Note: This document primarily consists of snippets of text copied from various online resources.
This “cheat sheet” is only for informational purposes.
Categories appearing in this document:
 Data Description and Formatting
 Middleware/GRID Technologies
 Model Description and Archive
 Portal Technologies
 Data Providers
 Modeling Infrastructure
Data Description and Formatting
Climate and Forecasting (CF) metadata
“The CF conventions for climate and forecast metadata are designed to promote the processing
and sharing of files created with the netCDF API. The conventions define metadata that provide
a definitive description of what the data in each variable represents, and of the spatial and
temporal properties of the data. This enables users of data from different sources to decide which
quantities are comparable, and facilitates building applications with powerful extraction,
regridding, and display capabilities.”
CF is backwards compatible with COARDS.
http://www.cgd.ucar.edu/cms/eaton/cf-metadata/ (home page?)
http://www.cgd.ucar.edu/cms/eaton/cf-metadata/clivar_article.pdf (article)
Cooperative Ocean-Atmosphere Research Data Service (COARDS)
“This standard is a set of conventions adopted in order to promote the interchange and sharing of
files created with the netCDF Application Programmer Interface (API).”
http://ferret.wrc.noaa.gov/noaa_coop/coop_cdf_profile.html (home page?)
ESML
Earth System Markup Language
“Earth science data is archived and distributed in many different formats varying from character
format, packed binary, "standard" scientific formats to self-describing formats. This heterogeneity
results in data-application interoperability problems for scientific tools. The Earth Science Markup
Language (ESML) is an elegant solution to this problem. ESML is an interchange technology that
enables data (both structural and semantic) interoperability with applications without enforcing a
standard format within the Earth science community. Users can write external files using ESML
schema to describe the structure of the data file. Applications can utilize the ESML Library to
parse this description file and decode the data format. As a result, software developers can now
build data format independent scientific applications utilizing the ESML technology. Furthermore,
semantic tags can be added to the ESML files by linking different domain ontologies to provide a
complete machine understandable data description. This ESML description file allows the
development of intelligent applications that can now understand and "use" the data.”
“ESML provides Syntactic (or structural) metadata describe the data in terms of bits and bytes.
These metadata are used by the ESML parser to give structure to the bit stream which is the data
file. For example, the syntactic metadata tell the parser that the next 32 bits of data are to be
interpreted as a big-endian 32-bit two’s complement integer value.”
http://esml.itsc.uah.edu/index.jsp (home page)
http://esml.itsc.uah.edu/documentation/ESML_Overview.pdf (overview)
http://esml.itsc.uah.edu/documentation/ESMLv3schemaDocumentation.doc (schema description)
FGDC - Content Standard for Digital Geospatial Metadata
Federal Geographic Data Committee (also see Data Providers)
“The objectives of the standard are to provide a common set of terminology and definitions for
the documentation of digital geospatial data. The standard establishes the names of data
elements and compound elements (groups of data elements) to be used for these purposes, the
definitions of these compound elements and data elements, and information about the values that
are to be provided for the data elements.”
http://www.fgdc.gov/metadata/contstan.html
“This program is a compiler to parse formal metadata, checking the syntax against the FGDC
Content Standard for Digital Geospatial Metadata and generating output suitable for viewing with
a web browser or text editor.”
http://geology.usgs.gov/tools/metadata/tools/doc/mp.html (mp metadata tool)
Geographic Markup Language (GML)
“Geography Markup Language is an XML grammar written in XML Schema for the modeling,
transport, and storage of geographic information.”
http://xml.coverpages.org/ni2004-03-26-a.html (article)
http://xml.coverpages.org/GMLv310-20040207-d20040326.pdf (GML specification)
GRIB Format
Timeline: released 1985
“The World Meteorological Organization (WMO) Commission for Basic Systems (CBS)
Extraordinary Meeting Number VIII (1985) approved a general purpose, bit-oriented data
exchange format, designated FM 92-VIII Ext. GRIB (GRIdded Binary). It is an efficient vehicle for
transmitting large volumes of gridded data to automated centers over high-speed
telecommunication lines using modern protocols. By packing information into the GRIB code,
messages (or records - the terms are synonymous in this context) can be made more compact
than character oriented bulletins, which will produce faster computer-to-computer transmissions.
GRIB can equally well serve as a data storage format, generating the same efficiencies relative to
information storage and retrieval devices.”
http://www.wmo.ch/web/www/WDM/Guides/Guide-binary-2.html (explanation of GRIB format)
Hierarchical Data Format (HDF5)
Timeline: latest release, 03/2005
“HDF5 is a general purpose library and file format for storing scientific data.”
”HDF5 can store two primary objects: datasets and groups. A dataset is essentially a
multidimensional array of data elements, and a group is a structure for organizing objects in an
HDF5 file. Using these two basic objects, one can create and store almost any kind of scientific
data structure, such as images, arrays of vectors, and structured and unstructured grids. You can
also mix and match them in HDF5 files according to your needs.”
http://hdf.ncsa.uiuc.edu/HDF5/ (home page)
HDF-EOS
Hierarchical Data Format – Earth Observing System
“In 1993 NASA chose NCSA's HDF format to be the standard file format for storing data from the
Earth Observing System (EOS), which is the data gathering system of sensors (mainly satellites)
supporting the Global Change Research Program.”
http://hdf.ncsa.uiuc.edu/hdfeos.html (home page)
http://edhs1.gsfc.nasa.gov/waisdata/rel7/pdf/170emd001r3.pdf (user’s guide)
NETCDF
“NetCDF (network Common Data Form) is an interface for array-oriented data access and a
library that provides an implementation of the interface. The netCDF library also defines a
machine-independent format for representing scientific data. Together, the interface, library, and
format support the creation, access, and sharing of scientific data.”
http://my.unidata.ucar.edu/content/software/netcdf/index.html (home page)
http://my.unidata.ucar.edu/content/software/netcdf/docs/netcdf.pdf (user’s guide)
PCMDI - Climate Model Output Rewriter (CMOR)
The "Climate Model Output Rewriter" (CMOR, pronounced "Seymour") comprises a set of
FORTRAN 90 functions that can be used to produce CF-compliant netCDF files that fulfill the
requirements of many of the climate community's standard model experiments. These
experiments are collectively referred to as MIP's and include, for example, AMIP, CMIP, CFMIP,
PMIP, APE, and IPCC scenario runs. The output resulting from CMOR is "self-describing" and
facilitates analysis of results across models.
http://www-pcmdi.llnl.gov/software/cmor/cmor_users_guide.pdf (CMOR user’s guide)
Middleware/GRID Technologies
Common Component Architecture
“The Common Component Architecture (CCA) Forum is a group of researchers from national labs
and academic institutions committed to defining a standard component architecture for high
performance computing. “
“The objective of the CCA Forum is to define a minimal set of standard interfaces that a highperformance component framework has to provide to components, and can expect from them, in
order to allow disparate components to be composed together to build a running application.
Such a standard will promote interoperability between components developed by different teams
across different institutions.”
http://www.cca-forum.org/ (CCA forum)
Condor-G
“Grid computing, the ability for communities to share resources, has emerged as an important
facet of computing. Condor-G is the marriage of technologies from the Condor project and the
Globus project.”
“The Condor-G system leverages recent advances in two distinct areas: (1) security and resource
access in multi-domain environments, as supported within the Globus Toolkit, and (2)
management of computation and harnessing of resources within a single administrative domain,
embodied within the Condor system. Condor-G combines the inter-domain resource management
protocols of the Globus Toolkit and the intra-domain resource and job management methods of
Condor to allow the user to harness multi-domain resources as if they all belong to one personal
domain.”
http://www.cs.wisc.edu/condor/condorg/ (home page)
Globus Toolkit / 4 (GT/4)
Timeline: v1.0 in 1998, v4.0 April 2005
“The open source Globus Toolkit is a fundamental enabling technology for the "Grid," letting
people share computing power, databases, and other tools securely online across corporate,
institutional, and geographic boundaries without sacrificing local autonomy. The toolkit includes
software services and libraries for resource monitoring, discovery, and management, plus
security and file management. In addition to being a central part of science and engineering
projects that total nearly a half-billion dollars internationally, the Globus Toolkit is a substrate on
which leading IT companies are building significant commercial Grid products.”
Used by Earth System Grid for moving large amounts of climate data.
http://www.globus.org/toolkit/ (home page)
http://www.globus.org/toolkit/docs/development/3.9.5/key/GT4_Primer_0.6.pdf (GT4 primer)
OGSA-DAI
Timeline: Release 1 1/2003, Release 7 scheduled 9/2005
Open Grid Services Architecture - Data Access and Integration
“The OGSA-DAI project is concerned with constructing middleware to assist with access and
integration of data from separate data sources via the grid. It is engaged in identifying the
requirements, designing solutions and delivering software that will meet this purpose. The project
was conceived by the UK Database Task Force and is working closely with the Global Grid
Forum DAIS-WG and the Globus team.”
Built on Globus Toolkit.
http://www.ogsadai.org.uk/ (home page)
OPeNDAP
“The OPeNDAP provides a way for ocean researchers to access oceanographic data anywhere
on the Internet from a wide variety of new and existing programs. By developing network versions
of commonly used data access Application Program Interface (API) libraries, such as NetCDF ,
HDF, JGOFS , and others, the OPeNDAP project can capitalize on years of development of data
analysis and display packages that use those APIs, allowing users to continue to use programs
with which they are already familiar.”
http://opendap.org/ (home page)
http://www.opendap.org/user/guide-html/guide.html (user’s guide)
THREDDS data catalog {Cinquini}
“The THREDDS (Thematic Realtime Environmental Distributed Data Services) project is
developing middleware to bridge the gap between data providers and data users. The goal is to
simplify the discovery and use of scientific data and to allow scientific publications and
educational materials to reference scientific data.”
“The mission of THREDDS is for students, educators and researchers to publish, contribute, find,
and interact with data relating to the Earth system in a convenient, effective, and integrated
fashion. Just as the World Wide Web and digital-library technologies have simplified the process
of publishing and accessing multimedia documents, THREDDS is building infrastructure needed
for publishing and accessing scientific data in a similarly convenient fashion.”
http://my.unidata.ucar.edu/content/projects/THREDDS/index.html (home page)
Web Feature Service
Web Feature Service… “takes the next logical step and proposes interfaces for describing data
manipulation operations on geographic features using HTTP as the distributed computing
platform. Data manipulation operations include the ability to:
1.
2.
3.
4.
Create a new feature instance
Delete a feature instance
Update a feature instance
Get or Query features based on spatial and non-spatial constraints
A Web Feature Service (WFS) request consists of a description of query or data transformation
operations that are to be applied to one or more features. The request is generated on the client
and is posted to a web feature server using HTTP. The web feature server then reads and (in a
sense) executes the request.”
“That is to say that the state of a geographic feature is described by a set of properties where
each property can be thought of as a {name, type, value} tuple. The name and type of each
feature property is determined by its type definition. Geographic features are those that may have
at least one property that is geometry-valued. This, of course, implies that features can be
defined with no geometric properties at all. The geometries of geographic features are restricted
to what OGC calls simple geometries. A simple geometry is one for which coordinates are
defined in two dimensions and the delineation of a curve is subject to linear interpolation.”
http://cite.occamlab.com/test_engine/wfs_1_0_0/wfs_1_0_0.html (home page)
http://cite.occamlab.com/test_engine/wfs_1_0_0/files/wfs_spec_1_0_0/ (WFS specification)
Web Services Resource Framework (WSRF)
“We have pointed out that even when a Web service implementation itself can be described as a
stateless message processor, the message exchanges that it implements (as defined by its
interface) are frequently intended to enable access to, and/or update of, state maintained by other
system components, whether database, file systems, or other entities.”
“Given the vital role that access to state plays in many Web service interfaces, it is important to
identify and standardize the patterns by which state is represented and manipulated, so as to
facilitate the construction and use of interoperable services. To this end, we introduce an
approach to modeling stateful resources in a Web services framework based on a construct that
we call a WS-Resource.”
http://www.globus.org/wsrf/ (home page)
http://www-128.ibm.com/developerworks/library/ws-resource/ws-modelingresources.pdf
XCAT C++
“XCAT allows scientists to compose applications with a set of distributed components. In recent
times the Web Services model has been adopted as the underlying architecture for Grid Systems.
One of the goals of the XCAT project is to be develop a distributed framework that is consistent
with this model. The distributed framework itself is designed to be compliant with the Common
Component Architecture (CCA) specification. An XCAT component can serve as both a CCA and
a Grid (OGSI based) service. XCAT has been developed in both C++ and Java.”
http://grid.cs.binghamton.edu/projects/xcat.html (home page)
Model Description and Archives
Biogeochemical Model Archive - ORNL-DAAC
“Archiving environmental data products has become recognized as a vital research practice: it
improves our ability to reproduce results and perform additional analyses while saving the cost of
redundant data collection activities.”
“The same rationale applies to archiving numerical models. Archived models will provide the
methodological detail of numerical modeling studies to recreate published modeling results,
enabling the synthesis of results across modeling studies and the investigation of new
hypotheses. In addition, archived models will allow determination of uncertainties for comparison
with results from other models in assessment / policy studies. The model source code will also
allow others to see how models treat individual processes.”
“The model archive contains comprehensive model documentation, input files, source code, code
version, output files, and output analysis approaches or software used to produce tables and
figures for a particular publication.”
“We are creating a two-tiered archive for numerical models. The first tier supports the storage and
retrieval of benchmark model versions, and the second tier supports the association of published
research results with specific model implementations. For both tiers, we present a set of
recommended best practices aimed at raising the standards for reproducibility in numerical
modeling studies through the use of a dedicated archive for numerical models and modeling
studies. The model archive is intended as a resource for experienced modelers.”
http://www-eosdis.ornl.gov/model_intro.shtml (home page)
Numerical Model Metadata XML
Timeline: latest release, 08/2005
“The Numerical Model Metadata XML - NMM XML, previously known as the EarleySuite, is an
evolving metadata standard intended for the exchange of information about numerical models or
codebases, and the simulations done using them. Providing a metadata standard to describe the
numerical codebase and its associated simulations, greatly extends and refines the researcher's
ability to understand how a resulting output data was produced.”
”The Numerical Model Metadata XML is built and based on XML and associated technologies.
The goal in the design of the suite of Numerical Model Metadata XML is to provide the clear, welldefined and flexible metadata needed for climate and forecast numerical models and the
simulations which produce numerical model output data. At this point the Numerical Model
Metadata XML is primarily concentrating on describing numerical climate models and the
simulations done using them.”
http://cgam.nerc.ac.uk/NMM/ (home page)
PCMDI
Timeline: est. 1989,
The Program for Climate Model Diagnosis and Intercomparison
“The PCMDI mission is to develop improved methods and tools for the diagnosis and
intercomparison of general circulation models (GCMs) that simulate the global climate. The need
for innovative analysis of GCM climate simulations is apparent, as increasingly more complex
models are developed, while the disagreements among these simulations and relative to climate
observations remain significant and poorly understood. The nature and causes of these
disagreements must be accounted for in a systematic fashion in order to confidently use GCMs
for simulation of putative global climate change.”
http://www-pcmdi.llnl.gov/ (home page)
http://www-pcmdi.llnl.gov/software/about_software.php (software tools)
http://www-pcmdi.llnl.gov/ipcc/Hawaii_viewgraphs.pdf
http://gaim.unh.edu/Structure/Future/MIPs/ (listing of numerous MIPs)
http://www.clivar.org/science/mips.htm (another listing of MIPs)
REM
Register of Ecological Models
The Register of Ecological Models (REM) is a meta-database for existing mathematical models in
ecology.
http://eco.wiz.uni-kassel.de/ecobas.html (home page)
WRF Metadata Registry
Timeline: first non-beta release, 05/2004
“The Weather Research and Forecasting (WRF) Model is a next-generation mesoscale numerical
weather prediction system designed to serve both operational forecasting and atmospheric
research needs. It features multiple dynamical cores, a 3-dimensional variational (3DVAR) data
assimilation system, and a software architecture allowing for computational parallelism and
system extensibility. WRF is suitable for a broad spectrum of applications across scales ranging
from meters to thousands of kilometers.”
http://www.wrf-model.org/ (home page)
http://wrf-model.org/wrfadmin/docs/ecmwf_2004.pdf (paper software architecture)
http://box.mmm.ucar.edu/wrf/WG2/software_2.0 (software tools and documentation)
Registry
“The Registry is a concise database of information about WRF data structures and a mechanism
for automatically generating large sections of WRF code from the notations in the database. The
Registry data base is a collection of tables that lists and describes the WRF state variables and
arrays with their attributes such as dimensionality, number of time levels, association with a
particular dynamical core, association with a particular physics package, membership in an input,
output, or restart dataset, communication operations on the data, and some descriptive meta-data
such as what the variable or array represents and its units. From this database, the Registry
generates code for interfaces between layers of the infrastructure, packing and unpacking code
for communication and nesting, and field-by-field calls to routines for model I/O -- code that would
otherwise be extremely time-consuming and error-prone to write and manage manually. Adding
or modifying a state variable or array in WRF is a matter of modifying a line or two in the Registry.
Currently, the Registry automatically generates 60-thousand of the total 250-thousand lines of
WRF code.”
http://www.mmm.ucar.edu/wrf/WG2/software_2.0/registry_schaffer.pdf (description of registry)
Portal Technologies
JSR 168
Timeline: API Draft 10/2002, Final Release 10/2003
“JSR 168 establishes a standard API for creating portlets, the integration component between
applications and portals that enables delivery of an application through a portal. Without this
standard, each version of an application has needed its own portlet API, and each of the various
portals required that these portlets be specifically tailored for implementation through that portal.
This has raised portlet developer time, effort, and costs with the net effect that fewer applications
have been made available through fewer portals to the detriment of the end-users, ISVs,
developers, and portal vendors.”
http://jcp.org/en/jsr/detail?id=168 (home page)
http://developers.sun.com/prodtech/portalserver/reference/techart/jsr168/pb_whitepaper.pdf
Open Grid Computing Environments (OGCE)
Timeline: RC5 8/2005
“The OGCE is developing standard compliant portlet components that can be reused by multiple
container providers. The JSR 168 Portlet Specification defines interoperability standards for portal
containers. JSR 168 compliant portlets may be deployed in multiple vendor containers.”
http://www.collab-ogce.org/nmi/index.jsp (home page)
Data Providers
Earth Science Information Partners (ESIP)
“The Federation of Earth Science Information Partners ("Federation") is a network of researchers
and associated groups that collects, interprets and develops applications for satellite-generated
Earth observation information. Founded in 1998 under a grant from NASA, the consortium
includes more than 80 member organizations, spanning NASA and NOAA's data centers,
government research laboratories, research universities, education resource providers,
technology developers, and nonprofit and commercial enterprises.”
http://www.esipfed.org/ (home page)
Earth System Grid (ESG)
“The primary goal of ESG is to address the formidable challenges associated with enabling
analysis of and knowledge development from global Earth System models. Through a
combination of Grid technologies and emerging community technology, distributed federations of
supercomputers and large-scale data & analysis servers will provide a seamless and powerful
environment that enables the next generation of climate research.”
https://www.earthsystemgrid.org/ (home page)
http://dataportal.ucar.edu/esg/docs/Agent_Grid_cluster_final.pdf (An Ontology for Scientific
Information in a Grid Environment: the Earth System Grid.)
https://www.earthsystemgrid.org/about/docs/ESG1.1.owl (ESG 1.1 Ontology)
Federal Geographical Data Committee
“The FGDC is developing the National Spatial Data Infrastructure (NSDI) in cooperation with
organizations from State, local and tribal governments, the academic community, and the private
sector. The NSDI encompasses policies, standards, and procedures for organizations to
cooperatively produce and share geographic data.”
http://www.fgdc.gov/ (home page)
http://www.fgdc.gov/metadata/meta_stand.html (geospatial metadata standards)
Clearinghouse
“Using the data elements defined in the Content Standards for Digital Geospatial Metadata,
governmental, non-profit, and commercial participants worldwide can make their collections of
spatial information searchable and accessible on the Internet using free reference implementation
software developed by the FGDC.”
http://www.fgdc.gov/clearinghouse/clearinghouse.html (Clearinghouse)
GO-ESSP
Timeline: 4th workshop held June 2005
“The Global Organization for Earth System Science Portal (GO-ESSP) is a collaboration
designed to develop a new generation of software infrastructure that will provide distributed
access to observed and simulated data from the climate and weather communities. GO-ESSP will
achieve this goal by developing individual software components and by building a federation of
frameworks that can work together using agreed-upon standards. The GO-ESSP portal
frameworks will provide efficient mechanisms for data discovery, access, and analysis of the
data.”
http://go-essp.gfdl.noaa.gov/ (home page)
Intergovernmental Panel for Climate Change (IPCC)
“The role of the IPCC is to assess on a comprehensive, objective, open and transparent basis the
scientific, technical and socio-economic information relevant to understanding the scientific basis
of risk of human-induced climate change, its potential impacts and options for adaptation and
mitigation.”
http://www.ipcc.ch/ (home page)
http://ipcc-ddc.cru.uea.ac.uk/ (IPCC Data Distribution Center)
Linked Environments for Atmospheric Discovery (LEAD)
Linked Environments for Atmospheric Discovery
“A multi-disciplinary effort involving 9 institutions and more than 100 scientists, students and
technical staff, LEAD is addressing the fundamental IT research challenges, and associated
development, needed to create an integrated, 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.”
http://lead.ou.edu/ (home page)
http://lead.ou.edu/pdfs/SystemCapabilities.pdf
http://lead.ou.edu/pdfs/LEAD_Year-2_Report.pdf (latest report)
WOORDS
“A major underpinning of LEAD is dynamic workflow orchestration and data management in a
web services framework – a concept we frame more generally as Workflow Orchestration for OnDemand, Real-Time, Dynamically-Adaptive Systems (WOORDS). WOORDS provides for the use
of analysis tools, forecast models, and data repositories not in fixed configurations or as static
recipients of data, as is now the case for most meteorological research and operational
forecasting technologies, but rather as dynamically adaptive, on-demand, grid-enabled systems
that can a) change configuration rapidly and automatically in response to weather; b) continually
be steered by new data; c) respond to decision-driven inputs from users; d) initiate other
processes automatically; and e) steer remote observing technologies to optimize data collection
for the problem at hand. Although mesoscale meteorology is the particular problem to which the
WOORDS concept is being applied, the methodologies and infrastructures being developed are
extensible to other domains such as medicine, ecology, oceanography and biology.”
http://lead.ou.edu/pdfs/SystemConcept.pdf (WOORDS description)
National Weather Service data format for RSS feed
“RSS is an XML based document format for syndicating news and other timely news-like
information. It provides headlines, URLs to the source document and brief description information
in an easy to understand and use format. RSS based "News Readers" and "News Aggregators"
allow the display of RSS headlines on workstation desktops. Software libraries exist to read the
RSS format and present RSS headlines on web pages and other online applications.”
http://www.weather.gov/alerts/ (RSS alerts)
http://blogs.law.harvard.edu/tech/rss (RSS 2.0 Specification)
Modeling Infrastructure
Earth System Modeling Framework (ESMF)
GFDL Flexible Modeling System (FMS)
“FMS is a software framework for supporting the efficient development, construction, execution,
and scientific interpretation of atmospheric, oceanic, and climate system models.”
1. A software infrastructure for constructing and running atmospheric, oceanic, and
2.
3.
4.
5.
climate system models. This infrastructure includes software to handle
parallelization, input and output, data exchange between various model grids,
orchestration of the time stepping, makefiles, and simple sample run scripts. This
infrastructure should largely insulate FMS users from machine-specific details.
A standardization of the interfaces between various component models.
Software for standardizing, coordinating, and improving diagnostic calculations of
FMS-based models, and input data preparation for such models. Common
preprocessing and post-processing software are included to the extent that the
needed functionality cannot be adequately provided by available third-party
software.
Contributed component models that are subjected to a rigorous software quality
review and improvement process. The development and initial testing of these
component models is largely a scientific question, and would not fall under FMS.
The quality review and improvement process includes consideration of (A)
compliance with FMS interface and documentation standards to ensure portability
and inter-operability, (B) understandability (clarity and consistency of
documentation, comments, interfaces, and code), and (C) general computational
efficiency without algorithmic changes.
A standardized technique for version control and dissemination of the software
and documentation.
http://www.gfdl.noaa.gov/~fms/ (home page)
http://gcmd.nasa.gov/records/GFDL_FMS.html (description)
PRISM
This European analog to ESMF has created a software infrastructure for coupling arbitrary
climate models.
http://www.prism.enes.org/ (home page)
Modeling Environment for Atmospheric Discovery (MEAD)
“The goal of the MEAD expedition is the development/adaptation of cyberinfrastructure that will
enable simulation, datamining/machine learning and visualization of hurricanes and storms
utilizing the TeraGrid. The focus is on retrospective computation and analysis (not real-time
prediction). Portal grid and web infrastructure will enable launching of hundreds of individual WRF
(Weather Research and Forecasting), Regional Ocean Modeling System (ROMS), or
WRF/ROMS simulations on the grid in either ensemble or parameter mode. Metadata and the
resulting large volumes of data will then be made available through the MEAD portal for further
study and for educational purposes. “
http://www.ncsa.uiuc.edu/expeditions/MEAD/ (home page)
http://www.ncsa.uiuc.edu/expeditions/MEAD/MEADoverview.pdf (overview)
Catalog Services for the Web virtual data set (CSW) {Liping}
????
Configuration Attributes for Textual I/O (CATTR) {Smith}
????
Geos Generic
????