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NASA NTRS2023

Commercial Smallsat Data Acquisition Program On-ramp #2 Airbus U.S. Synthetic Aperture Radar (SAR) Evaluation Report

In 2017, NASA’s Earth Science Division (ESD) launched the Private-Sector Small Constellation Satellite Data Product Pilot, now referred to as the Commercial Smallsat Data Acquisition (CSDA) program. The objective of CSDA is to identify, evaluate, and acquire commercial remote sensing data that support NASA’s Earth science research and application activities. The Pilot successfully concluded in early 2020, when CSDA transitioned into a sustained program with on-ramping opportunities for new vendors as the industry emerges with new candidates and capabilities. In October 2019, a Request for Information (RFI) seeking capability statements from parties interested in providing data from spaceborne platforms was released for the CSDA on-ramp #2 evaluations. To be responsive to the RFI, the commercial satellite constellations had to consist of three or more operating spacecraft actively collecting data in a non-geostationary orbit with full latitudinal coverage and be U.S. companies. Two vendors responded to the RFI and were evaluated by a committee composed of NASA ESD leadership, program managers, and scientists. Both vendors satisfied the RFI requirements and were asked to respond to a Request for Proposal (RFP). After review of the proposals, NASA entered into a Blanket Purchase Agreement (BPA) with Airbus Defense and Space GEO, Inc. (Airbus) U.S. in September 2021 and with BlackSky Geospatial Solutions, Inc. (BlackSky) in November 2021. In this report, CSDA provides an evaluation of the usefulness of data provided by the Airbus U.S. Synthetic Aperture Radar (SAR) satellite constellation, consisting of TerraSAR-X (launched in 2007), TanDEM-X (launched in 2010), and PAZ (launched in 2018), for advancing NASA’s Earth system science research and applications. The evaluation of the BlackSky commercial data will be provided in a separate report. To conduct the Airbus evaluation, NASA’s ESD augmented 13 existing research projects that could potentially benefit from, and had the expertise to evaluate, the commercial data being considered for longer-term purchase. Investigators from NASA’s Research and Analysis Program science focus areas and from NASA’s Applied Sciences Program elements participated in the evaluation. A summary of the research areas evaluated by the Principal Investigator (PI) teams is presented in Figure 3. CSDA also funded a dedicated activity to evaluate the satellite data quality (calibration and geolocation) independently by assessing the accuracy of data from Airbus. Evaluation activities were carried out by the selected PIs from December 7, 2022, to December 7, 2023. Delivery of datasets requested by the researchers began in January 2023. The vendors were evaluated on the accessibility of data, accuracy and completeness of metadata, and promptness and quality of user support services. Datasets purchased during the evaluation have been archived by NASA and will be made available to current and future government-funded researchers in accordance with the End User License Agreement (EULA). This synthesis report distills and integrates the findings of research reports commissioned by NASA for the Airbus evaluation. This report also includes recommendations that inform the way ahead for the program. The scientific results from the evaluations demonstrated that the commercial data from Airbus were able to advance NASA research and applications. However, the PIs encountered limitations that diminished the usefulness of the data due to the amount of effort that was required to access, preprocess, and analyze these data. One significant issue encountered was the limited spatial and temporal coverage of the data in the Airbus archive that could be used to conduct time series analyses or assessments over large spatial scales. Overall, however, the utility and the quality of the evaluated data outweighed the difficulties encountered, and NASA has concluded that the Airbus SAR data would complement NASA’s existing Earth observation capabilities and Airbus U.S. would qualify to participate in the sustained phase of the program.

Batuhan Osmanoglu↗

NASA NTRSDate not supplied

Assessment of High Resolution Commercial Satellite Geolocation Accuracy

Commercial companies such as Maxar, PlanetScope, and BlackSky have launched many satellites with revisit times ranging from two hours to one day and have built large archives of high resolution (1-3 m) Earth observing data. The high temporal resolution and global coverage of these satellites makes commercial satellite images ideal for scientists studying rapidly changing processes such as flooding and fires. A key step in assessing changes in these images is co-registration of various images to each other. High geolocation accuracy (at most 0.5 pixels of offset) allows for easy co-registration of images across different times and sensors. Here, we assess the latest PlanetScope imagery and evaluate it for geolocation accuracy. For our assessment, we compare the target image to a reference image with known geolocation accuracy (WorldView imagery) and determine the offset between these images by shifting them to maximize their Pearson Cross-Correlation (PCC) value. Offsets required to maximize the PCC give the geolocation accuracy of the target image relative to the reference image. Previously, our global assessment of Planet data revealed large variability in geolocation accuracy from one continent to another. The measured root mean squared errors (RMSEs) range from 5.4 m in North America to 14.9 m in Africa. We have updated this previous assessment to include both their newest SuperDove series as well as a more robust assessment of the temporal stability of PlanetScope's geolocation accuracy.

Alana G. Semple↗

NASA NTRS1994

Calculation of clear-sky outgoing longwave radiation using ECMWF gridded fields and ISCCP C1 cloud data

Clear-Sky OLR (outgoing longwave radiation) has a variety of definitions. Clear-sky OLR can be measured from satellites by examining the data to detect clouds, eliminating those observations that are contaminated with clouds, and averaging the remaining data. The disadvantage of this method is that satellites do not provide time continuous coverage, requiring many observations and careful analysis to remove sampling biases. Alternatively, clear-sky OLR can be found continuously using a radiative flux code, combined with analyzed fields of temperature, humidity and clouds, either from assimilated observations or a GCM simulation. The disadvantage is that the cloud field is typically very low resolution, on the order of 200 km, so they lack important small scale cloud detail. Even if fractional clouds data is available, it is not obvious how GCM and ERBE results should be compared. The purpose of this study is to assess clear-sky OLR calculated from these methods using available data. Cloud data from ISCCP provides the fractional cloud coverage data necessary to test these methods against calculations based on observed data. Clear-sky OLR is calculated using the ECMWF/TOGA archive. Monthly averages are made in the manner of the several methods listed above and compared to each other and to ERBE.

Ramsey, Perry G.↗

NASA NTRS1991

Satellite orbit considerations for a global change technology architecture trade study

A study was conducted to determine satellite orbits for earth observation missions aimed at obtaining data for assessing data global climate change. A multisatellite system is required to meet the scientific requirements for temporal coverage over the globe. The best system consists of four sun-synchronous satellites equally spaced in local time of equatorial crossing. This system can obtain data every three hours for all regions. Several other satellite systems consisting of combinations of sun-synchronous orbits and either the Space Station Freedom or a mid-altitude equatorial satellite can provide three to six hour temporal coverage, which is sufficient for measuring many of the parameters required for the global change monitoring mission. Geosynchronous satellites are required to study atmospheric and surface processes involving variations on the order of a few minutes to an hour. One or two geosynchronous satellites can be relocated in longitude to study processes over selected regions of earth.

Harrison, Edwin F.↗

NASA NTRS1978

RF coverage analysis and performance for Shuttle communication links

This paper describes the current work at NASA/Johnson Space Center in the area of RF coverage analysis and performance-assessment for the Space Shuttle Program communication and tracking radio links. Trajectories, antenna data, ground station and Shuttle hardware performance characteristics and RF link math models were assimilated to generate RF link performance predictions for the three basic mission phases - ascent, on-orbit, and descent. Results identify some earlier deficiencies that required re-configuration of the ground station. Overall performance is currently satisfactory.

Loh, Y.-C.↗

NASA NTRS2022

Global Landslide Forecasting System for Hazard Assessment and Situational Awareness

Landslides triggered by extreme rainfall can be devastating, resulting in loss of life, property, and infrastructure. Landslide forecasting systems provide an opportunity to build awareness of potential hazards and ultimately take preemptive measures. There is currently a dearth of forecasting systems that provide regional or global coverage, but these systems can offer important situational awareness in data-sparse, ungauged, or large-scale catchments. A near global, primarily satellite-based system calledthe Landslide Hazard Assessment for Situational Awareness (LHASA) provides near real-time estimates of potential landslide hazard and exposure around the world. In this work, a precipitation forecast module is introduced into LHASA to complement the existing LHASA framework and provide an estimate of landslide hazard up to three days in advanceat 1km resolution. The model-based Goddard Earth Observing System-Forward Processing (GEOS-FP) precipitation forecast product is used as the forcing input for the model in place of the satellite-based Integrated Multi-satellitE Retrievals for Global Precipitation Mission product. Soil moisture and snow depth from the GEOS-FP assimilated product are also incorporated. The study period January 2020–January 2021 is usedto test the model performance against the LHASA near real-time estimates at multiple spatiotemporal scales. Validation of the model is carried out using a collection of rainfall-triggered landslide inventories from around the world as case studies to demonstrate the potential utility and limitations of this system.The rescaling of the GEOS-FP precipitation product is a critical step in incorporating the forecasted precipitation data within LHASA-Forecast (LHASA-F). Combining different streams of forecasted data within the LHASA-F framework shows promise, particularly for larger events at the 1-and 2-day lead time for events. Results indicate that for the case studies evaluated, the LHASA-F is generally able to resolve major landslide events triggered by extreme rainfall, such as from tropical cyclones. The analysis shows that landslide forecast outputs may be represented differently depending on the user’s needs. This framework serves as a first milestone in providing a global predictive view of landslide hazard.

Landslide forecasting system↗

NASA NTRSDate not supplied

Geometric Assessment of PlanetScope Imagery

Commercial companies such as Maxar, Planet Labs, and BlackSky have built large archives of high resolution (1-3 m) Earth observing data. The high temporal resolution and global coverage of these satellites makes commercial satellite images ideal for scientists studying rapidly changing processes such as flooding and fires. The high spatial resolution allows scientists to push studies to a fine scale such as monitoring agricultural growth experiments or detecting vehicles for traffic management. Scientists using these data need to know geolocation accuracy, band-to-band registration (BBR), and pixel footprint size to best determine appropriate applications as well as what extra steps they will need to take to use the data. Here, we find those key geometric properties for images from Planet Labs’ SuperDove constellation. Geolocation accuracy is assessed relative to WorldView images at globally distributed cities, band-to-band registration (BBR) is examined for every image we acquired (200+ images), and pixel footprint sizes are calculated from edge responses of the images over Cal/Val sites in China, India, or USA both near launch time and 1+ years after launch. We find that SuperDove geolocation is highly self-consistent with average global offsets among SuperDove images of 3.80 m (1.27 pixels). Despite this self-consistency, relative geolocation accuracy (with WorldView images as reference) varies by location from 3.20 m – 28.09 m mean offset. SuperDove BBR is sub-pixel and varies by band, with a mean radial offset relative to red band varying from 0.39 - 1.13 m. SuperDove image footprint size improves after 1+ years in orbit, with an average footprint size of 3.41 pixels (10.24 m) soon after launch and 3.23 pixels (9.7 m) 1+ years after launch. The BBR and self-consistency offsets are relatively small, given the large footprint sizes. A similarly extensive investigation is in progress for Planet Labs’ Dove-R series.

Alana G. Semple↗

NASA NTRS2003

Airborne Radar Study of Mars Analogs in the Southwestern United States

The search for surface and near-surface liquid water on Mars is a central part of current and planned future exploration, which include radar sounders on Mars Express and MRO and proposed synthetic aperture radar (SAR) imagers. In order to penetrate sand and dust cover, these systems are proposed for longer wavelengths (e.g, from [2]: 24 cm / L-band and 74 cm / P-band) than those considered optimal for the detection of soil moisture (6 cm / C-band). However, there has been some success in detecting soil moisture at longer wavelengths. Given the size and mass constraints for Mars missions, the optimization of radar instrument parameters for meeting science objectives, such as searching for liquid water, is essential. In this on-going study, we are using repeat coverage of Mars analog sites with multifrequency (C, L and P band) airborne radar and ground truth soil sample data to assess the detectability of soil moisture.

Greeley, R.↗

NASA NTRS2013

Precise Comparisons of Bottom-Pressure and Altimetric Ocean Tides

A new set of pelagic tide determinations is constructed from seafloor pressure measurements obtained at 151 sites in the deep ocean. To maximize precision of estimated tides, only stations with long time series are used; median time series length is 567 days. Geographical coverage is considerably improved by use of the international tsunami network, but coverage in the Indian Ocean and South Pacific is still weak. As a tool for assessing global ocean tide models, the data set is considerably more reliable than older data sets : the root-mean-square difference with a recent altimetric tide model is approximately 5 mm for the M2 constituent. Precision is sufficiently high to allow secondary effects in altimetric and bottom-pressure tide differences to be studied. The atmospheric tide in bottom pressure is clearly detected at the S1, S2, and T2 frequencies. The altimetric tide model is improved if satellite altimetry is corrected for crustal loading by the atmospheric tide. Models of the solid body tide can also be constrained. The free corenutation effect in the K1 Love number is easily detected, but the overall estimates are not as accurate as a recent determination with very long baseline interferometry.

tides↗

NASA NTRS2004

A Real-Time Satellite-Based Icing Detection System

Aircraft icing is one of the most dangerous weather conditions for general aviation. Currently, model forecasts and pilot reports (PIREPS) constitute much of the database available to pilots for assessing the icing conditions in a particular area. Such data are often uncertain or sparsely available. Improvements in the temporal and areal coverage of icing diagnoses and prognoses would mark a substantial enhancement of aircraft safety in regions susceptible to heavy supercooled liquid water clouds. The use of 3.9 microns data from meteorological satellite imagers for diagnosing icing conditions has long been recognized (e.g., Ellrod and Nelson, 1996) but to date, no explicit physically based methods have been implemented. Recent advances in cloud detection and cloud property retrievals using operational satellite imagery open the door for real-time objective applications of those satellite datasets for a variety of weather phenomena. Because aircraft icing is related to cloud macro- and microphysical properties (e.g., Cober et al. 1995), it is logical that the cloud properties from satellite data would be useful for diagnosing icing conditions. This paper describes the a prototype realtime system for detecting aircraft icing from space.

Minnis, Patrick↗

NASA NTRS2010

Aerosol Mapping From Space: Strengths, Limitations, and Applications

The aerosol data products from the NASA Earth Observing System's MISR and MODIS instruments provide significant advances in regional and global aerosol optical depth (AOD) mapping, aerosol type measurement, and source plume characterization from space. These products have been and are being used for many applications, ranging from regional air quality assessment, to aerosol air mass type identification and evolution, to wildfire smoke injection height and aerosol transport model validation. However, retrieval uncertainties and coverage gaps still limit the quantitative constraints these satellite data place on some important questions, such as global-scale long-term trends and direct aerosol radiative forcing. Major advances in these areas seem to require a different paradigm, involving the integration of satellite with suborbital data and with models. This presentation will briefly summarize where we stand, and what incremental improvements we can expect, with the current MISR and MODIS aerosol products, and will then elaborate on some initial steps aimed at the necessary integration of satellite data with data from other sources and with chemical transport models.

Kahn, Ralph↗

NASA NTRS2014

Aerosol Properties Derived from Airborne Sky Radiance and Direct Beam Measurements in Recent NASA and DoE Field Campaigns

The AERONET (AErosol RObotic NETwork) ground-based suite of sunphotometers provides measurements of spectral aerosol optical depth (AOD), precipitable water and spectral sky radiance, which can be inverted to retrieve aerosol microphysical properties that are critical to assessments of aerosol-climate interactions. Because of data quality criteria and sampling constraints, there are significant limitations to the temporal and spatial coverage of AERONET data and their representativeness for global aerosol conditions.The 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) instrument, jointly developed by NASA Ames and PNNL (Pacific Northwest National Laboratory) with NASA Goddard collaboration, combines airborne sun tracking and AERONET-like sky scanning with spectroscopic detection. Being an airborne instrument, 4STAR has the potential to fill gaps in the AERONET data set. The 4STAR instrument operated successfully in the SEAC4RS (Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys) experiment in Aug./Sep. 2013 aboard the NASA DC-8 and in the DoE (Department of Energy)-sponsored TCAP (Two Column Aerosol Project, July 2012 & Feb. 2013) experiment aboard the DoE G-1 aircraft. 4STAR provided direct beam measurements of hyperspectral AOD, columnar trace gas retrievals (H2O, O3, NO2), and the first ever airborne hyperspectral sky radiance scans, which can be inverted to yield the same products as AERONET ground-based observations. In this presentation, we provide an overview of the new 4STAR capabilities, with an emphasis on 26 high-quality sky radiance measurements carried out by 4STAR in SEAC4RS. We compare collocated 4STAR and AERONET sky radiances, as well as their retrievals of aerosol microphysical properties for a subset of the available case studies. We summarize the particle property and air-mass characterization studies made possible by the combined 4STAR direct beam and sky radiance observations.

DoE↗

NASA NTRS2014

Aerosol, Cloud and Trace Gas Observations Derived from Airborne Hyperspectral Radiance and Direct Beam Measurements in Recent Field Campaigns

The AERONET (AErosol RObotic NETwork) ground-based suite of sunphotometers provides measurements of spectral aerosol optical depth (AOD), precipitable water and spectral sky radiance, which can be inverted to retrieve aerosol microphysical properties that are critical to assessments of aerosol-climate interactions. Because of data quality criteria and sampling constraints, there are significant limitations to the temporal and spatial coverage of AERONET data and their representativeness for global aerosol conditions. The 4STAR (Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research) instrument, jointly developed by NASA Ames and PNNL with NASA Goddard collaboration, combines airborne sun tracking and AERONET-like sky scanning with spectroscopic detection. Being an airborne instrument, 4STAR has the potential to fill gaps in the AERONET data set. Dunagan et al. [2013] present results establishing the performance of the instrument, along with calibration, engineering flight test, and preliminary scientific field data. The 4STAR instrument operated successfully in the SEAC4RS [Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys] experiment in Aug./Sep. 2013 aboard the NASA DC-8 and in the DoE [Department of Energy]-sponsored TCAP [Two Column Aerosol Project, July 2012 & Feb. 2013] experiment aboard the DoE G-1 aircraft (Shinozuka et al., 2013), and acquired a wealth of data in support of mission objectives on all SEAC4RS and TCAP research flights. 4STAR provided direct beam measurements of hyperspectral AOD, columnar trace gas retrievals (H2O, O3, NO2; Segal-Rosenheimer et al., 2014), and the first ever airborne hyperspectral sky radiance scans, which can be inverted to yield the same products as AERONET ground-based observations. In addition, 4STAR measured zenith radiances underneath cloud decks for retrievals of cloud optical depth and effective diameter. In this presentation, we provide an overview of the new 4STAR capabilities for airborne field campaigns, with an emphasis on comparisons between 4STAR and AERONET sky radiances, and retrievals of aerosol microphysical properties based on sky radiance measurements, column trace gas amounts from spectral direct beam measurements and cloud property retrievals from zenith mode observations for a few select case studies in the SEAC4RS and TCAP experiments. We summarize the aerosol, trace gas, cloud and airmass characterization studies made possible by the combined 4STAR direct beam, and sky/zenith radiance observations.

Aerosol-Climate↗

NASA NTRSDate not supplied

Enabling Exchange and Adequate Use of Data for Observation Based Atmospheric Research

Systematic long-term field observations have played a vital role in advancing atmospheric research over the past several decades. The use of these observations has expanded from primarily characterizing atmospheric processes and trends to evaluating satellite measurements, assessing models, and improving air quality forecasts. Consequently, the demand for atmospheric chemistry observational data have dramatically increased in terms of scope and coverage of measurements (i.e., parameters/species, spatiotemporal extent). In addition to high quality measurements, certain data reporting standards need to be agreed to ensure the data can be readily exchanged and are sufficiently documented to enable adequate use in different research activities. To this end, WMO has developed and implemented measurement guidelines and community practices for meteorology, climatology, atmospheric and hydrological sciences. In addition, the WMO Expert Team on Metadata Standards manages and evolves the existing metadata standards for the WMO Information System WIS and WMO Integrated Global Observing System WIGOS to support consistent and interoperable data descriptions, ensure relevance to research, and to apply data science principles. This team draws on a wide range of expertise from the research community, including atmospheric measurements, modeling, data management, and data science. The current activities include development of key performance indicators, vocabularies for metadata and the evolution of metadata standards to lower the barrier of application to weather/climate/water/environment data for all communities and the weather enterprise. This presentation intends to promote awareness of ongoing progress and actively solicit community feedback.

Field Observations↗

NASA NTRS1980

The application of remotely sensed data in support of emergency rehabilitation of wildfire-damage areas

The depth, texture, and water holding capacity of the soil before the fire in the Bridge Creek area of Deschutes National Forest (1979) were determined from available aerial photography and LANDSAT MSS digital data. Three days after the fire was out, complete coverage of the burned area was acquired on 35 mm color infrared film from a near vertical or low oblique perspective. These photographs were used in assessing the condition of vegetation, and in predicting the likelihood of survival. Negatives from vertical natural photography obtained during the same flight were used to produce 3R prints from which large scale mosaics of the entire burned area were obtained. LANDSAT MSS data obtained on the day the fire was under control were used to evaluate vegetative vigor (by calculating a band 7/band 5 ratio value for each spectral class) and to determine the boundary between altered and unaltered land.

Isaacson, D. L.↗

NASA NTRS1992

Monitoring global monthly mean surface temperatures

The accuracy of the global surface air temperature (SST) estimates for a particular month over the past decade is assessed using all of the in situ observations available today. The sources of noise in the data, the numbers of observations, and the spatial coverage are appraised for the comparison with the climate signal, and different analyzed results are compared to determine their reproducibility. The data are further evaluated by comparing anomalies of near-global monthly mean surface temperatures with those of global satellite channel 2 microwave sounding unit temperatures for 144 months from 1979 to 1990. The results indicate that the inherent noise level in an SST observation is about 1.0 C, and this is compounded when the observation is made in regions of large temperature gradient.

Trenberth, Kevin E.↗

NASA NTRS2010

Convective Weather Forecast Accuracy Analysis at Center and Sector Levels

This paper presents a detailed convective forecast accuracy analysis at center and sector levels. The study is aimed to provide more meaningful forecast verification measures to aviation community, as well as to obtain useful information leading to the improvements in the weather translation capacity models. In general, the vast majority of forecast verification efforts over past decades have been on the calculation of traditional standard verification measure scores over forecast and observation data analyses onto grids. These verification measures based on the binary classification have been applied in quality assurance of weather forecast products at the national level for many years. Our research focuses on the forecast at the center and sector levels. We calculate the standard forecast verification measure scores for en-route air traffic centers and sectors first, followed by conducting the forecast validation analysis and related verification measures for weather intensities and locations at centers and sectors levels. An approach to improve the prediction of sector weather coverage by multiple sector forecasts is then developed. The weather severe intensity assessment was carried out by using the correlations between forecast and actual weather observation airspace coverage. The weather forecast accuracy on horizontal location was assessed by examining the forecast errors. The improvement in prediction of weather coverage was determined by the correlation between actual sector weather coverage and prediction. observed and forecasted Convective Weather Avoidance Model (CWAM) data collected from June to September in 2007. CWAM zero-minute forecast data with aircraft avoidance probability of 60% and 80% are used as the actual weather observation. All forecast measurements are based on 30-minute, 60- minute, 90-minute, and 120-minute forecasts with the same avoidance probabilities. The forecast accuracy analysis for times under one-hour showed that the errors in intensity and location for center forecast are relatively low. For example, 1-hour forecast intensity and horizontal location errors for ZDC center were about 0.12 and 0.13. However, the correlation between sector 1-hour forecast and actual weather coverage was weak, for sector ZDC32, about 32% of the total variation of observation weather intensity was unexplained by forecast; the sector horizontal location error was about 0.10. The paper also introduces an approach to estimate the sector three-dimensional actual weather coverage by using multiple sector forecasts, which turned out to produce better predictions. Using Multiple Linear Regression (MLR) model for this approach, the correlations between actual observation and the multiple sector forecast model prediction improved by several percents at 95% confidence level in comparison with single sector forecast.

Wang, Yao↗

NASA NTRS2014

Preliminary Analysis of Aircraft Loss of Control Accidents: Worst Case Precursor Combinations and Temporal Sequencing

Aircraft loss of control (LOC) is a leading cause of fatal accidents across all transport airplane and operational classes, and can result from a wide spectrum of hazards, often occurring in combination. Technologies developed for LOC prevention and recovery must therefore be effective under a wide variety of conditions and uncertainties, including multiple hazards, and their validation must provide a means of assessing system effectiveness and coverage of these hazards. This requires the definition of a comprehensive set of LOC test scenarios based on accident and incident data as well as future risks. This paper defines a comprehensive set of accidents and incidents over a recent 15 year period, and presents preliminary analysis results to identify worst-case combinations of causal and contributing factors (i.e., accident precursors) and how they sequence in time. Such analyses can provide insight in developing effective solutions for LOC, and form the basis for developing test scenarios that can be used in evaluating them. Preliminary findings based on the results of this paper indicate that system failures or malfunctions, crew actions or inactions, vehicle impairment conditions, and vehicle upsets contributed the most to accidents and fatalities, followed by inclement weather or atmospheric disturbances and poor visibility. Follow-on research will include finalizing the analysis through a team consensus process, defining future risks, and developing a comprehensive set of test scenarios with correlation to the accidents, incidents, and future risks. Since enhanced engineering simulations are required for batch and piloted evaluations under realistic LOC precursor conditions, these test scenarios can also serve as a high-level requirement for defining the engineering simulation enhancements needed for generating them.

Belcastro, Christine M.↗