IN21A-1044
Instrument performance for IIP Tropospheric Infrared Mapping Spectrometers (TIMS) for vertically resolved CO
The NASA Earth Science Technology Office (ESTO) Instrument Incubator Program (IIP) Tropospheric Infrared Mapping Spectrometers (TIMS) have been developed to demonstrate measurement capability, when deployed in space, for multi-layer retrieval of CO from spectral measurements acquired in the solar reflective band ~ 4281 to 4301 cm-1 and in the thermal band ~ 2110 to 2165 cm-1. The presentation will describe [a] the top level designs [b] measured instrument performance parameters including spectral and spatial resolution, spectral quality and noise performance, [c] comparisons of the performance (spectral, spatial, noise) with instrument modeling and [d] calibration procedures and results for spectral registration, spectral response, flat fielding, zero level determination and radiometric. Good comparison with demonstration instrument performance and modeling gives a high level of confidence for instrument performance in the space based case. Lessons learned will be described. These are very valuable for the space deployed application. The TIMS are well suited for either LEO or GEO application.
IN21A-1045
IIP Tropospheric Infrared Mapping Spectrometers (TIMS) demonstration of CO retrieval, including multi-layer, from atmospheric data acquired simultaneously in the solar reflective region near 2.3 um and the thermal emissive region near 4.7 um
The NASA Earth Science Technology Office (ESTO) Instrument Incubator Program (IIP) Tropospheric Infrared Mapping Spectrometers (TIMS) have been developed to demonstrate measurement capability, when deployed in space, for multi-layer retrieval of CO from spectral measurements acquired in the solar reflective (SR) region ~ 4281 to 4301 cm-1 and in the thermal InfraRed (TIR) region ~ 2110 to 2165 cm-1. We describe joint deployment at Denver University (DU) with co-investigators there of the TIMS, and of the DU colleagues FTS, to acquire simultaneous measurements of atmospheric spectra in the SR and the TIR. The FTS provided validation radiance data for the TIMS. The TIMS retrievals of CO, H2O and CH4 agreed well with validation vs these as retrieved from the DU data, AIRS retrieval, standard models and ECMWF. The TIMS CO retrievals included column retrieved from the just the SR data, column retrieved from just the TIR data, and a simple two-layer retrieval from the combined data sets. The data were acquired in an operational mode that mimicked the operations in a conceptual application that would provide footprints, coverage, refresh time as in the Decadal Survey GEO-CAPE mission statement. Very encouraging CO precisions were achieved, e.g., the TIMS CO column retrieval from the SR data demonstrated better than the 10% precision requirement as listed on slide 32 of the GEO-CAPE Reference document http://geo- cape.larc.nasa.gov/docs/GEOMAC_FinalReport_no_costs.ppt
IN21A-1046
IIP Tropospheric Infrared Mapping Spectrometers (TIMS) measurements for widely varying terrain and atmospheric paths, example retrievals of albedos and atmospheric constituents
The NASA Earth Science Technology Office (ESTO) Instrument Incubator Program (IIP) Tropospheric Infrared Mapping Spectrometers (TIMS) have been developed to demonstrate measurement capability, when deployed in space, for multi-layer retrieval of CO from spectral measurements acquired in the solar reflective (SR) region ~ 4281 to 4301 cm-1 and in the thermal InfraRed (TIR) region ~ 2110 to 2165 cm 1. Measurements in the SR of widely varying terrain types were obtained in a single data frame. The slit was projected in a vertical orientation from a balcony on the Denver University building to a scene that included the foreground at slit bottom, then on going further up the slit to a near foothill range, and finally on top side of the slit to a distant snow capped mountain range. The scene provided albedo data for various surface types including green vegetation, a bright barren spot on the foothill, and the snow cap. It also provides varying path lengths through the atmosphere, e.g., 20 km to the foothill, and 100 km to the snow cap. We'll present examples of albedo retrieved for these various features, and for gasses retrieved along the various path lengths.
IN21A-1047
Exploring Earth Observation Time Series Data on the Web – Implementation of a Processing Service for Web-based Analysis.
Over the past decade there has been a general trend in information technology from monolithic desktop applications towards loosely coupled Web Services. Following this trend Web-based visualization of map like data (e.g. OGC Web Mapping Service) has found widespread use, especially as part of Spatial Data Infrastructures (SDI). In combination with metadata catalogues the primary aim of these map services is data publication and distribution, hence the capabilities are limited to viewing or browsing (e.g. zoom, pan, identify). Only a few examples exist enabling users to analyse data (e.g. calculating statistics or merging different data layers) through a web interface or Web Service. In this paper intermediate results are presented from research conducted on the implementation of an OGC Web Processing Service (WPS) for online analysis of Earth observation time series data. Earth observation data at regional to global scale has been collected with various sensors and satellite systems for more than three decades. The amounts of data acquired seem to have outpaced our ability to exploit and analysis it. With aid of consistent data products (e.g. MODIS suite of land surface products) and the advancements in information technology and in particular MDA, SOA and Grid computing the basis to overcome this shortfall is available. In this context the objective of this study was to develop a generic Processing Service for spatio- temporal exploration of coverage data. The advantage of implementing it as a WPS is that it can be accessed by any client (either a browser or a service) through the Internet and it delivers reproducible results facilitating interoperability and flexibility. Besides, WPS has been experimented as a standard processing interface for heterogeneous Grid infrastructures in the framework of the OGC-OGF interoperability initiative, facilitating scalability. Combining the WPS with a Catalogue Service (i.e. the OGC CS-W) allows users to select and access distributed data sources provided through Web Coverage Service (WCS) servers. They may be gridified, as well. This study is part of the development of the Siberian Earth System Science Cluster, a Spatial Data Infrastructure for remote sensing product generation, dissemination and analysis.
IN21A-1048
Extending TOPS: A Prototype MODIS Anomaly Detection Architecture
The management and processing of Earth science data has been gaining importance over the last decade
due to higher data volumes generated by a larger number of instruments, and due to the increase in
complexity of Earth science models that use this data. The volume of data itself is often a limiting factor in
obtaining the information needed by the scientists; without more sophisticated data volume reduction
technologies, possible key information may not be discovered. We are especially interested in automatic
identification of disturbances within the ecosystems (e,g, wildfires, droughts, floods, insect/pest damage, wind
damage, logging), and focusing our analysis efforts on the identified areas. There are dozens of variables
that define the health of our ecosystem and both long-term and short-term changes in these variables can
serve as early indicators of natural disasters and shifts in climate and ecosystem health. These changes can
have profound socio-economic impacts and we need to develop capabilities for identification, analysis and
response to these changes in a timely manner. Because the ecosystem consists of a large number of
variables, there can be a disturbance that is only apparent when we examine relationships among multiple
variables despite the fact that none of them is by itself alarming. We have to be able to extract information
from multiple sensors and observations and discover these underlying relationships. As the data volumes
increase, there is also potential for large number of anomalies to "flood" the system, so we need to provide
ability to automatically select the most likely ones and the most important ones and the ability to analyze the
anomaly with minimal involvement of scientists. We describe a prototype architecture for anomaly driven data
reduction for both near-real-time and archived surface reflectance data from the MODIS instrument collected
over Central California and test it using Orca and One-Class Support Vector Machines algorithms. We
demonstrate our efforts in the context of the Terrestrial Observation and Prediction System (TOPS), a flexible
modeling software system that integrates ecosystem models with frequent satellite and surface weather
observations to produce ecosystem nowcasts (assessments of current conditions) and forecasts useful in a
range of applications including natural resources management, public health and disaster management.
http://ecocast.arc.nasa.gov
IN21A-1049
Utilizing Grid Computing to Support Massive Real-time Computing
Static road routing applications consider a limited number of road characteristics in routing, and are well solved by Dijsktra and A* algorithms and their variations. However, the dynamics of our current traffic networks requires routing based on near real-time information, such as thunder storms, to produce timely routing results for end-users. The traditional Dijsktra and A* algorithms are not applicable because dynamic routing needs to route based on future predictions and time stamped travel time for road links. And the massive request numbers will require significant amount of computing power. This paper introduced a new approach using the grid computing techniques to support real-time routing. Within the approach, two hierarchies for the road network are constructed with the first hierarchy comprising the nodes of state highway and interstate highway, and the second one including the nodes of the entire road network. In the second hierarchy, besides the attributes of "real-time link traveling time" to adjacent nodes, each node of the network has additional attributes of "real-time link traveling time" to surrounding nodes of the first hierarchy. Then the second hierarchy network is partitioned into several grid sections, and each section with a route finding algorithm extended on Dijstra Algorithm, is submitted as a job to the grid computing to obtain real-time additional attributes of each node belong to this section. The attributes of each pair of OD, the origin and destination nodes, are read from grid computing in real-time, and a new network is constructed with the first hierarchy network and the pair of OD. Using the Extended Dijstra Algorithm, the real-time route for the pair of OD nodes in this new network, can be obtained.
IN21A-1050
Modeling of Tsunami Equations and Atmospheric Swirling Flows with a Graphics Processing Unit (GPU) and Radial Basis Functions (RBF)
The faster growth curves in the speed of GPUs relative to CPUs in recent years and its rapidly gained popularity has spawned a new area of development in computational technology. There is much potential in utilizing GPUs for solving evolutionary partial differential equations and producing the attendant visualization. We are concerned with modeling tsunami waves, where computational time is of extreme essence, for broadcasting warnings. In order to test the efficacy of the GPU on the set of shallow-water equations, we employed the NVIDIA board 8600M GT on a MacBook Pro. We have compared the relative speeds between the CPU and the GPU on a single processor for two types of spatial discretization based on second-order finite-differences and radial basis functions. RBFs are a more novel method based on a gridless and a multi- scale, adaptive framework. Using the NVIDIA 8600M GT, we received a speed up factor of 8 in favor of GPU for the finite-difference method and a factor of 7 for the RBF scheme. We have also studied the atmospheric dynamics problem of swirling flows over a spherical surface and found a speed-up of 5.3 using the GPU. The time steps employed for the RBF method are larger than those used in finite-differences, because of the much fewer number of nodal points needed by RBF. Thus, in modeling the same physical time, RBF acting in concert with GPU would be the fastest way to go.
IN21A-1051
The JPL Tropical Cyclone Information System: Data and Tools for Researchers
The JPL Tropical Cyclone Information System (TCIS) is now open to the public. This web portal is designed
to assist researchers by providing a one-stop shop for hurricane related data and analysis tools. While there
are currently many places that offer storm data, plots, and other information, none offer an extensive archive
of data files and images in a common space. The JPL TCIS was created to fill this gap.
As currently configured, the JPL Tropical Cyclone Portal has three main features for researchers. The first
feature consists of storm-scale data and plots for both observed and modeled data. As of the TCIS' first
release, the entire 2005 storm season has been populated with data and plots from AIRS, MLS, AMSU-A,
QuikSCAT, Argo floats, WRF models, GPS, and others. Storm data is subsetted to a 1000x1000 km window
around the hurricane track for all six oceanic cyclone basins, and all the available data during the life time of
any storm can be downloaded with one mouse click. Users can also view pre-generated storm-scale plots
from all these data sets that are all co-located to the same temporal and spatial parameters. Work is
currently underway to backfill all storm seasons to 1998 with as many relevant data sets as possible.
The second offering from this web portal are large-scale data sets and associated visualization tools powered
by Google Maps. On this interactive map, researchers can view a particular storm's intensity and track.
Users may also overlay large-scale data such as aerosol maps from MODIS and MISR, and a blended
microwave sea-surface temperature (SST) to gain an understanding of the large-scale environment of the
storm. For example, by using this map, the cold sea-surface temperature wake can be tracked as a storm
passes by.
The third feature of this portal deals with interactive model and data analysis. A single-parameter analysis
tools has recently been developed and added to this portal where users can plot maps, profiles, and
histograms of any given data set on this portal and also get several statistics, such as the mean, standard
deviation, and median of the data they are viewing. Also available is the ability to compare and condition
data sets with each other. For example, users can choose to view sea surface temperature when wind speed
is X m/s. Additional data sets continue to be added to this tool and it will eventually expand to include multi-
parameter analyses.
In this presentation, we will describe the current configuration of the JPL Tropical Cyclone Portal and
demonstrate how it will be an asset to researchers. Future plans for the site will also be discussed.
http://tropicalcyclone.jpl.nasa.gov
IN21A-1052
FPGA Platform for Satellite Observations of VLF Emissions
Transient Luminous Events (TLEs) are unique high-altitude phenomena which have recently been the
subject of intense study because they may provide insight into the energy exchange and electromagnetic
coupling of the high atmosphere and ionosphere. The systematic observation of TLEs is a difficult problem
due to their rare occurrence and low signal levels. Historically, optical observations have been the primary
method, and recent research indicates a potential correlation between TLE optical emissions and Very Low
Frequency (VLF) radio emissions of a particular signature.
Two opportunities present themselves for unique instrumentation development: first, a low-order "always-on"
sensor placed in-situ on board an observational satellite can record all VLF emissions and gather statistical
data on the correlation and rate of occurrence of these VLF signatures. Secondly, such a sensor can serve
as a triggering mechanism to activate high-fidelity optical instruments to catch the TLE events in real time.
Both of these scenarios present difficult challenges – real-time signal detection requires fast computations;
and the space-environment requires both low-power consumption and high resilience to radiation. In light of
these constraints, the preferred method is a specialized digital signal processor (DSP) implemented as a
Field Programmable Gate Array (FPGA). This technology enables highly parallelizable data processing and
due to the specialized hardware specific to this application, power consumption can be reduced. The
development of FPGA platforms also offers the capability for extensibility and interoperability with similar
ground-stations; additional features such as data recording, user-interfacing, and network connectivity are
possible without total system redesign via the FPGA's unique development methodology.
Currently, a hardware prototype has been developed which successfully performs the basic functionality for
real-time signal processing and data presentation. Using satellite data from the DEMETER probe, algorithms
were designed which could suitably detect the VLF signatures of interest, and these techniques were
translated into the FPGA's platform for real-time performance. Systematic benchmarking with this data has
verified that the implementation is capable of sustaining high-sensitivity detection, even in noisy
environments, by dynamically adapting to the signal environment. This instrument enables statistical
characterization of these VLF signatures; further work on the prototype platform will enable rapid delivery and
visualization of the scientific data.
http://spacenimur.stanford.edu/~nwmoussa/agu/fm08/
IN21A-1053
An Advanced Next Generation Archival and Distribution System for Global Atmospheric Science Research
NASA's Atmospheric Science Data Center at the NASA Langley Research Center has developed a new state-
of-the-art data archival, and distribution system to serve the atmospheric sciences data provider and user
communities. The new system, called Archive – Next Generation (ANGe), is replacing a large-scale science
data management system, and is designed with a distributed, multi-tier, serviced-based, message oriented
architecture enabling new methods for searching, accessing, and customizing data. The previous system
required a user to actively manage a session in a web browser to sequentially search for and obtain data.
The ANGe system is architected to allow programmatic calls to the archive via web services to obtain multiple
data sets of interest to the user.
The ANGe system is currently supporting Clouds and the Earth's Radiant Energy System (CERES) and
Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data ingest, archival and
distribution. In the future it will support CERES on National Polar-orbiting Operational Environmental Satellite
System (NPOESS).
Potential enhancements to this new system are web service access to the archive improving the user's ability
to utilize multiple data sets managed at different locations via a Grid/Cloud computing environment. This
technology distributes computationally intensive data processing for large data sets, and greatly improves
the efficiency of extracting smaller pieces of data of interest to a specific study. Geospatial metadata can be
managed in a PostGIS-enabled database, allowing for integration with mainstream GIS utilities and
applications. The Atmospheric Science Data Center proposes to produce custom value-added data products
and tailoring access to information and data to meet the needs of a diverse user community. Details of these
new data access tools and capabilities, and potential enhancements will be discussed.
The Atmospheric Science Data Center in Langley's Science Directorate leads NASA's program for the
processing, archival and distribution of Earth science data in the areas of radiation budget, clouds, aerosols,
and tropospheric chemistry. The Data Center was established in 1991 to support NASA's Earth Observing
System and the U.S. Global Change Research Program. It is unique among NASA data centers in the size of
its archive, cutting edge computing technology, and full range of data services. For more information
regarding ASDC data holdings, documentation, tools and services, visit http://eosweb.larc.nasa.gov
http://eosweb.larc.nasa.gov
IN21A-1054
Earth Science Research Discovery, Integration, 3D Visualization and Analysis using NASA World Wind
NASA plays a leadership role in the world of Advanced Information Technologies. Part of our mission is to leverage those technologies to increase the usability of the growing amount of earth observation produced by the science community. NASA World Wind open source technology provides a complete 3D visualization platform that is being continually advanced by NASA, its partners and the open source community. The technology makes scientific data and observations more accessible to Earth scientists and offers them a standards-based extensible platform to manipulate and analyze that data. The API-centric architecture of World Wind's SDK allows others to readily extend or embed this technology (including in web pages). Such multiple approaches to using the technology accelerate opportunities for the research community to provide "advances in fundamental understanding of the Earth system and increased application of this understanding to serve the nation and the people of the world" (NRC Decadal Survey). The opportunities to advance this NASA Open Source Agreement (NOSA) technology by leveraging advances in web services, interoperability, data discovery mechanisms, and Sensor Web are unencumbered by proprietary constraints and therefore provide the basis for an evolving platform that can reliably service the needs of the Earth Science, Sensor Web and GEOSS communities. The ability for these communities to not only use this technology in an unrestricted manner but to also participate in advancing it leads to accelerated innovation and maximum exchange of information. 3 characteristics enable World Wind to push the frontier in Advanced Information Systems: 1- World Wind provides a unifying information browser to enable a variety of 3D geospatial applications. World Wind consists of a coherent suite of modular components to be used selectively or in concert with any number of programs. 2- World Wind technology can be embedded as part of any application and hence makes it more possible to include virtual globe capability in support of any Earth science objective. 3- With the source code being fully accessible, anyone can advance this technology (including in a commercial or other proprietary manner). Such features enable World Wind to provide easy discovery, access and 3D integration/visualization/analysis of Earth observation data in a flexible, customizable open source tool. This positions World Wind to become a key part of an Advanced Information Systems infrastructure supporting a collaborative decision-making environment for a variety of applications.