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NASA NTRS2017

MESA: Message-Based System Analysis Using Runtime Verification

In this paper, we present a novel approach and framework for run-time verication of large, safety critical messaging systems. This work was motivated by verifying the System Wide Information Management (SWIM) project of the Federal Aviation Administration (FAA). SWIM provides live air traffic, site and weather data streams for the whole National Airspace System (NAS), which can easily amount to several hundred messages per second. Such safety critical systems cannot be instrumented, therefore, verification and monitoring has to happen using a nonintrusive approach, by connecting to a variety of network interfaces. Due to a large number of potential properties to check, the verification framework needs to support efficient formulation of properties with a suitable Domain Specific Language (DSL). Our approach is to utilize a distributed system that is geared towards connectivity and scalability and interface it at the message queue level to a powerful verification engine. We implemented our approach in the tool called MESA: Message-Based System Analysis, which leverages the open source projects RACE (Runtime for Airspace Concept Evaluation) and TraceContract. RACE is a platform for instantiating and running highly concurrent and distributed systems and enables connectivity to SWIM and scalability. TraceContract is a runtime verication tool that allows for checking traces against properties specified in a powerful DSL. We applied our approach to verify a SWIM service against several requirements.We found errors such as duplicate and out-of-order messages.

Message-based System↗

NASA NTRS2018

Chemical Modeling of the Reactivity of Short-Lived Greenhouse Gases: A Model Inter-Comparison Prescribing a Well-Measured, Remote Troposphere

We develop a new protocol for merging in situ measurements with 3-D model simulations of atmospheric chemistry with the goal of integrating over the data to identify the most reactive air parcels in terms of tropospheric production and loss of the greenhouse gases ozone and methane. Presupposing that we can accurately measure atmospheric composition, we examine whether models constrained by such measurements agree on the chemical budgets for ozone and methane. In applying our technique to a synthetic data stream of 14,880 parcels along 180W, we are able to isolate the performance of the photochemical modules operating within their global chemistry-climate and chemistry-transport models, removing the effects of modules controlling tracer transport, emissions, and scavenging. Differences in reactivity across models are driven only by the chemical mechanism and the diurnal cycle of photolysis rates, which are driven in turn by temperature, water vapor, solar zenith angle, clouds, and possibly aerosols and overhead ozone, which are calculated in each model. We evaluate six global models and identify their differences and similarities in simulating the chemistry through a range of innovative diagnostics. All models agree that the more highly reactive parcels dominate the chemistry (e.g., the hottest 10% of parcels control 25-30% of the total reactivities), but do not fully agree on which parcels comprise the top 10%. Distinct differences in specific features occur, including the regions of maximum ozone production and methane loss, as well as in the relationship between photolysis and these reactivities. Unique, possibly aberrant, features are identified for each model, providing a benchmark for photochemical module development. Among the 6 models tested here, 3 are almost indistinguishable based on the inherent variability caused by clouds, and thus we identify 4, effectively distinct, chemical models. Based on this work, we suggest that water vapor differences in model simulations of past and future atmospheres may be a cause of the different evolution of tropospheric O3 and CH4, and lead to different chemistry-climate feedbacks across the models.

greenhouse gases↗

NASA NTRS2018

Using GPS Receivers 1PPS Output to Verify Time Stamp Accuracy and Measure Propagation Delay

A simple Pulse Overlay (PO) circuit using a logic OR gate was developed to overlay a precise leading edge 1 Pulse Per Second (1PPS) time reference marker from a GPS receiver onto a Non-Return -to- Zero-Level (NRZ-L) Pulse Code Modulation (PCM) telemetry data stream to validate time stamp accuracy and measure propagation delay (PD) in telemetry equipment.

telemetry↗

NASA NTRS2018

History and Status of ALSEP and the Apollo Lunar Data Project

A suite of automated scientific instruments (the Apollo Lunar Surface Experiment Package, or ALSEP) was installed at each of the landing sites of Apollo 12, 14, 15, 16, and 17 from 1969 to 1972. They operated from deployment until decommissioning on 30 September 1977. These data were continuously transmitted to Earth and saved on the Range Tapes, which were recorded at the Manned Space Flight Network stations. These data were also broken out by experiment and sent to the experiment Principal Investigators on what were called the P.I. Tapes. Starting in April 1973 the Range Tape data were stored in digital format on 7-track magnetic tapes, the ARCSAV Tapes. In February 1976, the handling of the Range Tapes was transferred to UT Galveston. They produced 9-track tapes referred to as the Work Tapes. Following the Apollo program the Range and ARCSAV tapes, which were never archived, were lost. The Work Tapes were archived at the National Space Science Data Center (NSSDC). Some investigators archived their individual experiment data with NSSDC as well, but much of the data had minimal documentation, were not in digital form, or were stored in difficult to translate formats. Data from many experiments were never delivered to the NSSDC. The Lunar Data Project was started to address the problem of both missing and not readily usable data. Our effort has resulted in recovery of some of the ARCSAV tapes, recovery and digitization of a large volume of Apollo scientific and technical documentation, and restoration of many ALSEP and other Apollo data collections. Restoration involves deciphering formats, assembling necessary ancillary data (metadata), and packaging data in digital format to be archived with the Planetary Data System (PDS). Recovery of the data from the ARCSAV tapes involved having the tapes read on special equipment and extracting the individual experiment data out of the integrated data stream. We will report on the history and status of the various recovery efforts.

Work Tapes↗

NASA NTRS2016

Global Data Assembly Center (GDAC) Report to the GHRSST Science Team

In 2015-2016 the Global Data Assembly Center (GDAC) at NASA’s Physical Oceanography Distributed Active Archive Center (PO.DAAC) continued its role as the primary clearinghouse and access node for operational GHRSST data streams, as well as its collaborative role with the NOAA Long Term Stewardship and Reanalysis Facility (LTSRF) for archiving.

Armstrong, Edward↗

NASA NTRS2012

Space Weather Forecasting at NASA GSFC Space Weather Research Center

The NASA GSFC Space Weather Research Center (http://swrc.gsfc.nasa.gov) is committed to providing research forecasts and notifications to address NASA's space weather needs - in addition to its critical role in space weather education. We provide a host of services including spacecraft anomaly resolution, historical impact analysis, real-time monitoring and forecasting, tailored space weather alerts and products, weekly summaries and reports, and most recently - video casts. In this presentation, we will focus on how near real-time data (both in space and on ground), in combination with modeling capabilities and an innovative dissemination system called the Integrated Space Weather Analysis System (iSWA http://iswa.gsfc.nasa.gov), enable space weather forecasting and quality space weather products provided by our Center. A few critical near real-time data streams for space weather forecasting will be identified and discussed.

CMEs↗

NASA NTRS2018

Linking Asteroid Detections from the Large Synoptic Survey Telescope

We have conducted a detailed simulation of the Large Synoptic Survey Telescope (LSST) in order to understand the system’s ability to link detections of asteroids within and across nights in order to populate a catalog of asteroid orbits. We show that LSST, using its baseline survey cadence, should be able to successfully link and catalog asteroids. In our simulation of a single monthly observing cycle, LSST produced 66 million candidate detections of main belt asteroids (MBAs) and near Earth objects (NEOs), of which 77% were spurious detections related to detector noise or image processing. Using the Moving Object Processing System, we were able to assemble single-night “tracklets” with negligible losses, but a purity of only 43%. The next stage of linking led to three-night orbits with data sets no more than 12 days in length, and it is at this stage that the false detections are readily removed from the data stream. Main-belt linkages were essentially complete and 99.8% pure. Similarly, only 0.02% of linked detections involving NEOs were spurious. On the other hand, NEO linking was 93.6% complete, indicating that 6.4% of potentially findable NEOs were not successfully linked. We believe that this rate can be improved with careful tuning of the MOPS linking algorithms. The NEO catalog was affected by main-belt confusion so that mis-linked MBAs appeared as NEOs, and many correctly linked MBAs were consistent with NEO orbits. We show that these cases arise primarily from MBAs detected at lower solar elongations and we postulate that this is an artifact of a one month simulation that will be readily resolved by surveying over many months.

Chesley, Steven R.↗

NASA NTRS2019

Using GPS Receiver 1PPS Output to Verify Time Stamp Accuracy and Measure Propagation Delay

A simple pulse overlay circuit using a logic OR gate was developed to overlay a precise leading edge 1 pulse per second time reference marker from a global positioning system receiver onto a non-return -to- zero-level pulse code modulation telemetry data stream to validate time stamp accuracy and measure propagation delay in telemetry equipment.

time stamp offset↗

NASA NTRS2019

SWIM-Fused Data Products Used by ATD-2 Analysts for Quantifying NAS Performance and Benefits

The data used in ATD-2 analysis begins from a fused data stream from numerous SWIM sources, then undergoes additional processing to derive commonly used metrics. This has been a consistent focus of the analysis team and is the basis for many benefits and performance analyses that will be described in other sessions.

Churchill, Andrew M.↗

NASA NTRS2019

Integrating Remote Sensing Observations with NASA's GEOS-5 Modeling Framework in Support of Retrospective Analyses and Seasonal Prediction of Biosphere-Atmosphere CO2 Flux

The absorption of nearly half of all anthropogenic carbon dioxide (CO2) emissions by terrestrial and marine ecosystems has played a critical role in mitigating climate change. However, a persistent lack of understanding of these uptake processes impedes attribution, and thereby introduces large uncertainties into projections of the trajectory of carbon and climate in coming decades. A better understanding and quantification of the seasonal and interannual variability of carbon flux between the atmosphere and ocean and terrestrial biospheres is critically needed to improve predictions from Earth system models. We propose to bring together a diverse suite of remote sensing observations, mechanistic models, and NASA's Goddard Earth Observing System, version 5 (GEOS-5) model to address two objective 1) quantify the processes controlling the temporal variability of biosphere-atmosphere CO2 flux on seasonal and interannual timescales from 1989 to 2018 and 2) evaluating the predictability of the components of carbon flux on seasonal timescales. Because GEOS-5 has been developed to incorporate a variety of Earth system observations and includes a complete and physically consistent depiction of the atmosphere, land, and ocean carbon cycles, it represents a unique and ideal synthesis framework for this effort. By expanding the realism of processes that could be included in GEOS-5 seasonal forecasts, this effort supports NASA's goals toward an integrated Earth system modeling and prediction framework.We propose to integrate a number of observations into the GEOS-5 modeling system to refine retrospective estimates of both terrestrial and marine carbon flux and to test hypotheses regarding the effects of climate drivers on terrestrial carbon flux. This will include assimilating several satellite ocean color products in the NASA Ocean Biogeochemistry Model (NOBM) to improve the representation of ocean biology. We will also utilize remote sensing datasets to increase the temporal resolution of global land-use change estimates and fire emissions to better constrain the temporal variability of the terrestrial carbon cycle. This information will be incorporated into two NASA terrestrial biosphere models Catchment-CN, a dynamic vegetation model that is integrated within GEOS-5 and the Ecosystem Demography (ED) model, a core modeling resource supporting the Global Ecosystem Dynamics Investigation (GEDI) mission to map biomass. Fluxes will be evaluated through 1) comparison to top-down flux estimates inferred from surface CO2 observations and 2) comparison against available aircraft and satellite observations.By combining predictions of net ecosystem exchange and air-sea CO2 flux from land and ocean models with statistical predictions of land use change, fire, and fossil fuel emissions, we propose to create the first dynamical CO2 forecast on seasonal timescales. Because of the experimental nature of this endeavor, an important project objective will be to evaluate the limits to the predictability of different carbon cycle processes over lead times of 1-12 months using different satellite and surface data streams.

Ott, Lesley↗

NASA NTRS2019

Earth Observations from a New Generation of Geostationary Satellites

The latest generation of geostationary satellites carry sensors such as the Advanced Baseline Imager (GOES-16/17) and the Advanced Himawari Imager (Himawari-8/9) that closely mimic the spatial and spectral characteristics of widely used polar orbiting sensors such as EOS/MODIS. More importantly, they provide observations at 1-5-15 minute intervals, instead of twice a day from MODIS, offering unprecedented opportunities for monitoring large parts of the Earth. In addition to serving the needs of weather forecasting, these observations offer new and exciting opportunities in managing solar power, fighting wildfires, and tracking air pollution. Creation of actionable information in near real-time from these data streams is a challenge that is best addressed through collaborative efforts among the industry, academia and government agencies.

Nemani, Ramakrishna R.↗

NASA NTRS2019

Earth Observations from a New Generation of Geostationary Satellites

Nemani, Ramakrishna R.↗

NASA NTRS2020

Space Weather Architecture Options to Support Human and Robotic Deep Space Exploration

Understanding solar energetic particle (SEP) event characteristics is critical to the proper design of human and robotic space missions. This report details a study of operational response time for monitoring space weather for crewed flights, specifically targeting lunar and Mars missions. The NESC assessment team evaluated the required minimum latency for data streams and forecasts that will directly affect mission operations using a 41-year database (i.e., European Space Agency (ESA) Solar Energetic Particle Environment Modeling (SEPEM) RSDv2.0) of SEP events. The database contained 192 SEP events that resulted in a dose increase above background levels. Of those, 10% were “multiple events,” or events that occurred in quick succession. The analysis provides probabilistic values for time to peak flux and dose rate for the duration of each event. This NESC assessment also evaluated the SEP threshold levels for exploration missions to determine the relevant energy range of required proton measurements.

Solar energetic particle↗

NASA NTRSDate not supplied

MESA: Scalable Runtime Verification Tool Using Actors

This work presents our runtime verification approach implemented by the tool MESA (MEssage-based System Analysis) which allows for using concurrent monitors to check for properties specified in linear temporal logic and finite state machines.We employ the actor programing model to implement MESA where monitors are captured by concurrent actors that communicate via messaging. The paper also presents a case study where MESA is used to monitor flights in National Airspace System of United States using live air traffic data stream. The case study which motivated this work in the first place shows that our approach is effective.We also perform empirical study by conducting experiments using monitoring systems with different numbers of concurrent monitors and different layers of indexing.This paper describes our experiments, evaluates our results,and discusses challenges faced during the study. The evaluation shows our approach is scalable.

runtime verification, concurrency, actor programin↗

NASA NTRS2016

Global Data Assembly Center (GDAC) report to the GHRSST science team

Tsontos, Vardis↗

NASA NTRS2018

Global Data Assembly Center (GDAC) report to the GHRSST Science Team

In 2017-2018 the Global Data Assembly Center (GDAC) at NASA’s Physical Oceanography Distributed Active Archive Center (PO.DAAC) provided ingest, archive, distribution and user services for GHRSST operational data streams with improved and evolved tools, services, and tutorials and interfaced with the user community to address technical inquiries. The GDAC provided access to new GHRSST datasets as well retired a significant number of deprecated GHRSST datasets from its discovery services. The following sections summarize and document the specific achievements of the GDAC to the GHRSST community.

Finch, Chris↗

NASA NTRS2018

Global Data Assembly Center (GDAC) Report to the GHRSST Science Team

Finch, Chris↗

NASA NTRS2021

A New Approach to Evaluate and Reduce Uncertainty of Model-Based Biodiversity Projections for Conservation Policy Formulation

Biodiversity projections with uncertainty estimates under different climate, land-use, and policy scenarios are essential to setting and achieving international targets to mitigate biodiversity loss. Evaluating and improving biodiversity predictions to better inform policy decisions remains a central conservation goal and challenge. A comprehensive strategy to evaluate and reduce uncertainty of model outputs against observed measurements and multiple models would help to produce more robust biodiversity predictions. We propose an approach that integrates biodiversity models and emerging remote sensing and in-situ data streams to evaluate and reduce uncertainty with the goal of improving policy-relevant biodiversity predictions. In this article, we describe a multivariate approach to directly and indirectly evaluate and constrain model uncertainty, demonstrate a proof of concept of this approach, embed the concept within the broader context of model evaluation and scenario analysis for conservation policy, and highlight lessons from other modeling communities.

Bonnie J E Myers↗