SF12A-01 INVITED 10:20h
Tools for Online Access and Manipulation of Spatial Climate Data
Oregon State University's Spatial Climate Analysis Service (SCAS) is dedicated to the spatial analysis and mapping of climate. Using the well-known PRISM climate mapping system, SCAS has created digital climate data sets for the US, Canada, parts of Asia and Europe, and elsewhere. Major projects include official USDA precipitation maps for the US, and a new US climate atlas. SCAS also maintains and regularly updates an ongoing monthly time series of digital precipitation, temperature, and dew point maps for the conterminous US, spanning 1895-present. Many PRISM data sets are made accessible to the public online via Web tools that allow users to views map images, download grids, and explore the data. The Minnesota Mapserver has been implemented to allow users to view and query map layers, and create monthly climate time series over the past century for individual grid cells. Time series data are presented as downloadable graphs and tables. Mapserver is also being used by SCAS in a separate Web application, which is geared towards agriculture. In this application, spatial climate and soils data are used to produce suitability maps for various crop species. In the future, we envision greater use of MapServer capabilities for spatial data quality control activities. SCAS is cooperating with the several institutions in developing the WestMap initiative. WestMap aims to provide an easily accessible, comprehensive package of 1 km monthly (or better) resolution climate data series, with associated accuracy estimates, online analysis tools, and educational resources to the highly diverse user communities of climate data stakeholders in the United States.
http://www.ocs.oregonstate.edu/prism/
SF12A-02 10:33h
The next generation of McIDAS: A look toward the future
The Man computer Interactive Data Access System (McIDAS) software was developed over 30 years ago at the University of Wisconsin-Madison to visualize data from the then first generation geostationary satellites. Over the years, the software has been kept current by including access to data from new instruments and by adapting to changing computing hardware and display platforms. The last major effort was during the 1990s when McIDAS was moved into Unix, X Windows, and the use of ADDE (Abstract Data Distribution Environment) for data access. That effort has taken McIDAS into the 21st century. New sensors being developed for future operational satellites will exceed the design of the current data structures and the visualization capabilities of the McIDAS software. Innovative techniques for visualizing and developing algorithms with these new data types are needed. The Integrated Data Viewer (IDV), a reference application based on the VisAD system that is being developed by the Unidata Program, demonstrates the flexibility that is needed in this evolving environment, using a modern, object-oriented approach. A plan has been developed to explore the transition of the current McIDAS-X users into a VisAD-based system, to be known as McIDAS-V. The goal of the transition is two-fold: 1. Allow the extensive library of McIDAS-X heritage code that operates with the current satellites to be used for at least another decade, 2. Provide a new environment for developing algorithms and new visualizations that are required for data from future sensors. A status of the plan will be presented, including identified trade-offs and future directions.
SF12A-03 10:46h
Multi-Sensor Distributive On-line Processing, Visualization, and Analysis Infrastructure for an Agricultural Information System at the NASA Goddard Earth Sciences DAAC
The Goddard Space Flight Center Earth Sciences Data and Information Services Center (GES DISC) Distributed Active Archive Center (DAAC) is developing an Agricultural Information System (AIS), evolved from an existing TRMM Online Visualization and Analysis System (TOVAS), which will operationally provide precipitation and other satellite data products and services. AIS outputs will be integrated into existing operational decision support systems for global crop monitoring, such as that of the U.N. World Food Program. The ability to use the raw data stored in the GES DAAC archives is highly dependent on having a detailed understanding of the data's internal structure and physical implementation. To gain this understanding is a time-consuming process and not a productive investment of the user's time. This is an especially difficult challenge when users need to deal with multi-sensor data that usually are of different structures and resolutions. The AIS has taken a major step towards meeting this challenge by incorporating an underlying infrastructure, called the GES-DISC Interactive Online Visualization and Analysis Infrastructure or "Giovanni," that integrates various components to support web interfaces that allow users to perform interactive analysis on-line without downloading any data. Several instances of the Giovanni-based interface have been or are being created to serve users of TRMM precipitation, MODIS aerosol, and SeaWiFS ocean color data, as well as agricultural applications users. Giovanni-based interfaces are simple to use but powerful. The user selects geophysical parameters, area of interest, and time period; and the system generates an output on screen in a matter of seconds. The currently available output options are (1) area plot - averaged or accumulated over any available data period for any rectangular area; (2) time plot - time series averaged over any rectangular area; (3) Hovmoller plots - longitude-time and latitude-time plots; (4) ASCII output - for all plot types; and (5) image animation - for area plot. Planned output options for the near-future include correlation plots and GIS-compatible outputs. The AIS will enable the remote, interoperable access to distributed data, because the current Giovanni implementation incorporates the GrADS-DODS Server (GDS), a stable, secure data server that provides subsetting and analysis services across the Internet, for any GrADS-readable data set. The subsetting capability allows users to retrieve a specified spatial region from a large data set, eliminating the need to first download the entire data set. The analysis capability allows users to retrieve the results of an operation applied to one or more data sets on the server. The Giovanni-GDS technology allows the serving of data, through convenient on-line analysis tools, from any location where GDS and a few GrADS scripts are installed. The GES-DISC implementation of this technology is unique in the way it enables multi-sensor processing and analysis.
http://daac.gsfc.nasa.gov/www/agriculture/
SF12A-04 10:59h
Micro Rain Radar data visualization tool
We present a method for visualizing the consequences of variability in drop size distribution (DSD) of precipitation on the parameters radar reflectivity and rain rate. The displayed data are those of the Micro Rain Radar (MRR-2), which measures the vertical Doppler spectrum in multiple altitudes to estimate the DSD using the relation between drop diameter and terminal fall velocity. The relation between radar reflectivity factor Z and the rain rate R has been the subject of much research for the last 40 years since it is of central importance for the quantitative estimation of precipitation. Usual representations of occurring Z-R relations as power laws in logarithmic scatter-plots without information on temporal evolution have sometimes led to misunderstandings concerning the nature of the variability of these rain properties, as well as to misjudgements on the correct approach for Z-R approximation. Researchers have repeatedly tried to find connections between appearance of rain structures in weather radar data with Z-R relation in order to exploit spatial structure to improve quantitative precipitation estimations. The recent more versatile instrumentation for DSD measurement gives the opportunity to combine more information on precipitation structure (spatial and temporal variability, vertical reflectivity profile, occurring melting layer). The intent of the chosen representation of Z/R ratio as a function of time and rain intensity in connection with the corresponding vertical reflectivity profiles is to have a fast and easy way to understand the nature of the precipitation process as well as the implications for the quantitative measurement of rain rate with weather radar. Using the presented tool for quick visualization has been extremely useful while analyzing long periods of measurements with the desired time resolution and necessary information for rain classification. Additional available observations such as weather radar scans, disdrometer, rain gauge, or wind speed measurements may be incorporated to better understand errors and deviations from other precipitation measuring instrument.
SF12A-05 11:12h
Multiresolution Precipitation Visualization of Weather Radar Volume Scans
Weather radars measure the backscatter from atmospheric hydrometeors. The three-dimensional structure of a complete radar scan contains information which can improve rainfall rate estimates which is crucial for hydrological modeling and simulations. For the understanding and conveyance of the data, interactive volume visualization tools within visual geographic information systems are required. However, due to the large size of the data it is difficult to achieve real-time visualization performance. Furthermore, the data has to be put in a context for better comprehension, e.g. by additionally rendering the local terrain or satellite image data which further increases the amount of data which has to be displayed. In addition, the simultaneous display of volume and surface data leads to algorithmic visualization difficulties. In this talk, we address these problems by adaptive multiresolution algorithms (see [1]). Multiresolution methods allow a fast coarse display of the data for overview images or interaction, while higher resolution is used when zooming into the data or for detail images. The algorithms are adaptive in the sense that the resolution does not have to be uniform everywhere but may be variable in space. For example, in smooth areas a lower resolution can be sufficient to provide a good representation of the data while in areas with greater variation a higher resolution is used. The adaptive refinement is controlled by suitable error indicators which can be specified by the user. The employed volume visualization algorithm is based on the simultaneous extraction of several transparent isosurfaces. In this way, interactive visualization performance of time-varying three-dimensional radar data can be achieved without the usage of special-purpose hardware (apart from a standard graphics card). [1] T. Gerstner, D. Meetschen, S. Crewell, M. Griebel, and C. Simmer. A Case Study on Multiresolution Visualization of Local Rainfall from Weather Radar Measurements. In H. Pfister and M. Bailey, editors, Proceedings IEEE Visualization 2002, pages 533-536. IEEE Computer Society Press, 2002.
SF12A-06 11:25h
GIS Tools for Visualization and Analysis of NEXRAD Radar (WSR-88D) Archived Data at the National Climatic Data Center (NCDC)
The NCDC ingests and archives, on average, 80 terabytes of NEXRAD Radar Data and products annually. These data are in high demand globally by both the public and private sectors. As much as one terabyte of data have been accessed monthly through the NCDC radar resources web page. In an effort to provide better support to these end users, NCDC has developed visualization tools for browsing and displaying these data. The NCDC NEXRAD Interactive Viewer and Data Exporter load Level-II and Level-III NEXRAD data into an OPEN GIS compliant environment. The applications are launched via Java WebStart and run on the client machine while accessing the data remotely from the archive at the NCDC. The NEXRAD Interactive Viewer provides tools for custom data overlays, animations and basic queries. The export of images and movies is provided in multiple formats. The NEXRAD Data Exporter allows for data export in both vector polygon (Shapefile, GML, Well-Known Text) and raster (GeoTIFF, ESRI Grid, HDF, NetCDF, GrADS) formats.
http://www.ncdc.noaa.gov/oa/radar/radarresources.html
SF12A-07 INVITED 11:38h
Online Tools at the U.S. Bureau of Reclamation
Reclamation is the major Federal water resources management agency operating in the 17 western States, where it has over 350 reservoirs, numerous irrigation systems, and related infrastructure. Escalating human needs for finite water supplies make it essential that Reclamation manage its many water systems with the greatest practical efficiency. Efficient system operation depends heavily on accurate short-term and seasonal streamflow forecasts. Spring streamflows, derived largely from snowmelt and rains on snow, are especially critical to Reclamation's water management. The inability to quantitatively predict such streamflows beyond climatological values has been a major problem, and one of the major causes of this inability is inaccurate or spatially sparse quantitative precipitation estimate (QPE) data. To address these shortcomings, Reclamation's River Systems and Meteorology group has developed several online tools for QPE data access and visualization. The major tool is the Agricultural WAter Resources Decision Support (AWARDS) system. The purpose of the AWARDS system is to improve the efficiency of water management and irrigation scheduling by providing guidance on when and where to deliver water, and how much to apply. The AWARDS system has been designed for use by reservoir system operators, water district staff, and on-farm irrigators. AWARDS is operational in several regions of the West. At the heart of AWARDS is near-real-time QPE from the national WSR-88D radar network, providing hourly and daily accumulations at a nominal 2 km spatial resolution. The QPE is produced by either the National Weather Service Multi-sensor Precipitation Estimator (MPE) or Reclamation's Precipitation Accumulation Algorithm (PAA). The latter algorithm can estimate snow water equivalent (SWE) or snow depth from snowfall. Reclamation scientists have pursued close collaboration with other agencies in the formulation of AWARDS and precipitation-related information systems. A recent example of such collaboration is with the NOAA National Severe Storms Laboratory (NSSL). This partnership has resulted in application of NSSL's Quantitative Precipitation Estimation and Segregation Using Multiple Sensors (QPE SUMS) system in the Lower Colorado River basin. QPE SUMS combines gauge, radar, and satellite measurements into a single sophisticated suite of algorithms, producing 3-D mosaicked data and several QPE ensembles. QPE SUMS will be deployed in Colorado soon to assist snowpack assessment. Data for this assessment are already being displayed on the web via the Snow Data Assimilation System (SNODAS). SNODAS is a fully-distributed, energy-and-mass-balance snow model that assimilates several types of snow observations, numerical weather model output, satellite, radar and airborne data. SNODAS was developed by the NWS National Operational Hydrologic Remote Sensing Center. We display SNODAS SWE at 1 km resolution and compute basin-average SWE from those data, on a daily basis. This output is used for decision support by the Colorado Water Conservation Board and other water management agencies in the state. It is planned to include several more variables (e.g., snow depth, snowmelt, snowpack temperature) on the web site. The principal goal is to demonstrate any value added to water management over traditional snow measurements, which are primarily taken from surface Snow Telemetry (SNOTEL) sites. Finally, we intend to couple QPE data with hydrologic models and river basin modeling decision support systems, thereby improving those schemes. Such a coupling has already been tested with Reclamation's PAA and two distributed models in the Lower Colorado River basin.
http://www.usbr.gov/pmts/rivers/awards/index.html
SF12A-08 11:51h
New Methods For Hydrologic Data Retrieval, Analysis And Visualization
One of the most difficult tasks in initiating any research is to collect all relevant data. In the field of hydrology, the process of data search and retrieval occupies a large portion of one's research time because of the different formats, structure and increased data size. To address this issue, we developed a prototype system called the Hydrologic Data Management, Retrieval and Analysis System (HDMRAS) as part of an integrated effort of CUAHSI HIS activities. The prototype system is capable of querying, retrieving, integrating and visualizing hydrologic data with heterogeneous formats and large sizes produced from various agencies. Our prototype system demonstrates a metadata-based approach to an integrated data management system. With the metadata mechanism, diverse data formats and structures from many heterogeneous hydrologic data sources can be handled efficiently. The developed system includes four components, a metadata mechanism, a main application, add-on visualization and analysis toolkits, and data storage. A dynamic spatial query function that enables users to interactively locate data through a GIS-based environment will be added to the system based on the extensible features of the system. We will use a watershed boundary as an identifier to define a hydrologist's spatial domain and locate data relevant to it. In addition to the stand-alone prototype system, we are developing an online system of this kind which can mine, retrieve and visualize various data from disparate systems remotely through the Internet. The ideas, approaches, and system architecture involved in developing this prototype are general, and can be readily applied to other fields as well.
SF12A-09 INVITED 12:04h
Web-based Dissemination of TRMM Data via TerraFly
Florida International University's High Performance Database Research Center (FIU HPDRC) is collaborating with the Goddard Earth Sciences Data and Information Service Center's Distributed Active Archive Center (GES DISC DAAC) to provide an easy-to-use and powerful Web-based interface to Tropical Rainfall Measuring Mission (TRMM) and other satellite data from NASA's Earth Science Enterprise (ESE). The collaboration uses FIU's TerraFly data dissemination tools to make TRMM and other data available to a wider audience of users. TerraFly is a Web-enabled system (http://terrafly.fiu.edu) designed to aid in the visualization of spatial and remote sensed imagery. This system allows one to "fly" over the Earth's surface and explore spatial data such as aerial photography, satellite imagery, street maps, and locale information. Internet capability allows the system to access numerous data sets without the installation of any specialized GIS programs. Designed for users of all levels and unlike other geographic information systems, TerraFly runs via standard Web browsers, with no need to download software or data prior to visualization. TerraFly can be delivered as a standalone application or a Web-based tool. FIU's technology of streaming incremental tiles to a Java applet allows the user to "fly" even via modem connections. While "flying" over imagery in TerraFly, the user can see various overlays, such as road names, application-relevant points that are hyperlinked to more information, and shaded zones that depict thematic map layers. The user can also view multi-spectral data by assigning bands to the RGB display and by visualizing the application of various algorithms and filters on multiple spectral bands or multiple data sets. The user can thus compare imagery of the same area acquired at different times or different imagery of the same area acquired concurrently and apply advanced visualization algorithms to the data. The FIU-GES DISC DAAC project aims to make TRMM and other NASA ESE data more easily accessible by enabling it to be visualized via the Web by a broad spectrum of user communities, in an integrated, transparent manner, from within the TerraFly environment. The user will be able to select any point in the displayed TRMM imagery and retrieve, for an area the center of which is represented by the selected point, the previous day's average rainfall. Additional links will be available to provide more detailed TRMM visualizations, along with other data relevant to the selected point. This networked collaboration and integration of resources will enable the GES DISC DAAC to leverage the existing capabilities of TerraFly to better publicize and disseminate NASA ESE data to the broader TerraFly audience, including K-12 educators and students, operational users, and the general public. Conversely, the information available from TerraFly will be easily accessible to GES DISC DAAC users of TRMM and other ESE data, via the Web-accessible, TOVAS tool (http://lake.nascom.nasa.gov/tovas/).