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At least 1,099 records · Page 61

The EOSDIS Version 0 Distributed Active Archive Center for physical oceanography and air-sea interaction

The Distributed Active Archive Center (DAAC) at the Jet Propulsion Laboratory will support scientists specializing in physical oceanography and air-sea interaction. As part of the NASA Earth Observing System Data and Information System Version 0 the DAAC will build on existing capabilities to provide services for data product generation, archiving, distribution and management of information about data. To meet scientist's immediate needs for data, existing data sets from missions such as Seasat, Geosat, the NOAA series of satellites and the Global Positioning Satellite system will be distributed to investigators upon request. In 1992, ocean topography, wave and surface roughness data from the Topex/Poseidon radar altimeter mission will be archived and distributed. New data products will be derived from Topex/Poseidon and other sensor systems based on recommendations of the science community. In 1995, ocean wind field measurements from the NASA Scatterometer will be supported by the DAAC.

Hilland, Jeffrey E.↗

Remote Sensing Data from CLARET: A Prototype Cart Data Set

A data set containing radiation, meteorological, and cloud sensor observations is documented. It was prepared for use by the Department of Energy's Atmospheric Radiation Measurement (ARM) program and other interested scientists. These data are a precursor of the types of data that ARM Cloud And Radiation Testbed (CART) sites will provide. The data are from the Cloud Lidar And Radar Exploratory Test (CLARET) conducted by the Wave Propagation Laboratory during autumn 1989 in the Denver-Boulder area of Colorado primarily for the purpose of developing new cloud-sensing techniques on cirrus. After becoming aware of this experiment, ARM scientists requested archival of subsets or the data to assist in the developing ARM program. Five CLARET cases were selected: two with cirrus, one with stratus, one with mixed-phase clouds, and one with clear skies. The cases range from 2 to 9.5 h in length. A pyranometer, pyrgeometer, pyrheliometer, and an infrared radiometer constituted the ensemble of instruments that provided surface radiation data. A lidar, radar, and ceilometer observed the cloud geometrical structure, and visual reports and all-sky camera observations were assimilated to provide cloud cover data. Radiosondes, wind profiler, RASS (profiling virtual temperature), microwave radiometers (observing column integrated liquid water and water vapor), and standard surface measurements provided meteorological data. Satellite data from the stratus case and one cirrus case were analyzed for statistics on cloud cover and top height. The main body of the selected data are available on diskette from the Wave Propagation Laboratory or Los Alamos National Laboratory. In addition to documenting the data set, this report describes CLARET and gives a bibliography of publications associated with the project. Some preliminary results of CLARET' research are also summarized. Simultaneous CO 2 lidar and radar backscatter measurements were shown to provide estimates of the effective radius of ice particles. Simultaneous radar and infrared radiometer data appear useful for estimating column-integrated numbers and average sizes of ice cloud particles. Ice water content obtained with this method compared favorably with values from another empirical technique using radar data alone. Depolarization of the CO 2 lidar signal from ice clouds was surprisingly small, suggesting that calculation of backscatter from nonspherical particles for this lidar is a tractable problem. Examples are also cited of CO 2 lidar measurements of the effective radius of water cloud drop size distributions and of inference of the size of pristine ice crystals that assume a particular orientation in the air. These parameters are all important to radiative transfer through clouds.

Clouds (Meteorology)↗

Multiresolution pattern recognition of small volcanos in Magellan data

The Magellan data is a treasure-trove for scientific analysis of venusian geology, providing far more detail than was previously available from Pioneer Venus, Venera 15/16, or ground-based radar observations. However, at this point, planetary scientists are being overwhelmed by the sheer quantities of data collected--data analysis technology has not kept pace with our ability to collect and store it. In particular, 'small-shield' volcanos (less than 20 km in diameter) are the most abundant visible geologic feature on the planet. It is estimated, based on extrapolating from previous studies and knowledge of the underlying geologic processes, that there should be on the order of 10(exp 5) to 10(exp 6) of these volcanos visible in the Magellan data. Identifying and studying these volcanos is fundamental to a proper understanding of the geologic evolution of Venus. However, locating and parameterizing them in a manual manner is very time-consuming. Hence, we have undertaken the development of techniques to partially automate this task. The goal is not the unrealistic one of total automation, but rather the development of a useful tool to aid the project scientists. The primary constraints for this particular problem are as follows: (1) the method must be reasonably robust; and (2) the method must be reasonably fast. Unlike most geological features, the small volcanos of Venus can be ascribed to a basic process that produces features with a short list of readily defined characteristics differing significantly from other surface features on Venus. For pattern recognition purposes the relevant criteria include the following: (1) a circular planimetric outline; (2) known diameter frequency distribution from preliminary studies; (3) a limited number of basic morphological shapes; and (4) the common occurrence of a single, circular summit pit at the center of the edifice.

Smyth, P.↗

Annual report

The overall goal of the Tuskegee University Center for Food Production, Processing and Waste Management in Controlled Ecological Life Support Systems (CELSS) is to provide tested information and technologies applicable to bioregenerative food production systems for life support on long-term manned space mission. Specifically, the center is developing information, computer simulated models, methodologies and technology for sweetpotato and peanut biomass production and processing, inclusive of waste management and recycling of these crops selected by NASA for CELSS. The Center is organized into interdisciplinary teams of life scientists and engineers that work together on specific objectives and long-term goals. Integral to the goal of the Center is the development of both basic and applied research information and the training of young scientists and engineers, especially underrepresented minorities that will increase the professional pool in these disciplines and contribute to the advancement of space sciences and exploration.

Source record↗

Hubble space telescope: The GO and GTO observing programs, version 3.0

A portion of the observing time with the Hubble Space Telescope (HST) was awarded by NASA to scientists involved in the development of the HST and its instruments. These scientists are the Guaranteed Time Observers (GTO's). Observing time was also awarded to General Observers (GO's) on the basis of the proposal reviews in 1989 and 1991. The majority of the 1989 programs have been completed during 'Cycle 1', while the 1991 programs will be completed during 'Cycle 2', nominally a 12-month period beginning July 1992. This document presents abstracts of these GO and GTO programs, and detailed listings of the specific targets and exposures contained in them. These programs and exposures are protected by NASA policy, as detailed in the HST Call for Proposals (CP), and are not to be duplicated by new programs.

Downes, Ron↗

Issues in knowledge representation to support maintainability: A case study in scientific data preparation

Scientific data preparation is the process of extracting usable scientific data from raw instrument data. This task involves noise detection (and subsequent noise classification and flagging or removal), extracting data from compressed forms, and construction of derivative or aggregate data (e.g. spectral densities or running averages). A software system called PIPE provides intelligent assistance to users developing scientific data preparation plans using a programming language called Master Plumber. PIPE provides this assistance capability by using a process description to create a dependency model of the scientific data preparation plan. This dependency model can then be used to verify syntactic and semantic constraints on processing steps to perform limited plan validation. PIPE also provides capabilities for using this model to assist in debugging faulty data preparation plans. In this case, the process model is used to focus the developer's attention upon those processing steps and data elements that were used in computing the faulty output values. Finally, the dependency model of a plan can be used to perform plan optimization and runtime estimation. These capabilities allow scientists to spend less time developing data preparation procedures and more time on scientific analysis tasks. Because the scientific data processing modules (called fittings) evolve to match scientists' needs, issues regarding maintainability are of prime importance in PIPE. This paper describes the PIPE system and describes how issues in maintainability affected the knowledge representation used in PIPE to capture knowledge about the behavior of fittings.

Chien, Steve↗

Systems engineering and the user: Incorporation of user requirements into the SE process

This paper is organized into four parts. In the Gestation Phase, I describe the process of starting a new mission and establishing its rough boundaries. Next I show how the scientific experiments are selected. Then we enter the Preliminary Design Phase, where we incorporate the scientist's instruments into the systems engineering process. Finally, I show how the Preliminary Design Review (PDR) assures NASA management and the scientists that the scientific requirements have been incorporated into the systems engineering process to everyone's satisfaction.

Naugle, John E.↗

Data archaeology at ICES

This paper provides a brief overview of the function of the International Council for the Exploration of the Sea (ICES), both past and present, in particular in the context of its interest in compiling oceanographic data sets. Details are provided of the procedures it adopted to ensure adequate internationally collaborative marine investigations during the first part of the century, such as how it provided a forum for action by its member states, how it coordinated and published the results of scientific programs, and how it provided a foundation, through scientists employed in the ICES Office, for the establishment of the original oceanographic marine databases and associated products, and the scientific interpretation of the results. The growth and expansion of this area of ICES activity is then traced, taking into account the changing conditions for oceanographic data management resulting from the establishment of the National Data Centres, as well as the World Data Centres for Oceanography, which were created to meet the needs of the International Geophysical Year (IGY). Finally, there is a discussion of the way in which the very existence of ICES has proved to be a valuable source of old data, some of which have not yet been digitized, but which can be readily retrieved because they have been very carefully documented throughout the years. Lessons from this activity are noted, and suggestions are made on how the past experiences of ICES can be utilized to ensure the availability of marine data to present and future generations of scientists.

Dooley, Harry D.↗

Data management for community research projects: A JGOFS case study

Since the mid 1980s, much of the marine science research effort in the United Kingdom has been focused into large scale collaborative projects involving public sector laboratories and university departments, termed Community Research Projects. Two of these, the Biogeochemical Ocean Flux Study (BOFS) and the North Sea Project incorporated large scale data collection to underpin multidisciplinary modeling efforts. The challenge of providing project data sets to support the science was met by a small team within the British Oceanographic Data Centre (BODC) operating as a topical data center. The role of the data center was to both work up the data from the ship's sensors and to combine these data with sample measurements into online databases. The working up of the data was achieved by a unique symbiosis between data center staff and project scientists. The project management, programming and data processing skills of the data center were combined with the oceanographic experience of the project communities to develop a system which has produced quality controlled, calibrated data sets from 49 research cruises in 3.5 years of operation. The data center resources required to achieve this were modest and far outweighed by the time liberated in the scientific community by the removal of the data processing burden. Two online project databases have been assembled containing a very high proportion of the data collected. As these are under the control of BODC their long term availability as part of the UK national data archive is assured. The success of the topical data center model for UK Community Research Project data management has been founded upon the strong working relationships forged between the data center and project scientists. These can only be established by frequent personal contact and hence the relatively small size of the UK has been a critical factor. However, projects covering a larger, even international scale could be successfully supported by a network of topical data centers managing online databases which are interconnected by object oriented distributed data management systems over wide area networks.

Lowry, Roy K.↗

Wrap-up session

Listening to the case studies that were presented it became quite evident that the best data management systems were the ones where data managers and research scientists worked as a team developed in the early stages of project planning. Examples that were given included WOCE Data Assembly Centres e.g., Drifters, the Global Temperature Salinity Pilot Project (GTSPP) collaboration with Joint Analyses Centres in the U.S. and Australia, and JGOFS/BOFS development of Topical Centres. While each of these has some elements unique to the project, each had brought together 'teams' of Principal Investigators (PI's) and data management experts at an early stage of project development. Conversely, projects which had considered data management as a totally separate activity with lower priority often failed to provide the service required to meet scientific objectives. Therefore, the following actions should be brought to the attention of relevant groups within the IOC and other international organizations: (1) Publicize, at the national and international level, underway data/scientist collaborations that may be used as models in planning for the future. (2) Reduce adversarial situations where data managers and scientists appear to be in competition. (3) Colocation and other forms of collaboration often results in very high quality data sets and more timely data submission. Improved timeliness of data submissions was a common theme throughout the workshop and must be considered an important element in all future plans. Improvements in timely submission of data were noted. In order to continue this trend the advantages of timely submission of data must be stressed to those planning new ocean science projects.

Holland, Geoffrey↗

Geographic information system for fusion and analysis of high-resolution remote sensing and ground truth data

We seek to combine high-resolution remotely sensed data with models and ground truth measurements, in the context of a Geographical Information System, integrated with specialized image processing software. We will use this integrated system to analyze the data from two Case Studies, one at a bore Al forest site, the other a tropical forest site. We will assess the information content of the different components of the data, determine the optimum data combinations to study biogeophysical changes in the forest, assess the best way to visualize the results, and validate the models for the forest response to different radar wavelengths/polarizations. During the 1990's, unprecedented amounts of high-resolution images from space of the Earth's surface will become available to the applications scientist from the LANDSAT/TM series, European and Japanese ERS-1 satellites, RADARSAT and SIR-C missions. When the Earth Observation Systems (EOS) program is operational, the amount of data available for a particular site can only increase. The interdisciplinary scientist, seeking to use data from various sensors to study his site of interest, may be faced with massive difficulties in manipulating such large data sets, assessing their information content, determining the optimum combinations of data to study a particular parameter, visualizing his results and validating his model of the surface. The techniques to deal with these problems are also needed to support the analysis of data from NASA's current program of Multi-sensor Airborne Campaigns, which will also generate large volumes of data. In the Case Studies outlined in this proposal, we will have somewhat unique data sets. For the Bonanza Creek Experimental Forest (Case I) calibrated DC-8 SAR data and extensive ground truth measurement are already at our disposal. The data set shows documented evidence to temporal change. The Belize Forest Experiment (Case II) will produce calibrated DC-8 SAR and AVIRIS data, together with extensive measurements on the tropical rain forest itself. The extreme range of these sites, one an Arctic forest, the other a tropical rain forest, has been deliberately chosen to find common problems which can lead to generalized observations and unique problems with data which raise issues for the EOS System.

Freeman, Anthony↗

Construction of an advanced software tool for planetary atmospheric modeling

Scientific model-building can be a time intensive and painstaking process, often involving the development of large complex computer programs. Despite the effort involved, scientific models cannot be distributed easily and shared with other scientists. In general, implemented scientific models are complicated, idiosyncratic, and difficult for anyone but the original scientist/programmer to understand. We propose to construct a scientific modeling software tool that serves as an aid to the scientist in developing, using and sharing models. The proposed tool will include an interactive intelligent graphical interface and a high-level domain-specific modeling language. As a test bed for this research, we propose to develop a software prototype in the domain of planetary atmospheric modeling.

Friedland, Peter↗

A database for propagation models

In June 1991, a paper at the fifteenth NASA Propagation Experimenters Meeting (NAPEX 15) was presented outlining the development of a database for propagation models. The database is designed to allow the scientists and experimenters in the propagation field to process their data through any known and accepted propagation model. The architecture of the database also incorporates the possibility of changing the standard models in the database to fit the scientist's or the experimenter's needs. The database not only provides powerful software to process the data generated by the experiments, but is also a time- and energy-saving tool for plotting results, generating tables, and producing impressive and crisp hard copy for presentation and filing.

Kantak, Anil V.↗

Astrophysics science operations in the Great Observatories era

Plans for Astrophysics science operations during the decade of the nineties are described from the point of view of a scientist who wishes to make a space-borne astronomical observation or to use archival astronomical data. 'Science Operations' include the following: proposal preparation, observation planning and execution, data collection, data processing and analysis, and dissemination of results. For each of these areas of science operations, we derive technology requirements for the next ten to twenty years. The scientist will be able to use a variety of services and infrastructure, including the 'Astrophysics Data System.' The current status and plans for these science operations services are described.

Riegler, Guenter R.↗

Science operations for future space astrophysics missions

Plans for astrophysics science operations during the decade of the nineties are described from the point of view of a scientist who wishes to make a space-borne astronomical observation or to use archival astronomical data. In the process of preparing a proposal making an observation, and carrying out data processing, analysis, and dissemination of results, the scientist will be able to use a variety of services and infrastructure, including the 'Astrophysics Data System'. The current status and plans for these science operations services are described.

Riegler, Guenther H.↗

Spacecraft design considerations for an Inner Magnetosphere Imager mission

Imaging the Earth's magnetosphere from space will enable scientists to better understand the global shape of the inner magnetosphere, its components and processes. The proposed Inner Magnetosphere Imager (IMI) mission will obtain the first simultaneous images of the component regions of the inner magnetosphere and will enable scientists to relate these global images to internal and external influences as well as local observations. NASA's Marshall Space Flight Center (MSFC) is performing a concept definition study of the proposed mission. As currently envisioned, the baseline mission calls for an instrument complement of approximately seven imagers to be flown in an elliptical Earth orbit with an apogee of seven Earth Radii (RE). Several spacecraft concepts have been examined for the mission. The baseline concept utilizes a spinning spacecraft with a despun platform, the second uses a three-axis stabilized spacecraft with a spinning platform, while the third option splits the instruments onto two small satellites; a spinning spacecraft and a complementary three-axis stabilized spacecraft. This paper will address the mission objectives, the rationale for using proven spacecraft designs, and the preliminary concept definition study team results for all three options.

Herrmann, Melody C.↗

Artificial intelligence support for scientific model-building

Scientific model-building can be a time-intensive and painstaking process, often involving the development of large and complex computer programs. Despite the effort involved, scientific models cannot easily be distributed and shared with other scientists. In general, implemented scientific models are complex, idiosyncratic, and difficult for anyone but the original scientific development team to understand. We believe that artificial intelligence techniques can facilitate both the model-building and model-sharing process. In this paper, we overview our effort to build a scientific modeling software tool that aids the scientist in developing and using models. This tool includes an interactive intelligent graphical interface, a high-level domain specific modeling language, a library of physics equations and experimental datasets, and a suite of data display facilities.

Keller, Richard M.↗

A program of correlated observations using the EGRET instrument on GRO and the IMB neutrino detector

A reliable, real-time supernova monitoring system was devised using the IMB neutrino detector to serve as an 'early-warning' system for EGRET and other instruments on GRO. New methods and software were developed to allow the IMB monitoring computer in Cleveland to: recognize that a trigger burst had occurred; make a judgement on whether the burst was spurrious or an actual supernova; prepare brief summary files and 'quick-look' data so that a final disposition could be made by a trained scientist; and contact the 'watch' scientist via personal beeper in Baton Rouge. This system ran from Dec. 1990 to Apr. 1991, when the neutrino detector failed for unrelated reasons. In addition to the supernova system, high-energy neutrino data was prepared and formatted for comparison with EGRET gamma-ray data.

Svoboda, Robert C.↗