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NASA NTRS1991

A guide to NASA's Pilot Land Data System (PLDS)

NASA's Pilot Land Data System (PLDS) is a distributed information management system designed to support NASA's land science community. The PLDS provides a wide range of services including management of information about scientific data, access to a library of scientific data, a data ordering capability, communications, connection to data analysis facilities, and electronic mail. The PLDS provides these services by offering the scientist the capability to search for and order data, and to communicate electronically with other scientists and computers. Three functions enable scientists to find what data are available and where they reside. The first two, Find data summaries and Read detailed descriptions give summary and detailed descriptions about data sets or groups of related data sets, science, projects, and institutions which archive land data. The third, gives information about specific pieces of data. This last function has two components, Search systemwide inventory and Search local inventory. The first component enables the user to find data elements (images, geological samples, transects, maps, etc.) that exist anywhere in the PLDS while the second has only information about data at the local site. The first enables the user to find pieces of data from several different data sets with the same temporal and spatial coverage and other elements common to most data sets, while the second allows the user to select a data set based on these descriptors and on those that are unique to a data set. The PLDS provides capabilities that enable electronic file transfers, intercomputer connection, and electronic mail. Both TCP/IP and DECnet protocols are supported via the NASA Science Internet (NIS). Access is also available through Telenet.

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NASA NTRS1992

Decision fusion with reliabilities in multisource data classification

In this paper, a new multisource classifier which is based on a fusion of the class decisions of each separate data set is proposed. Each data set is separately fed into the local classifier and a final classification is performed by summarizing these local class decisions. An optimum decision fusion rule based on the minimum expected cost is derived. This new decision fusion rule can handle not only data set reliabilities but also classwise reliabilities of each data set. Classification experiments with two remotely sensed Thematic Mapper (TM) data sets show promising improvement over conventional multisource classification algorithms.

Jeon, Byeungwoo↗

NASA NTRS2020

Development of a Display Tool to Quality Control Weather Balloon Data for Space Launch Vehicles Using Python

Continuous atmospheric data analysis is an important factor for space launch vehicle design and operations. The balloon quality control tool was developed by NASA’s Marshall Space Flight Center (MSFC) Natural Environments Branch (NEB) for monitoring quality control processes and verifying the automated flags created on the balloon data sets analyzed. The data sets currently analyzed are comprised of high-resolution and low-resolution balloon data from NASA Kennedy Space Center (KSC), co-located on the United States Air Force’s Eastern range (ER) at the Cape Canaveral Air Force Station. The NEB was tasked to perform a quality assessment of these data sets and needed a tool to confirm the quality control (QC) flags produced from an automated process and add additional QC flags if necessary. This Graphical User Interface (GUI) was developed to visualize all of the data from these balloon sets, display any flags from the automated QC process, and add additional flags to variables if necessary. The GUI was developed in Python 3.6 utilizing different packages available such as pandas for data analysis and manipulation, NumPy for high-performance multidimensional array and tools to compute with and manipulate arrays, Matplotlib for plotting data and Tkinter to build the GUI.

Jessica K Headley↗

NASA NTRS2020

Development of a Display Tool to Quality Control Weather Balloon Data for Space Launch Vehicles

Jessica K Headley↗

NASA NTRS1988

Integration of space and in situ observations to study global climate change

The use of model-based global data sets of atmospheric circulation for studying fundamental dynamical and physical processes is discussed, focusing on limitations of the available model-based data sets. Data from the Global Weather Experiment in 1979 were analyzed by two authorized level IIIb data centers in 1980 and in 1981. The analyses led to difference in data-sparse regions such as the tropics. Study areas which can be addressed by an internally-consistent long-term multivariate data set for the atmospheric circulation are considered, including mean climate, forcing for the ocean models, global hydrological cycle, atmospheric energetics, intraseasonal variability, land surface processes, and structure and variability of vertical velocity, divergence, and diabatic heating. It is concluded that the most comprehensive technique for integrating space and in situ observations to produce this type of data set would be a four-dimensional data assimilation system with a realistic physical model of the type employed in operational numerical weather prediction.

Bengtsson, L.↗

NASA NTRS2001

A Closed-Loop Optimal Neural-Network Controller to Optimize Rotorcraft Aeromechanical Behaviour: Output from Two Sample Cases - Volume 2

A closed-loop optimal neural-network controller technique was developed to optimize rotorcraft aeromechanical behaviour. This technique utilities a neural-network scheme to provide a general non-linear model of the rotorcraft. A modem constrained optimisation method is used to determine and update the constants in the neural-network plant model as well as to determine the optimal control vector. Current data is read, weighted, and added to a sliding data window. When the specified maximum number of data sets allowed in the data window is exceeded, the oldest data set is and the remaining data sets are re-weighted. This procedure provides at least four additional degrees-of-freedom in addition to the size and geometry of the neural-network itself with which to optimize the overall operation of the controller. These additional degrees-of-freedom are: 1. the maximum length of the sliding data window, 2. the frequency of neural-network updates, 3. the weighting of the individual data sets within the sliding window, and 4. the maximum number of optimisation iterations used for the neural-network updates.

Leyland, Jane Anne↗

NASA NTRS2012

Directed Design of Experiments for Validating Probability of Detection Capability of a Testing System

A method of validating a probability of detection (POD) testing system using directed design of experiments (DOE) includes recording an input data set of observed hit and miss or analog data for sample components as a function of size of a flaw in the components. The method also includes processing the input data set to generate an output data set having an optimal class width, assigning a case number to the output data set, and generating validation instructions based on the assigned case number. An apparatus includes a host machine for receiving the input data set from the testing system and an algorithm for executing DOE to validate the test system. The algorithm applies DOE to the input data set to determine a data set having an optimal class width, assigns a case number to that data set, and generates validation instructions based on the case number.

Generazio, Edward R.↗

NASA NTRS2007

Science Archives in the 21st Century: A NASA LAMBDA Report

Lambda is a thematic data center that focuses on serving the cosmic microwave background (CMB) research community. LAMBDA is an active archive for NASA's Cosmic Background Explorer (COBE) and Wilkinson Microwave Anisotropy Probe (WMAP) mission data sets. In addition, LAMBDA provides analysis software, on-line tools, relevant ancillary data and important web links. LAMBDA also tries to preserve the most important ground-based and suborbital CMB data sets. CMB data is unlike other astrophysical data, consisting of intrinsically diffuse surface brightness photometry with a signal contrast of the order 1 part in 100,000 relative to the uniform background. Because of the extremely faint signal levels, the signal-to-noise ratio is relatively low and detailed instrument-specific knowledge of the data is essential. While the number of data sets being produced is not especially large, those data sets are becoming large and complex. That tendency will increase when the many polarization experiments currently being deployed begin producing data. The LAMBDA experience supports many aspects of the NASA data archive model developed informally over the last ten years-that small focused data centers are often more effective than larger more ambitious collections, for example; that data centers are usually best run by active scientists; that it can be particularly advantageous if those scientists are leaders in the use of the archived data sets; etc. LAMBDA has done some things so well that they might provide lessons for other archives. A lot of effort has been devoted to developing a simple and consistent interface to data sets, for example; and serving all the documentation required via simple 'more' pages and longer explanatory supplements. Many of the problems faced by LAMBDA will also not surprise anyone trying to manage other space science data. These range from persuading mission scientists to provide their data as quickly as possible, to dealing with a high volume of nuisance (spam) messages. Because so many data center problems and solutions are common across individual data centers and disciplines it would be very valuable to establish some new systems of communication - such as informal email lists for administrators and developers. But resources are very limited, so new timeconsuming and inefficient mechanisms - like too-frequent and too-structured meetingsshould be avoided. Although there are great advantages to being small, agile and independent, there are also some areas where science data centers within and without NASA could be better coordinated - for the assignment of persistent identifiers; to encourage the early adoption of useful standards and technologies; etc. Some super-structure to facilitate such coordination might be beneficial as long as it doesn't begin to control the other work of the archives, and become a "methodology police". In this respect the CCSDS "Reference Model for an Open Archive Information System" is a little worrying. It may be that the closer a data center gets to following such a detailed prescription, the less effective it will become. It is much better to have an informal coordination process than a bureaucratic straight-jacket.

Butterworth, P.↗

DOE OSTI2025

Cambium 2024 Scenario Descriptions and Documentation

The National Renewable Energy Laboratory's (NREL's) Cambium data sets are annually released sets of simulated hourly data for a range of modeled futures of the U.S. electric sector with metrics designed to be useful for long-term decision- making. The 2024 Cambium data set is the fifth annual release. The data sets are a companion product to NREL's Standard Scenarios, which are likewise released annually and are a set of projections of how the U.S. electric sector could evolve across a suite of different potential futures, but covering more scenarios with less temporal granularity. Information about Cambium and related publications can be found at https://www.nrel.gov/analysis/cambium.html, and the Cambium data sets can be viewed and downloaded at https://scenarioviewer.nrel.gov/. In this documentation, we describe Cambium 2024's scenarios, define the metrics, and document the Cambium-specific methods for calculating those metrics.

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NASA NTRSDate not supplied

Identifying Trends in Landing Profiles After Long Duration Spaceflight

BACKGROUND As NASA’s mission programs begin to shift from Low Earth Orbit (LEO) to planetary mission profiles, the importance of understanding the phenomena a human experience when returning from spaceflight is of increased importance. The purpose of this study was to assess trends across individuals in the symptoms experienced during the landing process of long duration ISS missions. METHODS Data for this study is an aggregation of mission level data from forms used by crew surgeons at R+0, electronic medical records, notes from weekly Space Medicine Operation Team meetings, records in the Shuttle Mission Data Archive, and data collected by research teams in the Human Research Program (HRP). Aggregated data was used in descriptive analysis of the trends in medical events and countermeasure use. The data was also used to identify high value targets for emphasis in on going surveillance efforts. RESULTS Completeness of reporting varied greatly over time and across missions dependent on information sources available for data extraction. Landing forms provided the most complete data but still missed or left unconfirmed, several, common symptoms, and countermeasures. Data aggregation did show to cover gaps within individual data sources. Commonly reported symptoms included nystagmus, vertigo, and nausea. Common protocols for fluid loading and meclizine are reflected within the data set. DISCUSSION The data set generated in this project provides a foundation that show how symptoms of astronauts as they return to Earth varies across the long duration ISS missions. While there is an abundance of information provided within the data set, there are still inconsistencies in reporting especially in the absence of the landing day form. Further data collection practices should be standardized to ease the burden on crew surgeons during R+0 exams and better collect high value variables.

Sam Jacobs↗

NASA NTRS1976

A self-documenting source-independent data format for computer processing of tensor time series

The UCLA Space Science Group has developed a fixed format intermediate data set called a block data set, which is designed to hold multiple segments of multicomponent sampled data series. The format is sufficiently general so that tensor functions of one or more independent variables can be stored in the form of virtual data. This makes it possible for the unit data records of the block data set to be arrays of a single dependent variable rather than discrete samples. The format is self-documenting with parameter, label and header records completely characterizing the contents of the file. The block data set has been applied to the filing of satellite data (of ATS-6 among others).

Mcpherron, R. L.↗

NASA NTRS2004

Archiving Space Geodesy Data for 20+ Years at the CDDIS

Since 1982, the Crustal Dynamics Data Information System (CDDIS) has supported the archive and distribution of geodetic data products acquired by NASA programs. These data include GPS (Global Positioning System), GLONASS (GLObal NAvigation Satellite System), SLR (Satellite Laser Ranging), VLBI (Very Long Baseline Interferometry), and DORIS (Doppler Orbitography and Radiolocation Integrated by Satellite). The data archive supports NASA's space geodesy activities through the Solid Earth and Natural Hazards (SENH) program. The CDDIS data system and its archive have become increasingly important to many national and international programs, particularly several of the operational services within the International Association of Geodesy (IAG), including the International GPS Service (IGS), the International Laser Ranging Service (ILRS), the International VLBI Service for Geodesy and Astrometry (IVS), the International DORIS Service (IDS), and the International Earth Rotation Service (IERS). The CDDIS provides easy and ready access to a variety of data sets, products, and information about these data. The specialized nature of the CDDIS lends itself well to enhancement and thus can accommodate diverse data sets and user requirements. All data sets and metadata extracted from these data sets are accessible to scientists through ftp and the web; general information about each data set is accessible via the web. The CDDIS, including background information about the system and its user communities, the computer architecture, archive contents, available metadata, and future plans will be discussed.

Noll, Carey E.↗

NASA NTRS2002

Global Precipitation Analyses at Time Scales of Monthly to 3-Hourly

Global precipitation analysis covering the last few decades and the impact of the new TRMM precipitation observations are discussed. The 20+ year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/GEWEX) Global Precipitation Climatology Project (GPCP) is used to explore global and regional variations and trends and is compared to the much shorter TRMM (Tropical Rainfall Measuring Mission) tropical data set. The GPCP data set shows no significant trend in precipitation over the twenty years, unlike the positive trend in global surface temperatures over the past century. Regional trends are also analyzed. A trend pattern that is a combination of both El Nino and La Nina precipitation features is evident in the Goodyear data set. This pattern is related to an increase with time in the number of combined months of El Nino and La Nina during the Goodyear period. Monthly anomalies of precipitation are related to ENRON variations with clear signals extending into middle and high latitudes of both hemispheres. The GPCP daily, 1 degree latitude-longitude analysis, which is available from January 1997 to the present is described and the evolution of precipitation patterns on this time scale related to El Nino and La Nina is described. Finally, a TRMM-based Based analysis is described that uses TRMM to calibrate polar-orbit microwave observations from SSM/I and geosynchronous OR observations and merges the various calibrated observations into a final, Baehr resolution map. This TRMM standard product will be available for the entire TRMM period (January Represent). A real-time version of this merged product is being produced and is available at 0.25 degree latitude-longitude resolution over the latitude range from 50 deg. N -50 deg. S. Examples will be shown, including its use in monitoring flood conditions.

Adler, Robert F.↗

NASA NTRS2002

Global Precipitation Analyses (3-Hourly to Monthly) Using TRMM, SSM/I and other Satellite Information

Global precipitation analysis covering the last few decades and the impact of the new TRMM precipitation observations are discussed. The 20+ year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/GEWEX) Global Precipitation Climatology Project (GPCP) is used to explore global and regional variations and trends and is compared to the much shorter TRMM(Tropical Rainfall Measuring Mission) tropical data set. The GPCP data set shows no significant trend in precipitation over the twenty years, unlike the positive trend in global surface temperatures over the past century. Regional trends are also analyzed. A trend pattern that is a combination of both El Nino and La Nina precipitation features is evident in the 20-year data set. This pattern is related to an increase with time in the number of combined months of El Nino and La Nina during the 20 year period. Monthly anomalies of precipitation are related to ENS0 variations with clear signals extending into middle and high latitudes of both hemispheres. The GPCP daily, 1 deg. latitude-longitude analysis, which is available from January 1997 to the present is described and the evolution of precipitation patterns on this time scale related to El Nino and La Nina is discussed. Finally, a TRMM-based 3-hr analysis is described that uses TRMM to calibrate polar-orbit microwave observations from SSM/I and geosynchronous IR observations and merges the various calibrated observations into a final, 3-hr resolution map. This TRMM standard product will be available for the entire TRMM period (January 1998-present). A real-time version of this merged product is being produced and is available at 0.25 deg. latitude-longitude resolution over the latitude range from 5O deg. N-50 deg. S. Examples are shown, including its use in monitoring flood conditions.

Adler, Robert F.↗

NASA NTRS2006

Stratospheric Aerosol and Gas Experiment (SAGE) II and III Aerosol Extinction Measurements in the Arctic Middle and Upper Troposphere

In recent years, substantial effort has been expended toward understanding the impact of tropospheric aerosols on Arctic climate and chemistry. A significant part of this effort has been the collection and documentation of extensive aerosol physical and optical property data sets. However, the data sets present significant interpretive challenges because of the diverse nature of these measurements. Among the longest continuous records is that by the spaceborne Stratospheric Aerosol and Gas Experiment (SAGE) II. Although SAGE tropospheric measurements are restricted to the middle and upper troposphere, they may be able to provide significant insight into the nature and variability of tropospheric aerosol, particularly when combined with ground and airborne observations. This paper demonstrates the capacity of aerosol products from SAGE II and its follow-on experiment SAGE III to describe the temporal and vertical variations of Arctic aerosol characteristics. We find that the measurements from both instruments are consistent enough to be combined. Using this combined data set, we detect a clear annual cycle in the aerosol extinction for the middle and upper Arctic troposphere.

Treffeisen, R. E.↗

NASA NTRS2004

Benchmarking Memory Performance with the Data Cube Operator

Data movement across a computer memory hierarchy and across computational grids is known to be a limiting factor for applications processing large data sets. We use the Data Cube Operator on an Arithmetic Data Set, called ADC, to benchmark capabilities of computers and of computational grids to handle large distributed data sets. We present a prototype implementation of a parallel algorithm for computation of the operatol: The algorithm follows a known approach for computing views from the smallest parent. The ADC stresses all levels of grid memory and storage by producing some of 2d views of an Arithmetic Data Set of d-tuples described by a small number of integers. We control data intensity of the ADC by selecting the tuple parameters, the sizes of the views, and the number of realized views. Benchmarking results of memory performance of a number of computer architectures and of a small computational grid are presented.

Frumkin, Michael A.↗

NASA NTRS2012

Quasi-Global Precipitation as Depicted in the GPCPV2.2 and TMPA V7

After a lengthy incubation period, the year 2012 saw the release of the Global Precipitation Climatology Project (GPCP) Version 2.2 monthly dataset and the TRMM Multi-satellite Precipitation Analysis (TMPA) Version 7. One primary feature of the new data sets is that DMSP SSMIS data are now used, which entailed a great deal of development work to overcome calibration issues. In addition, the GPCP V2.2 included a slight upgrade to the gauge analysis input datasets, particularly over China, while the TMPA V7 saw more-substantial upgrades: 1) The gauge analysis record in Version 6 used the (older) GPCP monitoring product through April 2005 and the CAMS analysis thereafter, which introduced an inhomogeneity. Version 7 uses the Version 6 GPCC Full analysis, switching to the Version 4 Monitoring analysis thereafter. 2) The inhomogeneously processed AMSU record in Version 6 is uniformly processed in Version 7. 3) The TMI and SSMI input data have been upgraded to the GPROF2010 algorithm. The global-change, water cycle, and other user communities are acutely interested in how these data sets compare, as consistency between differently processed, long-term, quasi-global data sets provides some assurance that the statistics computed from them provide a good representation of the atmosphere's behavior. Within resolution differences, the two data sets agree well over land as the gauge data (which tend to dominate the land results) are the same in both. Over ocean the results differ more because the satellite products used for calibration are based on very different algorithms and the dominant input data sets are different. The time series of tropical (30 N-S) ocean average precipitation shows that the TMPA V7 follows the TMI-PR Combined Product calibrator, although running approximately 5% higher on average. The GPCP and TMPA time series are fairly consistent, although the GPCP runs approximately 10% lower than the TMPA, and has a somewhat larger interannual variation. As well, the GPCP and TMPA interannual variations have an apparent phase shift, with GPCP running a few months later. Additional diagnostics will include mean maps and selected scatter plots.

Huffman, George J.↗

NASA NTRS2010

Community-Based Services that Facilitate Interoperability and Intercomparison of Precipitation Datasets from Multiple Sources

Over the past 12 years, large volumes of precipitation data have been generated from space-based observatories (e.g., TRMM), merging of data products (e.g., gridded 3B42), models (e.g., GMAO), climatologies (e.g., Chang SSM/I derived rain indices), field campaigns, and ground-based measuring stations. The science research, applications, and education communities have greatly benefited from the unrestricted availability of these data from the Goddard Earth Sciences Data and Information Services Center (GES DISC) and, in particular, the services tailored toward precipitation data access and usability. In addition, tools and services that are responsive to the expressed evolving needs of the precipitation data user communities have been developed at the Precipitation Data and Information Services Center (PDISC) (http://disc.gsfc.nasa.gov/precipitation or google NASA PDISC), located at the GES DISC, to provide users with quick data exploration and access capabilities. In recent years, data management and access services have become increasingly sophisticated, such that they now afford researchers, particularly those interested in multi-data set science analysis and/or data validation, the ability to homogenize data sets, in order to apply multi-variant, comparison, and evaluation functions. Included in these services is the ability to capture data quality and data provenance. These interoperability services can be directly applied to future data sets, such as those from the Global Precipitation Measurement (GPM) mission. This presentation describes the data sets and services at the PDISC that are currently used by precipitation science and applications researchers, and which will be enhanced in preparation for GPM and associated multi-sensor data research. Specifically, the GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) will be illustrated. Giovanni enables scientific exploration of Earth science data without researchers having to perform the complicated data access and match-up processes. In addition, PDISC tool and service capabilities being adapted for GPM data will be described, including the Google-like Mirador data search and access engine; semantic technology to help manage large amounts of multi-sensor data and their relationships; data access through various Web services (e.g., OPeNDAP, GDS, WMS, WCS); conversion to various formats (e.g., netCDF, HDF, KML (for Google Earth)); visualization and analysis of Level 2 data profiles and maps; parameter and spatial subsetting; time and temporal aggregation; regridding; data version control and provenance; continuous archive verification; and expertise in data-related standards and interoperability. The goal of providing these services is to further the progress towards a common framework by which data analysis/validation can be more easily accomplished.

Liu, Zhong↗