehicle performance, and strategic conflict management methods to inform future Cooperative Operating Practices (COPs) development with industry - Evaluated system performance metrics such as number of simultaneous operations and ground delays that can help define system-level requirements. The simulation results showed that the UAM traffic demand could be managed to minimize the needs of tactical separation provision with ground delays assigned by DCB and S&S. These accomplishments and the lessons learned from the PSU Prototype X5 simulation activities will be valuable inputs for the Air Mobility Pathfinders (AMP) project, which is NASA’s new project to create and evaluate a reference architecture for safe, secure, and scalable UAM operations.

Simulation↗

NASA's East and Southeast Asia Initiatives: BASE-ASIA and EAST-AIRE

Airborne dust from northern China influences air quality and regional climate in Asia during springtime. However, with the economic growth in China, increased emission of particulate air pollutants from industrial and vehicular sources will not only impact the earth's radiation balance, but also adversely affect human health year round. In addition, both of dust and aerosol pollutants can be transported swiftly across the Pacific affecting North America within a few days. Asian dust and pollutant aerosols can be detected by their colored appearance using current Earth observing satellites (e.g., MODIS, SeaWiFS, TOMS, etc.) and by sunphotometers deployed on the surface of the earth. Biomass burning has been a regular practice for land clearing and conversion in many countries, especially those in Africa, South America, and Southeast Asia. However, the climatology of Southeast Asia is very different than that of Africa and South America, such that large-scale biomass burning causes smoke to interact extensively with clouds during the peak-burning season of March to April. Globally significant sources of greenhouse gases (eg., CO2, CH4), chemically active gases (e.g., NO, CO, HC, CH3Br), and atmospheric aerosols are produced by biomass burning. These gases influence the Earth-atmosphere system, impacting both global climate and tropospheric chemistry. Some aerosols can serve as cloud condensation nuclei, which play a role in determining cloud lifetime and precipitation, altering the earth's radiation and water budgets. Biomass burning also affects the biogeochemical cycling of nitrogen and carbon compounds; the hydrological cycle; land surface reflectivity and emissivity; and ecosystem biodiversity and stability. Two NASA initiatives, EAST-AIRE (East Asian Study of Tropospheric Aerosols: an International Regional Experiment) and BASE-ASIA (Biomass-burning Aerosols in South East-Asia: Smoke Impact Assessment) will be presented. The objectives of these initiatives is to develop a better understanding of the impacts of aerosols on regional-to-global climate, hydrological and carbon cycles, and tropospheric chemistry.

Tsay, S.↗

Spacecraft Environment May Reduce Resistance To Infection

Living and working in a spacecraft exposes the crew to a unique environment. This environment includes microgravity, increased radiation, chemical and biological contamination, and a variety of stressors. Disturbances in this balance are often manifested by diminished immunity in astronauts/cosmonauts. Reactivation of Epstein- Barr virus (EBV), cytomegalovirus (CMV), and varicella-zoster virus (VZV) has been used as an indicator of immune status. Reactivation of EBV and VZV were detected and quantified in saliva. CMV was measured in urine. The DNA was extracted using a Qiagen Inc. kit and viral DNA was detected by real time polymerase chain reaction (PCR) based assay with Taqman 7700 (PE Biosystems). Patterns of Epstein-Barr virus (EBV) reactivation in 32 astronauts and 18 healthy age-matched control subjects were characterized by quantifying EBV shedding. Saliva samples were collected before, during, and after 10 space shuttle missions of 5 to 14 d duration. Of 1398 saliva specimens from 32 astronauts, 314 (23%) were positive for EBV DNA. Examination by flight phase showed that 29% of the saliva specimens collected from 28 astronauts before flight were positive for EBV DNA, as were 16% of those collected from 25 astronauts during flight and 16% of those collected after flight from 23 astronauts. The mean number of EBV copies/mL from samples taken during the flights was 417, ten-fold greater (p < 0.05) than the copies from the preflight (40) and post flight (44) phases. In contrast, the control subjects shed EBV DNA with a frequency of 3.7% and mean EBV copies of 40 per mL of saliva. Ten days before flight and on landing day, titers of antibody to EBV viral capsid antigen were significantly (p < 0.05) greater than baseline levels. Increases in the number of viral copies and in the amount of EBV-specific antibody were consistent with EBV reactivation before, during, and after space flight. Similarly, CMV and VZV reactivation increased in response to space flight conditions. Data indicates that space flight is a unique stress environment that may produce stress-induced changes in the host-microbe relationship resulting in increased risk of infection.

Pierson, Duane L.↗

Accelerated Monte Carlo Simulation for Safety Analysis of the Advanced Airspace Concept

Safe separation of aircraft is a primary objective of any air traffic control system. An accelerated Monte Carlo approach was developed to assess the level of safety provided by a proposed next-generation air traffic control system. It combines features of fault tree and standard Monte Carlo methods. It runs more than one order of magnitude faster than the standard Monte Carlo method while providing risk estimates that only differ by about 10%. It also preserves component-level model fidelity that is difficult to maintain using the standard fault tree method. This balance of speed and fidelity allows sensitivity analysis to be completed in days instead of weeks or months with the standard Monte Carlo method. Results indicate that risk estimates are sensitive to transponder, pilot visual avoidance, and conflict detection failure probabilities.

Thipphavong, David↗

Small-Scale Flux Transfer Events Formed in the Reconnection Exhaust Region Between Two X Lines

We report MMS observations of the ion-scale flux transfer events (FTEs) that may involve two main X lines and tearing instability between the two X lines. The four spacecraft detected multiple isolated regions with enhanced magnetic field strength and bipolar B(sub )n signatures normal to the nominal magnetopause, indicating FTEs. The currents within the FTEs flow mostly parallel to B, and the magnetic tension force is balanced by the total pressure gradient force. During these events, the plasma bulk flow velocity was directed southward. Detailed analysis of the magnetic and electric field and plasma moments variations suggests that the FTEs were initially embedded within the exhaust region north of an X line but were later located southward/downstream of a subsequent X line. The cross sections of the individual FTEs are in the range of ~2.5-6.8 ion inertial lengths. The observations suggest the formation of multiple secondary FTEs. The presence of an X line in the exhaust region southward of a second X line results from the southward drift of an old X line and the reformation of a new X line. The current layer between the two X lines is unstable to the tearing instability, generating multiple ion-scale flux-rope-type secondary islands.

Hwang, K.-J.↗

Statistical and Neural Network for Real Sensor-Data-Driven Anomaly Detection in Nuclear Applications

Anomaly detection (AD) in sensor data is critical to ensure uninterrupted functionality of nuclear power plants (NPPs). Consequently, AD model validation through real-world sensor data is important for applications in nuclear facilities. In this paper, we propose an Autoencoder (AE)—a multi-layered neural network, for AD in sensor data from an operational NPP testbed. Since the dataset lacks labels for irregularities, we introduce random noise and label them to effectively train our model. The proposed AE model assigns a higher reconstruction error to the abnormal samples that deviate from those encountered during the training phase and uses the reconstruction loss to detect anomalies in a representative imbalanced dataset. We also introduce an analytical solution—seasonal trend decomposition (STD)—as another AD scheme for identifying irregularities withinthe same time-series dataset. In contrast to the AE model which relies on reconstruction loss, the STD scheme decomposes the entire dataset into its trend, seasonality, and residual components to pinpoint irregularities. Our findings indicate that the proposed AE and STD models individually achieve recall scores of 97% and 92%, respectively. We validate the performance of the two models on both balanced and imbalanced data. We further solidify the results by picking the combined selected anomalies of the two solutions with an "AND" operator for more reliable predictions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Observations of Mercury's Exosphere: Composition and Structure: Chapter - 14

Mercury is surrounded by a tenuous exosphere in which particles travel on ballistic trajectories under the influence of a combination of gravity and solar radiation pressure. The densities are so small that the surface forms the exobase and particles in the exosphere are more likely to collide with it rather than with each other. For a planet with a more substantial collision­-dominated atmosphere, a population of particles that enters from below the exobase supplies the exosphere. In contrast Mercury's exosphere is supplied both by incoming sources including the solar wind (hydrogen and helium), micrometeoroids (dust), meteoroids and cornets, and by particles released from the surface through a variety of processes that include sputtering by solar wind ions, desorption by solar photons and electrons, impacts by micrometeoroids, and thermal desorption of surface materials. These source processes are balanced by loss processes, which include impact with and sticking to the surface, Jeans (or thermal) escape, ionization followed by trans­port along magnetic field lines, and acceleration by solar radia­tion pressure to escape velocity. Ground-based attempts to detect an atmosphere around Mercury before Mariner 10 first visited the planet in 1974 were unsuccessful and led only to increasingly tight upper limits, culminating in a limiting value for surface atmospheric pressure of 0.015 Pascal (Pa) determined by Fink et al. (1974).

Solar↗

Assimilating microwave cloudy observations into NASA GEOS model using a novel Bayesian Monte Carlo technique

Despite the importance of clouds and their influence on atmospheric water and energy balance, Numerical Weather Prediction (NWP) centers systematically exclude cloud information from the assimilation process and only assimilate clear-sky radiances (Janiskov´a et al. 2012). In order to ensure that only clear sky radiances are assimilated, strict cloud detection thresholds are applied before radiances are fed into data assimilation (DA) systems. This process not only excludes a large portion of satellite radiances, but causes loss of information in the regions that are of high interest to meteorologists and are most challenging for weather forecasts (Errico et al. 2007; Haddad et al. 2015). Although, in recent years there has been great advances in the operational weather forecasting, the prediction of tropical cyclones (TC), especially the intensity of TCs, remains challenging. According to Aksoy et al. (2013), in addition to the model deficiencies, another important factor that contributes to this challenge includes lack of observations in the peripheral environment (rain- bands) of TCs mainly because of the selective assimilation of existing observations. Satellite observations provide more than 90 % of the input data for the initialization of NWP models but more than 75 % of satellite observations are discarded due to the cloud contamination as well as land, snow, and ice emissivity issues (Bauer et al. 2010).

Rainband↗

Statistical and Neural Network for Real Sensor-Data-Driven Anomaly Detection in Nuclear Applications

Anomaly detection (AD) in sensor data is critical to ensure uninterrupted functionality of nuclear power plants (NPPs). Consequently, validation of AD models through real-world sensor data is important for their application in nuclear facilities. In this paper, we propose an Autoencoder (AE)— a multi-layered neural network, for AD in sensor data from an operational NPP testbed. Since the dataset lacks labels for irregularities, we introduce random noise and label them to effectively train our model. The proposed AE model assigns a higher reconstruction error to the abnormal samples that deviate from those encountered during the training phase and uses the reconstruction loss to detect anomalies in a representative imbalanced dataset. We also introduce an analytical solution—seasonal trend decomposition (STD) — as another AD scheme for identifying irregularities within the same time-series dataset. In contrast to the AE model which relies on reconstruction loss, the STD scheme decomposes the entire dataset into its trend, seasonality, and residual components to pinpoint irregularities. Our findings indicate that the proposed AE and STD models individually achieve recall scores of 97% and 92%, respectively. We also validate the performance of the two models on both balanced and imbalanced data. We further solidify the results by picking the combined selected anomalies of the two solutions with an "AND" operator for more reliable predictions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗