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At least 433 records · Page 24

Characteristics and Global Impact of Aerosols from Southern Africa and Eastern Asia

Supported mainly by the NASA GACP and ACMAP, we have made significant progress in the global modeling of tropospheric aerosols and their precursors in the past few years, especially in the development of the GOCART model, simulation of anthropogenic and natural aerosols, data analysis of field observations and satellite retrievals, assessment of global and regional budgets, estimate of aerosol direct radiative forcing, and aerosol forecasting and data analysis for the ACE-Asia field experiment. Our results and findings are summarized in Chin et al. Model calculated multiple-year optical thickness for individual and total aerosols are at internet. These results have been frequently used by other groups, for example, to impose initial conditions for regional models, provide dust source functions for other global models, supply aerosol fields for chemistry and climate models, help data group interpret their measurements, select monitoring sites for ground observation network, and assist satellite retrievals.

Chin, Mian↗

Dust, Pollution, and Biomass Burning Aerosols in Asian Pacific: A Column Satellite-Surface Perspective

Airborne dusts from northern China contribute a significant part of the air quality problem and, to some extent, regional climatic impact in Asia during spring-time. However, with the economical growth in China, increases in the emission of air pollutants generated from industrial and vehicular sources will not only impact the radiation balance, but adverse health effects to humans all year round. In addition, both of these dust and air pollution clouds can transport swiftly across the Pacific reaching North America within a few days, possessing an even larger scale effect. The Asian dust and air pollution aerosols can be detected by its colored appearance on current Earth observing satellites (e.g., MODIS, SeaWiFS, TOMS, etc.) and its evolution monitored by satellites and surface network. Biomass burning has been a regular practice for land clearing and land conversion in many countries, especially those in Africa, South America, and Southeast Asia. However, the unique 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. Significant global sources of greenhouse gases (e.g., CO2, CH4), chemically active gases (e.g., NO, CO, HC, CH3Br), and atmospheric aerosols are produced by biomass burning processes. These gases influence the Earth-atmosphere system, impacting both global climate and tropospheric chemistry. Some aerosols can serve as cloud condensation nuclei, which play an important role in determining cloud lifetime and precipitation, hence, altering the earth's radiation and water budget. Biomass burning also affects the biogeochemical cycling of nitrogen and carbon compounds from the soil to the atmosphere; the hydrological cycle (i.e., run off and evaporation); land surface reflectivity and emissivity; as well as ecosystem biodiversity and stability. Two new 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 and discussed their contribution to better understand the impacts of aerosols on regional-to-global climate, hydrological and carbon cycles, and tropospheric chemistry.

Tsay, Si-Chee↗

Asian Dust Storm Outbreaks: A Satellite-Surface Perspective

Airborne dusts from northern China contribute a significant part of the air quality problem and, to some extent, regional climatic impact in Asia during springtime. Asian dust typically originates in desert areas far from polluted urban regions. During the transport, dust layers can interact with anthropogenic sulfate and soot aerosols from heavily polluted urban areas. Added to the complex effects of clouds and natural marine aerosols, dust particles reaching the marine environment can have drastically different properties than those from the source. Thus, understanding the unique temporal and spatial variations of Asian dust is of special importance in regional-to-global climate issues (e.g., radiative forcing, hydrological cycle, and primary biological productivity in the mid-Pacific Ocean, etc.), as well as societal concerns (e.g., adverse health effects to humans). The Asian dust and air pollution aerosols can be detected by its colored appearance on current Earth observing satellites (e.g., MODIS, SeaWiFS, TOMS, etc.) and its evolution monitored by satellites and surface network (e.g. AERONET, SKY NET, MPLNET, etc.). Recently, many field campaigns (e.g., ACE-Asia-2001, TRACEP-2001, ADE-2002 & -2003, APEX-2001 & -2003, etc.) were designed and executed to study the compelling variability in spatial and temporal scale of both pollution-derived and naturally occurring aerosols, which often exist in high concentrations over eastern Asia and along the rim of the western Pacific. I will present an overview of the outbreak of Asian dust storms from space and surface observations and to address the climatic effects and societal impacts.

Tsay, Si-Chee↗

Long-range Transport of Asian Dust Storms: A Satellite/Surface Perspective on Societal and Scientific Influence

Among the many components contributing to air pollution, airborne mineral dust plays an important role due to its biogeochemical impact on the ecosystem and its radiative forcing effect on the weather/climate system. As much as one-third to half of the global dust emissions, estimated about 800 Tg, are introduced annually into Earth's atmosphere from various deserts in China. Asian dust storm outbreaks are believed to have persisted for hundreds and thousands years over the vast territory of north and northwest China, but not until recent decades that many studies reveal the compelling evidence in recognizing the importance of these eolian dust particles for forming Chinese Loess Plateau and for biogeochemical cycling in the North Pacific Ocean to as far as in the Greenland ice-sheets through long-range transport. The Asian dust and air pollution aerosols can be detected by its colored appearance on current Earth observing satellites and its evolution monitored by satellite and surface network. In this paper, we will demonstrate the capability of a new satellite algorithm, called Deep Blue, to retrieve aerosol properties, particularly but not limited to, over bright-reflecting surfaces such as urban areas and deserts. Recently, many field campaigns were designed and executed to study the compelling variability in spatial and temporal scale of both pollution-derived and naturally occurring aerosols, which often exist in high concentrations over eastern Asia and along the rim of the western Pacific. We will provide an overview of the outbreak of Asian dust storms, near source/sink and their evolution along transport pathway, from space and surface observations. The climatic effects and societal impacts of the Asian dusts will be addressed in depth. (to be presented in the International Workshop on Semi-Arid Land Surface-

Source record↗

Developing an Approach for Analyzing and Verifying System Communication

This slide presentation reviews a project for developing an approach for analyzing and verifying the inter system communications. The motivation for the study was that software systems in the aerospace domain are inherently complex, and operate under tight constraints for resources, so that systems of systems must communicate with each other to fulfill the tasks. The systems of systems requires reliable communications. The technical approach was to develop a system, DynSAVE, that detects communication problems among the systems. The project enhanced the proven Software Architecture Visualization and Evaluation (SAVE) tool to create Dynamic SAVE (DynSAVE). The approach monitors and records low level network traffic, converting low level traffic into meaningful messages, and displays the messages in a way the issues can be detected.

Stratton, William C.↗

Climatological Aspects of the Optical Properties of Fine/Coarse Mode Aerosol Mixtures

Aerosol mixtures composed of coarse mode desert dust combined with fine mode combustion generated aerosols (from fossil fuel and biomass burning sources) were investigated at three locations that are in and/or downwind of major global aerosol emission source regions. Multiyear monitoring data at Aerosol Robotic Network sites in Beijing (central eastern China), Kanpur (Indo-Gangetic Plain, northern India), and Ilorin (Nigeria, Sudanian zone of West Africa) were utilized to study the climatological characteristics of aerosol optical properties. Multiyear climatological averages of spectral single scattering albedo (SSA) versus fine mode fraction (FMF) of aerosol optical depth at 675 nm at all three sites exhibited relatively linear trends up to 50% FMF. This suggests the possibility that external linear mixing of both fine and coarse mode components (weighted by FMF) dominates the SSA variation, where the SSA of each component remains relatively constant for this range of FMF only. However, it is likely that a combination of other factors is also involved in determining the dynamics of SSA as a function of FMF, such as fine mode particles adhering to coarse mode dust. The spectral variation of the climatological averaged aerosol absorption optical depth (AAOD) was nearly linear in logarithmic coordinates over the wavelength range of 440-870 nm for both the Kanpur and Ilorin sites. However, at two sites in China (Beijing and Xianghe), a distinct nonlinearity in spectral AAOD in logarithmic space was observed, suggesting the possibility of anomalously strong absorption in coarse mode aerosols increasing the 870 nm AAOD.

Eck, T. F.↗

NASA Tech Briefs, August 2003

Topics covered include: Stable, Thermally Conductive Fillers for Bolted Joints; Connecting to Thermocouples with Fewer Lead Wires; Zipper Connectors for Flexible Electronic Circuits; Safety Interlock for Angularly Misdirected Power Tool; Modular, Parallel Pulse-Shaping Filter Architectures; High-Fidelity Piezoelectric Audio Device; Photovoltaic Power Station with Ultracapacitors for Storage; Time Analyzer for Time Synchronization and Monitor of the Deep Space Network; Program for Computing Albedo; Integrated Software for Analyzing Designs of Launch Vehicles; Abstract-Reasoning Software for Coordinating Multiple Agents; Software Searches for Better Spacecraft-Navigation Models; Software for Partly Automated Recognition of Targets; Antistatic Polycarbonate/Copper Oxide Composite; Better VPS Fabrication of Crucibles and Furnace Cartridges; Burn-Resistant, Strong Metal-Matrix Composites; Self-Deployable Spring-Strip Booms; Explosion Welding for Hermetic Containerization; Improved Process for Fabricating Carbon Nanotube Probes; Automated Serial Sectioning for 3D Reconstruction; and Parallel Subconvolution Filtering Architectures.

Source record↗

Addressing Software Security

Historically security within organizations was thought of as an IT function (web sites/servers, email, workstation patching, etc.) Threat landscape has evolved (Script Kiddies, Hackers, Advanced Persistent Threat (APT), Nation States, etc.) Attack surface has expanded -Networks interconnected!! Some security posture factors Network Layer (Routers, Firewalls, etc.) Computer Network Defense (IPS/IDS, Sensors, Continuous Monitoring, etc.) Industrial Control Systems (ICS) Software Security (COTS, FOSS, Custom, etc.)

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Environmental Enrichment in the ISS Rodent Habitat Hardware System

Responses of animals exposed to microgravity during in-space experiments were observed via available video recording stored in the NASA Ames Life Sciences Data Archive. These documented observations of animal behavior, as well as the range and level of activities during spaceflight, demonstrate that weightlessness conditions and the extreme novelty of the surroundings may exert damaging psychological stresses on the inhabitants. In response to a recognized need for in-flight animals to improve their wellbeing we propose to reduce such stresses by shaping and interrelating structures and surroundings to satisfying vital physiological needs of inhabitants. A Rodent Habitat Hardware System (RHHS) based housing facility incorporating a tubing network system, to maintain and monitor rodent health environment with advanced accessories has been proposed. Placing mice in a tubing-configured environment creates more natural space-restricted nesting environment for rodents, thereby facilitating a more comfortable transition to living in microgravity. A sectional tubing structure of the RHHS environment will be more beneficial under microgravity conditions than the provision of a larger space area that is currently utilized. The new tubing configuration was found suitable for further incorporation of innovative monitoring technology and accessories in the animal holding habitat unit which allow to monitor in real-time monitoring of valuable health related biological parameters under weightlessness environment of spaceflight.

modifications↗

Environmental Enrichment in the ISS Rodent Habitat Hardware System

Responses of animals exposed to microgravity during in-space experiments were reviewed from NASAs and ESA available video recording archives. These documented observation of animal behavior, as well as the range and level of activities during spaceflight, clearly demonstrate that weightlessness conditions and the extreme novelty of the surroundings exert damaging psychological stresses on the inhabitants. In response to a recognized need for in-flight animals to improve their wellbeing we propose to reduce such stresses by shaping and interrelating structures and surroundings to satisfying vital physiological needs of inhabitants. Rodent Habitat Hardware System based housing facility incorporating a tubing network system, to maintain and monitor rodent health environment with advanced accessories has been proposed. The new tubing configuration was found suitable for further incorporation of innovative monitoring technology and accessories in the animal holding habitat unit which allow to monitor in real-time the most valuable health related biological parameter under weightlessness environment of spaceflight.

Orr, Sophie↗

Air Quality Forecasting at Sub-City Scale by Combining Models, Satellites, and Surface Measures

While there are a variety of sources for air quality information, no one source simultaneously allows for high accuracy, low bias, fine spatial resolution, wide spatial coverage, high temporal frequency, and the capability for near-term forecasting of air quality. Global models, like the NASA’s Goddard Earth Observing System -Composition Forecasting (GEOS-CF) model, provide global coverage and forecasting capabilities, but operate at relatively coarse spatial resolution and require ground-truthing with in-situ data. Polar-orbiting satellite data products, like those of the ESA TROPOspheric Monitoring Instrument (TROPOMI), provide higher-spatial-resolution remote sensing of atmospheric composition, but are limited by cloud cover and overpass times and report column-integrated quantities. Surface measurements, both from regulatory-grade monitors and low-cost networks, measure “nose-level” air quality, but may not represent concentration variability across large spatial domains, and (in the case of low-cost sensors) are subject to interference and biases. There exists a great potential to combine these diverse data sources together, using the strengths of some to offset the weaknesses of others to build a more comprehensive picture of air quality. This presentation will summarize results from ongoing efforts to produce such a combined forecast, with application case studies for surface-level Nitrogen Dioxide forecasting in several major US cities. Furthermore, we will examine the relative impacts and benefits of different data sources on the forecasting accuracy at different spatial and temporal scales. Finally, we will examine the potential for integrating low-cost sensors into such a system, both in terms of using these integrated air quality estimates as a baseline from which to calibrate networks of low-cost sensors in the field, and in terms of using dense networks of low-cost sensors to refine the spatial resolution of integrated air quality forecasts.

Air Quality↗

Runtime Analysis with R2U2: A Tool Exhibition Report

We present R2U2 (Realizable, Responsive, Unobtrusive Unit), a hardware- supported tool and framework for the continuous monitoring of safetycritical and embedded cyber-physical systems.With the widespread advent of autonomous systems such as Unmanned Aerial Systems (UAS), satellites, rovers, and cars, real-time, on-board decision making requires unobtrusive monitoring of properties for safety, performance, security, and system health. R2U2 models combine past-time and future-time Metric Temporal Logic, “mission time” Linear Temporal Logic, probabilistic reasoning with Bayesian Networks, and modelbased prognostics. The R2U2 monitoring engine can be instantiated as a hardware solution, running on an FPGA, or as a software component. The FPGA realization enables R2U2 to monitor complex cyber-physical systems without any overhead or instrumentation of the flight software. In this tool exhibition report, we present R2U2 and demonstrate applications on system runtime monitoring, diagnostics, software health management, and security monitoring for a UAS. Our tool demonstration uses a hardware-based processor-in-the-loop “iron-bird” configuration.

Johann Martin Schumann↗

Instrumentation and data acquisition systems

A comprehensive and integrated measurement system was identified and a design and development effort initiated to meet the criteria imposed by the National Transonic Facility operating environment. Specific measurement areas receiving concentrated attention include: data acquisition, force measurement, pressure instrumentation, flow visualization techniques, model attitude and model deformation measurement, and temperature measurement. The NTF instrument complex will be centered around four 32-bit, 1-microsecond-cycle-time central processing units connected in a multipoint-distributed network configuration. The principal activities to be supported by these computers are: (1) data base management and processing; (2) research measurement data acquisition and display; (3) tunnel and model control; and (4) process monitoring and communication control. The distributed network approach was chosen to modularize the functional software into definable and implementable parts by the various groups involved in the design and to permit use of similar hardware configurations to improve reliability and maintainability.

Guarino, J. F.↗

Clean Energy Cybersecurity Accelerator: Cohort 2 - runZero Public Report

The U.S. Department of Energy (DOE) Office of Cybersecurity, Energy Security, and Emergency Response (CESER) sponsors the Clean Energy Cybersecurity Accelerator™ (CECA) to expedite the deployment of emerging security technologies that address the most urgent security concerns facing modern and future electric grids. CECA Cohort 2 assessed solutions focused on hidden risks due to incomplete system visibility and device security and configuration. Improving visibility can be achieved through operational technology (OT) asset identification solutions, including capabilities like automatic discovery, vulnerability reporting, and configuration monitoring. Solutions that monitor and identify assets in information technology (IT) networks in other domains are widely used; however, there is far less adoption of monitoring solutions for operational technology environments. Wider adoption may increase with increased confidence in the ability for these solutions to understand and respond to the specific requirements of OT environments. CECA Cohort 2 evaluated the active and passive asset discovery capabilities of market-ready solutions, documented and analyzed results, and identified gaps in functionality or capabilities. This report and describes how these results can help advance the adoption of these and similar solutions in the electric sector.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Clean Energy Cybersecurity Accelerator: Cohort 2 - Asimily Public Report

The U.S. Department of Energy (DOE) Office of Cybersecurity, Energy Security, and Emergency Response (CESER) sponsors the Clean Energy Cybersecurity Accelerator (TM) (CECA) to expedite the deployment of emerging security technologies that address the most urgent security concerns facing modern and future electric grids. CECA Cohort 2 assessed solutions focused on hidden risks due to incomplete system visibility and device security and configuration. Improving visibility can be achieved through operational technology (OT) asset identification solutions, including capabilities like automatic discovery, vulnerability reporting, and configuration monitoring. Solutions that monitor and identify assets in information technology (IT) networks in other domains are widely used; however, there is far less adoption of monitoring solutions for operational technology environments. Wider adoption may increase with increased confidence in the ability for these solutions to understand and respond to the specific requirements of OT environments. CECA Cohort 2 evaluated the active and passive asset discovery capabilities of market-ready solutions, documented and analyzed results, and identified gaps in functionality or capabilities. This report and describes how these results can help advance the adoption of these and similar solutions in the electric sector.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Analyzing Risks of Virtual Private Network Connections

The use of Splunk for analyzing VPN logs is an effective approach for identifying vulnerabilities in network endpoints. Splunk, a powerful platform for searching, monitoring, and analyzing machine-generated data, enables organizations to aggregate VPN logs in real-time, providing insights into network activity, user behavior, and potential security risks. By indexing VPN traffic and authentication logs, security teams can track abnormal patterns such as multiple failed login attempts, unusual IP addresses, or unexpected changes in bandwidth usage, all of which could indicate potential vulnerabilities or breaches. With Splunk’s advanced search and reporting capabilities, users can create custom dashboards and alerts to detect suspicious activities. Automated searches can flag endpoints exhibiting unusual behavior, while correlation analysis can identify links between compromised devices and broader network vulnerabilities. In particular, Splunk's machine learning capabilities can be leveraged to predict and prevent threats by identifying trends that might otherwise be missed in traditional log analysis. This proactive approach to monitoring VPN logs allows for the early detection of security weaknesses, enabling rapid response and minimizing potential damage to network integrity. By enhancing endpoint visibility, Splunk plays a crucial role in securing remote connections and safeguarding sensitive information. Additionally, Splunk’s automation and alerting features allow teams to create custom workflows that notify them of vulnerable or misconfigured endpoints identified through Shodan. This synergy between Splunk’s log analysis and Shodan’s device intelligence enhances an organization’s ability to proactively identify and mitigate security risks, improving the overall resilience of their VPN infrastructure.

97 MATHEMATICS AND COMPUTING↗

Deep Space Network Antenna Logic Controller

The Antenna Logic Controller (ALC) software controls and monitors the motion control equipment of the 4,000-metric-ton structure of the Deep Space Network 70-meter antenna. This program coordinates the control of 42 hydraulic pumps, while monitoring several interlocks for personnel and equipment safety. Remote operation of the ALC runs via the Antenna Monitor & Control (AMC) computer, which orchestrates the tracking functions of the entire antenna. This software provides a graphical user interface for local control, monitoring, and identification of faults as well as, at a high level, providing for the digital control of the axis brakes so that the servo of the AMC may control the motion of the antenna. Specific functions of the ALC also include routines for startup in cold weather, controlled shutdown for both normal and fault situations, and pump switching on failure. The increased monitoring, the ability to trend key performance characteristics, the improved fault detection and recovery, the centralization of all control at a single panel, and the simplification of the user interface have all reduced the required workforce to run 70-meter antennas. The ALC also increases the antenna availability by reducing the time required to start up the antenna, to diagnose faults, and by providing additional insight into the performance of key parameters that aid in preventive maintenance to avoid key element failure. The ALC User Display (AUD) is a graphical user interface with hierarchical display structure, which provides high-level status information to the operation of the ALC, as well as detailed information for virtually all aspects of the ALC via drill-down displays. The operational status of an item, be it a function or assembly, is shown in the higher-level display. By pressing the item on the display screen, a new screen opens to show more detail of the function/assembly. Navigation tools and the map button allow immediate access to all screens.

Ahlstrom, Harlow↗

DroughtCast: A Machine Learning Forecast of the United States Drought Monitor

Drought is one of the most ecologically and economically devastating natural phenomena affecting the United States, causing the U.S. economy billions of dollars in damage, and driving widespread degradation of ecosystem health. Many drought indices are implemented to monitor the current extent and status of drought so stakeholders such as farmers and local governments can appropriately respond. Methods toforecast drought conditions weeks to months in advance are less common but would provide a more effective early warning system to enhance drought response, mitigation, and adaptation planning. To resolve this issue, we introduce DroughtCast, a machine learning framework for forecasting the United States Drought Monitor (USDM). DroughtCast operates on the knowledge that recent anomalies in hydrology and meteorology drive future changes in drought conditions. We use simulated meteorology and satellite observed soil moisture as inputs into a recurrent neural network to accurately forecast the USDM between 1 and 12 weeks into the future. Our analysis shows that precipitation, soil moisture, and temperature are the most important input variables when forecasting future drought conditions. Additionally, a case study of the 2017 Northern Plains Flash Drought shows that DroughtCast was able to forecast a very extreme drought event up to 12 weeks before its onset. Given the favorable forecasting skill of the model, DroughtCast may provide a promising tool for land managers and local governments in preparing for and mitigating the effects of drought.

Machine Learning↗