A number of events and publications have highlighted the need for a high degree of transparency and best practices in the publication, management, provenance tracking, traceability, identification, and citability of science data, and particularly for Earth Science data. Motivation to publish data also comes from publisher and funding agency mandates to make data accessible and a desire to give greater credit for the sharing of data. This session is for the tools, approaches, and cultural changes to increase the transparency of scientific work, improve the analysis of the impact of data sharing, and provide credit for researchers and institutions openly sharing data. This session is accompanied by an overview Union session, U17.

A number of events and publications have highlighted the need for a high degree of transparency and best practices in the publication, management, provenance tracking, traceability, identification, and citability of science data, and particularly for Earth Science data. Motivation to publish data also comes from publisher and funding agency mandates to make data accessible and a desire to give greater credit for the sharing of data. This session is for the tools, approaches, and cultural changes to increase the transparency of scientific work, improve the analysis of the impact of data sharing, and provide credit for researchers and institutions openly sharing data. This session is accompanied by an overview Union session, U17.

A number of events and publications have highlighted the need for a high degree of transparency and best practices in the publication, management, provenance tracking, traceability, identification, and citability of science data, and particularly for Earth Science data. In addition, the importance of free, open, authoritative sources of quality data that are available for peer review and for collaborative purposes is increasing rapidly. Motivation to share and publish data also comes from publisher and funding agency mandates to make data accessible and a desire to give greater credit for the sharing of data. Focus will be on applications and opportunities for enhancing existing and common community-agreed data exchange standards for use with Earth and space science data. Requirements include tools, approaches, and cultural changes. The goal is to increase the transparency of scientific work, improve the analysis of the impact of data sharing, and provide credit for researchers and institutions openly sharing data. This Union session comprises invited papers only. Contributed papers should be submitted to one of the companion sessions, IN02 or IN16.

Visualizing the trajectory and the sounding profile of the COSMIC netCDF dataset, and its evolution through time is developed in Unidata's Integrated data Viewer (IDV). The COSMIC radio occultation data is located in a remote data server called RAMADDA, which is a content management system for earth science data. The combination of these two software packages provides a powerful visualization and analysis tools for sharing real time and archived data for research and education. In this presentation we would like to demonstrate the development and the usage of these two software packages.

Two decades of experience facilitating the creation of and access to portable, self-describing scientific data have resulted in Unidata's network Common Data Form (netCDF), with an associated data model, freely available reference software, and endorsement as a standard by groups including NASA's Earth Science Data Systems Standards Process Group. NetCDF is now widely used in climate, ocean, and atmospheric sciences, and has proved general enough for other uses, such as neural imaging, molecular dynamics, and fusion energy research. A variety of software packages, data archives, and client/server systems are available for the access, analysis, visualization, and use of netCDF data, as well as other kinds of data through a netCDF programming interface. The widely used Climate and Forecast (CF) Metadata Conventions, based on the netCDF "classic" data model but applicable to other formats, add a useful layer of semantics for interoperability, and define "CF compliance" as a standard for Earth science metadata. Broad adoption of CF Conventions make practical the development of CF-compliant software that can access such data and metadata. The simple netCDF data model has recently been extended to improve its ability to faithfully represent earth science data and metadata. The netCDF software that implements the enhanced data model provides backward compatibility with existing data and applications, while making access to useful features available through additional programming interfaces that extend the netCDF classic interfaces. This presentation provides an up-to-date overview of netCDF including a summary of the enhanced netCDF data model, describes experience developing generic software to handle its features, and offers guidelines based on that experience for incrementally adapting existing netCDF software to take advantage of benefits offered by the enhanced netCDF data model.

Hydrologic information science requires several different kinds of information: GIS coverages of water features of the land surface and subsurface; time series of observations of streamflow, water quality, groundwater levels and climate; and space-time arrays of weather, climate and remotely sensed information. Increasingly, such information is being published as web services, in standardized data structures that transmit smoothly through the internet. A large "Digital Divide" exists between the world of discrete spatial objects in GIS and associated time series, and the world of continuous space-time arrays as is used weather and climate science. In order to cross this divide, it should be possible to search for quantities such as “precipitation” and to find the information no matter whether it comprises time series of precipitation at gage sites, or space-time arrays of precipitation from Nexrad radar rainfall measurements. This means that servers of discrete space-time hydrologic data, such as the CUAHSI HydroServer, and servers of continuous space-time weather and climate data, such as the Unidata THREDDS server, should be able to be indexed in a unified manner that will permit discovery of common information types across different classes of information services. This paper will explore options for accomplishing this goal using the CUAHSI HydroServer and the Unidata THREDDS server as representative examples of information service providers. Among the options to be explored is GI-cat, a federated, standards-based catalog service developed at the Earth and Space Science Informatics Laboratory of the University of Florence.

Increasingly earth system models perform computations on grids that are not describable as simple, rectangular arrays (e.g. lon by lat), instead requiring a mosaic of interacting, logically rectangular tiles. Such grids are developed for a variety of reasons that include removal of coordinate singularities that may degrade numerical reliability in a region of interest (e.g. the north pole in an ocean model) and increasing the uniformity of numerical precision over the globe. Coupled earth system models, typically characterized by independent coordinate reference systems for modeling atmosphere, ocean, ice, and terrestrial processes, are themselves examples of such mosaic grids. GRIDSPEC is a proposed set of conventions to the Climate and Forecast library (LibCF) describing data on mosaic grids developed by V. Balaji et al. (Geophysical Fluid Dynamics Laboratory). It supports unstructured assemblies of structured grids, including the cubed-sphere and tripolar meshes. Here we review a GRIDSPEC NetCDF format based on host, contact, grid, and data files. We will show how mosaic grids can be created from the ground up using a C API and the Python Climate Data Anaysis Tools (CDAT) for visualization. As an application we use GRIDSPEC to regrid cubed-sphere data onto a longitude-latitude grid.

The Laboratory for Atmospheric and Space Physics at the University of Colorado has developed an Open Source, OPeNDAP compliant, Java Servlet based, RESTful web service to serve time series data. In addition to handling OPeNDAP style requests and returning standard responses, existing modules for alternate output formats can be reused or customized. It is also simple to reuse or customize modules to directly read various native data sources and even to perform some processing on the server. The server is built around a common data model based on the Unidata Common Data Model (CDM) which merges the NetCDF, HDF, and OPeNDAP data models. The server framework features a modular architecture that supports pluggable Readers, Writers, and Filters via the common interface to the data, enabling a workflow that reads data from their native form, performs some processing on the server, and presents the results to the client in its preferred form. The service is currently being used operationally to serve time series data for the LASP Interactive Solar Irradiance Data Center (LISIRD, http://lasp.colorado.edu/lisird/) and as part of the Time Series Data Server (TSDS, http://tsds.net/). I will present the data model and how it enables reading, writing, and processing concerns to be separated into loosely coupled components. I will also share thoughts for evolving beyond the time series abstraction and providing a general purpose data service that can be orchestrated into larger workflows.

In the coastal zone, storms are one of the primary environmental forces causing coastal change. These discrete events often produce large waves, storm surges, and flooding, resulting in coastal erosion. In addition, strong storm-generated currents may pose threats to life, property, and navigation. The ability to predict these events, their location, duration, and magnitude allows resource managers to better prepare for the storm impacts as well as guide post-storm survey assessments and recovery efforts. As a step towards increasing our capability for prediction of these events and to help us study the physical processes that occur we have developed an automated system to run components of the Coupled Ocean - Atmosphere - Wave - Sediment Transport (COAWST) Modeling System as a daily forecast. The current daily system couples Regional Ocean Model System (ROMS) and Simulation Waves Nearshore (SWAN) models to predict currents, salinity, temperature, wave height and direction, and sediment transport for the US East Coast and Gulf of Mexico on a 5 km scale. As part of the system a refined grid for the area of Cape Hatteras, NC at a resolution of 1 km is included. Management of the system is controlled by the Windows Scheduler to start Matlab® and run scripts and functions. Data required by the modeling system include daily modeled wave, wind, atmospheric surface inputs, and climatology fields. The Unidata Internet Data Distribution/Local Data Manager (http://www.unidata.ucar.edu/software/ldm/) is used to download National Centers for Environmental Prediction (NCEP) GFS global 5 degree data and NCEP NAM Conus 12km data to a local server. The Matlab “structs” tool and NJ-Toolbox (http://njtbx.sourceforge.net/njdocs/njtbxhelp/njtbxhelp.html) are used to access these large data sets on the local server as well as Wave Watch 3 (WW3) and NCEP model data sets available remotely on the Nomads http://nomads.ncep.noaa.gov site and Hybrid Coordinate Ocean Model (HYCOM) data available at http://tds.hycom.org . Data from the previously listed sources are used to create the required inputs for the ROMS and SWAN models. Currently the output from the coupled ROMS-SWAN system is displayed at http://woodshole.er.usgs.gov/project-pages/cccp/public/COAWST.htm. The modeling system, data flow and visualization methods will be described. Comparisons between the COAWST output and National Data Buoy Center wave, current, and tidal observations will be presented.

The Unidata LDM is a near real-time, event-driven system for transmitting frequently-generated data-products, 24/7, from a producer to multiple subscribers using the Internet. Once received, a data-product is processed according to user specifications. A data-product can be anything up to 4 gigabytes in size. Downstream LDM-s register a regular expression based selection predicate with upstream LDM-s. Network topologies include point-to-point, star, and tree. Based on ONC RPC, the LDM system is extremely robust and efficient. Since its initial release in 1994, a network of LDM-s called the Internet Data Distribution (IDD) system has been the primary means by which many if not most Earth Sciences departments in the US obtain and process meteorological data (up to 20 GB/hour and 250k products/hour) with latencies measured in seconds or less. Data-products include numerical model output, radar data, WMO bulletins, and lightning data. Users of the LDM also include the international atmospheric science university community, NOAA, NASA, USGS, the US military, ECMWF, and the meteorological agencies of China, Australia, Brazil, South Korea, and Vietnam. The LDM is the highest volume advanced application on Internet-2 (currently averaging 27 terabytes per week). The LDM history and architecture is presented together with an analysis of its strengths and weaknesses.

The University of Wisconsin’s Space Science and Engineering Center (SSEC) has been at the forefront in developing data analysis and visualization tools for environmental satellites and other geophysical data. The fifth generation of the Man-computer Interactive Data Access System (McIDAS-V) is Java-based, open-source, freely available software that operates on Linux, Macintosh and Windows systems. The software tools provide powerful new data manipulation and visualization capabilities that work with geophysical data in research, operational and educational environments. McIDAS-V provides unique capabilities to support innovative techniques for evaluating research results, teaching and training. McIDAS-V is based on three powerful software elements. VisAD is a Java library for building interactive, collaborative, 4 dimensional visualization and analysis tools. The Integrated Data Viewer (IDV) is a reference application based on the VisAD system and developed by the Unidata program that demonstrates the flexibility that is needed in this evolving environment, using a modern, object-oriented software design approach. The third tool, HYDRA, allows users to build, display and interrogate multi and hyperspectral environmental satellite data in powerful ways. The McIDAS-V software is being used for training and education in several settings. The McIDAS User Group provides training workshops at its annual meeting. Numerous online tutorials with training data sets have been developed to aid users in learning simple and more complex operations in McIDAS-V, all are available online. In a University of Wisconsin-Madison undergraduate course in Radar and Satellite Meteorology, McIDAS-V is used to create and deliver laboratory exercises using case study and real time data. At the high school level, McIDAS-V is used in several exercises in our annual Summer Workshop in Earth and Atmospheric Sciences to provide young scientists the opportunity to examine data with friendly and powerful tools. This presentation will describe the McIDAS-V software and demonstrate some of the capabilities of McIDAS-V to analyze and display many types of global data. The presentation will also focus on describing how McIDAS-V can be used as an educational window to examine global geophysical data.

Scientific visualization of complex fusions of heterogeneous 2, 3, and 4-D data sets is a challenge in most fields of geosciences and oceanography is no exception. Despite increased computing power, dedicated graphic processing units, and more capable software, 30 years of change in the ways that geophysical sciences are conducted continues to challenge our ability to present the data in visually meaningful ways. Oceanography, for example, changed from a science in which a sole researcher studied a single phenomena, e.g. ocean currents to one in which a multidisciplinary collaborative teams study complex coupled systems. In three decades we’ve moved from a time where a map of mean circulation and a coastline rendered on a pen-plotter would suffice, to one in which we require detailed dynamic views of relationships and change. We now need to visualize multiple parameters of relatively sparse observed data combined with computer generated output on dense numerical model grids. We want parameters within ocean and atmosphere volumes rendered over detailed earth terrains with illumination and infrastructure. We want to “see” the dynamic relations between the oceans, atmosphere, land, biogeochemistry, biota, and ecosystem all at once and in context. As the computational power increased, the density of the model grid points increased accordingly. The latest challenge has been due to the internet, the notion of sensor webs, and the near real-time availability of high-bandwidth interoperable standards-based data streams. Not only do we want to see it all, we want to see it now, and we want to see it the way we want and that may change from moment to moment. Increasingly this involves 4D visualizations combined with a strong element of traditional Geographic Information System type presentation. The Gulf of Mexico Coastal Ocean Observing System Regional Association (GCOOS-RA) is one of 11 regional observing systems that comprise the non-federal part of the U.S. Integrated Ocean Observing System (IOOS). With IOOS guidance, and cooperation of regional data providers, GCOOS-RA has established a regional interoperable system of systems which has the potential to deliver marine, and coastal marine oceanographic, atmospheric, biogeochemical, and ecosystem related data in an automated and largely unattended way from sensors to products. GCOOS-RA devotes 10% of it’s funding to Education and Outreach activities and we have a number of modeling partners producing terabytes of output. With the interoperable parts of the data delivery system complete, our current challenge has been producing automated workflows that generate useful interactive graphical representations over the web. We have used a variety of commercial and free software packages. Some are net-enabled and can acquire remote datasets. Several are designed for 3D including ITTVIS IDL, Unidata IDV, and IVS’s Fledermaus. This talk will present a survey of software packages we’ve used, our successes and remaining challenges.

AB: Lightning is a significant natural source of nitrogen oxides (NO_x). The high temperatures that occur in a lightning channel fix atmospheric N2, producing nitrogen monoxide (NO) that quickly forms NO2 (NO_x = NO + NO₂). Lightning-produced NO_x (LNO_x) dominates NO_x concentrations in the upper troposphere, which affect tropospheric ozone and OH concentrations and in turn the oxidizing capacity of the atmosphere. The main sink for NO_x in the atmosphere is formation of nitric acid (HNO₃) and subsequent deposition of nitrate (NO₃). A widely accepted estimate for the global LNO_x production rate is ˜5±3 TgN/yr (uncertainty of 1-20 TgN/yr). The global source term for NO_x is an estimated 50 TgN/yr. Global chemical transport model studies have found that LNO_x contributes to NO₃ deposition (wet+dry) that is nearly equal over both land and ocean, with the greatest deposition between 30°N and 30°S. Models also predict that lightning can be the dominant source of NO₃ deposition in areas where industrial sources are limited. Is it possible that an empirical relationship exists between NO₃ deposition and lightning? Using 10 years of deposition, lightning, and meteorological data, we investigate the relationship between lightning and NO₃ in the subtropics and assess meteorological variables that contribute significantly to the distribution of LNO_x and NO₃. For NO₃ deposition, we use weekly, monthly, and event-based wet deposition data from 8 coastal sites in Florida, the US Virgin Islands, and Puerto Rico (NADP); satellite and ground-based lightning data in the same region is from TRMM and Unidata; meteorology is obtained from the NCEP/NCAR Reanalysis. We use multiple linear regression in an attempt to explain variance among historical NO₃ data, lightning and meteorology. We expect certain meteorological variables — particularly those related to transport and deposition — to help illuminate a relation between lightning and NO₃. The relation between NO_x emissions and NO₃ deposition is unclear, as is the ability to constrain NO₃ sources to any given location and decouple anthropogenic versus natural effects. Our investigation addresses such questions as: from daily and monthly rain data, can total, average, or extreme precipitation events explain temporal/spatial NO₃ distribution? Using numerical weather models, can regional meteorology predict NO₃ deposition related to LNO_x? Moreover, could such a prediction distinguish between free troposphere and planetary boundary layer sources of NO₃? How much of NO₃ deposition is due to local LNO_x sources versus regional transport? Quantifying the relationship between lightning and NO₃ will be useful in evaluating atmospheric chemistry models, and such results could provide insight in predicting lightning-influenced NO₃ deposition under future climate change scenarios. Furthermore, elucidating LNO_x's impact on NO₃ would provide a means to better constrain natural and anthropogenic effects on the global N cycle.

Visualization and analysis of earth-science data has been a core component of the atmospheric science community for decades. While virtual globe applications such as Google Earth and NASA World Wind have gained broad use and have amazing display capabilities, they lack many of the fundamental data handling and visualization capabilities that are required for advanced research and educational purposes in the geosciences. The Integrated Data Viewer (IDV), developed at the Unidata Program Center as part of the University Corporation for Atmospheric Research, is a 3 dimensional, open source visualization application designed to display a wide variety of geo-referenced earth system data. The IDV is widely used in the atmospheric science education and research community. The IDV currently ingests many common atmospheric data formats and provides a broad range of visualization, analysis and product generation capabilities. This talk will explore some of the capabilities of the IDV and its ability to display and perform scientific analysis of heterogeneous Arctic observation data.

NetCDF has long been a de facto standard for data storage and access in several communities. More recently it has been recognized by the NASA Standards Process Group and the NOAA IOOS DMAC as a de jure standard. Within the OGC, CF-netCDF is being considered as an extension to the latest recognized version of the WCS. A new initiative is underway to establish CF-netCDF as an OGC binary encoding standard in its own right. The idea is that, establishing CF-netCDF as a separate OGC encoding standard will simplify the process of using it as a payload for other standard access protocols such as the WFS and SOS. The approach is modeled on that taken for establishing KML as an OGC standard for XML encoding. One difference is that CF-netCDF will be standardized with a core and a set of extensions.. The standardization process for the core and each of the extension will involve the following steps: -- Make the existing NASA standard the basis for the OGC Core Candidate Standard for CF-netCDF -- Submit an initial draft Candidate Standard to the OGC Technical Committee (TC) -- Form a CF-netCDF Standard Working Group (SWG) -- In the CF-netCDF SWG, refine the Candidate Standard document into a draft for public comment -- Submit the Candidate Standard to the OGC TC to be submitted for public comment -- Incorporate public comment suggestions and submit the result as an OGC Standard Specification. In parallel initiatives will be undertaken for extension standard for specific CF conventions (e.g., gridded data, point data collections, swath data, etc.)., for netCDF APIs, and for NcML (the netCDF Markup Language)-GML. The presentation will outline the plan and provide a report on the status of the initiative at the time of the meeting.

AB: The LASP Interactive Solar IRradiance Datacenter (LISIRD), http://lasp.colorado.edu/lisird, seeks to provide exploration of and access to solar irradiance data, models and other related data. These irradiance datasets, from the SME, UARS, TIMED, and SORCE missions, are primarily a function of time and often also wavelength. Their measurements are typically made on a scale of seconds and derived products are provided at daily cadence. The first version of the LISIRD site was built using non standard, proprietary software. The non standard application structure and tight coupling to a variety of dataset representations made changes arduous and maintenance difficult. Eventually the software vender decided to no longer support a critical software component, further decreasing the viability of the site. In LISIRD 2, through the application of the Java EE standard coupled with open source software to fetch and plot the data, the functionality of the original site is being improved while the code structure is being streamlined and simplified. With a relatively minimal effort, the new site can access and serve a greater variety of datasets in an easier fashion, and produce responsive, interactive plots of datasets overlaid and/or linked in time. And it does so using a significantly smaller code base that is, at the same time, much more flexible and extensible. In particular, LISIRD 2 heavily leverages powerful, flexible functionality provided by the Time Series Data Server (TSDS). The OPeNDAP compliant TSDS supports requests for any data that are function of time. It can support scalar, vector, and spectra data types. Through the use of the Unidata NetCDF-Java library and NcML, the TSDS supports multiple input and output formats and is easily extended to support more. It also supports a variety of filters that can be chained and applied to the data on the server before being delivered. TSDS thinning capabilities make it easy for the clients to request appropriate data volumes - smaller, thinned quantities for plotting purposes and full volume for download purposes. Its RESTful interface provides access to data in a uniform fashion, so that client code remains completely independent of data location, storage method, or format. (Please see the paper entitled "The Time Series Data Server (TSDS) for Convenient and Efficient Access to Time Series Data" in this session for more information about the TSDS.) The LISIRD 2 web site also leverages open source plotting software such as Amcharts and Flot to create interactive plotting capabilities. With these tools, a user can explore the data by zooming and panning over time while simultaneously viewing related indices. For downloading, the user can select an output format, such as csv, HDF, or NetCDF. The requested data can be further shaped by defining a chain of filters to be applied to the downloaded data. This talk will illustrate the new LISIRD's usage of the TSDS and other open source packages to produce a smaller, simpler, easier to maintain, and yet more powerful framework for serving time series data.

Data analysis in the physical sciences is often plagued by the difficulty in acquiring the desired data. A great deal of work has been done in the area of metadata and data discovery, however, many such discoveries simply provide links that lead directly to a data file. Often these files are impractically large, containing more time samples or variables than desired, and are slow to access. Once these files are downloaded, format issues further complicate using the data. Some data servers have begun to address these problems by improving data virtualization and ease of use. However, these services often don't scale to large datasets. Also, the generic nature of the data models used by these servers, while providing greater flexibility, may complicate setting up such a service for data providers and limit sufficient semantics that would otherwise simplify use for clients, machine or human. The Time Series Data Server (TSDS) aims to address these problems within the limited, yet common, domain of time series data. With the simplifying assumption that all data products served are a function of time, the server can optimize for data access based on time subsets, a common use case. The server also supports requests for specific variables, which can be of type scalar, structure, or sequence. It also supports data types with higher level semantics, such as "spectrum." The TSDS is implemented using Java Servlet technology and can be dropped into any servlet container and customized for a data provider's needs. The interface is based on OPeNDAP (http://opendap.org) and conforms to the Data Acces Protocol (DAP) 2.0, a NASA standard (ESDS-RFC-004), which defines a simple HTTP request and response paradigm. Thus a TSDS server instance is a compliant OPeNDAP server that can be accessed by any OPeNDAP client or directly via RESTful web service requests. The TSDS reads the data that it serves into a common data model via the NetCDF Markup Language (NcML, http://www.unidata.ucar.edu/software/netcdf/ncml/) which enables dataset virtualization. An NcML file can expose a single file, a subset, or an aggregation of files as a single, logical dataset. With the appropriate NcML adapter, the TSDS can read data from its native format, eliminating the need for data providers to reformat their data and lowering the barrier for integration. Data can even be read via remote services which is important for enabling VxOs to be truly virtual. The TSDS provides reading, writing, and filtering capabilities through a modular framework. A collection of standard modules is available and customized modules are easy to create and integrate. This way the TSDS can read and write data in a variety of formats and apply filters to them an a manner customizable to meet the needs of both the data providers and consumers. The TSDS server is currently in use serving solar irradiance data from the LASP Interactive Solar IRradiance Datacenter (LISIRD, http://lasp.colorado.edu/lisird/), and is being introduced into the space physics virtual observatory community. The TSDS software is Open Source and available at SourceForge.

The scientific data collected by government funded research belongs to the public. As such, the scientific and technical communities are responsible to make scientific data accessible and usable by the educational community. However, much geoscience data are difficult for educators and students to find and use. Such data are generally described by metadata that are narrowly focused and contain scientific language. Thus, data access presents a challenge to educators in determining if a particular dataset is relevant to their needs, and to effectively access and use the data. The AccessData project (EAR-0623136, EAR-0305058) has developed a model for bridging the scientific and educational communities to develop robust inquiry-based activities using scientific datasets in the form of Earth Exploration Toolbook (EET, http://serc.carleton.edu/eet) chapters. EET chapters provide step-by-step instructions for accessing specific data and analyzing it with a software analysis tool to explore issues or concepts in science, technology, and mathematics. The AccessData model involves working directly with small teams made up of data providers from scientific data archives or research teams, data analysis tool specialists, scientists, curriculum developers, and educators (AccessData, http://serc.carleton.edu/usingdata/accessdata). The process involves a number of steps including 1) building of the team; 2) pre-workshop facilitation; 3) face-to-face 2.5 day workshop; 4) post-workshop follow-up; 5) completion and review of the EET chapter. The AccessData model has been evolved over a series of six annual workshops hosting ~10 teams each. This model has been expanded to other venues to explore expanding its scope and sustainable mechanisms. These venues include 1) workshops focused on the data collected by a large research program (RIDGE, EarthScope); 2) a workshop focused on developing a citizen scientist guide to conducting research; and 3) facilitating a team on an annual basis within the structure of the Federation of Earth Science Information Partners (ESIP Federation), leveraging their semi-annual meetings. In this presentation we will describe the AccessData model of making geoscience data accessible and usable in educational contexts from the perspective of both the organizers and from a team. We will also describe how this model has been adapted to other contexts to facilitate a broader reach of geoscience data.

The Repository for Archiving, Managing and Accessing Diverse DAta (RAMADDA), is a web based application that provides a myriad of services for data access, subsetting, and visualization. RAMADDA accomodates many ways to populate its database with meta-data, data, and products. RAMADDA provides a myriad of services including, OPeNDAP, THREDDS, and RSS and can be extended to offer other services. RAMADDA is data agnostic, although created with earth system science in mind, it can handle any data type. Some services are data-centric, but the development of RAMADDA allows other users to provide other types of data handlers or services. RAMADDA is also closely integrated with Unidata's freely available 3D visualization client, the Integrated Data Viewer (IDV). One can directly access the data via the IDV and publish content directly back to the RAMADDA, allowing ease in navigating the full cycle of data use: discovery, access, 3D visualization, and publication back to RAMADDA. These capabilities lend themselves well to educational and research environments, and also facilitate collaboration.

Linked Environments for Atmospheric Discovery (LEAD) is a bold and revolutionary paradigm that through a Web-based Service Oriented Architecture (SOA) exposes the user to a rich environment of data, models, data mining and visualization and analysis tools, enabling the user to ask science questions of applications while the complexity of the software and middleware managing these applications is hidden from the user. From its inception in 2003, LEAD has championed goals that have context for the future of weather and related research and education. LEAD espouses to lowering the barrier for using complex end-to-end weather technologies by a) democratizing the availability of advanced weather technologies, b) empowering the user of these technologies to tackle a variety of problems, and c) facilitating learning and understanding. LEAD, as it exists today, is poised to enable a diverse community of scientists, educators, students, and operational practitioners. The project has been informed by atmospheric and computer scientists, educators, and educational consultants who, in search of new knowledge, understanding, ideas, and learning methodologies, seek easy access to new capabilities that allow for user-directed and interactive query and acquisition, simulation, assimilation, data mining, computational modeling, and visualization. As one component of the total LEAD effort, the LEAD education team has designed interactive, integrated, instructional pathways within a set of learning modules (LEAD-to-Learn) to facilitate, enhance, and enable the use of the LEAD gateway in the classroom. The LEAD education initiative focuses on the means to integrate data, tools, and services used by researchers into undergraduate meteorology education in order to provide an authentic and contextualized environment for teaching and learning. Educators, educational specialists, and students from meteorology and computer science backgrounds have collaborated on the design and development of learning materials, as well as new tools and features, to enhance the appearance and use of the LEAD portal gateway and its underlying cyberinfrastructure in an educational setting. The development of educational materials has centered on promoting the accessibility and use of meteorological data and analysis tools through the LEAD portal by providing instructional materials, additional custom designed tools that build off of Unidata's Integrated Data Viewer (IDV) (e.g. IDV Basic and NCDestroyer), and an interactive component that takes the user through specific tasks utilizing multiple tools. In fact, select improvements to parameter lists and domain subsetting have inspired IDV developers to incorporate changes in IDV revisions that are now available to the entire community. This collection of materials, demonstrations, interactive guides, student exercises, and customized tools, which are now available to the educator and student through the LEAD portal gateway, can serve as an instructional pathway for a set of guided, phenomenon-based exercises (e.g. fronts, lake-effect snows, etc.). This paper will provide an overview of the LEAD education and outreach efforts with a focus on the design of Web-based educational materials and instructional approaches for user interaction with the LEAD portal gateway and the underlying cyberinfrastructure, and will encourage educators, especially those involved in undergraduate meteorology education, to begin incorporating these capabilities into their course materials.

The scientific data collected by research programs funded by the government belongs to the public. As such it is the responsibility of the scientific and technical communities to make scientific data accessible and usable by the educational community. However, much geoscience data are difficult for educators and students to find and use. They are generally described by metadata that are narrowly focused, challenging educators and researchers in other fields to determine if the dataset is relevant to their needs, and to effectively access and use the data. Two strands of work directly address this issue. First, recommendations have been developed to implement 1) educationally relevant review criteria for data-rich Web sites (http://serc.carleton.edu/usingdata/site_criteria.html), and 2) educationally relevant metadata for datasets called DataSheets (http://serc.carleton.edu/usingdata/browse_sheets.html). These recommendations [Ledley et al., 2008] are to directly address data sites that are not by themselves an educational activity, but are intended to help educators and others easily find data sets, determine their relevance to their needs, and how to access them. Second, a model for bridging the scientific and educational communities to develop robust inquiry-based activities using scientific datasets in the form of Earth Exploration Toolbook (EET, http://serc.carleton.edu/eet) chapters has been developed. This model involves working directly with small teams made up of data providers from large scientific data archives, data analysis tool specialists, scientists, curriculum developers, and educators (AccessData, http://serc.carleton.edu/usingdata/accessdata). In this presentation we will 1) present the educationally relevant review criteria and metadata for data sets as a form of curation of the data for broad use and 2) describe the model of the AcccessData workshops as a model to facilitate collaboration between scientists and educators. Ledley, T. S., A. Prakash, C. Manduca, and S. Fox (2008), Recommendations for Making Geoscience Data Accessible and Usable in Education, Eos, 89(32), 291 (DOI: 210.1029/2008EO2003).

The recent 4.0 release of the netCDF library allows users to create HDF5 data files; this format provides new features such and chunking and data compression. This paper describes modifications to the Weather Research and Forecasting (WRF) Model to allow use of netCDF-4. Some performance measurements are presented.

The NOAA Weather and Climate Toolkit (WCT) is an application that provides simple visualization and data export of weather and climate data archived at the National Climatic Data Center (NCDC) and other organizations. The WCT is built on the Unidata Common Data Model and supports defined feature types such as Grid, Radial, Point, Time Series and Trajectory. Current NCDC datasets supported include NEXRAD Radar data, GOES Satellite imagery, NOMADS Model Data, Integrated Surface Data and the U.S. Drought Monitor (part of the National Integrated Drought Information System (NIDIS)). The WCT Viewer provides tools for displaying custom data overlays, Web Map Services (WMS), animations and basic filters. The export of images and movies is provided in multiple formats. The WCT Data Exporter allows for data export in both vector polygon (Shapefile, Well-Known Text) and raster (GeoTIFF, Arc/Info ASCII Grid, VTK, NetCDF) formats. By decoding and exporting data into multiple common formats, a diverse user community can perform analysis using familiar tools such as ArcGIS, MatLAB and IDL. This brings new users to a vast array of weather and climate data at NCDC.

The CF-netCDF data format has been proposed as a standard extension to the OGC (Open Geospatial Consortium) WCS (Web Coverage Service) core specification. The WCS core specification defines a protocol for describing and requesting grid (or "simple") coverages but leaves various details, including defining response encoding formats, for extension standards. The CF-netCDF format is widely used in the weather, climate, and ocean modeling community and the need for CF-netCDF as a supported WCS format was a key conlusion of the GALEON (Geo-interface for Air, Land, Environment, Ocean NetCDF) OGC Interoperability Experiment. This presentation outlines the key aspects of the proposed CF-netCDF encoding extension standard. The proposed extension consists of a mapping of the CF-netCDF data model (as embodied in Unidata's Common Data Model) to the ISO 19123 coverage specification, example WCS responses to describeCoverage and getCoverage requests for CF-netCDF encoded coverages as well as pointers to definitive documentation, examples, and implementations.

Beginning in 2008 OPeNDAP and Unidata have been working on an ambitious project to merge the functionality of two different implementations of the netCDF API into a single body of code. Unidata's implementation reads and writes to disk files while OPeNDAP's reads from data servers that support its Data Access Protocol (DAP). The reasons for combining the two are principally to reduce maintenance costs and delays for the introduction of new features, but a side affect has been to focus both groups on the issues of data model flexibility and simplicity. The netCDF format/API have been used in a wide range of contexts spanning the gamut of earth science disciplines including meteorology, oceanography, et c., as well as GIS applications. The Data Access Protocol has seen a similar breadth of use. Both of these software systems employ general data structuring technology based on well-understood information science principals such as data typing and grouping. However, the actual data models of DAP 2.0 and netCDF 3 are different in some significant ways. In merging the two both will require significant changes. We will discuss the on-going process of deciding which changes should be made, where they should be made and how to implement them without breaking software that uses the existing software and data models. In addition we will discuss the exciting prospects that combining these two libraries will provide, particularly how the combination of hierarchical, relational and array data types can facilitate data fusion.

UNAVCO and the IRIS DMC are data service partners for seismic visualization, particularly for hypocentral data and tomography. UNAVCO provides the GEON Integrated Data Viewer (IDV), an extension of the Unidata IDV, a free, interactive, research-level, software display and analysis tool for data in 3D (latitude, longitude, depth) and 4D (with time), located on or inside the Earth. The GEON IDV is designed to meet the challenge of investigating complex, multi-variate, time-varying, three- dimensional geoscience data in the context of new remote and shared data sources. The GEON IDV supports data access from data sources using HTTP and FTP servers, OPeNDAP servers, THREDDS catalogs, RSS feeds, and WMS (web map) servers. The IRIS DMC (Data Management System) has developed web services providing data for earthquake hypocentral data and seismic tomography model grids. These services can be called by the GEON IDV to access data at IRIS without copying files. The IRIS Earthquake Browser (IEB) is a web-based query tool for hypocentral data. The IEB combines the DMC's large database of more than 1,900,000 earthquakes with the Google Maps web interface. With the IEB you can quickly find earthquakes in any region of the globe and then import this information into the GEON Integrated Data Viewer where the hypocenters may be visualized. You can select earthquakes by location region, time, depth, and magnitude. The IEB gives the IDV a URL to the selected data. The IDV then shows the data as maps or 3D displays, with interactive control of vertical scale, area, map projection, with symbol size and color control by magnitude or depth. The IDV can show progressive time animation of, for example, aftershocks filling a source region. The IRIS Tomoserver converts seismic tomography model output grids to NetCDF for use in the IDV. The Tomoserver accepts a tomographic model file as input from a user and provides an equivalent NetCDF file as output. The service supports NA04, S3D, A1D and CUB input file formats, contributed by their respective creators. The NetCDF file is saved to a location that can be referenced with a URL on an IRIS server. The URL for the NetCDF file is provided to the user. The user can download the data from IRIS, or copy the URL into IDV directly for interpretation, and the IDV will access the data at IRIS. The Tomoserver conversion software was developed by Instrumental Software Technologies, Inc. Use cases with the GEON IDV and IRIS DMC data services will be shown.

Creating learning modules that utilize IPY data requires knowledge about the data, science, curriculum design, and educational context. The AccessData group has designed a 2.5 day workshop and follow-up strategy to facilitate the creation of effective IPY data-rich educational modules, making this data more accessible and usable by educators and students. Planning for the AccessData Workshop begins with the identification of teams of experts that include data providers, tool specialists, scientists, curriculum developers, and educators. Each team focuses on specific geoscience datasets and analysis tools. Prior to and during the workshop, each team is given a set of tasks that lead to developing an educational activity. The teams have time to work together at the workshop and the services of a professional curriculum developer who completes the learning activity after the workshop is over. Work begun at the workshop culminates when the activity is published as a chapter in the Earth Exploration Toolbook (EET, http://serc.carleton.edu/eet). The theme of the 2007 AccessData Workshop was IPY and Global Climate Change. This resulted in four of the ten teams focusing their efforts on IPY issues and data, and will result in at least four new EET chapters covering topics such as: 1) the collapse of the Larsen Ice Shelf, 2) changes in Arctic sea ice extent over the past 30 years, 3) the impact of climate changes in Alaska on the plant phenology, and 4) the melting of the Greenland ice sheet. In addition to developing outlines of educational modules on these topics, the teams also work together to produce a set of educationally relevant metadata for the datasets they plan to use in their activities. These are called DataSheets (http://serc.carleton.edu/usingdata/browse_sheets.html); and they enable educators, students, and other non-specialists to access the datasets and use them for learning. This presentation will focus on how the workshop facilitates the communication between IPY scientists and educational communities. It will also provide an overview of IPY-related EET chapters and how they can be integrated into teacher professional development programs and classrooms.

We have developed techniques and software tools for efficiently managing large geosciences data sets. While the techniques were developed as part of an NSF-Funded ITR project that focuses on making NEXRAD weather data and rainfall products available to hydrologists and other scientists, they are relevant to other geosciences disciplines that deal with large data sets. Metadata, relational databases, data compression, and networking are central to our methodology. Data and derived products are stored on file servers in a compressed format. URLs to, and metadata about the data and derived products are managed in a PostgreSQL database. Virtually all access to the data and products is through this database. Geosciences data normally require a number of processing steps to transform the raw data into useful products: data quality assurance, coordinate transformations and georeferencing, applying calibration information, and many more. We have developed the concept of crawlers that manage this scientific workflow. Crawlers are unattended processes that run indefinitely, and at set intervals query the database for their next assignment. A database table functions as a roster for the crawlers. Crawlers perform well-defined tasks that are, except for perhaps sequencing, largely independent from other crawlers. Once a crawler is done with its current assignment, it updates the database roster table, and gets its next assignment by querying the database. We have developed a library that enables one to quickly add crawlers. The library provides hooks to external (i.e., C-language) compiled codes, so that developers can work and contribute independently. Processes called ingesters inject data into the system. The bulk of the data are from a real-time feed using UCAR/Unidata's IDD/LDM software. An exciting recent development is the establishment of a Unidata HYDRO feed that feeds value-added metadata over the IDD/LDM. Ingesters grab the metadata and populate the PostgreSQL tables. These and other concepts we have developed have enabled us to efficiently manage a 70 Tb (and growing) data weather radar data set.

Hydro-NEXRAD is a software system with web-based user interface for obtaining historical customized NEXRAD- based radar-rainfall maps (products) from some 40 WSR-88D radars covering mainly the central and eastern U.S. These products have increased spatial and temporal resolution in comparison to the operational products available from the National Weather Service. Hydrologists can request customized products by selecting various algorithmic modules and parameter values and projected on a grid of choice. The output is formatted for ingest by geographic information systems and mapping software. The authors discuss the system architecture, the database extent and the possibilities of including additional algorithms in the future versions. They illustrate the utility of the software with several applications where side-by-side comparisons of various products allow studies of uncertainty propagation and sensitivity analysis. One of the comparisons presented involves the NWS products obtained with the Precipitation Processing System. Since one of the features of Hydro-NEXRAD is repeatability of the results, the system promotes systematic studies of new algorithms, comparisons with rain gauge data and error modeling, and uncertainty propagation in hydrologic applications. The authors also discuss future extensions of the system including a real-time version being developed in collaboration with Unidata of UCAR.

The Man computer Interactive Data Access System (McIDAS) project began over 30 years ago at the University of Wisconsin-Madison Space Science and Engineering Center (SSEC) to analyze and visualize data from the first generation polar and geostationary satellites. A new generation of imaging and sounding sensors developed for current and future operational satellites will be supported through innovative techniques for developing algorithms, visualizing data and products, and validating results. The Integrated Data Viewer (IDV), a reference application based on the VisAD library, is being developed by the Unidata Program and demonstrates the flexibility that is needed in this evolving environment, using a modern, object-oriented software design approach. The HYDRA software developed at SSEC within the VisAD library allows users to interrogate multi and hyper- spectral data in powerful ways. A project is underway at SSEC to transition the current McIDAS into a VisAD/IDV/HYDRA-based open-source system, known as McIDAS-V (fifth generation), and to provide researchers, algorithm developers, and operational users of multi-spectral and hyper-spectral data with the data manipulation and visualization tools to work in this data rich environment. NASA EOS MODIS and AIRS data and well as MSG SEVERI and METOP IASI data have been used in conjunction with other in situ and gridded data to develop new tools, techniques and products in the prototype McIDAS-V environment. This new data analysis and visualization software tool will support the advanced measurement systems on GOES R and NPOESS. A review of the current state of McIDAS-V will be presented as well as plans for future development to support both the polar and geostationary environmental satellite programs.

The overall goal of the NASA Rapid Prototyping Capability is to speed the evaluation of potential uses of NASA research products and technologies to improve future operational systems by reducing the time to access, configure, and assess the effectiveness of NASA products and technologies. The infrastructure to support the RPC is thus expected to provide the capability to rapidly evaluate innovative methods of linking science observations. The RPC infrastructure supports two major categories of experiments (and subsequent analysis): comparing results of a particular model as fed with data coming from different sources, and comparing different models using the data coming from the same source. In spite of being conceptually simple, two use cases in fact entail a significant technical challenge. Enabling RPC experiments requires thus a radical simplification of access to both actual and simulated data, as well as tools for data pre- and post-processing. The tools must be interoperable, allowing the user to create computational workflows with the data seamlessly transferred as needed, including third-party transfers to high-performance computing platforms. In addition, the provenance of the data must be preserved in order to document results of different what-if scenarios and to enable collaboration and data sharing between users. The functionality of the RPC splits into several independent modules such as interactive Web site, data server, tool's interfaces, or monitoring service. Each such module is implemented as an independent portlet. The RPC Portal aggregates the different contents provided by the portlets into a single interface employing a popular GridSphere portlet container. The RPC data access is based on Unidata's THREDDS Data server (TDS) extended to support, among others, interactive creation of containers for new data collections and uploading new data sets, downloading the data either to the user desktop or transferring it to a remote location using gridFTP, displaying the provenance of datasets, and invoking tools for the selected files. To enable performing experiments, RPC supports three types of tools integrated with TDS: (1) Standalone tools capable of connecting to the RPC data server to browse datasets, but otherwise performing all operations independently of the RPC infrastructure; (2) Transformations that take a dataset or a collection as an input, and output the transformed files, such as HEG, MRT, ART, and TSPT; (3) The data viewers and statistical analysis tools which do not produce new datasets.

In the past several years, interoperability gaps have made cross-protocol and cross-community data access a challenge within the Earth science community. One such gap is between two protocol families developed within the geospatial and Earth science communities. The Earth science community has developed a family of related geoscience protocols that includes OPeNDAP for data access and the Thematic Real-time Environmental Distributed Data Services (THREDDS) catalog capability. The corresponding protocols in the geospatial community are the Open Geospatial Consortium (OGC) protocols Web Coverage Service for geospatial data access and Catalog Services for Web (CSW) for data search. We have developed a catalog gateway to mediate client/server interactions between OGC catalog clients and THREDDS servers. In essence, the gateway is an OGC Catalog server that enables OGC clients to search for data registered in THREDDS catalogs. The gateway comprises two parts: the CSW server and a THREDDS-to-CSW ingestion tool. There are two key challenges in constructing such gateway, the first is to define the mapping relationship between the catalog metadata schema of CSW and that of the THREDDS, and the second one is to ingest the THREDDS catalog content into the CSW server. Since our CSW server is based on the ISO19115/ISO19119 Application Profile, a key challenge is to semantically map the ISO 19115 metadata attributes in ISO Application Profile to the THREDDS metadata attributes in the THREDDS Dataset Inventory Catalog Specification Version 1.0. With the mapping established, tools that translate the THREDDS catalog information model into the CSW/ISO Profile information model were developed. These dynamically poll THREDDS catalog servers and ingest the THREDDS catalog information into the CSW server's database, maintaining the hierarchical relationships inherent in the THREDDS catalogs. A prototype system has been implemented to demonstrate the concept and approach.

The planned Global Precipitation Measurement (GPM) mission will provide better coverage and more accurate satellite-based rain fall estimates than the current satellite measurements. The capabilities of the GPM-era rainfall products to meet the decision making needs for water resources management applications are being evaluated using land surface and hydrological modeling. A number of precipitation products that are derived from both satellite data and ground observation are being evaluated at spatial and temporal scales that are relevant for water management applications. Routine evaluation techniques and metrics, such as root mean squared error, false alarm ratio and other skill scores, used in the research community have been adopted in a rapid prototyping computational environment. In addition, novel fuzzy-based methodologies are also be implemented to characterize the uncertainties in the rainfall data. The Noah land surface model (LSM), incorporated with the NASA Land Information System (LIS), is used to simulate land surface and hydrological properties that are relevant for the decision making needs of the water resources management applications. Since June 2007, GPM proxy data, based on the NRL-Blended algorithm, was implemented for data collection over the continental United States and surrounding areas (0N-50N, 130W-50W). The collection of the various precipitation data sets has been automated. These precipitation data are then catalogued and distributed via the Unidata THREDDS server. The statistical verification algorithms are being incorporated into an "evaluation toolbox" used to characterize the uncertainties of the various rainfall estimates. The integration of the THREDDS server and the evaluation toolbox will provide a common framework for the evaluation of rainfall estimation techniques and their application using the land surface models in NASA LIS.

We examine the possibility of using the Web Coverage Service (WCS) protocol to deliver observational point data. An important implementation question is whether to encode the data in XML or binary. We implement a prototype server and measure the performance of returning the data in XML using a profile of the Geography Markup Language (GML) or returning the data in a netCDF binary file. We may also discuss related encoding issues, including XML variants and the use of the netCDF CF Conventions.

At the OGC (Open Geospatial Consortium) Technical Committee meetings, Unidata hosted a special Interoperability Day workshop to address the use of web services via standard interfaces for accessing a broad range of environmental data. These interfaces include: WCS (Web Coverage Service), WFS (Web Feature Service, SOS (Sensor Observation Service, CS-W/ebRIM (Catalog Service for the Web / electronic business Registry Information Model) for providing access to data currently served via THREDDS (THematic Real-time Environmental Distributed Data Services), OPeNDAP (Open source Project for a Network Data Access Protocol), netCDF-CF (network Common Data Form - Climate and Forecast conventions) and IDD/LDM (Internet Data Distribution / Local Data Manager) technologies. The primary data served includes weather, climate and ocean data from the community sometimes referred to as Fluid Earth Sciences (FES). An international set of representatives from industry, government, and academia, spanning many geosciences disciplines participated actively in the workshop and are committed to continued collaboration. The overall objective for the day was to come up with practical and concrete ideas for how to deliver various classes of FES data via web services through the standard interfaces. The primary focus was on gridded datasets (e.g., forecast model output) and station/observation/point datasets (e.g. the observational data collected at weather stations, ocean buoys, river gaging stations. As time allowed, other categories (profile/trajectory, swath, radial, unstructured grids) were addressed. The main objective was to come up with a realistic plan for dealing with gridded and station/observation/point datasets. Then the remaining categories can be addressed incrementally. This presentation summarizes the highlights of the Interoperability Day and the resulting plans for future implementation and testing.

Coastal Carolina University (CCU) students in Computer Science participated in a project to set up an operational weather forecast for the local community. The project involved the construction of two computing clusters and the automation of daily forecasting. Funded by NSF-MRI, two high-performance clusters were successfully established to run the University of Oklahoma's Advance Regional Prediction System (ARPS). Daily weather predictions are made over South Carolina and North Carolina at 3-km horizontal resolution (roughly 1.9 miles) using initial and boundary condition data provided by UNIDATA. At this high resolution, the model is cloud- resolving, thus providing detailed picture of heavy thunderstorms and precipitation. Forecast results are displayed on CCU's website (https://marc.coastal.edu/HPC) to complement observations at the National Weather Service in Wilmington N.C. Present efforts include providing forecasts at 1-km resolution (or finer), comparisons with other models like Weather Research and Forecasting (WRF) model, and the examination of local phenomena (like water spouts and tornadoes). Through these activities the students learn about shell scripting, cluster operating systems, and web design. More importantly, students are introduced to Atmospheric Science, the processes involved in making weather forecasts, and the interpretation of their forecasts. Simulations generated by the forecasts will be integrated into the contents of CCU's course like Fluid Dynamics, Atmospheric Sciences, Atmospheric Physics, and Remote Sensing. Operated jointly between the departments of Applied Physics and Computer Science, the clusters are expected to be used by CCU faculty and students for future research and inquiry-based projects in Computer Science, Applied Physics, and Marine Science.

The Climate and Forecast (CF) conventions governing metadata have become important to earth system science communities as a standard way of capturing the meaning of multidimensional data and the intent of data providers. The CF Conventions have proved useful for comparing conforming data from different sources and for unambiguously determining the space-time location of data. Originally developed and maintained by a small group in the climate modeling community, the CF Conventions have recently transitioned to a community governance structure. We discuss the process of evolving the development, maintenance, and community governance of an international data standard, as well as successes, challenges, and issues in maintaining and scaling the standard to broader uses through an open process.

The terms "Team Science" and "Networked Science" have been coined to describe a virtual organization of researchers tied via some intellectual challenge, but often located in different organizations and locations. A critical component to these endeavors is publishing and sharing of content, including scientific data. Imagine pointing your web browser to a web page that interactively lets you upload data and metadata to a repository residing on a remote server, which can then be accessed by others in a secure fasion via the web. While any content can be added to this repository, it is designed particularly for storing and sharing scientific data and metadata. Server support includes uploading of data files that can subsequently be subsetted, aggregrated, and served in NetCDF or other scientific data formats. Metadata can be associated with the data and interactively edited. The THREDDS Data Repository (TDR) is a server that provides client initiated, on demand, location transparent storage for data of any type that can then be served by the THREDDS Data Server (TDS). The TDR provides functionality to: 1) securely store and "own" data files and associated metadata; 2) upload files via HTTP and gridftp; 3) upload a collection of data as single file; 4) modify and restructure repository contents; 5) incorporate metadata provided by the user; 6) generate additional metadata programmatically; and 7) edit individual metadata elements. The TDR can exist separately from a TDS, serving content via HTTP. Also, it can work in conjunction with the TDS, which includes functionality to provide: 1) access to data in a variety of formats via OPeNDAP, OGC Web Coverage Service (for gridded datasets), and bulk HTTP file transfer; 2) a NetCDF view of datasets in NetCDF, OPeNDAP, HDF-5, GRIB, and NEXRAD formats; 3) serving of very large volume datasets, such as NEXRAD radar; 4) aggregation into virtual datasets; and 5) subsetting via OPeNDAP and NetCDF Subsetting services. This talk will discuss TDR/TDS capabilities as well as how users can install this software to create their own repositories.

The Arctic Observing Network (AON) is intended to be a federation of 34 land, atmosphere and ocean observation sites, some already operating and some newly funded by the U.S. National Science Foundation. This International Polar Year (IPY) initiative will acquire a major portion of the data coming from the interagency Study of Environmental Arctic Change (SEARCH). AON will succeed in supporting the science envisioned by its planners only if it functions as a system and not as a collection of independent observation programs. Development and implementation of a comprehensive data management strategy will key a key to the success of this effort. AON planners envision an ideal data management system that includes a portal through which scientists can submit metadata and datasets at a single location; search the complete archive and find all data relevant to a location or process; all data have browse imagery and complete documentation; time series or fields can be plotted on line, and all data are in a relational database so that multiple data sets and sources can be queried and retrieved. The Cooperative Arctic Data and Information Service (CADIS) will provide near-real-time data delivery, a long-term repository for data, a portal for data discovery, and tools to manipulate data by building on existing tools like the Unidata Integrated Data Viewer (IDV). Our approach to the data integration challenge is to start by asking investigators to provide metadata via a general purpose user interface. An entry tool assists PIs in writing metadata and submitting data. Data can be submitted to the archive in NetCDF with Climate and Forecast conventions or in one of several other standard formats where possible. CADIS is a joint effort of the University Corporation for Atmospheric Research (UCAR), the National Snow and Ice Data Center (NSIDC), and the National Center for Atmospheric Research (NCAR). In the first year, we are concentrating on establishing metadata protocols that are compatible with international standards, and on demonstrating data submission, search and visualization tools with a subset of AON data. These capabilities will be expanded in years 2 and 3. By working with AON investigators and by using evolving conventions for in situ data formats as they mature, we hope to bring CADIS to the full level of data integration imagined by AON planners. The CADIS development will be described in terms of challenges, implementation strategies and progress to date. The developers are making a conscious effort to integrate this system and its data holdings with the complementary efforts in the SEARCH and IPY programs. The interdisciplinary content of the data, the variations in format and documentation, as well as its geographic coverage across the Arctic Basin all impact the form and effectiveness of the CADIS system architecture. The clever solutions to the complexity of implementing a comprehensive data management strategy implied in this diversity will be a focus of the presentation.

The THREDDS Data Server (TDS) is a web server that provides metadata and data access for scientific datasets. It provides OPeNDAP, WCS, HTTP and netCDF subsetting services for a number of data formats, including netCDF, HDF5, GRIB, BUFR, etc. The TDS is 100% Java, and runs within the Tomcat web server. We have added a new way to serve model data, which takes a collection of Forecast Model Run datasets, and constructs a single dataset with a 2D time coordinate (run time, forecast time). In the case of Unidata's server, these are collections of GRIB files, and we deal correctly with missing data records by using the forecast and run dates, rather than array indices. The TDS also creates various other "synthetic" datasets from the collection: 1) all data from one analysis run; 2) data with the same forecast offset hour (eg all the 3 hour forecasts, from different runs); 3) data with a constant forecast date (eg all the data with forecast/valid time of 2006-08-08T12:00:00Z, from different runs); and 4) the "best" time series, taking the data from the most recent run available. We are currently working with a number of data partners to test and extend this functionality.

The International Polar Year is an opportunity to simultaneously increase our scientific understanding of the polar regions and to engage the next generation of Earth scientists and socially responsible citizens. However, building the bridge between the scientific community who conduct the research and the education community who convey that information to students requires specific and continuing efforts. The Earth Exploration Toolbook (EET, http://serc.carleton.edu/eet) and the accompanying spectrum of activities encompassing development of materials that can provide access and understanding of IPY data and knowledge, and teacher professional development to facilitate the effective use of these materials with students can help build that bridge. The EET is an online resource that provides an easy way for educators to learn how to use Earth science datasets and data analysis tools to convey science concepts. Modules (called chapters) in the EET provide step-by-step instructions for accessing and analyzing these datasets within compelling case studies, and provide pedagogical information to help the educator use the data with their students. New EET chapters, featuring IPY data, can be developed through the use of an EET chapter template that standardizes the content and structure of the chapter. The initiation of new chapters can be facilitated through our Data in Education Workshops (previously DLESE Data Services Workshops, http://swiki.dlese.org/2006- dataservicesworkshop/). During these workshops IPY data providers, analysis tool specialists, IPY scientists, curriculum developers, and educators participate on teams of 5-6 members to create an outline of a new EET chapter featuring the IPY data and analysis tools represented on the team. New chapters will be completed by a curriculum developer following the workshop. Use of the IPY EET chapters will be facilitated by a range of professional development activities ranging from two 2-hour telecon-online workshops over the period of a month, to a year long professional development program that includes telecon-online workshops, a two-week summer workshop, follow-up online discussions and one-day meetings. In this paper we will discuss the EET and the spectrum of activities that can facilitate building a bridge between the IPY scientific community and future scientists and socially responsible citizens.

Those who have experienced the devastation of a tornado, the raging waters of a flash flood, or the paralyzing impacts of lake-effect snows understand that mesoscale weather develops rapidly, often with considerable uncertainty with regard to location. Such weather is also locally intense and frequently influenced by processes on both larger and smaller scales. Ironically, few of the technologies used to observe the atmosphere, predict its evolution, and compute, transmit, or store information about it operate in a manner that accommodates the dynamic behavior of mesoscale weather. Radars do not adaptively scan specific regions of thunderstorms; numerical models are run largely on fixed time schedules in fixed configurations; and cyberinfrastructure does not allow meteorological tools to run on-demand, change configurations in response to the weather, or provide the fault tolerance needed for rapid reconfiguration. As a result, today's weather technology is highly constrained and far from optimal when applied to any particular situation. This presentation describes a major paradigm shift now underway in the field of meteorology -- away from today's environment in which remote sensing systems, atmospheric prediction models, and hazardous weather detection systems operate in fixed configurations, and on fixed schedules largely independent of weather -- to one in which they can change their configuration dynamically in response to the evolving weather. A major driver of this change is a project known as Linked Environments for Atmospheric Discovery (LEAD) -- a 5-year NSF Large Information Technology Research (ITR) grant that is developing cyberinfrastructure to allow scientists, students, tools and sensors to interact with weather. This presentation will describe the research and technology development being performed to establish this capability

On July 13th 2006 during the triannual Unidata Workshop, members of the Unidata community got their first experience with capabilities being developed under the Linked Environments for Atmospheric Discovery (LEAD) project (see: http://lead.ou.edu). The key LEAD goal demonstrated during the workshop was that of "Democratization," that is, providing capabilities that typically have a high barrier to entry to the larger meteorological community. At the workshop, participants worked with software that demonstrated the specific concepts of: 1) Lowering the barrier to entry by making it easy for users to: - Experiment using meteorological tools - Create meteorological forecasts - Perform mesoscale modeling and forecasting - Access data (source and product) - Make use of large scale cyberinfrastructure (E.g. TeraGrid) 2) Giving users the freedom from technological issues such as: - Hassle-free access to supercomputing resources - Hassle-free execution of forecast models and related tools - Data format independence This talk will overview the capabilities presented to the Unidata workshop participants as well as capabilities developed since the workshop. There will also be a lessons-learned section. This overview will be accomplished with a live demonstration of some of the capabilities. Capabilities that will be discussed and demonstrated have applicability across many disciplines - e.g. discovering, acquiring and using data and orchestrating of complex workflow. Acknowledgement: The LEAD project involves the work of nearly 100 individuals whose dedication has resulted in the capabilities that will be shown here. The authors would like to recognize all of them, but in particular we'd like to recognize: John Caron, Rich Clark, Ethan Davis, Charles Hart, Yuan Ho, Scott Jenson, Rob Kambic, Brian Kelly, Ning Liu, Jeff McWhirter, Don Murray, Beth Plale, Rahul Ramachandran, Yogesh Simmhan, Kevin Thomas, Nithya Vijayakumar, Yunheng Wang, Dan Weber, and Bob Wilhelmson.

For many years Unidata has provided easy, low cost data access to universities and research labs. Historically Unidata technology provided access to data in near real time. In recent years Unidata has additionally turned to providing middleware to serve longer term data and associated metadata via its THREDDS technology, the most recent offering being the THREDDS Data Server (TDS). The TDS provides middleware for metadata access and management, OPeNDAP data access, and integration with the Unidata Integrated Data Viewer (IDV), among other benefits. The TDS was designed to support rolling archives of data, that is, data that exist only for a relatively short, predefined time window. Now we are creating an addition to the TDS, called the THREDDS Data Repository (TDR), which allows users to store and retrieve data and other objects for an arbitrarily long time period. Data in the TDR can also be served by the TDS. The TDR performs important functions of locating storage for the data, moving the data to and from the repository, assigning unique identifiers, and generating metadata. The TDR framework supports pluggable components that allow tailoring an implementation for a particular application. The Linked Environments for Atmospheric Discovery (LEAD) project provides an excellent use case for the TDR. LEAD is a multi-institutional Large Information Technology Research project funded by the National Science Foundation (NSF). The goal of LEAD is to create a framework based on Grid and Web Services to support mesoscale meteorology research and education. This includes capabilities such as launching forecast models, mining data for meteorological phenomena, and dynamic workflows that are automatically reconfigurable in response to changing weather. LEAD presents unique challenges in managing and storing large data volumes from real-time observational systems as well as data that are dynamically created during the execution of adaptive workflows. For example, in order to support storage of many large data products, the LEAD implementation of the TDR will provide a variety of data movement options, including gridftp. It will have a web service interface and will be callable programmatically as well as via interactive user requests. Future plans include the use of a mass storage device to provide robust long term storage. This talk will present the current state of the TDR effort.

Linked Environments for Atmospheric Discovery (LEAD) has as its goal to make meteorological data, forecast models, and analysis and visualization tools available to anyone who wants to interactively explore the weather as it evolves. LEAD advances through the development and beta-deployment of Integrated Test Beds (ITBs), which are technology build-outs that are the fruition of collaborative IT and meteorological research. As the ITBs mature, opportunities emerge for the integration of this new technological capability into the education arena. The LEAD education and outreach initiative is aimed at bringing new capabilities into classroom from the middle school level to graduate education and beyond, and ensuring the congruency of this technology with curricular. One of the principal goals of LEAD is to democratize the availability of advanced weather technologies for research and education. The degree of democratization is tied to the growth of student knowledge and skills, and is correlated with education level (though not for every student in the same way). The average high school student may experience LEAD through an environment that retains a higher level of instructor control compared to the undergraduate and graduate student. This is necessary to accommodate not only differences in knowledge and skills, but the computer capabilities in the classroom such that the "teachable moment" is not lost.Undergraduates will have the opportunity to query observation data and model output, explore and discover relationships through concept mapping using an ontology service, select domains of interest based on current weather, and employ an experiment builder within the LEAD portal as an interface to configure, launch the WRF model, monitor the workflow, and visualize results using Unidata's Integrated Data Viewer (IDV), whether it be on a local server or across the TeraGrid. Such a robust and comprehensive suite of tools and services can create new paradigms for embedding students in an authentic, contextualized environment where the knowledge domain is an extension, yet integral supplement, to the classroom experience.This presentation describes two different approaches for the use of LEAD in undergraduate education: 1) a use-case for integrating LEAD technology into undergraduate subject material; and 2) making LEAD capability available to a select group of students participating in the National Collegiate Forecasting Contest (NCFC). The use-case (1) is designed to have students explore a particular weather phenomenon (e.g., a frontal boundary, jet streak, or lake effect snow event) through self-guided inquiry, and is intended as a supplement to classroom instruction. Students will use interactive, Web-based, LEAD-to-Learn modules created specifically to build conceptual knowledge of the phenomenon, adjoin germane terminology, explore relationships between concepts and similar phenomena using the LEAD ontology, and guide them through the experiment builder and workflow orchestration process in order to establish a high-resolution WRF run over a region that exhibits the characteristics of the phenomenon they wish to study. The results of the experiment will be stored in the student's MyLEAD workspace from which it can be retrieved, visualized and analyzed for atmospheric signatures characteristic of the phenomenon. The learning process is authentic in that students will be exposed to the same process of investigation, and will have available many of the same tools, as researchers. The modules serve to build content knowledge, guide discovery, and provide assessment while the LEAD portal opens the gateway to real-time observations, model accessibility, and a variety of tools, services, and resources.

With a modest investment in computer hardware and the open source local data manger (LDM) software from UCAR's Unidata Program Center, an individual researcher can receive a variety of NEXRAD Level III gridded rainfall products, and the unprocessed Level II data in real-time from most NEXRAD radars. Additionally, the National Climatic Data Center has vast archives of these products and Level II data. Still, significant obstacles remain in order to unlock the full potential of the data. One set of obstacles is related to effective management of multi-terrabyte data sets: storing, compressing, and backing up. A second set of obstacles, for hydrologists and hydrometeorologists in particular, is that the NEXRAD Level III products are not well suited for application in hydrology. There is a strong need for the generation of high-quality products directly from the Level II data with well-documented step that include quality control, removal of false echos, rainfall estimating, coordinate conversion and georeferencing, conversion to a convenient data format(s), and integration with GIS. For hydrologists it is imperative that these procedures are basin-centered as opposed to radar-centered. Thirdly, the amount of data present in a multi-year, multi-radar dataset is such that simple cataloging and indexing of the data is not sufficient. Rather, sophisticated metadata extraction and management techniques are required. With support from the National Science Foundation through it ITR program, the authors are developing a basin- centered framework for addressing all these issues in a comprehensive manner, tailored specifically for use of NEXRAD data in hydrology and hydrometeorology. Through a flexible web interface users can search a large metadata database base, managed by in relational database engine, for subsets of interest. Well-chosen and documented defaults are provided for the flow from unprocessed NEXRAD data to basin-centered rainfall estimates. In addition to the web interface, there are web services that provide access to scripts and compiled programs.

Modern geoscience data are often spatially intricate and temporally variable. Finding and studying significant features in such data is greatly improved with new approaches that use the mind's sensitivity to details in temporally-changing 3D visualizations, with data-specific colors and symbols. UNAVCO's GEON IDV, an extension of the Unidata atmospheric science-emphasis IDV, is a powerful tool for exploration and display of data in solid earth geophysics. The GEON IDV accepts most any earth-located data, including 2D, 3D, and 4D grids, point observations, and tracks and soundings. Distributed data from several protocols and sources can be used together, including local files, URLs, web catalog servers such as THREDDS catalogs and OPeNDAP data servers, and web map servers. Diverse data sets can be viewed simultaneously in three-dimensional displays with full control of vertical scale, depth, color, and time animation. True 3D stereographic visualizations are possible with dual projectors using polarized filters and glasses. Data computations and analysis can also be accomplished using formulas written in the Python language. Recent work has demonstrated IDV value in seismic tomography and mantle geodynamics. Studies from global convective flow for the past 170 my, to the time-varying topography of California during the past 3 my, to studies of the present earth crust using seismicity and earth strain, use the IDV. IDV displays are as useful in education as in research, both as a tool in the classroom or for building content. The IDV relies on the power of the netCDF file format. NetCDF data files provide complete metadata including geolocation, data units, data provenance, publication references, data creator credits, affiliations, and contact information, and information to support data discovery by geospatial, temporal, and keyword searches. All netCDF metadata can be seen with the IDV. The GEON IDV web site provides complete description of formatting data for the GEON and software tools for data conversion to netCDF. New IDV installer files and a plug-in for the GEON IDV make installation of the GEON IDV quick in most cases. Unidata and UNAVCO provide ongoing support and development for the IDV. UNAVCO registers published geophysical data in the GEON Portal, where users can find recognized and new data sets for use in the GEON IDV. The GEON Portal uses a Service Oriented Architecture to provide online data registration and online search service to support quick data discovery and downloads. NetCDF capability has recently been integrated into the GEON portal. Seamless visualization of 3D/4D volumes, additional integration capabilities at the portal, and registration of OPeNDAP/netCDF data servers are under development.

New imaging and sounding sensors under development for future geostationary and polar-orbiting operational environmental satellites will offer exciting new challenges to the design of the data structures and to the capabilities of current visualization tools. 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 library that is being developed by the Unidata Program, demonstrates the flexibility that is needed in this evolving environment, using a modern, object-oriented software design approach. A project is underway at the University of Wisconsin-Madison SSEC/CIMSS to transition the current McIDAS- X (Man computer Interactive Data Access System for X-Windows) users into an IDV-based, open-source system to be known as McIDAS-V. The McIDAS-V will provide multi-spectral and hyper-spectral researchers and algorithm developers with the data manipulation and visualization tools to work in this data rich environment. This poster describes the IDV and McIDAS-V software, data structures and data access, and demonstrates its' powerful 4-dimensional data analysis, product generation and display capabilities. NASA EOS MODIS and AIRS as well as GOES data are used in conjunction with other in situ and gridded data to develop these new tools, techniques and products in the prototype McIDAS-V environment.

The Open Geospatial Consortium (OGC) Web Coverage Service (WCS) revision 1.1 specification includes many modifications that are important to the communities working with existing services and clients based on netCDF (network Common Data Form), THREDDS THematic Real-time Environmental Distributed Data Services), OPeNDAP Open-source Project for Network Data Access Protocol), and ADDE (Abstract Data Distribution Envrironment) technologies. Chief among the WCS changes is the requirement that WCS binary encoding formats have documented application profiles. NetCDF will be among the first WCS binary encoding format profiles. In addition, WCS 1.1 enables multiple fields in a coverage, 3 spatial dimensions, 2 time dimensions (e.g., the time a forecast was run and the forecast times within the run), relative time ( e.g., the latest image), non-spatial dimension (e.g., pressure or density), irregular grids. In Phase 2 of the GALEON (Geo-interface for Land, Environment, Earth, Ocean NetCDF) Interoperability experiment, the participants will 1. Implement and test clients and servers that conform to the new WCS 1.1 spec and experiment with them on a wide range of real-world datasets. 2. Test the OGC CS-W (Catalog Services for the Web) as a means for accessing lists of datasets available on WCS servers. as well as WCS. As an illustration of the challenge, the top level 3. Evaluate various OGC GML (Geography Markup Language) dialects as a means for representing the information in netCDF datasets. This will include: ncML-GML (netCDF Markup Language-GML), CSML (Climate Sciences Modeling Language), and GMLJP2 (GML for JPEG 2000). Many of the datasets and catalogs for these experiements will be from existing netCDF, THREDDS, OPeNDAP, and ADDE servers.

Case studies, in the past, have generally been a collection of static data sets. Often these data sets were required to be in the same data format and location, for use in the case study. This project is generating a new concept on how to create case studies so that they can incorporate a myriad of data types from various sources and allow the end user many options on viewing the data based on their interests and perspective. This project also plans to allow for the community to contribute datasets to a case study as well as curriculum, and other views on the data. For example, a hurricane case study would offer datasets that would be useful for atmospheric researchers, but allow the flexibility to request other parameters of the data sets that may be of interest to other scientific disciplines such as oceanography, hydrology, and emergency management. To achieve these goals new and existing technologies will be implemented. The client capable of utilizing these technologies is the Unidata Integrated Data Viewer (IDV), and it will be utilizing a variety of servers and data catalogs to allow the distributed and disparate data to be viewed together via a single client. Other technologies being used are the THREDDS (Thematic Realtime Environmental Distributed Data Services) servers and cataloging service, ADDE (Abstract Distributed Data Environment) servers, OPeNDAP (Open- source Project for a Network Data Access Protocol) servers, HTTP (Hypertext Transfer Protocol) and (WMS) Web Map Servers. This will allow data sets, and educational materials, to be accessed and manipulated by the end user. Another technology currently being developed, the TDR (THREDDS Data Repository) will allow the user to contribute back either additional datasets pertinent to the case study, curriculum, or their own perspective of the event, allowing for a dynamic case study that can grow and be enriched over time.

The CUAHSI hydrologic information system (HIS) is designed to be a live, multiscale web portal system for accessing, querying, visualizing, and publishing distributed hydrologic observation data and models for any location or region in the United States. The HIS design follows the principles of open service oriented architecture, i.e. system components are represented as web services with well defined standard service APIs. WaterOneFlow web services are the main component of the design. The currently available services have been completely re-written compared to the previous version, and provide programmatic access to USGS NWIS. (steam flow, groundwater and water quality repositories), DAYMET daily observations, NASA MODIS, and Unidata NAM streams, with several additional web service wrappers being added (EPA STORET, NCDC and others.). Different repositories of hydrologic data use different vocabularies, and support different types of query access. Resolving semantic and structural heterogeneities across different hydrologic observation archives and distilling a generic set of service signatures is one of the main scalability challenges in this project, and a requirement in our web service design. To accomplish the uniformity of the web services API, data repositories are modeled following the CUAHSI Observation Data Model. The web service responses are document-based, and use an XML schema to express the semantics in a standard format. Access to station metadata is provided via web service methods, GetSites, GetSiteInfo and GetVariableInfo. The methdods form the foundation of CUAHSI HIS discovery interface and may execute over locally-stored metadata or request the information from remote repositories directly. Observation values are retrieved via a generic GetValues method which is executed against national data repositories. The service is implemented in ASP.Net, and other providers are implementing WaterOneFlow services in java. Reference implementation of WaterOneFlow web services is available. More information about the ongoing development of CUAHSI HIS is available from http://www.cuahsi.org/his/.

Data discovery is often compartmentalized into discovery at the "catalog" level - high level, broad descriptions of data sets or collections - and discovery at the "inventory" level - detailed listings of granules in data sets. The catalog and inventory levels are also generally viewed as distinct from the data level, where the actual data granules reside. With an increase in on-line access to data such as that offered by OPeNDAP, WFS, WCS and WMS, there has been an increase in interest in discovery capabilities that provide the data, or lists of URLs for the data, meeting a variety of search criteria - in other words, a seamless capability to find and retrieve data of interest. In order to address issues related to discovery in a distributed environment, a workshop was held in May 2006 at Unidata/UCAR in Boulder, Colorado. Participants were drawn from 8 organizations dealing with various issues related to data discovery. The workshop began with the description of a number of different data discovery capabilities, including ECHO, GCMD, THREDDS, and ADL. This was followed by the analysis of two case studies with specific attention given to the ability, or lack thereof, of current data discovery components to find data relevant to the case studies. Several key findings resulted from this analysis which, although obvious in retrospect, we believe to be major deficiencies in the way data discovery is being approached today. These findings are: 1) there is no consistency in the inventorying of data; 2) links between the catalog, inventory and data levels are tenuous at best; moving from the catalog to the inventory level and from the inventory to the data level is tedious at best; and 3) there is little to no consistency in the access protocols that are used by data discovery components. This is especially true at the inventory level. These findings suggest that the level of effort involved in finding data of interest could be substantially reduced by either reducing the number of steps in the discovery process or by reducing the number of protocols used. These findings will be discussed in detail in this presentation.

Although Earth science data and tools are officially freely available to the public, specific data are generally difficult to find, and are often provided in formats that are difficult to use. The Earth Exploration Toolbook (EET, http://serc.carleton.edu/eet) and DLESE (Digital Library for Earth Systems Education) Data Services (http://www.dlese.org/cms/dataservices/) projects are working to facilitate the use of these data and analysis tools by teachers and students, and can serve as mechanisms, facilitated by eGY, for extending the reach of data resulting from the various I*Y scientific efforts. The EET gives educators and students an easy way to learn how to use Earth science data and data analysis tools for learning. Modules (called chapters) in the EET provide step-by-step instructions for accessing and analyzing Earth science datasets within the context of compelling case studies. Each chapter also provides pedagogical information to help the teacher use the data with their students. To introduce datasets and analysis tools to teachers, and to encourage them to use them with their students, the EET team provides telecon-online teacher professional development workshops. During these workshops teachers are guided through the use of a specific EET chapter. When a workshop is complete, participants have the software and data they have worked with installed and available on their own computers. We have run 17 of these workshops reaching over 230 teachers. New EET chapters can be developed through the use of an EET chapter template. The template provides a mechanism by which those outside the project can make their datasets and data analysis tools more accessible to teachers and students, and assures that new chapters are consistent with the EET format and that users have access to the support they need. The development of new EET chapters is facilitated through the DLESE Data Services Workshops. During these workshops data providers, tool developers, scientists, curriculum developers, and educators are invited to participate on teams of 5-6 members (with all these areas of expertise represented) who work to create an EET chapter featuring the data and data analysis tools represented on the team. We found that face-to-face collaboration on these teams allowed the sharing of perspectives and encouraged the contribution of individual expertise, facilitating development of data-rich EET chapters. During this presentation we will discuss the structure of the EET and its chapters, the teacher telecon-online workshops and their outcomes, the EET template and how it facilitates the development of new chapters, mainly through the DLESE Data Services Workshops.

A revolution is underway in the role played by cyberinfrastructure and data services in the conduct of research and education. We live in an era of an unprecedented data volume from diverse sources, multidisciplinary analysis and synthesis, and active, learner-centered education emphasis. For example, modern remote-sensing systems like hyperspectral satellite instruments generate terabytes of data each day. Environmental problems such as global change and water cycle transcend disciplinary as well as geographic boundaries, and their solution requires integrated earth system science approaches. Contemporary education strategies recommend adopting an Earth system science approach for teaching the geosciences, employing new pedagogical techniques such as enquiry-based learning and hands-on activities. Needless to add, today's education and research enterprise depends heavily on robust, flexible and scalable cyberinfrastructure, especially on the ready availability of quality data and appropriate tools to manipulate and integrate those data. Fortuitously, rapid advances in computing and communication technologies have also revolutionized how data, tools and services are being incorporated into the teaching and scientific enterprise. The exponential growth in the use of the Internet in education and research, largely due to the advent of the World Wide Web, is by now well documented. On the other hand, how some of the other technological and community trends that have shaped the use of cyberinfrastructure, especially data services, is less well understood. For example, the computing industry is converging on an approach called Web services that enables a standard and yet revolutionary way of building applications and methods to connect and exchange information over the Web. This new approach, based on XML - a widely accepted format for exchanging data and corresponding semantics over the Internet - enables applications, computer systems, and information processes to work together in a fundamentally different way. Likewise, the advent of digital libraries, grid computing platforms, interoperable frameworks, standards and protocols, open-source software, and community atmospheric models have been important drivers in shaping the use of a new generation of end-to-end cyberinfrastructure for solving some of the most challenging scientific and educational problems. In this talk, I will present an overview of the scientific, technological, and educational drivers and discuss recent developments in cyberinfrastructure and Unidata's role and directions in providing robust, end-to-end data services for solving geoscientific problems and advancing student learning.

Disparate, "stove-pipe" data systems are among the main impediments to many interdisciplinary research projects in the geosciences. The solid earth disciplines and hydrology tend to use Geographic Information Systems (GIS) which enable them to store and interact with data representing as discrete features on or near the surface of the earth. Studies of the oceans and atmosphere on the other hand involve systems that represent data as discrete points in the continuous function space of fluid dynamics. Attempts to understand the nature of severe precipitation and flooding events are hampered by the difficulty of integrating data such as streamflows from hydrological data systems with radar data and precipitation forecasts from atmospheric science data systems. An effort is underway to address some of these issues with an interoperability experiment within the framework of the Open Geospatial Consortium (OGC). The experiment is called GALEON (Geo-interface to Atmosphere, Land, Earth, Ocean NetCDF). Teams at the Unidata Program Center and University of Florence are working with a number of international partners to implement a web services interface to traditional atmospheric and oceanographic datasets currently stored in netCDF form or served via the OPeNDAP protocol . The project will result in a gateway service using Web Coverage Service (WCS) specification of the OGC. Underneath the WCS interface will be a combination of technologies including THREDDS (THematic Real-time Environmental Distributed Data Services) and HDF5 (Heirarchical Data Format) in addition to netCDF and OPeNDAP. A key component of the project is to develop mechanisms for explicit encoding of coordinate system information in the form of Coordinate System extensions to NcML (the netCDF Markup Language), directly in the data files themselves and in the form of GML (Geography Markup Language) extensions to NcML. These extensions, called NcML-GML, include a subset profile of the standard GML which is in the late stages of adoption by the International Standards Organization (ISO). The paper presents the current status and updated objectives of the project

AB: The Unidata Internet Data Distribution (IDD) network delivers gigabytes of data per day in near real time to sites across the U.S. and beyond. The THREDDS Data Server (TDS) supports public browsing of metadata and data access via OPeNDAP enabled URLs for datasets such as these. With such large quantities of data, sites generally employ a simple data management policy, keeping the data for a relatively short term on the order of hours to perhaps a week or two. In order to save interesting data in longer term storage and make it available for sharing, a user must move the data herself. In this case the user is responsible for determining where space is available, executing the data movement, generating any desired metadata, and setting access control to enable sharing. This task sequence is generally based on execution of a sequence of low level operating system specific commands with significant user involvement. The LEAD (Linked Environments for Atmospheric Discovery) project is building a cyberinfrastructure to support research and education in mesoscale meteorology. LEAD orchestrations require large, robust, and reliable storage with speedy access to stage data and store both intermediate and final results. These requirements suggest storage solutions that involve distributed storage, replication, and interfacing to archival storage systems such as mass storage systems and tape or removable disks. LEAD requirements also include metadata generation and access in order to support querying. In support of both THREDDS and LEAD requirements, Unidata is designing and prototyping the THREDDS Data Repository (TDR), a framework for a modular data repository to support distributed data storage and retrieval using a variety of back end storage media and interchangeable software components. The TDR interface will provide high level abstractions for long term storage, controlled, fast and reliable access, and data movement capabilities via a variety of technologies such as OPeNDAP and gridftp. The modular structure will allow substitution of software components so that both simple and complex storage media can be integrated into the repository. It will also allow integration of different varieties of supporting software. For example, if replication is desired, replica management could be handled via a simple hash table or a complex solution such as Replica Locater Service (RLS). In order to ensure that metadata is available for all the data in the repository, the TDR will also generate THREDDS metadata when necessary. Users will be able to establish levels of access control to their metadata and data. Coupled with a THREDDS Data Server, both browsing via THREDDS catalogs and querying capabilities will be supported. This presentation will describe the motivating factors, current status, and future plans of the TDR.

NetCDF is already widely used for creating, accessing, distributing, archiving, and sharing data in the geosciences. Independently developed HDF software implements another popular data model, data access libraries, and format for scientific data. Recently, we have developed software that implements an enhanced data model for netCDF using the HDF5 storage layer. The new software provides compatibility with existing netCDF programs and data but also supports the use of more powerful data modeling abstractions that may be used to capture more of the meaning in data. We discuss how the new features are intended to be used, and make recommendations for both data providers and developers who may be considering the use of netCDF for future archives or applications.

The problems monitoring, predicting, and responding to coastal inundation and inland flooding situations are inherently multidisciplinary. Predicting precipitation and streamflow require expertise in meteorology and hydrology. Oceanography also enters the picture in the cases where the severe storm occurs in a coastal area. Appropriate responses to such natural hazards requires integration of infrastructure and demographics data systems associated with the societal impacts community. Building and disseminating a system that will address this problem in a comprehensive and coherent manner can only be done by a team with the a broad range of technological and scientific expertise and community connections. Efforts are underway to develop interoperable data systems among the atmospheric science, hydrology, coastal oceans, and societal impacts communities, so they may conveniently and rapidly share data among their systems in cases where hazardous events threaten infrastructure and human health. The basic approach is to build on a dynamically adaptive data access and high resolution, local forecasting system being developed for the LEAD (Linked Environments for Atmospheric Discovery) project. At present, the LEAD technology is confined to local weather forecasts automatically steered by algorithms analyzing data from national forecasts. But efforts are underway to develop an expanded team that would include expertise in coupling atmospheric forecast models with hydrological and storm surge forecast models and, in turn, to coordinate those data systems with those of the GIS (Geographic Information System) community which contain most of the demographic and infrastructure information related to societal impacts. The paper will provide an update on the status of these efforts and a demonstration of how such a dynamically adaptive forecasting system focused high resolution local forecast model runs on Hurricane Katrina.

The THREDDS Data Server (TDS) is an open-source, pure Java web application that runs inside a Tomcat web server and provides metadata and data access to scientific datasets. The TDS integrates THREDDS Catalog services, an OpenDAP data server, an experimental OGC Web Coverage Server, and other web services, using the NetCDF Common Data Model to read and serve scientific data. The Common Data Model (CDM) is an abstract data model that the NetCDF (Unidata), HDF5 (NCSA) and OPeNDAP (University of Rhode Island) developers are working towards. The CDM also adds "Georeferencing Coordinate Systems" and specialized "Scientific Data Type" layers, which provide the semantics needed to convert datasets to other protocols and formats such as those required by GIS systems. This talk will overview the TDS and CDM functionality, and report on present status and future plans.

Since its initial release in 1994, the Unidata Local Data Manager (LDM) has been adopted by numerous entities and agencies to distribute and process data in near real-time via the Internet. User's of the LDM include universities engaged in geoscience research and education in the US, Canada, Costa Rica, Brazil, Argentina, and Italy. Non-educational entities include NOAA/NWS, NASA, USGS, the US Army Corps of Engineers, the US Navy, and governmental entities in Brazil, South Korea, Vietnam, and Taiwan. The LDM is the top user of Internet II in the "Advanced Applications" category. This paper describes the current LDM release. Its structure, behavior, and performance are presented as well as current usage, lessons learned, and future development plans.

In recent years, the access to data from the national network of NEXRAD weather radars has increased considerably. This is the result of efforts such as the collaborative radar acquisition field test (CRAFT), changes in policy by the National Weather Service, and investments and changes in procedure by the National Climatic Data Center. With a modest investment in computer hardware and the open source local data manger (LDM) software from UCAR's Unidata Program Center, an individual researcher can now receive the various NEXRAD Level III gridded rainfall products in real-time from most NEXRAD radars. More significantly, researchers also can also obtain the unprocessed Level II data from these radars, which are needed for the generation of high quality rainfall products for use by professional in research, engineering, and education. Still, significant obstacles remain in order to unlock the full potential of the data. Among these are data management issues-storing multi-terrabyte data sets, metadata extraction and cataloging, indexing the data and products, and data compression. Before rainfall estimation algorithms are applied, data must be carefully quality controlled to remove false echoes. Another set of hurdles include coordinate conversion and georeferencing, conversion to a convenient data format(s), and integration with GIS. The authors are developing a basin-centered framework for addressing all these issues in a comprehensive manner tailored specifically for use of NEXRAD data in hydrology and hydrometeorology. An important aspect of this framework is the concept of the flow of NEXRAD data through a number of data-processing steps. Well-chosen and documented defaults are provided for this scientific workflow, but users can also tailor the flow according to their needs. Another important aspect of the framework is the management of metadata or descriptive data in a searchable database. This will allow users to search for interesting subsets over extended periods and geographic region(s). The searchable metadata database and the datasets are accessible through flexible interfaces that include common web browsers, a downloadable Java client, and web services for programmatic access from compiled programs and scripts.

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.

Over the last five years, UNIDATA has developed an extensible and flexible software framework for analyzing and visualizing geoscience data and models. The Integrated Data Viewer (IDV), initially developed for visualization and analysis of atmospheric data, has broad interdisciplinary application across the geosciences including atmospheric, ocean, and most recently, earth sciences. As part of the NSF-funded GEON Information Technology Research project, UNAVCO has enhanced the IDV to display earthquakes, GPS velocity vectors, and plate boundary strain rates. These and other geophysical parameters can be viewed simultaneously with three-dimensional seismic tomography and mantle geodynamic model results. Disparate data sets of different formats, variables, geographical projections and scales can automatically be displayed in a common projection. The IDV is efficient and fully interactive allowing the user to create and vary 2D and 3D displays with contour plots, vertical and horizontal cross-sections, plan views, 3D isosurfaces, vector plots and streamlines, as well as point data symbols or numeric values. Data probes (values and graphs) can be used to explore the details of the data and models. The IDV is a freely available Java application using Java3D and VisAD and runs on most computers. UNIDATA provides easy-to-follow instructions for download, installation and operation of the IDV. The IDV primarily uses netCDF, a self-describing binary file format, to store multi-dimensional data, related metadata, and source information. The IDV is designed to work with OPeNDAP-equipped data servers that provide real-time observations and numerical models from distributed locations. Users can capture and share screens and animations, or exchange XML "bundles" that contain the state of the visualization and embedded links to remote data files. A real-time collaborative feature allows groups of users to remotely link IDV sessions via the Internet and simultaneously view and control the visualization. A Jython-based formulation facility allows computations on disparate data sets using simple formulas. Although the IDV is an advanced tool for research, its flexible architecture has also been exploited for educational purposes with the Virtual Geophysical Exploration Environment (VGEE) development. The VGEE demonstration added physical concept models to the IDV and curricula for atmospheric science education intended for the high school to graduate student levels.

The APDRC is building towards a vision of one-stop shopping of climate data and products for our users. Our data server infrastructure is built on OPeNDAP that makes local data accessible to remote locations regardless of the local storage format. Most of our locally-stored datasets are served by a GrADS DODS server (GDS) developed at COLA. NASA's satellite data in HDF format, ECMWF's reanalysis data in GRIB format and the Earth Simulator's model output in simple binary are all transformed into OPeNDAP through GDS. We also utilize Unidata's THREDDS (Thematic Real-time Environmental Distributed Data Services) to customize remote datasets via aggregation to allow for more user-friendly access. The JPL ECCO assimilation-based ocean product is one example of a dataset that we serve in this way. In addition to direct access to the datasets served by our OPeNDAP servers, LAS and EPIC servers, both developed by PMEL, allow users to use search, select, make plots and download datasets all though a web-browser based interface. The LAS enables easy regional subsetting of global gridded products. An EPIC server provides Argo float data, GODAE/FNMOC daily real-time profile data, WOCE WHPO (CTD and bottle) data, WOCE upper ocean thermal (UOT) and current meter data. At present the APDRC serves approximately 50 data sets of relevance to climate research, including atmospheric, air-sea flux and ocean data collected both in situ and remotely (e.g., via satellite). In the future we will expand our holdings and links to include data and products that would be of interest to applications users and the general public, for example, nowcasts and forecasts of coastal ocean conditions, weather, climatic variability, etc.

This paper is an example of what we call data interactive publications. With a properly configured workstation, the readers can click on "hotspots" in the document that launches an interactive analysis tool called the Unidata Integrated Data Viewer (IDV). The IDV will enable the readers to access, analyze and display datasets on remote servers as well as documents describing them. Beyond the parameters and datasets initially configured into the paper, the analysis tool will have access to all the other dataset parameters as well as to a host of other datasets on remote servers. These data interactive publications are built on top of several data delivery, access, discovery, and visualization tools developed by Unidata and its partner organizations. For purposes of illustrating this integrative technology, we will use data from the event of Hurricane Charley over Florida from August 13-15, 2004. This event illustrates how components of this process fit together. The Local Data Manager (LDM), Open-source Project for a Network Data Access Protocol (OPeNDAP) and Abstract Data Distribution Environment (ADDE) services, Thematic Realtime Environmental Distributed Data Service (THREDDS) cataloging services, and the IDV are highlighted in this example of a publication with embedded pointers for accessing and interacting with remote datasets. An important objective of this paper is to illustrate how these integrated technologies foster the creation of documents that allow the reader to learn the scientific concepts by direct interaction with illustrative datasets, and help build a framework for integrated Earth System science.

From natural disasters such as flooding and forest fires to man-made disasters such as toxic gas releases, the impact of weather-influenced severe events on society can be profound. Understanding, predicting, and mitigating such local, mesoscale events calls for a cyberinfrastructure to integrate multidisciplinary data, tools, and services as well as the capability to generate and use high resolution data (such as wind and precipitation) from localized models. The need for such end to end systems -- including data collection, distribution, integration, assimilation, regionalized mesoscale modeling, analysis, and visualization -- has been realized to some extent in many academic and quasi-operational environments, especially for atmospheric sciences data. However, many challenges still remain in the integration and synthesis of data from multiple sources and the development of interoperable data systems and services across those disciplines. Over the years, the Unidata Program Center has developed several tools that have either directly or indirectly facilitated these local modeling activities. For example, the community is using Unidata technologies such as the Internet Data Distribution (IDD) system, Local Data Manger (LDM), decoders, netCDF libraries, Thematic Realtime Environmental Distributed Data Services (THREDDS), and the Integrated Data Viewer (IDV) in their real-time prediction efforts. In essence, these technologies for data reception and processing, local and remote access, cataloging, and analysis and visualization coupled with technologies from others in the community are becoming the foundation of a cyberinfrastructure to support an end-to-end regional forecasting system. To build on these capabilities, the Unidata Program Center is pleased to be a significant contributor to the Linked Environments for Atmospheric Discovery (LEAD) project, a NSF-funded multi-institutional large Information Technology Research effort. The goal of LEAD is to create an integrated and scalable framework for identifying, accessing, preparing, assimilating, predicting, managing, analyzing, mining, and visualizing a broad array of meteorological data and model output, independent of format and physical location. To that end, LEAD will create a series of interconnected, heterogeneous Grid environments to provide a complete framework for mesoscale research, including a set of integrated Grid and Web Services. This talk will focus on the transition from today's end-to-end systems into the types of systems that the LEAD project envisions and the multidisciplinary research problems they will enable.

The Consortium of Universities for Advancement of Hydrologic Science, Inc. (CUAHSI) seeks to build a Hydrologic Information System (HIS) for which hydrologic data sources will be assembled in space and time to create a digital representation of atmospheric, surface and subsurface water flow through a watershed. Unidata provides a rich stream of atmospheric data through their Internet Data Distribution system that would greatly benefit the CUAHSI HIS effort, but these data have are not typically used by the hydrologic community, in part because Unidata focuses on real-time data distribution, while hydrologic science has traditionally been based on interpretation of past information. To more effectively utilize Unidata atmospheric science information in CUAHSI HIS requires the synthesis of continuous atmospheric fields with discrete space objects like watershed boundaries and stream networks, and also a better synchronization in time between weather and hydrologic information needs and data sources. Examples are presented from the Neuse basin in North Carolina to illustrate how these goals might be accomplished.

The overall objective of this project is to provide the broad science and engineering communities with ready access to the vast archives and real-time information collected by the national network of NEXRAD weather radars. The main focus is on radar-rainfall data for use in hydrology, hydrometeorology, and water resources. Currently, the NEXRAD data, which are archived at NOAA's National Climatic Data Center (NCDC), are converted to operational products and used by forecasters in real time. The scientific use of the full resolution NEXRAD information is presently limited because current methods of accessing this data require considerable expertise in weather radars, data quality control, formatting and handling, and radar-rainfall algorithms. The goal is to provide professionals in the scientific, engineering, education, and public policy sectors with on-demand NEXRAD data and custom products that are at high spatial and temporal resolutions. Furthermore, the data and custom products will be of a quality suitable for scientific discovery in hydrology and hydrometeorology and in data formats that are convenient to a wide spectrum of users. We are developing a framework and a set of tools for access, visualization, management, rainfall estimation algorithms, and scientific analysis of full resolution NEXRAD data. The framework will address the issues of data dissemination, format conversions and compression, management of terabyte-sized datasets, rapid browsing and visualization, metadata selection and calculation, relational and XML databases, integration with geographic information systems, data queries and knowledge mining, and Web Services. The tools will perform instantaneous comprehensive quality control and radar-rainfall estimation using a variety of algorithms. The algorithms that the user can select will range from "quick look" to complex, and computing-intensive and will include operational algorithms used by federal agencies as well as research grade experimental methods. Options available to the user will include user-specified spatial and temporal resolution, ancillary products such as storm advection velocity fields, estimation of uncertainty associated with rainfall maps, and mathematical synthesis of the products. The data and the developed tools will be provided to the community via the services and the infrastructure of Unidata and the NCDC.

This is a report on the construction of a network of digital libraries for the hydrology community as part of the CUAHSI Hydrologic Information System (HIS) based on an architecture developed for the publication of oceanographic data acquired by oceanographic research vessels. Our results show that this architecture and implementation are appropriate for a broad range of scientific disciplines and that the approach scales from the desk of the individual investigator to that of a major research institution and to the interoperation of institutions. We are able to run the entire digital library from a laptop computer as well as from supercomputer-center-size resources. The underlying architecture and prototype set of tools have been developed as a part of the SIOExplorer project (http://SIOExplorer.ucsd.edu), funded by National Science Digital Library (NSDL), Information Technology Research (ITR) and Ocean Science (OCE) awards over the last three years. With funding from the NSF Geosciences Directorate, this approach has been adapted to hydrology and is operating in a multi-site configuration representing a network of hydrological observatories and oceanographic archives. The system is integrated with the GEONgrid (http://geongrid.org) and includes automatic methods of harvesting data and metadata from existing web-sites (e.g., USGS and NASA) as well as real-time and near-real-time sensors through other data systems such as Unidata OpenDAP and Local Data Manager.

Sediment productions from storm-proofed forest roads were investigated at four locations in the managed forested land of Northwestern California (annual rainfall @1000 mm), where rocks have been characterized as Wildcat group consisting of mudstone, siltstone, claystone, and minor conglomerate. Rocked road (storm-proofed road) constitutes a part of the effective road management practices in the study area where other management practices include disconnection of roads from watercourses, reduction in distance between culverts, frequent road maintenance, and seasonal (or during rainfall) restrictions of log traffic. Specifically, this study examines the influence of rainstorm and road characteristics on sediment production from storm-proofed road in the context of varieties of road management practices in place. Continuous ditch flow during the rainstorm events was monitored using an UNIDATA float device and data logger. An ISCO sampler collected suspended sediment at temporal resolution of 2-h during the rainstorm events, and collected sediment samples were analyzed for turbidity and suspended sediment concentration in the laboratory. Sediment samples were also collected for particle size distribution analysis. Two tipping bucket rain gages located in the vicinity of road sites collected rainfall. Using an electronic total station, road surface was surveyed in detail, and a road Digital Elevation Model (DEM) was generated. Thus produced DEM was processed to delineate the road surface area contributing to ditch flow. The analysis of collected data for rainstorm events of hydrological year 2003/2004 reveals that the suspended sediment concentration conforms closely to rainfall hyetograph and ditch flow hydrograph with rapid flushing of road sediments for about 15-h following the onset of rainstorm. In general, ditch flow and suspended sediment concentration relation illustrates that the sediment transport is evidently "supply limited". For this reason, suspended sediment concentration decreases to a low level after about 15-h of onset of rainstorm even when ditch flow as well as rainfall are considerably high. In addition to rainstorm characteristics, road characteristics such as slope gradient, and road use (traffic volume) caused differences in the short-term sediment concentration and total sediment yield among road segments during rainstorm events. Temporal distribution of suspended sediment concentration and short-term peak suspended sediment concentration dependent on the traffic volume prior to the onset of rainstorm event since truck traffic was ceased during rainstorms. During the same storm, road segments with high traffic volume produced peak suspended sediment concentration of up to 30-fold compared to road segments with low traffic volume; however, the total sediment yield during the rainstorm did not vary that much among road segments.

DLESE Data Services will work, in coordination with the other DLESE Core Service activities, toward DLESE's mission 'To improve the quality, quantity, and efficiency of teaching and learning about the Earth system' by facilitating the development and effective use of educational materials that make use of Earth system science datasets and data access and analysis tools. The currently planned major activities of DLESE Data Services are 1. To conduct a needs assessment for data and data analysis tools in the educational community 2. To identify existing educational modules utilizing data and data access and analysis tools for cataloging in DLESE 3. To organize and run DLESE Data Services Workshops in which we will bring together a wide range of Earth science data providers, developers of data access and analysis/exploration tools, with curriculum developers and educators to improve the use of Earth science data in education. Each of these activities and the benefits and opportunities they make available to the community will be described in more detail during the presentation.

The central mission of the THREDDS (THematic Real-time Environmental Distributed Data Services) project is to make it possible for educators and researchers to publish, locate, analyze, and visualize data in a wide variety educational settings. In the initial phase THREDDS established a solid, working prototype of services and tools to enable data providers to create inventory catalogs of the data holdings at their site and educational module builders to author compound documents with embedded pointers to environmental datasets and analysis tools. These catalogs and data-interactive documents can then be harvested into digital libraries using standard protocols. THREDDS Second Generation (THREDDS2G) will further enhance collaborations among data providers, toolbuilders, researchers and educators. It will do so by expanding the team of contributors and the breadth of data in the collections, taking advantage of recent technological advancements, and integrating THREDDS technologies with emerging standards and related environmental data systems. Since much of this expansion will involve Geographic Information Systems (GIS), THREDDS will actively engage the GIS community with the disciplines and tools that make the end products more useful at all educational levels, for decision makers and for the general public.

On-line access to geoscience data and tools for data visualization and analysis are creating exciting new opportunities for engaging undergraduate students with data. The National Science Digital Library (NSDL) and DLESE both include access to data and tools as fundamental aspects of their vision and are currently striving to support faculty in using data in their courses. The Using Data in the College/University Classroom Workgroup at the 2003 DLESE Annual meeting brought together data providers, resource developers, and faculty to discuss issues surrounding data access and use in the undergraduate classroom. In order to improve understanding among these diverse viewpoints, workgroup participants created concept maps showing the relationships between data and education. These maps and other highlights of the working group discussion are available at http://swiki.dlese.org/ReportOut2003/26. The working group discussions built on substantial existing resources including: 2001 Report of the DLESE Data Access Working Group bringing together data providers and tool developers (www.dlese.org/documents/reports/meeting/Feb\_01/dawg20801 \_outcomes.html); 2002 Using Data in the Classroom workshop bringing together faculty from across the disciplines (serc.carleton.edu/research\_education/usingdata/workshop02/); 2003 Using Data in the Classroom report describing current uses of data in undergraduate science courses and faculty needs for data access and tools (serc.carleton.edu/ research\_education/usingdata/report.html); NSDL Using Data in the Classroom Portal providing access to data, tools, teaching materials, and a discussion of pedagogic and development issues and opportunites for community contribution to these collections (serc.carleton.edu/research\_education/usingdata/); Starting Point "Teaching with Models" site supporting faculty teaching at the entry level in using mathematical, statistical, and other types of models in their courses (serc.carleton.edu/introgeo/); Earth Exploration Toolbook providing step-by-step instructions for using Earth science datasets and software tools in educational settings. (serc.carleton.edu/eet/); and NSDL projects developing data access and tools including THREDDS (www.unidata.ucar.edu /projects/THREDDS/); Data Discovery Toolkit and Foundry (www.newmediastudio.org/DataDiscovery/index.html); Collection and Distribution of Geoscience (Solid Earth) Data Sets (atlas.geo.cornell.edu/nsdl/nsdl.html); and Atmospheric Visualization Collection (www.nsdl.arm.gov/index.shtml) These resources will be available for exploration at our poster.

The Visual Geophysical Exploration Environment (VGEE) is an online learning environment designed to help undergraduate students understand fundamental Earth system science concepts. The guiding principle of the VGEE is the importance of hands-on interaction with scientific visualization and data. The VGEE consists of four elements: 1) an online, inquiry-based curriculum for guiding student exploration; 2) a suite of El Nino-related data sets adapted for student use; 3) a learner-centered interface to a scientific visualization tool; and 4) a set of concept models (interactive tools that help students understand fundamental scientific concepts). There are two key innovations featured in this interactive poster session. One is the integration of concept models and the visualization tool. Concept models are simple, interactive, Java-based illustrations of fundamental physical principles. We developed eight concept models and integrated them into the visualization tool to enable students to probe data. The ability to probe data using a concept model addresses the common problem of transfer: the difficulty students have in applying theoretical knowledge to everyday phenomenon. The other innovation is a visualization environment and data that are discoverable in digital libraries, and installed, configured, and used for investigations over the web. By collaborating with the Integrated Data Viewer developers, we were able to embed a web-launchable visualization tool and access to distributed data sets into the online curricula. The Thematic Real-time Environmental Data Distributed Services (THREDDS) project is working to provide catalogs of datasets that can be used in new VGEE curricula under development. By cataloging this curricula in the Digital Library for Earth System Education (DLESE), learners and educators can discover the data and visualization tool within a framework that guides their use.

AB: WRF (Weather and Research Forecasting Model) is a limited-area weather model that has been used intensively for both weather research and prediction. Due to the heavy computational volume, WRF is using multi-layer domain decomposition method to run the model in parallel supercomputing environments. Although there are several performance metrics to measure the overall model behavior; the IO performance has never been thoroughly evaluated. The Hierarchical Data Format (HDF) developed at the National Center for Supercomputing Application (NCSA) at University of Illinois at Urbana-Champaign has become the primary standard file format for storing data from NASA's Earth Observing System (EOS). Since 1999, NCSA has developed a more general and robust data format, called HDF 5, which will support the future demands of Earth Science. HDF5 provides chunking storage of the data, which improves the performance. HDF5 is also easily to hook with external compression packages and make the data storage more efficient and flexible. Furthermore, HDF5 supports the Message Passing Interface (MPI-I/O) standard, which is capable of performing I/O efficiently in parallel computing environments. Currently NCSA is developing an implementation of WRF sequential and parallel I/O modules that reads and writes HDF5 datasets. The module will be available to anyone using WRF as a new option for I/O. In this poster, we report three case studies to compare the performance among NetCDF IO module, sequential HDF5 IO module and parallel HDF5 IO module. In other work, Unidata and NCSA are collaborating to design netCDF4, a new netCDF built on top of HDF5. We hope the current study will provide some insights for scientists, researchers and developers to make decisions in choosing the best file I/O in their computational applications.

Unidata's netCDF data model, data access libraries, and machine independent format are used in the creation, access, and sharing of much geoscience data. NCSA's HDF5 data model, libraries, and format have also been used in high-performance computing that require parallel I/O and very large data volumes. HDF5 is used by the NASA Earth Science Enterprise to archive and distribute remote sensing data and is used in many large computational models. In a NASA sponsored project, Unidata and NCSA are collaborating to merge netCDF and HDF5 to achieve gains in performance and interoperability. The project aims to create and deploy software that will preserve the desirable characteristics of netCDF and HDF5 while taking advantage of their separate strengths: the widespread use and simplicity of netCDF and the generality and performance of HDF5. When completed, users of netCDF will benefit from support for packed data, large datasets, and parallel I/O, and users of HDF5 will benefit from the availability of a simple high-level interface suitable for array-oriented scientific data, wider use of the HDF5 data format, and additional software for data management, analysis and visualization. We summarize the current status of the work, including new software that uses the current netCDF interface with the HDF5 format to provide backward compatibility with current data and application software. We also describe how the software under development will make use of advanced features of HDF5 including scalable access to very large datasets, parallel I/O, and compression.