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At least 379 records · Page 21

Scientific analysis of satellite ranging data

A network of satellite laser ranging (SLR) tracking systems with continuously improving accuracies is challenging the modelling capabilities of analysts worldwide. Various data analysis techniques have yielded many advances in the development of orbit, instrument and Earth models. The direct measurement of the distance to the satellite provided by the laser ranges has given us a simple metric which links the results obtained by diverse approaches. Different groups have used SLR data, often in combination with observations from other space geodetic techniques, to improve models of the static geopotential, the solid Earth, ocean tides, and atmospheric drag models for low Earth satellites. Radiation pressure models and other non-conservative forces for satellite orbits above the atmosphere have been developed to exploit the full accuracy of the latest SLR instruments. SLR is the baseline tracking system for the altimeter missions TOPEX/Poseidon, and ERS-1 and will play an important role in providing the reference frame for locating the geocentric position of the ocean surface, in providing an unchanging range standard for altimeter calibration, and for improving the geoid models to separate gravitational from ocean circulation signals seen in the sea surface. However, even with the many improvements in the models used to support the orbital analysis of laser observations, there remain systematic effects which limit the full exploitation of SLR accuracy today.

Smith, David E.↗

Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (LDAS) and Other Assimilated Hydrological Data at NASA GES DISC

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) provides science support for several data sets relevant to agriculture and food security, including the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (LDAS), or FLDAS data set. The GES DISC is one of twelve NASA Earth Observing System (EOS) data centers that process, archive, document, and distribute data from Earth science missions and related projects. The GES DISC hosts a wide range of remote sensing and model data, and provides reliable and robust data access and other services to users worldwide. Beyond data archive and access, the GES DISC offers many services to visualize and analyze the data. This presentation provides a summary of the hydrological data available at the GES DISC, along with an overview of related data services. Specifically, the FLDAS data set has been adapted to work with domains, data streams, and monitoring and forecast requirements associated with food security assessment in data-sparse, developing country settings. The FLDAS global monthly data have a 0.1 x 0.1 degree spatial resolution covering the period from January 1982 to present. Global FLDAS monthly anomaly and monthly climatology data are also available at the GES DISC to evaluate how current conditions compare to averages over the FLDAS 35-year period. Several case studies using the FLDAS soil moisture, evapotranspiration, rainfall, runoff, and surface temperature data will be presented.

Loeser, Carlee↗

Diving into the Data Plane of Delay Tolerant Networks

This presentation details early research towards applying data plane programming and software defined networking (SDN) to delay tolerant networking (DTN). This involved using the Programming Protocol-Independent Packet Processors (P4) language to program the data plane to handle DTN bundles natively in hardware. The results presented include a proof of concept DTN Bundle Protocol (BP) translator network middlebox, the challenges of programming a data plane to process BP, a software-defined DTN (SDDTN) architecture, and potential future applications of SDDTN. It is demonstrated that SDN and the P4 language has high potential for improving the scalability of DTN networks, although further research must be done to enable this.

Dominick Ta↗

Fiber Optic Tactical Local Network (FOTLAN)

A 100 Mbit/s FDDI (fiber distributed data interface) network interface unit is described that supports real-time data, voice and video. Its high-speed interrupt-driven hardware architecture efficiently manages stream and packet data transfer to the FDDI network. Other enhancements include modular single-mode laser-diode fiber optic links to maximize node spacing, optic bypass switches for increased fault tolerance, and a hardware performance monitor to gather real-time network diagnostics.

Bergman, L. A.↗

The 1991 research and technology report, Goddard Space Flight Center

The 1991 Research and Technology Report for Goddard Space Flight Center is presented. Research covered areas such as (1) earth sciences including upper atmosphere, lower atmosphere, oceans, hydrology, and global studies; (2) space sciences including solar studies, planetary studies, Astro-1, gamma ray investigations, and astrophysics; (3) flight projects; (4) engineering including robotics, mechanical engineering, electronics, imaging and optics, thermal and cryogenic studies, and balloons; and (5) ground systems, networks, and communications including data and networks, TDRSS, mission planning and scheduling, and software development and test.

Soffen, Gerald↗

On Estimating End-to-End Network Path Properties

The more information about current network conditions available to a transport protocol, the more efficiently it can use the network to transfer its data. In networks such as the Internet, the transport protocol must often form its own estimates of network properties based on measurements per-formed by the connection endpoints. We consider two basic transport estimation problems: determining the setting of the retransmission timer (RTO) for are reliable protocol, and estimating the bandwidth available to a connection as it begins. We look at both of these problems in the context of TCP, using a large TCP measurement set [Pax97b] for trace-driven simulations. For RTO estimation, we evaluate a number of different algorithms, finding that the performance of the estimators is dominated by their minimum values, and to a lesser extent, the timer granularity, while being virtually unaffected by how often round-trip time measurements are made or the settings of the parameters in the exponentially-weighted moving average estimators commonly used. For bandwidth estimation, we explore techniques previously sketched in the literature [Hoe96, AD98] and find that in practice they perform less well than anticipated. We then develop a receiver-side algorithm that performs significantly better.

Allman, Mark↗

High Degree and Order Gravity Fields of the Moon Derived from GRAIL Data

The Gravity Recovery and Interior Laboratory (GRAIL) spacecraft conducted the mapping of the gravity field of the Moon from March 1, 2012 to May 29, 2012. The twin spacecraft acquired highly precise K Band range-rate (KBRR) intersatellite ranging data and Deep Space Network (DSN) data during this prime mission phase from altitudes of 15 to 75 km above the lunar surface over three lunar months. We have processed these data using the NASA GSFC GEODYN orbit determination and geodetic parameter estimation program, and we have determined gravity fields up to degree and order 420 in spherical harmonics. The new gravity solutions show improved correlations with LOLA-derived topography to high degree and order and resolve many lunar features in the geopotential with a resolution of less than 30 km, including for example the central peak of the crater Tycho. We discuss the methodology used for the processing of the GRAIL data, the quality of the orbit determination on the GRAIL satellites and the derivation of the solutions, and their evaluation with independent data, including Lunar Prospector. We show that with these new GRAIL gravity solutions, we can now fit the low altitude, extended mission Lunar Prospector tracking data better than with any previous gravity model that included the LP data.

Lemoine, F. G.↗

Additional Metadata Guidelines to Improve the Structure and Usability of HDF and NetCDF Files

The Hierarchical Data Format (HDF) and Network Common Data Form (NetCDF) are data file formats created to aid users in the creation or use of scientific data. These file formats are useful for handling large data volumes and hosting extensive metadata as global attributes or variables and are popular with the modeling community. HDF and NetCDF files are largely used with remote sensing data and have been used to support measurements from numerous campaigns, from satellite to aircraft or ground and mobile based measurements. The files from airborne field studies, however, vary greatly in terms of the file structure and the amount and content of metadata. Information relevant to the file that can be useful to the user such as the data producer, location where data was taken, variable descriptions, or information about the instrument might not be included in the file. This metadata might be present in another file in the dataset containing the same data using the International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) format. Recently, the Aerosols, Clouds, and their Interactions for Earth System Models (MACIE) group started a grassroots effort to develop a set of requirements for the HDF and NetCDF files for field studies, aiming to make the data products more interoperable and usable. Particularly, these requirements seek to make the files more compliant to Climate and Forecast (CF) metadata conventions and to standardize the file structure and the global and variable attributes. These requirements would help to ensure that HDF and NetCDF files contain adequate metadata to better support their use for research, e.g., the modeling community, and to enhance the usability and interoperability of data for research communities at large. To be presented are the details of the MACIE requirements as well as examples of the implementation of these requirements for merge files and lidar observation data files.

Sean Leavor↗

Extending CF Conventions to Enhance Data FAIRness for Atmospheric Composition Observations

The Hierarchical Data Format (HDF) and Network Common Data Form (NetCDF) are data file formats created to aid users in the creation or use of scientific data. These file formats are useful for handling large data volumes and hosting extensive metadata as global, group, or variable attributes and are popular with the modeling community. HDF and NetCDF files are widely used with atmospheric remote sensing data and have been used to support measurements from numerous field campaigns, from satellite to aircraft or ground and mobile based measurements. The files from airborne field studies, however, vary greatly in terms of the file structure and the amount and content of their metadata. Information relevant to the file that can be useful to the user such as the data producer, location where data was taken, variable descriptions, or information about the instrument might not be included in the file. Recently, the Measurements of Aerosols, Clouds, and their Interactions for Earth System Models (MACIE) group started a grassroots effort to develop a CF-based template for the HDF and NetCDF files for field studies, with the aim of making the data products more interoperable and usable. This template seeks to make the files more compliant to Climate and Forecast (CF) metadata conventions and to standardize the file structure and the global and variable attributes. The template would help to ensure that HDF and NetCDF files contain adequate metadata to better support their use for research, e.g., the modeling community, and to enhance the usability and interoperability of data for research communities at large. The draft template has been applied to recent field studies for various instruments and their merge files in support of the Atmosphere Observing System (AOS) project. The details of the revised template are to be presented, as well as examples of the implementation of these requirements for merge files and lidar observation data files and issues revealed during the implementation process.

Sean Leavor↗

Data fusion with artificial neural networks (ANN) for classification of earth surface from microwave satellite measurements

A data fusion system with artificial neural networks (ANN) is used for fast and accurate classification of five earth surface conditions and surface changes, based on seven SSMI multichannel microwave satellite measurements. The measurements include brightness temperatures at 19, 22, 37, and 85 GHz at both H and V polarizations (only V at 22 GHz). The seven channel measurements are processed through a convolution computation such that all measurements are located at same grid. Five surface classes including non-scattering surface, precipitation over land, over ocean, snow, and desert are identified from ground-truth observations. The system processes sensory data in three consecutive phases: (1) pre-processing to extract feature vectors and enhance separability among detected classes; (2) preliminary classification of Earth surface patterns using two separate and parallely acting classifiers: back-propagation neural network and binary decision tree classifiers; and (3) data fusion of results from preliminary classifiers to obtain the optimal performance in overall classification. Both the binary decision tree classifier and the fusion processing centers are implemented by neural network architectures. The fusion system configuration is a hierarchical neural network architecture, in which each functional neural net will handle different processing phases in a pipelined fashion. There is a total of around 13,500 samples for this analysis, of which 4 percent are used as the training set and 96 percent as the testing set. After training, this classification system is able to bring up the detection accuracy to 94 percent compared with 88 percent for back-propagation artificial neural networks and 80 percent for binary decision tree classifiers. The neural network data fusion classification is currently under progress to be integrated in an image processing system at NOAA and to be implemented in a prototype of a massively parallel and dynamically reconfigurable Modular Neural Ring (MNR).

Lure, Y. M. Fleming↗

Lunar Relay Satellite Network for Space Exploration: Architecture, Technologies and Challenges

NASA is planning a series of short and long duration human and robotic missions to explore the Moon and then Mars. A key objective of these missions is to grow, through a series of launches, a system of systems infrastructure with the capability for safe and sustainable autonomous operations at minimum cost while maximizing the exploration capabilities and science return. An incremental implementation process will enable a buildup of the communication, navigation, networking, computing, and informatics architectures to support human exploration missions in the vicinities and on the surfaces of the Moon and Mars. These architectures will support all space and surface nodes, including other orbiters, lander vehicles, humans in spacesuits, robots, rovers, human habitats, and pressurized vehicles. This paper describes the integration of an innovative MAC and networking technology with an equally innovative position-dependent, data routing, network technology. The MAC technology provides the relay spacecraft with the capability to autonomously discover neighbor spacecraft and surface nodes, establish variable-rate links and communicate simultaneously with multiple in-space and surface clients at varying and rapidly changing distances while making optimum use of the available power. The networking technology uses attitude sensors, a time synchronization protocol and occasional orbit-corrections to maintain awareness of its instantaneous position and attitude in space as well as the orbital or surface location of its communication clients. A position-dependent data routing capability is used in the communication relay satellites to handle the movement of data among any of multiple clients (including Earth) that may be simultaneously in view; and if not in view, the relay will temporarily store the data from a client source and download it when the destination client comes into view. The integration of the MAC and data routing networking technologies would enable a relay satellite system to provide end-to-end communication services for robotic and human missions in the vicinity, or on the surface of the Moon with a minimum of Earth-based operational support.

Bhasin, Kul B.↗

Flare Statistics for Young Stars from a Convolutional Neural Network Analysis of TESS Data

All-sky photometric time-series missions have allowed for the monitoring of thousands of young (t(age) < 800 Myr) stars in order to understand the evolution of stellar activity. Here, we developed a convolutional neural network (CNN), stella, specifically trained to find flares in Transiting Exoplanet Survey Satellite (TESS) short-cadence data. We applied the network to 3200 young stars in order to evaluate flare rates as a function of age and spectral type. The CNN takes a few seconds to identify flares on a single light curve. We also measured rotation periods for 1500 of our targets and find that flares of all amplitudes are present across all spot phases, suggesting high spot coverage across the entire surface. Additionally, flare rates and amplitudes decrease for stars t(age) > 50 Myr across all temperatures T(eff) ≥ 4000 K, while stars from 2300 ≤ T(eff) < 4000 K show no evolution across 800 Myr. Stars of T(eff) ≤ 4000 K also show higher flare rates and amplitudes across all ages. We investigate the effects of high flare rates on photoevaporative atmospheric mass loss for young planets. In the presence of flares, planets lose 4%–7% more atmosphere over the first 1 Gyr. stella is an open-source Python toolkit hosted on GitHub and PyPI.

Adina D. Feinstein↗

Alsep data processing: How we processed Apollo Lunar Seismic Data

The Apollo lunar seismic station network gathered data continuously at a rate of 3 x 10 to the 8th power bits per day for nearly eight years until the termination in September, 1977. The data were processed and analyzed using a PDP-15 minicomputer. On the average, 1500 long-period seismic events were detected yearly. Automatic event detection and identification schemes proved unsuccessful because of occasional high noise levels and, above all, the risk of overlooking unusual natural events. The processing procedures finally settled on consist of first plotting all the data on a compressed time scale, visually picking events from the plots, transferring event data to separate sets of tapes and performing detailed analyses using the latter. Many problems remain especially for automatically processing extraterrestrial seismic signals.

Latham, G. V.↗

How we processed Apollo lunar seismic data

The Apollo lunar seismic station network gathered data continuously at a rate of 3 x 10 to the 8th bits per day for nearly eight years until termination in September, 1977. The data were processed and analyzed using a PDP-15 minicomputer. On average, 1500 long-period seismic events were detected yearly. Automatic event detection and identification schemes proved unsuccessful because of occasional high noise levels and, above all, the risk of overlooking unusual natural events. The processing procedures which were finally chosen consist of plotting all the data on a compressed time scale, visually picking events from the plots, transferring event data to separate sets of tapes and performing detailed analyses using the latter. Many problems remain, especially in the automatic processing of extraterrestrial seismic signals.

Nakamura, Y.↗

User data dissemination concepts for earth resources

Domestic data dissemination networks for earth-resources data in the 1985-1995 time frame were evaluated. The following topics were addressed: (1) earth-resources data sources and expected data volumes, (2) future user demand in terms of data volume and timeliness, (3) space-to-space and earth point-to-point transmission link requirements and implementation, (4) preprocessing requirements and implementation, (5) network costs, and (6) technological development to support this implementation. This study was parametric in that the data input (supply) was varied by a factor of about fifteen while the user request (demand) was varied by a factor of about nineteen. Correspondingly, the time from observation to delivery to the user was varied. This parametric evaluation was performed by a computer simulation that was based on network alternatives and resulted in preliminary transmission and preprocessing requirements. The earth-resource data sources considered were: shuttle sorties, synchronous satellites (e.g., SEOS), aircraft, and satellites in polar orbits.

Davies, R.↗

Earth and environmental science in the 1980's: Part 1: Environmental data systems, supercomputer facilities and networks

Overview descriptions of on-line environmental data systems, supercomputer facilities, and networks are presented. Each description addresses the concepts of content, capability, and user access relevant to the point of view of potential utilization by the Earth and environmental science community. The information on similar systems or facilities is presented in parallel fashion to encourage and facilitate intercomparison. In addition, summary sheets are given for each description, and a summary table precedes each section.

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