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NASA NTRS2007

Improving Public Health DSSs by Including Saharan Dust Forecasts Through Incorporation of NASA's GOCART Model Results

Approximately 2-3 billion metric tons of soil dust are estimated to be transported in the Earth's atmosphere each year. Global transport of desert dust is believed to play an important role in many geochemical, climatological, and environmental processes. This dust carries minerals and nutrients, but it has also been shown to carry pollutants and viable microorganisms capable of harming human, animal, plant, and ecosystem health. Saharan dust, which impacts the eastern United States (especially Florida and the southeast) and U.S. Territories in the Caribbean primarily during the summer months, has been linked to increases in respiratory illnesses in this region and has been shown to carry other human, animal, and plant pathogens. For these reasons, this candidate solution recommends integrating Saharan dust distribution and concentration forecasts from the NASA GOCART global dust cycle model into a public health DSS (decision support system), such as the CDC's (Centers for Disease Control and Prevention's) EPHTN (Environmental Public Health Tracking Network), for the eastern United States and Caribbean for early warning purposes regarding potential increases in respiratory illnesses or asthma attacks, potential disease outbreaks, or bioterrorism. This candidate solution pertains to the Public Health National Application but also has direct connections to Air Quality and Homeland Security. In addition, the GOCART model currently uses the NASA MODIS aerosol product as an input and uses meteorological forecasts from the NASA GEOS-DAS (Goddard Earth Observing System Data Assimilation System) GEOS-4 AGCM. In the future, VIIRS aerosol products and perhaps CALIOP aerosol products could be assimilated into the GOCART model to improve the results.

Berglund, Judith↗

NASA NTRSDate not supplied

Introduction to our COSPAR-Sponsored Session: Space-Observation Contributions Supporting Climate Action

• The challenge for us at COSPAR in putting this program together was that we are primarily a scientifically oriented organization. “Climate Action,” as it is often expressed publicly, tends to be the domain of “activists.” As scientists, on the other hand, to retain our credibility – and for the contributions we make to continue carrying the weight of scientific truth – it is critical that we remain even-handed in our analysis and our reporting of results. • COSPAR is the Committee on Space Research, and fortunately, much of what we observe from space bears objectively on the attributes of the Earth System and how it is evolving. We can measure from space changes in the cryosphere, in the oceans, the land surface and the atmosphere, frequently, on a global scale, to a degree that is generally not possible any other way. And we have been making such observations, in increasing detail, scope, and precision, for about 60 years. • These data help us characterize the current state and identify patterns of change in the Earth System that allow us to infer processes and to improve climate models. With modeling we can test and refine our inferences, and make some predictions. The results can then inform policy and decision-makers, the public in general, as well as those taking direct action. • So, for today’s session we have invited 7 15-minute presentations spanning a broad range of climate-related topics, covering observations from space that can inform climate-related decision-making – from sea-ice extent and sea-level rise, to land surface properties and land-based water resources, to interactions between land or water surfaces and the atmosphere, to severe events in the atmosphere itself. • We begin with an overview of the observations contributed by one of the premier space agencies, given by NASA Chief Scientist and Senior Climate Advisor Dr. Kate Calvin, which will be followed by talks on what we are learning about specific attributes of the Earth System from space-based measurements that can inform climate-related policy and action.

Ralph Kahn↗

NASA NTRS1991

Modeling multi-frequency diurnal backscatter from a walnut orchard

The Michigan Microwave Canopy Scattering Model (MIMICS) is used to model scatterometer data that were obtained during the August 1987 EOS (Earth Observing System) synergism study. During this experiment, truck-based scatterometers were used to measure radar backscatter from a walnut orchard in Fresno County, California. Multipolarized L- and X-band data were recorded for orchard plots for which dielectric and evapotranspiration characteristics were monitored. MIMICS is used to model a multiangle data set in which a single orchard plot was observed at varying impedance angles and a series of diurnal measurements in which backscatter from this same plot was measured continuously over several 24-h periods. MIMICS accounts for variations in canopy backscatter driven by changes in canopy state that occur diurnally as well as on longer time scales. L-band backscatter is dependent not only on properties of the vegetation but also on properties of the underlying soil surface. The behavior of the X-band backscatter is dominated by properties of the tree crowns.

Mcdonald, Kyle C.↗

NASA NTRS2013

Sabots, Obturator and Gas-In-Launch Tube Techniques for Heat Flux Models in Ballistic Ranges

For thermal protection system (heat shield) design for space vehicle entry into earth and other planetary atmospheres, it is essential to know the augmentation of the heat flux due to vehicle surface roughness. At the NASA Ames Hypervelocity Free Flight Aerodynamic Facility (HFFAF) ballistic range, a campaign of heat flux studies on rough models, using infrared camera techniques, has been initiated. Several phenomena can interfere with obtaining good heat flux data when using this measuring technique. These include leakage of the hot drive gas in the gun barrel through joints in the sabot (model carrier) to create spurious thermal imprints on the model forebody, deposition of sabot material on the model forebody, thereby changing the thermal properties of the model surface and unknown in-barrel heating of the model. This report presents developments in launch techniques to greatly reduce or eliminate these problems. The techniques include the use of obturator cups behind the launch package, enclosed versus open front sabot designs and the use of hydrogen gas in the launch tube. Attention also had to be paid to the problem of the obturator drafting behind the model and impacting the model. Of the techniques presented, the obturator cups and hydrogen in the launch tube were successful when properly implemented

obturators↗

NASA NTRSDate not supplied

Agile Satellite Planning for Multi-Payload Observations in Earth Science Models

We present the planner methods and preliminary results for a new paradigm of earth observing systems based on coordinating science observations for a constellation of agile satellites which can quickly maneuver to change viewing angles. Each satellite has multiple heterogeneous instruments.

Satellite Constellation↗

NASA NTRS2005

Business Intelligence Modeling in Launch Operations

This technology project is to advance an integrated Planning and Management Simulation Model for evaluation of risks, costs, and reliability of launch systems from Earth to Orbit for Space Exploration. The approach builds on research done in the NASA ARC/KSC developed Virtual Test Bed (VTB) to integrate architectural, operations process, and mission simulations for the purpose of evaluating enterprise level strategies to reduce cost, improve systems operability, and reduce mission risks. The objectives are to understand the interdependency of architecture and process on recurring launch cost of operations, provide management a tool for assessing systems safety and dependability versus cost, and leverage lessons learned and empirical models from Shuttle and International Space Station to validate models applied to Exploration. The systems-of-systems concept is built to balance the conflicting objectives of safety, reliability, and process strategy in order to achieve long term sustainability. A planning and analysis test bed is needed for evaluation of enterprise level options and strategies for transit and launch systems as well as surface and orbital systems. This environment can also support agency simulation .based acquisition process objectives. The technology development approach is based on the collaborative effort set forth in the VTB's integrating operations. process models, systems and environment models, and cost models as a comprehensive disciplined enterprise analysis environment. Significant emphasis is being placed on adapting root cause from existing Shuttle operations to exploration. Technical challenges include cost model validation, integration of parametric models with discrete event process and systems simulations. and large-scale simulation integration. The enterprise architecture is required for coherent integration of systems models. It will also require a plan for evolution over the life of the program. The proposed technology will produce long-term benefits in support of the NASA objectives for simulation based acquisition, will improve the ability to assess architectural options verses safety/risk for future exploration systems, and will facilitate incorporation of operability as a systems design consideration, reducing overall life cycle cost for future systems. The future of business intelligence of space exploration will focus on the intelligent system-of-systems real-time enterprise. In present business intelligence, a number of technologies that are most relevant to space exploration are experiencing the greatest change. Emerging patterns of set of processes rather than organizational units leading to end-to-end automation is becoming a major objective of enterprise information technology. The cost element is a leading factor of future exploration systems.

Bardina, Jorge E.↗

NASA NTRS1994

Simulation of interference between Earth stations and Earth-orbiting satellites

It is often desirable to determine the potential for radio frequency interference between earth stations and orbiting spacecraft. This information can be used to select frequencies for radio systems to avoid interference or it can be used to determine if coordination between radio systems is necessary. A model is developed that will determine the statistics of interference between earth stations and elliptical orbiting spacecraft. The model uses orbital dynamics, detailed antenna patterns, and spectral characteristics to obtain accurate levels of interference at the victim receiver. The model is programmed into a computer simulation to obtain long-term statistics of interference. Two specific examples are shown to demonstrate the model. The first example is a simulation of interference from a fixed-satellite earth station to an orbiting scatterometer receiver. The second example is a simulation of interference from earth-exploration satellites to a deep-space earth station.

Bishop, D. F.↗

NASA NTRS2009

Integrating and Visualizing Tropical Cyclone Data Using the Real Time Mission Monitor

The Real Time Mission Monitor (RTMM) is a visualization and information system that fuses multiple Earth science data sources, to enable real time decision-making for airborne and ground validation experiments. Developed at the NASA Marshall Space Flight Center, RTMM is a situational awareness, decision-support system that integrates satellite imagery, radar, surface and airborne instrument data sets, model output parameters, lightning location observations, aircraft navigation data, soundings, and other applicable Earth science data sets. The integration and delivery of this information is made possible using data acquisition systems, network communication links, network server resources, and visualizations through the Google Earth virtual globe application. RTMM is extremely valuable for optimizing individual Earth science airborne field experiments. Flight planners, scientists, and managers appreciate the contributions that RTMM makes to their flight projects. A broad spectrum of interdisciplinary scientists used RTMM during field campaigns including the hurricane-focused 2006 NASA African Monsoon Multidisciplinary Analyses (NAMMA), 2007 NOAA-NASA Aerosonde Hurricane Noel flight, 2007 Tropical Composition, Cloud, and Climate Coupling (TC4), plus a soil moisture (SMAP-VEX) and two arctic research experiments (ARCTAS) in 2008. Improving and evolving RTMM is a continuous process. RTMM recently integrated the Waypoint Planning Tool, a Java-based application that enables aircraft mission scientists to easily develop a pre-mission flight plan through an interactive point-and-click interface. Individual flight legs are automatically calculated "on the fly". The resultant flight plan is then immediately posted to the Google Earth-based RTMM for interested scientists to view the planned flight track and subsequently compare it to the actual real time flight progress. We are planning additional capabilities to RTMM including collaborations with the Jet Propulsion Laboratory in the joint development of a Tropical Cyclone Integrated Data Exchange and Analysis System (TC IDEAS) which will serve as a web portal for access to tropical cyclone data, visualizations and model output.

Goodman, H. Michael↗

NASA NTRSDate not supplied

Simulation of the Aerosol Size Distribution Using a Neural Network Surrogate for the Modal Aerosol Module (MAM7)

One objective of atmospheric simulations is to quantify the distribution of aerosols and their properties. Accurate parameterizations of the processes governing aerosol mass, particle number, and particle size distribution are important for predicting the Earth’s net radiative balance and aerosol-cloud interactions. The Modal Aerosol Module (MAM7) is a two-moment aerosol model that simulates mass, number, and size distribution of seven modes comprised of internally mixed aerosol species. The two-moment scheme adds significant computational expense but allows for the prediction of varying particle size distribution relative to the bulk method which predicts only total mass. In this work, we developed a neural network surrogate model for MAM7 (MAMnet) to predict the aerosol number concentration in NASA’s Global Earth Observing System (GEOS) without adding prohibitive computational expense. MAMnet, can be driven by output from a single moment, mass-based, aerosol scheme (Goddard Chemistry Aerosol and Radiation model (GOCART)) or from reanalysis products (Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2)). MAMnet was trained using number concentrations from a 5-year GEOS/MAM7 simulation at 1-degree horizontal resolution and using the total mass calculated across modes as inputs, as well as temperature and air density. The model architecture for MAMnet was based on AlexNet, the 2012 winner of the ImageNet Large Scale Visual Recognition Challenge. While some modifications were necessary to accommodate our problem, important aspects of the network were preserved. MAMnet was able to reproduce zonal dynamics and spatial distributions of the aerosol number concentration however predictability in the upper troposphere was poor.

Katherine H Breen↗

NASA NTRS2013

On the Performance of Global Magnetohydrodynamic Models in the Earth's Magnetosphere

We study the performance of four magnetohydrodynamic models (BATS-R-US, GUMICS, LFM, Open GGCM) in the Earths magnetosphere. Using the Community Coordinated Modeling Centers Run-on-Request system, we compare model predictions with magnetic field measurements of the Cluster, Geotail and Wind spacecraft during a multiple substorm event. We also compare model cross polar cap potential results to those obtained from the Super Dual Auroral Radar Network(SuperDARN) and the model magnetopause standoff distances to an empirical magnetopause model. The correlation coefficient (CC) and prediction efficiency (PE) metrics are used to objectively evaluate model performance quantitatively. For all four models, the best performance outside geosynchronous orbit is found on the dayside. Generally, the performance of models decreases steadily down stream from the Earth. On the dayside most CCs are above 0.5 with CCs for Bx and Bz close to 0.9 for three out of four models. In the magnetotail at a distance of about -130 Earth radii from Earth, the prediction efficiency of all models is below that of using an average value for the prediction with the exception of Bz. Bx is most often best predicted and correlated both on the dayside and the nightside close to the Earth whereas in the far tail the CC and PE for Bz are substantially higher than other components in all models. We also find that increasing the resolution or coupling an additional physics module does notautomatically increase the model performance in the magnetosphere.

geomagnetic tail↗

NASA NTRSDate not supplied

Particle-Based Fiber Models of Woven Materials for Earth Entry Thermal Protection

Applications requiring materials with layer-to-layer strength, from basketry to thermal protection systems, use interlaced, three-dimensional woven materials. NASA is developing and deploying woven material heat shields for missions, including Artemis I (3D-MAT for compression pads) and potentially Mars Sample Return - Earth Entry System. These materials are complex, hierarchical and must protect from extreme environments and phenomena, such as deformation, impact and high-enthalpy heating. Woven material performance depends on microstructure, damage and weave geometry. Therefore, fiber-specific models are needed to simulate fiber contacts within the weave hierarchical geometry (fiber to tow to yarn to weave) and the inherent directionality of fibers. Explicit fiber models can simulate how weave microstructure evolution affects thermal and mechanical properties. We parameterize a discrete element bonded particle models (DEM-BPM) of fibers to capture thermal and mechanical behavior within and between fibers, with bonded and contact forces, respectively. We study the proportion of heat transfer and stress via the contact network, fiber bonds and the weave geometry, for example, with respect to yarn warp-weft identity (whether it interlaces weave layers). Our results demonstrate the importance of explicit fiber modeling for connecting microstructure with thermal and mechanical properties.

woven material↗

NASA NTRSDate not supplied

Particle-Based Fiber Models of Woven Materials for Earth Entry Thermal Protection

woven material↗

NASA NTRS2000

The Distribution of Carbon Monoxide in the GOCART Model

Carbon monoxide (CO) is an important trace gas because it is a significant source of tropospheric Ozone (O3) as well as a major sink for atmospheric hydroxyl radical (OH). The distribution of CO is set by a balance between the emissions, transport, and chemical processes in the atmosphere. The Georgia Tech/Goddard Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) model is used to simulate the atmospheric distribution of CO. The GOCART model is driven by the assimilated meteorological data from the Goddard Earth Observing System Data Assimilation System (GEOS DAS) in an off-line mode. We study the distribution of CO on three time scales: (1) day to day fluctuation produced by the synoptic waves; (2) seasonal changes due to the annual cycle of CO sources and sinks; and (3) interannual variability induced by dynamics. Comparison of model results with ground based and remote sensing measurements will also be presented.

Fan, Xiaobiao↗

NASA NTRS2014

The Status of Spacecraft Bus and Platform Technology Development Under the NASA ISPT Program

The In-Space Propulsion Technology (ISPT) program is developing spacecraft bus and platform technologies that will enable or enhance NASA robotic science missions. The ISPT program is currently developing technology in three areas that include Propulsion System Technologies, Entry Vehicle Technologies, and Systems Mission Analysis. ISPTs propulsion technologies include: 1) NASAs Evolutionary Xenon Thruster (NEXT) ion propulsion system, a 0.6-7 kW throttle-able gridded ion system; 2) a Hall-effect electric propulsion (HEP) system for sample return and low cost missions; 3) the Advanced Xenon Flow Control System (AXFS); ultra-lightweight propellant tank technologies (ULTT); and propulsion technologies for a Mars Ascent Vehicle (MAV). The AXFS and ULTT are two component technologies being developed with nearer-term flight infusion in mind, whereas NEXT and the HEP are being developed as EP systems. ISPTs entry vehicle technologies are: 1) Aerocapture technology development with investments in a family of thermal protection system (TPS) materials and structures; guidance, navigation, and control (GNC) models of blunt-body rigid aeroshells; and aerothermal effect models; and 2) Multi-mission technologies for Earth Entry Vehicles (MMEEV) for sample return missions. The Systems Mission Analysis area is focused on developing tools and assessing the application of propulsion, entry vehicle, and spacecraft bus technologies to a wide variety of mission concepts. Several of the ISPT technologies are related to sample return missions and other spacecraft bus technology needs like: MAV propulsion, MMEEV, and electric propulsion. These technologies, as well as Aerocapture, are more vehicle and mission-focused, and present a different set of technology development challenges. These in-space propulsion technologies are applicable, and potentially enabling for future NASA Discovery, New Frontiers, Flagship and sample return missions currently under consideration. This paper provides a brief overview of the ISPT program, describing the development status and technology infusion readiness.

electric propulsion↗

NASA NTRS2019

Analyzing Machine Learning Predictions of Passive Microwave Brightness Temperature Spectral Difference Over Snow-Covered Terrain in High Mountain Asia

Snow is an important component of the terrestrial freshwater budget in high mountainAsia (HMA) and contributes to the runoff in Himalayan rivers through snowmelt. Despitethe importance of snow in HMA, considerable spatiotemporal uncertainty exists across the different estimates of snow water equivalent for this region. In order to better estimate snow water equivalent, radiative transfer models are often used in conjunction with microwave brightness temperature measurements. In this study, the efficacy of support vector machines (SVMs), a machine learning technique, to predict passive microwave brightness temperature spectral difference (1Tb) as a function of geophysical variables (snow water equivalent, snow depth, snow temperature, and snow density) is explored through a sensitivity analysis. The use of machine learning (as opposed to radiative transfer models) is a relatively new and novel approach for improving snow water equivalent estimates. The Noah-MP land surface model within the NASALand Information System framework is used to simulate the hydrologic cycle over HMA and model geophysical variables that are then used for SVM training. The SVMsserve as a nonlinear map between the geophysical space (modeled in Noah-MP) andthe observation space (1Tb as measured by the radiometer). Advanced MicrowaveScanning Radiometer-Earth Observing System measured passive microwave brightness temperatures over snow-covered locations in the HMA region are used as training data during the SVM training phase. Sensitivity of well-trained SVMs to each Noah-MP modeled state variable is assessed by computing normalized sensitivity coefficients. Sensitivity analysis results generally conform with the known first-order physics. Input states that increase volume scattering of microwave radiation, such as snow density and snow water equivalent, exhibit a plurality of positive normalized sensitivity coefficients. In general, snow temperature was the most sensitive input to the SVM predictions. The sensitivity of each state is location and time dependent. The signs of normalized sensitivity coefficients that indicate physical irrationality are ascribed to significant cross-correlation between Noah-MP simulated states and decreased SVM prediction capability at specific locations due to insufficient training data. SVM prediction pitfalls do exist that serve to highlight the limitations of this particular machine learning algorithm.

high mountain Asia↗

NASA NTRS2012

Understanding Climate Policy Data Needs. NASA Carbon Monitoring System Briefing: Characterizing Flux Uncertainty, Washington D.C., 11 January 2012

Climate policy in the United States is currently guided by public-private partnerships and actions at the local and state levels. This mitigation strategy is made up of programs that focus on energy efficiency, renewable energy, agricultural practices and implementation of technologies to reduce greenhouse gases. How will policy makers know if these strategies are working, particularly at the scales at which they are being implemented? The NASA Carbon Monitoring System (CMS) will provide information on carbon dioxide fluxes derived from observations of earth's land, ocean and atmosphere used in state of the art models describing their interactions. This new modeling system could be used to assess the impact of specific policy interventions on CO2 reductions, enabling an iterative, results-oriented policy process. In January of 2012, the CMS team held a meeting with carbon policy and decision makers in Washington DC to describe the developing modeling system to policy makers. The NASA CMS will develop pilot studies to provide information across a range of spatial scales, consider carbon storage in biomass, and improve measures of the atmospheric distribution of carbon dioxide. The pilot involves multiple institutions (four NASA centers as well as several universities) and over 20 scientists in its work. This pilot study will generate CO2 flux maps for two years using observational constraints in NASA's state-of -the-art models. Bottom-up surface flux estimates will be computed using data-constrained land and ocean models; comparison of the different techniques will provide some knowledge of uncertainty in these estimates. Ensembles of atmospheric carbon distributions will be computed using an atmospheric general circulation model (GEOS-5), with perturbations to the surface fluxes and to transport. Top-down flux estimates will be computed from observed atmospheric CO2 distributions (ACOS/GOSAT retrievals) alongside the forward-model fields, in conjunction with an inverse approach based on the CO2 model of GEOS ]Chem. The forward model ensembles will be used to build understanding of relationships among surface flux perturbations, transport uncertainty and atmospheric carbon concentration. This will help construct uncertainty estimates and information on the true spatial resolution of the top-down flux calculations. The relationship between the top-down and bottom-up flux distributions will be documented. Because the goal of NASA CMS is to be policy relevant, the scientists involved in the flux modeling pilot need to understand and be focused on the needs of the climate policy and decision making community. If policy makers are to use CMS products, they must be aware of the modeling effort and begin to design policies that can be evaluated with information. Improving estimates of carbon sequestered in forests, for example, will require information on the spatial variability of forest biomass that is far more explicit than is presently possible using only ground observations. Carbon mitigation policies being implemented by cities around the United States could be designed with the CMS data in mind, enabling sequential evaluation and subsequent improvements in incentives, structures and programs. The success of climate mitigation programs being implemented in the United States today will hang on the depth of the relationship between scientists and their policy and decision making counterparts. Ensuring that there is two-way communication between data providers and users is important for the success both of the policies and the scientific products meant to support them..

Brown, Molly E.↗

NASA NTRS2011

Wallops' Low Elevation Link Analysis for the Constellation Launch/Ascent Links

Prior to the redirection of the Constellation Program, the Wallops 11.3-meter ground station was tasked to support the Orion's Dissimilar Voice (DV) link and the Ares's Development Flight Instrument (DFI) link. Detailed analysis of the launch trajectories indicates that during the launch and ascent operation, the critical events of Orion-Ares main engine cut off (MECO) and Separation occur at low elevation angle. We worked with engineers from both Wallops Flight Facility (WFF) and Johnson Space Center (JSC) to perform an intensive measurement and link analysis campaign on the DV and DFI links. The main results were as follows: (1) The DV links have more than 3 dB margin at MECO and Separation. (2) The DFI links have 0 dB margin at Separation during certain weather condition in summer season. (3) Tropospheric scintillation loss is the major impairment at low elevation angle. (4) The current scintillation models in the Recommendation ITU-R P.618 (Propagation data and prediction methods required for the design of Earth-space telecommunication systems), which are based on limited experimental and theoretical work, exhibit idiosyncratic behaviors. We developed an improved model based on the measurements of recent Shuttle mission launch and ascent links and the ITU propagation data. (5) Due to the attitude uncertainty of the Orion-Ares stack, the high dynamics of the launch and ascent trajectory, and the irregularity of the Orion and Ares antenna patterns, we employed new link analysis approach to model the spacecraft antenna gain. In this paper we discuss the details of the aforementioned results.

Cheung, Kar-Ming↗

NASA NTRS2012

Availability Estimation for Facilities in Extreme Geographical Locations

A value added analysis for the Reliability. Availability and Maintainability of McMurdo Ground Station was developed, which will be a useful tool for system managers in sparing, maintenance planning and determining vital performance metrics needed for readiness assessment of the upgrades to the McMurdo System. Output of this study can also be used as inputs and recommendations for the application of Reliability Centered Maintenance (RCM) for the system. ReliaSoft's BlockSim. a commercial Reliability Analysis software package, has been used to model the availability of the system upgrade to the National Aeronautics and Space Administration (NASA) Near Earth Network (NEN) Ground Station at McMurdo Station in the Antarctica. The logistics challenges due to the closure of access to McMurdo Station during the Antarctic winter was modeled using a weighted composite of four Weibull distributions. one of the possible choices for statistical distributions throughout the software program and usually used to account for failure rates of components supplied by different manufacturers. The inaccessibility of the antenna site on a hill outside McMurdo Station throughout one year due to severe weather was modeled with a Weibull distribution for the repair crew availability. The Weibull distribution is based on an analysis of the available weather data for the antenna site for 2007 in combination with the rules for travel restrictions due to severe weather imposed by the administrating agency, the National Science Foundation (NSF). The simulations resulted in an upper bound for the system availability and allowed for identification of components that would improve availability based on a higher on-site spare count than initially planned.

Fischer, Gerd M.↗