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NASA NTRS2001

Simple, Scalable, Script-Based Science Processor (S4P)

The development and deployment of data processing systems to process Earth Observing System (EOS) data has proven to be costly and prone to technical and schedule risk. Integration of science algorithms into a robust operational system has been difficult. The core processing system, based on commercial tools, has demonstrated limitations at the rates needed to produce the several terabytes per day for EOS, primarily due to job management overhead. This has motivated an evolution in the EOS Data Information System toward a more distributed one incorporating Science Investigator-led Processing Systems (SIPS). As part of this evolution, the Goddard Earth Sciences Distributed Active Archive Center (GES DAAC) has developed a simplified processing system to accommodate the increased load expected with the advent of reprocessing and launch of a second satellite. This system, the Simple, Scalable, Script-based Science Processor (S42) may also serve as a resource for future SIPS. The current EOSDIS Core System was designed to be general, resulting in a large, complex mix of commercial and custom software. In contrast, many simpler systems, such as the EROS Data Center AVHRR IKM system, rely on a simple directory structure to drive processing, with directories representing different stages of production. The system passes input data to a directory, and the output data is placed in a "downstream" directory. The GES DAAC's Simple Scalable Script-based Science Processing System is based on the latter concept, but with modifications to allow varied science algorithms and improve portability. It uses a factory assembly-line paradigm: when work orders arrive at a station, an executable is run, and output work orders are sent to downstream stations. The stations are implemented as UNIX directories, while work orders are simple ASCII files. The core S4P infrastructure consists of a Perl program called stationmaster, which detects newly arrived work orders and forks a job to run the appropriate executable (registered in a configuration file for that station). Although S4P is written in Perl, the executables associated with a station can be any program that can be run from the command line, i.e., non-interactively. An S4P instance is typically monitored using a simple Graphical User Interface. However, the reliance of S4P on UNIX files and directories also allows visibility into the state of stations and jobs using standard operating system commands, permitting remote monitor/control over low-bandwidth connections. S4P is being used as the foundation for several small- to medium-size systems for data mining, on-demand subsetting, processing of direct broadcast Moderate Resolution Imaging Spectroradiometer (MODIS) data, and Quick-Response MODIS processing. It has also been used to implement a large-scale system to process MODIS Level 1 and Level 2 Standard Products, which will ultimately process close to 2 TB/day.

Lynnes, Christopher↗

NASA NTRS2005

NASA GES DISC On-line Visualization and Analysis System for Gridded Remote Sensing Data

The ability to use data stored in the current NASA Earth Observing System (EOS) archives for studying regional or global phenomena is highly dependent on having a detailed understanding of the data's internal structure and physical implementation. Gaining this understanding and applying it to data reduction is a time-consuming task that must be undertaken before the core investigation can begin. This is an especially difficult challenge when science objectives require users to deal with large multi-sensor data sets that are usually of different formats, structures, and resolutions. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has taken a major step towards meeting this challenge by developing an infrastructure with a Web interface that allows users to perform interactive analysis online without downloading any data, the GES-DISC Interactive Online Visualization and Analysis Infrastructure or "Giovanni." Giovanni provides interactive, online, analysis tools for data users to facilitate their research. There have been several instances of this interface created to serve TRMM users, Aerosol scientists, Ocean Color and Agriculture applications users. The first generation of these tools support gridded data only. The user selects geophysical parameters, area of interest, time period; and the system generates an output on screen in a matter of seconds. The currently available output options are: Area plot averaged or accumulated over any available data period for any rectangular area; Time plot time series averaged over any rectangular area; Hovmoller plots image view of any longitude-time and latitude-time cross sections; ASCII output for all plot types; Image animation for area plot. Another analysis suite deals with parameter intercomparison: scatter plots, temporal correlation maps, GIs-compatible outputs, etc. This allow user to focus on data content (i.e. science parameters) and eliminate the need for expensive learning, development and processing tasks that are redundantly incurred by an archive's user community. The current implementation utilizes the GrADS-DODS Server (GDS), and provides subsetting and analysis services across the Internet for any GrADS-readable dataset. The subsetting capability allows users to retrieve a specified temporal and/or spatial subdomain from a large dataset, eliminating the need to download everything simply to access a small relevant portion of a dataset. The analysis capability allows users to retrieve the results of an operation applied to one or more datasets on the server. We use this approach to read pre-processed binary files and/or to read and extract the needed parts directly from HDF or HDF-EOS files. These subsets then serve as inputs into GrADS analysis scripts. It can be used in a wide variety of Earth science applications: climate and weather events study and monitoring; modeling. It can be easily configured for new applications.

Leptoukh, Gregory G.↗

NASA NTRS1996

The EOS CERES Global Cloud Mask

To detect long-term climate trends, it is essential to produce long-term and consistent data sets from a variety of different satellite platforms. With current global cloud climatology data sets, such as the International Satellite Cloud Climatology Experiment (ISCCP) or CLAVR (Clouds from Advanced Very High Resolution Radiometer), one of the first processing steps is to determine whether an imager pixel is obstructed between the satellite and the surface, i.e., determine a cloud 'mask.' A cloud mask is essential to studies monitoring changes over ocean, land, or snow-covered surfaces. As part of the Earth Observing System (EOS) program, a series of platforms will be flown beginning in 1997 with the Tropical Rainfall Measurement Mission (TRMM) and subsequently the EOS-AM and EOS-PM platforms in following years. The cloud imager on TRMM is the Visible/Infrared Sensor (VIRS), while the Moderate Resolution Imaging Spectroradiometer (MODIS) is the imager on the EOS platforms. To be useful for long term studies, a cloud masking algorithm should produce consistent results between existing (AVHRR) data, and future VIRS and MODIS data. The present work outlines both existing and proposed approaches to detecting cloud using multispectral narrowband radiance data. Clouds generally are characterized by higher albedos and lower temperatures than the underlying surface. However, there are numerous conditions when this characterization is inappropriate, most notably over snow and ice of the cloud types, cirrus, stratocumulus and cumulus are the most difficult to detect. Other problems arise when analyzing data from sun-glint areas over oceans or lakes over deserts or over regions containing numerous fires and smoke. The cloud mask effort builds upon operational experience of several groups that will now be discussed.

Berendes, T. A.↗

NASA NTRSDate not supplied

Why Near Real-time/Low Latency is Important to Monitor the Changing World

An essential factor for remote sensing data products in impacting decision making is latency, or the time between earth observation and data are available to users. In many applications areas, latency plays an important or even decisive role where low latency earth observations help people to make timely, data-based decisions. Within the open and free NASA resources, NASA’s Land, Atmosphere Near real-time Capability for Earth Observing System (EOS) (LANCE) supports users interested in monitoring a wide variety of natural and man-made phenomena using near real-time (NRT) data products that are made available much quicker than routine processing allows. The combination of all available LANCE satellite products provides global coverage at multiple times per day, which makes it possible to meet user needs in various areas of applications including water resources, agriculture, air quality, wildland fire and many other disasters monitoring and management. As one of the prime users of LANCE, NASA’s Earth Science Applied Sciences Program promotes the use of LANCE data products to demonstrate applications in decision making and facilitates the end-user feedback to the science team to improve data products. One of the most critical applications that we expect data to be processed as close to the user as possible is wildland file response and management. User feedback indicates that LANCE NRT fire data products within 3 hours latency would meet the needs of the wildland fire community. Other examples of earth science application areas for which low latency is particularly important include detecting volcanic eruptions, early warning of disasters, tracking extreme weather events, and monitoring air quality.

Tian Yao↗

NASA NTRS2004

Distributive On-line Processing, Visualization and Analysis System for Gridded Remote Sensing Data

The ability to use data stored in the current Earth Observing System (EOS) archives for studying regional or global phenomena is highly dependent on having a detailed understanding of the data's internal structure and physical implementation. Gaining this understanding and applying it to data reduction is a time- consuming task that must be undertaken before the core investigation can begin. This is an especially difficult challenge when science objectives require users to deal with large multi-sensor data sets that are usually of different formats, structures, and resolutions, for example, when preparing data for input into modeling systems. The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has taken a major step towards meeting this challenge by developing an infrastructure with a Web interface that allows users to perform interactive analysis online without downloading any data, the GES-DISC Interactive Online Visualization and Analysis Infrastructure or "Giovanni." Giovanni provides interactive, online, analysis tools for data users to facilitate their research. There have been several instances of this interface created to serve TRMM users, Aerosol scientists, Ocean Color and Agriculture applications users. The first generation of these tools support gridded data only. The user selects geophysical parameters, area of interest, time period; and the system generates an output on screen in a matter of seconds. The currently available output options are: Area plot averaged or accumulated over any available data period for any rectangular area; Time plot time series averaged over any rectangular area; Time plots image view of any longitude-time and latitude-time cross sections; ASCII output for all plot types; Image animation for area plot. In the future, we will add correlation plots, GIS-compatible outputs, etc. This allow user to focus on data content (i.e. science parameters) and eliminate the need for expensive learning, development and processing tasks that are redundantly incurred by an archive's user community. The current implementation utilizes the GrADS-DODS Server (GDS), a stable, secure data server that provides subsetting and analysis services across the Internet for any GrADS-readable dataset. The subsetting capability allows users to retrieve a specified temporal and/or spatial subdomain from a large dataset, eliminating the need to download everything simply to access a small relevant portion of a dataset. The analysis capability allows users to retrieve the results of an operation applied to one or more datasets on the server. In our case, we use this approach to read pre-processed binary files and/or to read and extract the needed parts from HDF or HDF-EOS files. These subsets then serve as inputs into GrADS processing and analysis scripts. It can be used in a wide variety of Earth science applications: climate and weather events study and monitoring; modeling. It can be easily configured for new applications.

Leptoukh, G.↗

NASA NTRS1993

(abstract) The SIR-C/X-SAR Mission

The Shuttle Imaging Radar-C and X-Band Synthetic Aperture Radar (SIR-C/X-SAR) is a cooperative experiment between the National Aeronautics and Space Administration (NASA), the German Space Agency (DARA), and the Italian Space Agency (ASI). The experiment is the next evolutionary step in NASA's Spaceborne Imaging Radar (SIR) program that began with the Seasat SAR in 1978, and continued with SAR -A in 1981 and SAR-B in 1984. The program will eventually lead to the Earth Observing System (EOS) SAR later in this decade. SIR-C will provide increased capability over Seasat, SIR-A, and SIR-B by acquiring polarimetric images simultaneously at two microwave frequencies: L-band (wavelength 24 cm) and C-band (wavelength 6 cm). X-SAR will operate at X-band (wavelength 3 cm) with VV polarization, resulting in a three-frequency capability. Because radar backscatter is most strongly influenced by objects comparable in size to the radar wavelength, this multifrequency capability will provide information about the Earth's surface over a wide range of scales not discernable with single-frequency experiments. The polarimetric data will yield quantitative information about the surface geometric structure, vegetation dielectric properties, and surface discontinuities. The first SIR-C/X-SAR flight is planned for early in 1994, with two subsequent flights in different seasons to enable data aquisition under different environmental conditions. SIR-C/X-SAR will collect data for a period of 6 to 9 days during each flight. The instrument will be flown in a 57(deg) inclination orbit with a nomimal orbit altitude of 215 km. This altitude will result in a slightly drifting orbit. The latest status of the SIR-C/X-SAR mission and instrument design, science activities, and expected results will be presented.

SIR-C/XSAR radar backscatter surface geometric str↗

NASA NTRS2008

On-Orbit Noise Characterization for MODIS Reflective Solar Bands

Since launch, the Moderate Resolution Imaging Spectroradiometer (MODIS) has operated successfully on-board the NASA Earth Observing System (EOS) Terra and EOS Aqua spacecraft. MODIS is a passive cross-track scanning radiometer that makes observations in 36 spectral bands with spectral wavelengths from visible (VIS) to long-wave infrared. MODIS bands 1-19 and 26 are the reflective solar bands (RSB) with wavelengths from 0.41 to 2.2 micrometers. They are calibrated on-orbit using an on-board solar diffuser (SD) and a SD stability monitor (SDSM) system. For MODIS RSB, the level 1B calibration algorithm produces top of the atmosphere reflectance factors and radiances for every pixel of the Earth view. The sensor radiometric calibration accuracy, specified at each spectral band's typical scene radiance, is 2% for the RSB reflectance factors and 5% for the RSB radiances. Also specified at the typical scene radiance is the detector signal-to-noise ratio (SNR), a key sensor performance parameter that directly impacts its radiometric calibration accuracy and stability, as well as the image quality. This paper describes an on-orbit SNR characterization approach developed to evaluate and track MODIS RSB detector performance. In order to perform on-orbit SNR characterization, MODIS RSB detector responses to the solar illumination reflected from the SD panel must be corrected for factors due to variations of the solar angles and the SD bi-directional reflectance factor. This approach enables RSB SNR characterization to be performed at different response levels for each detector. On-orbit results show that both Terra and Aqua MODIS RSB detectors have performed well since launch. Except for a few noisy or inoperable detectors which were identified pre-launch, most RSB detectors continue to meet the SNR design requirements and are able to maintain satisfactory short-term stability. A comparison of on-orbit noise characterization results with results derived from pre-launch calibration and characterization are also provided.

Xiong, X.↗

NASA NTRS2005

The Case of Ozone Depletion

While the National Aeronautics and Space Administration (NASA) is widely perceived as a space agency, since its inception NASA has had a mission dedicated to the home planet. Initially, this mission involved using space to better observe and predict weather and to enable worldwide communication. Meteorological and communication satellites showed the value of space for earthly endeavors in the 1960s. In 1972, NASA launched Landsat, and the era of earth-resource monitoring began. At the same time, in the late 1960s and early 1970s, the environmental movement swept throughout the United States and most industrialized countries. The first Earth Day event took place in 1970, and the government generally began to pay much more attention to issues of environmental quality. Mitigating pollution became an overriding objective for many agencies. NASA's existing mission to observe planet Earth was augmented in these years and directed more toward environmental quality. In the 1980s, NASA sought to plan and establish a new environmental effort that eventuated in the 1990s with the Earth Observing System (EOS). The Agency was able to make its initial mark via atmospheric monitoring, specifically ozone depletion. An important policy stimulus in many respects, ozone depletion spawned the Montreal Protocol of 1987 (the most significant international environmental treaty then in existence). It also was an issue critical to NASA's history that served as a bridge linking NASA's weather and land-resource satellites to NASA s concern for the global changes affecting the home planet. Significantly, as a global environmental problem, ozone depletion underscored the importance of NASA's ability to observe Earth from space. Moreover, the NASA management team's ability to apply large-scale research efforts and mobilize the talents of other agencies and the private sector illuminated its role as a lead agency capable of crossing organizational boundaries as well as the science-policy divide.

Lambright, W. Henry↗

NASA NTRS2006

Constellation Operations: Lessons Learned For Future Exploration

The Earth science community has long advocated placing numerous instruments in space to study the Earth and its environment. Space agencies from many countries have responded to this call with a wide range of orbiting satellites. Scientists also envisioned placing some satellites in constellations, to enable diverse remote sensing instruments to observe the same part of the Earth (or its atmosphere) at about the same time, thereby increasing the opportunities for coincident science observations. The Earth Science Afternoon Constellation is answering this call, but there have been unique challenges on the way to its deployment. Currently, the Afternoon Constellation is to comprise six satellites. Three are currently on orbit: NASA's Earth Observing System (EOS)-Aqua (2002) and EOS-Aura (2004), and CNES's Polarization & Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) (2004). Two more satellites, the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and Cloudsat, are to be jointly launched in late 2005, followed by the Orbiting Carbon Observatory (OCO) in 2008. The Afternoon Constellation is unlike most satellite constellations in that: 1) It is not a homogenous mix of identical satellites; rather it comprises several satellites with complementary observational capabilities; 2) The satellites are not spaced around the Earth to provide instantaneous, global coverage (as for a communications satellite constellation); rather they orbit in close proximity so observations occur at about the same time over approximately the same region; and 3) Lastly, the satellites are not managed and controlled by one organization; rather the list of organizations is diverse: CNES in France, NASA Centers at Goddard, Langley, and the Jet Propulsion Laboratory, and the US Air Force facility in New Mexico. The PARASOL launch and early orbit (L&EO) phase proved to be a learning experience for constellation members (including Constellation management). Prior to launch, all members signed an operations coordination document that spelled out basic requirements for keeping the constellation safe and resolving non-nominal events. Once PARASOL reached orbit and the mission teams gained experience using the newly-developed constellation monitoring tools, it became clear that some of the guidelines in the signed agreements had to be adjusted. This paper presents the L&EO lessons learned and how they were used to prepare for the next phase - the period following the CloudSat/CALIPSO launch.

Kelly, Angelita C.↗

NASA NTRS1989

Improved capabilities of the Multispectral Atmospheric Mapping Sensor (MAMS)

The Multispectral Atmospheric Mapping Sensor (MAMS) is an airborne instrument being investigated as part of NASA's high altitude research program. Findings from work on this and other instruments have been important as the scientific justification of new instrumentation for the Earth Observing System (EOS). This report discusses changes to the instrument which have led to new capabilities, improved data quality, and more accurate calibration methods. In order to provide a summary of the data collected with MAMS, a complete list of flight dates and locations is provided. For many applications, registration of MAMS imagery with landmarks is required. The navigation of this data on the Man-computer Interactive Data Access System (McIDAS) is discussed. Finally, research applications of the data are discussed and specific examples are presented to show the applicability of these measurements to NASA's Earth System Science (ESS) objectives.

Jedlovec, Gary J.↗

NASA NTRS2000

Remote Sensing of Aerosol Over the Land from the Earth Observing System MODIS Instrument

On Dec 18, 1999, NASA launched the Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument on the Earth Observing System (EOS) Terra mission, in a spectacular launch. The mission will provide morning (10:30 AM) global observations of aerosol and other related parameters. It will be followed a year later by a MODIS instrument on EOS Aqua for afternoon observations (1:30 PM). MODIS will measure aerosol over land and ocean with its eight 500 m and 250 m channels in the solar spectrum (0-41 to 2.2 micrometers). Over the land MODIS will measure the total column aerosol loading, and distinguish between submicron pollution particles and large soil particles. Standard daily products of resolution of ten kilometers and global mapped eight day and monthly products on a 1x1 degree global scale will be produced routinely and make available for no or small reproduction charge to the international community. Though the aerosol products will not be available everywhere over the land, it is expected that they will be useful for assessments of the presence, sources and transport of urban pollution, biomass burning aerosol, and desert dust. Other measurements from MODIS will supplement the aerosol information, e.g., land use change, urbanization, presence and magnitude of biomass burning fires, and effect of aerosol on cloud microphysics. Other instruments on Terra, e.g. Multi-angle Imaging SpectroRadiometer (MISR) and the Clouds and the Earth's Radiant Energy System (CERES), will also measure aerosol, its properties and radiative forcing in tandem with the MODIS measurements. During the Aqua period, there are plans to launch in 2003 the Pathfinder Instruments for Cloud and Aerosol Spaceborne Observations (PICASSO) mission for global measurements of the aerosol vertical structure, and the PARASOL mission for aerosol characterization. Aqua-MODIS, PICASSO and PARASOL will fly in formation for detailed simultaneous characterization of the aerosol three-dimensional field, which will feed and evaluate global aerosol transport and climate models. In this talk, some examples of the MODIS measurements will be shown.

Kaufman, Yoram↗

NASA NTRS1995

Clouds and the Earth's Radiant Energy System (CERES) Algorithm Theoretical Basis Document: Cloud Analyses and Determination of Improved Top of Atmosphere Fluxes (Subsystem 4) - Volume 3

The theoretical bases for the Release 1 algorithms that will be used to process satellite data for investigation of the Clouds and Earth's Radiant Energy System (CERES) are described. The architecture for software implementation of the methodologies is outlined. Volume 3 details the advanced CERES methods for performing scene identification and inverting each CERES scanner radiance to a top-of-the-atmosphere (TOA) flux. CERES determines cloud fraction, height, phase, effective particle size, layering, and thickness from high-resolution, multispectral imager data. CERES derives cloud properties for each pixel of the Tropical Rainfall Measuring Mission (TRMM) visible and infrared scanner and the Earth Observing System (EOS) moderate-resolution imaging spectroradiometer. Cloud properties for each imager pixel are convolved with the CERES footprint point spread function to produce average cloud properties for each CERES scanner radiance. The mean cloud properties are used to determine an angular distribution model (ADM) to convert each CERES radiance to a TOA flux. The TOA fluxes are used in simple parameterization to derive surface radiative fluxes. This state-of-the-art cloud-radiation product will be used to substantially improve our understanding of the complex relationship between clouds and the radiation budget of the Earth-atmosphere system.

Source record↗

NASA NTRSDate not supplied

Conjunction Assessment(CA) Support Overview for the EOS Satellites

When a satellite is placed into its desired orbit, to achieve its designed mission objectives, it is imperative to maintain orbit requirements as well as the overall health and safety of the vehicle. One integral part of this process is ensuring that the satellite does not collide with any other vehicle or object in space, which can cause a detrimental consequence to the mission as well as to other satellites within the same orbit regime. To prevent such an occurrence, a thorough collision avoidance process must be followed. This process includes constantly monitoring potential conjunctions and performing collision avoidance maneuvers when necessary, while remaining within the limitations of the mission’s orbit maintenance requirements. This presentation will describe the Earth Observing System (EOS) Aqua, Aura and Terra satellite’s operational collision a! voidance process. It will highlight the routine conjunction assessment screening and data evaluation process performed by the NASA/GSFC EOS Collision Avoidance Engineers. The presentation will include background information, a summary of operational activities and duties, internal tools used for support, EOS High Interest Event statistics, and potential challenges expected in the future.

Syed Hasan↗

NASA NTRS2003

The Orbiting Carbon Observatory mission

The Orbiting Carbon Observatory (OCO) mission was selected by NASA's Office of Earth Science as the fifth mission in its Earth System Science Pathfinder (ESSP) Program. OCO will make the first global, space-based measurements of atmospheric CO2 with the precision, resolution, and coverage needed to characterize sources and sinks of this important greenhouse gas. These measurements will improve our ability to forecasts CO2-induced climate change. OCO will fly in a 1:15 PM sun-synchronous orbit, sharing its ground track with the Earth Observing System (EOS) Aqua platform. It will carry high-resolution spectrometers to measure reflected sunlight in the molecular oxygen (O2) A-band at 0.76-microns and the CO2 bands at 1.61 and 2.06 microns to retrieve the column-averaged CO2 dry air mole fraction, XCO2. A comprehensive validation and correlative measurement program has been incorporated into this mission to ensure that XCO2 can be retrieved with precisions of 0.3% (1 ppm) on regional scales.

atmospheric chemistry↗

NASA NTRS2006

Development and Implementation of a Comprehensive Radiometric Validation Protocol for the CERES Earth Radiation Budget Climate Record Sensors

The CERES Flight Models 1 through 4 instruments were launched aboard NASA's Earth Observing System (EOS) Terra and Aqua Spacecraft into 705 Km sun-synchronous orbits with 10:30 a.m. and 1:30 p.m. equatorial crossing times. These instruments supplement measurements made by the CERES Proto Flight Model (PFM) instrument launched aboard NASA's Tropical Rainfall Measuring Mission (TRMM) into a 350 Km, 38-degree mid-inclined orbit. CERES Climate Data Records consist of geolocated and calibrated instantaneous filtered and unfiltered radiances through temporally and spatially averaged TOA, Surface and Atmospheric fluxes. CERES filtered radiance measurements cover three spectral bands including shortwave (0.3 to 5 microns), total (0.3 to 100 microns) and an atmospheric window channel (8 to 12 microns). The CERES Earth Radiation Budget measurements represent a new era in radiation climate data, realizing a factor of 2 to 4 improvement in calibration accuracy and stability over the previous ERBE climate records, while striving for the next goal of 0.3-percent per decade absolute stability. The current improvement is derived from two sources: the incorporation of lessons learned from the ERBE mission in the design of the CERES instruments and the development of a rigorous and comprehensive radiometric validation protocol consisting of individual studies covering different spatial, spectral and temporal time scales on data collected both pre and post launch. Once this ensemble of individual perspectives is collected and organized, a cohesive and highly rigorous picture of the overall end-to-end performance of the CERES instrument's and data processing algorithms may be clearly established. This approach has resulted in unprecedented levels of accuracy for radiation budget instruments and data products with calibration stability of better than 0.2-percent and calibration traceability from ground to flight of 0.25-percent. The current work summarizes the development, philosophy and implementation of the protocol designed to rigorously quantify the quality of the data products as well as the level of agreement between the CERES TRMM, Terra and Aqua climate data records.

Priestley, K. J.↗

NASA NTRS2009

An Intelligent Archive Testbed Incorporating Data Mining

Many significant advances have occurred during the last two decades in remote sensing instrumentation, computation, storage, and communication technology. A series of Earth observing satellites have been launched by U.S. and international agencies and have been operating and collecting global data on a regular basis. These advances have created a data rich environment for scientific research and applications. NASA s Earth Observing System (EOS) Data and Information System (EOSDIS) has been operational since August 1994 with support for pre-EOS data. Currently, EOSDIS supports all the EOS missions including Terra (1999), Aqua (2002), ICESat (2002) and Aura (2004). EOSDIS has been effectively capturing, processing and archiving several terabytes of standard data products each day. It has also been distributing these data products at a rate of several terabytes per day to a diverse and globally distributed user community (Ramapriyan et al. 2009). There are other NASA-sponsored data system activities including measurement-based systems such as the Ocean Data Processing System and the Precipitation Processing system, and several projects under the Research, Education and Applications Solutions Network (REASoN), Making Earth Science Data Records for Use in Research Environments (MEaSUREs), and the Advancing Collaborative Connections for Earth-Sun System Science (ACCESS) programs. Together, these activities provide a rich set of resources constituting a value chain for users to obtain data at various levels ranging from raw radiances to interdisciplinary model outputs. The result has been a significant leap in our understanding of the Earth systems that all humans depend on for their enjoyment, livelihood, and survival. The trend in the community today is towards many distributed sets of providers of data and services. Despite this, visions for the future include users being able to locate, fuse and utilize data with location transparency and high degree of interoperability, and being able to convert data to information and usable knowledge in an efficient, convenient manner, aided significantly by automation (Ramapriyan et al. 2004; NASA 2005). We can look upon the distributed provider environment with capabilities to convert data to information and to knowledge as an Intelligent Archive in the Context of a Knowledge Building system (IA-KBS). Some of the key capabilities of an IA-KBS are: Virtual Product Generation, Significant Event Detection, Automated Data Quality Assessment, Large-Scale Data Mining, Dynamic Feedback Loop, and Data Discovery and Efficient Requesting (Ramapriyan et al. 2004).

Ramapriyan, H.↗

NASA NTRS1988

Plans for the development of EOS SAR systems using the Alaska SAR facility

The Alaska SAR Facility (ASF) program for the acquisition and processing of data from the ESA ERS-1, the NASDA ERS-1, and Radarsat and to carry out a program of science investigations using the data is introduced. Agreements for data acquisition and analysis are in place except for the agreement between NASA and Radarsat which is in negotiation. The ASF baseline system, consisting of the Receiving Ground System, the SAR Processor System and the Archive and Operations System, passed critical design review and is fully in implementation phase. Augments to the baseline system for systems to perform geophysical processing and for processing of J-ERS-1 optical data are in the design and implementation phase. The ASF provides a very effective vehicle with which to prepare for the Earth Observing System (EOS) in that it will aid the development of systems and technologies for handling the data volumes produced by the systems of the next decades, and it will also supply some of the data types that will be produced by EOS.

Carsey, F. D.↗

NASA NTRS1999

Point Response Characteristics for the CERES/EOS-PM, FM3 & FM4 instruments.

This paper describes the point source functions (PSF s) of the Clouds and the Earth s Radiant Energy System (CERES,) Earth Observing System (EOS,) afternoon platform (PM,) Flight Model 3 (FM3,) and Flight Model 4 (FM4) scanning instruments. The PSF (also known as the Point Response Function, or PRF) is vital to the accurate geo-location of the remotely sensed radiance measurements acquired by the instrument. This paper compares the characteristics of the FM3 and FM4 instruments with the earlier Proto Flight Model (PFM) on the Tropical Rainfall Measuring Mission (TRMM) platform, and the FM1 and FM2 Models on the EOS morning orbiting (AM) platform, which has recently been renamed "Terra". All of the PSF s were found to be quite comparable, and the previously noted "spreading" characteristic of the window (water vapor) channel PSF is analyzed Keywords: PSF, PRF, CERES, TRMM, EOS, Earth Radiation Budget

Paden, Jack↗