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At least 109 records · Page 6

Pulse Code Modulation (PCM) data storage and analysis using a microcomputer

The current widespread use of microcomputers has led to the creation of some very low-cost instrumentation. A Pulse Code Modulation (PCM) storage device/data analyzer -- a peripheral plug-in board especially constructed to enable a personal computer to store and analyze data from a PCM source -- was designed and built for use on the NASA Sounding Rocket Program for PMC encoder configuration and testing. This board and custom-written software turns a computer into a snapshot PCM decommutator which will accept and store many hundreds or thousands of PCM telemetry data frames, then sift through them repeatedly. These data can be converted to any number base and displayed, examined for any bit dropouts or changes (in particular, words or frames), graphically plotted, or statistically analyzed.

Massey, D. E.↗

Providing the Persistent Data Storage in a Software Engineering Environment Using Java/COBRA and a DBMS

An investigation was undertaken to build the software foundation for the WHERE (Web-based Hyper-text Environment for Requirements Engineering) project. The TCM (Toolkit for Conceptual Modeling) was chosen as the foundation software for the WHERE project which aims to provide an environment for facilitating collaboration among geographically distributed people involved in the Requirements Engineering process. The TCM is a collection of diagram and table editors and has been implemented in the C++ programming language. The C++ implementation of the TCM was translated into Java in order to allow the editors to be used for building various functionality of the WHERE project; the WHERE project intends to use the Web as its communication back- bone. One of the limitations of the translated software (TcmJava), which militated against its use in the WHERE project, was persistent data management mechanisms which it inherited from the original TCM; it was designed to be used in standalone applications. Before TcmJava editors could be used as a part of the multi-user, geographically distributed applications of the WHERE project, a persistent storage mechanism must be built which would allow data communication over the Internet, using the capabilities of the Web. An approach involving features of Java, CORBA (Common Object Request Broker), the Web, a middle-ware (Java Relational Binding (JRB)), and a database server was used to build the persistent data management infrastructure for the WHERE project. The developed infrastructure allows a TcmJava editor to be downloaded and run from a network host by using a JDK 1.1 (Java Developer's Kit) compatible Web-browser. The aforementioned editor establishes connection with a server by using the ORB (Object Request Broker) software and stores/retrieves data in/from the server. The server consists of a CORBA object or objects depending upon whether the data is to be made persistent on a single server or multiple servers. The CORBA object providing the persistent data server is implemented using the Java progranu-ning language. It uses the JRB to store/retrieve data in/from a relational database server. The persistent data management system provides transaction and user management facilities which allow multi-user, distributed access to the stored data in a secure manner.

Dhaliwal, Swarn S.↗

Using Enhanced Grace Water Storage Data to Improve Drought Detection by the U.S. and North American Drought Monitors

NASA's Gravity Recovery and Climate Experiment (GRACE) satellites measure time variations of the Earth's gravity field enabling reliable detection of spatio-temporal variations in total terrestrial water storage (TWS), including groundwater. The U.S. and North American Drought Monitors rely heavily on precipitation indices and do not currently incorporate systematic observations of deep soil moisture and groundwater storage conditions. Thus GRACE has great potential to improve the Drought Monitors by filling this observational gap. GRACE TWS data were assimilating into the Catchment Land Surface Model using an ensemble Kalman smoother enabling spatial and temporal downscaling and vertical decomposition into soil moisture and groundwater components. The Drought Monitors combine several short- and long-term drought indicators expressed in percentiles as a reference to their historical frequency of occurrence. To be consistent, we generated a climatology of estimated soil moisture and ground water based on a 60-year Catchment model simulation, which was used to convert seven years of GRACE assimilated fields into drought indicator percentiles. At this stage we provide a preliminary evaluation of the GRACE assimilated moisture and indicator fields.

Houborg, Rasmus↗

Integrating Enhanced Grace Terrestrial Water Storage Data Into the U.S. and North American Drought Monitors

NASA's Gravity Recovery and Climate Experiment (GRACE) satellites measure time variations nf the Earth's gravity field enabling reliable detection of spatio-temporal variations in total terrestrial water storage (TWS), including ground water. The U.S. and North American Drought Monitors are two of the premier drought monitoring products available to decision-makers for assessing and minimizing drought impacts, but they rely heavily on precipitation indices and do not currently incorporate systematic observations of deep soil moisture and groundwater storage conditions. Thus GRACE has great potential to improve the Drought Monitors hy filling this observational gap. Horizontal, vertical and temporal disaggregation of the coarse-resolution GRACE TWS data has been accomplished by assimilating GRACE TWS anomalies into the Catchment Land Surface Model using ensemble Kalman smoother. The Drought Monitors combine several short-term and long-term drought indices and indicators expressed in percentiles as a reference to their historical frequency of occurrence for the location and time of year in question. To be consistent, we are in the process of generating a climatology of estimated soil moisture and ground water based on m 60-year Catchment model simulation which will subsequently be used to convert seven years of GRACE assimilated fields into soil moisture and groundwater percentiles. for systematic incorporation into the objective blends that constitute Drought Monitor baselines. At this stage we provide a preliminary evaluation of GRACE assimilated Catchment model output against independent datasets including soil moisture observations from Aqua AMSR-E and groundwater level observations from the U.S. Geological Survey's Groundwater Climate Response Network.

Housborg, Rasmus↗

Pulse Code Modulation (PCM) data storage and analysis using a microcomputer

A PCM storage device/data analyzer is described. This instrument is a peripheral plug-in board especially built to enable a personal computer to store and analyze data from a PCM source. This board and custom written software turns a computer into a snapshot PCM decommutator. This instrument will take in and store many hundreds or thousands of PCM telemetry data frames, then sift through them over and over again. The data can be converted to any number base and displayed, examined for any bit dropouts or changes in particular words or frames, graphically plotted, or statistically analyzed. This device was designed and built for use on the NASA Sounding Rocket Program for PCM encoder configuration and testing.

Massey, D. E.↗

A data storage, retrieval and analysis system for endocrine research

This retrieval system builds, updates, retrieves, and performs basic statistical analyses on blood, urine, and diet parameters for the M071 and M073 Skylab and Apollo experiments. This system permits data entry from cards to build an indexed sequential file. Programs are easily modified for specialized analyses.

Newton, L. E.↗

Testing the Archivas Cluster (Arc) for Ozone Monitoring Instrument (OMI) Scientific Data Storage

The Ozone Monitoring Instrument (OMI) launched on NASA's Aura Spacecraft, the third of the major platforms of the EOS program on July 15,2004. In addition to the long term archive and distribution of the data from OM1 through the Goddard Earth Science Distributed Active Archive Center (GESDAAC), we are evaluating other archive mechanisms that can archive the data in a more immediately available method where it can be used for futher data production and analysis. In 2004, Archivas, Inc. was selected by NASA s Small Business Innovative Research (SBIR) program for the development of their Archivas Cluster (ArC) product. Arc is an online disk based system utilizing self-management and automation on a Linux cluster. Its goal is to produce a low cost solution coupled with the ease of management. The OM1 project is an application partner of the SBIR program, and has deployed a small cluster (5TB) based on the beta Archwas software. We performed extensive testing of the unit using production OM1 data since launch. In 2005, Archivas, Inc. was funded in SBIR Phase II for further development, which will include testing scalability with the deployment of a larger (35TB) cluster at Goddard. We plan to include Arc in the OM1 Team Leader Computing Facility (TLCF) hosting OM1 data for direct access and analysis by the OMI Science Team. This presentation will include a brief technical description of the Archivas Cluster, a summary of the SBIR Phase I beta testing results, and an overview of the OMI ground data processing architecture including its interaction with the Phase II Archivas Cluster and hosting of OMI data for the scientists.

Tilmes, Curt↗

Content Platforms Meet Data Storage, Retrieval Needs

Earth is under a constant barrage of information from space. Whether from satellites orbiting our planet, spacecraft circling Mars, or probes streaking toward the far reaches of the Solar System, NASA collects massive amounts of data from its spacefaring missions each day. NASA s Earth Observing System (EOS) satellites, for example, provide daily imagery and measurements of Earth s atmosphere, oceans, vegetation, and more. The Earth Observing System Data and Information System (EOSDIS) collects all of that science data and processes, archives, and distributes it to researchers around the globe; EOSDIS recently reached a total archive volume of 4.5 petabytes. Try to store that amount of information in your standard, four-drawer file cabinet, and you would need 90 million to get the job done. To manage the flood of information, NASA has explored technologies to efficiently collect, archive, and provide access to EOS data for scientists today and for years to come. One such technology is now providing similar capabilities to businesses and organizations worldwide.

Source record↗

Advanced Compact Holographic Data Storage System

JPL, under current sponsorship from NASA Space Science and Earth Science Programs, is developing a high-density, nonvolatile and rad-hard Advanced Holographic Memory (AHM) system to enable large-capacity, high-speed, low power consumption, and read/write of data in a space environment. The entire read/write operation will be controlled with electro-optic mechanism without any moving parts. This CHDS will consist of laser diodes, photorefractive crystal, spatial light modulator, photodetector array, and I/O electronic interface. In operation, pages of information would be recorded and retrieved with random access and highspeed. The nonvolatile, rad-hard characteristics of the holographic memory will provide a revolutionary memory technology to enhance mission capabilities for all NASA's Earth Science Mission. In this paper, recent technology progress in developing this CHDS at JPL will be presented.

Chao, Tien-Hsin↗

Assimilation of GRACE Terrestrial Water Storage Data into a Land Surface Model: Results for the Mississippi River Basin

NASA's GRACE mission has the potential to be extremely valuable for water resources applications and global water cycle research. What makes GRACE unique among Earth Science satellite systems is that it is able to monitor variations in water stored in all forms, from snow and surface water to soil moisture to groundwater in the deepest aquifers. However, the space and time resolutions of GRACE observations are coarse. GRACE typically resolves water storage changes over regions the size of Nebraska on a monthly basis, while city-scale, daily observations would be more useful for water management, agriculture, and weather prediction. High resolution numerical (computer) hydrology models have been developed, which predict the fates of water and energy after they strike the land surface as precipitation and sunlight. These are similar to weather and climate forecast models, which simulate atmospheric processes. We integrated the GRACE observations into a hydrology model using an advanced technique called data assimilation. The results were new estimates of groundwater, soil moisture, and snow variations, which combined the veracity of GRACE with the high resolution of the model. We tested the technique over the Mississippi River basin, but it will be even more valuable in parts of the world which lack reliable data on water availability.

Zaitchik, Benjamin F.↗

Problems in the long-term storage of data obtained from scientific space experiments

It is shown that long-term data storage systems can be achieved when the system which organizes and conducts the scientific space experiments is equipped with a specialized subsystem: the information filing system. Its main functions are described along with the necessity of stage-by-stage development and compatibility with the data processing systems. The requirements for long-term data storage media are discussed.

Zlotin, G. N.↗

Circuitry selectively limits data storage in general purpose computer

Circuitry limits storage in the memory of a stored program general purpose digital computer by permitting storage or writing to certain, specified areas of memory. The limit register used in the computer is easily set under program control, and the memory block size and position is readily changed to suit each specific program.

Slopper, D. K.↗