HR: 0800h
AN: SF31A-0715    [Abstracts]
TI: Cyberinfrastructure for Atmospheric Discovery
AU: Wilhelmson, R
EM: bw@ncsa.uiuc.edu
AF: National Center for Supercomputing Applications, 605 E. Springfield Ave, Champaign, IL 61820 United States
AU: * Moore, C W
EM: Christopher.Moore@noaa.gov
AF: NOAA/University of Washington, NOAA-PMEL, Bldg 3 7600 Sand Point Way, NE, Seattle, WA 98115 United States
AB: Each year across the United States, floods, tornadoes, hail, strong winds, lightning, hurricanes, and winter storms cause hundreds of deaths, routinely disrupt transportation and commerce, and result in billions of dollars in annual economic losses . MEAD and LEAD are two recent efforts aimed at developing the cyberinfrastructure for studying and forecasting these events through collection, integration, and analysis of observational data coupled with numerical simulation, data mining, and visualization. MEAD (Modeling Environment for Atmospheric Discovery) has been funded for two years as an NCSA (National Center for Supercomputing Applications) Alliance Expedition. The goal of this expedition has been the development/adaptation of cyberinfrastructure that will enable research simulations, datamining, machine learning and visualization of hurricanes and storms utilizing the high performance computing environments including the TeraGrid. Portal grid and web infrastructure are being tested that will enable launching of hundreds of individual WRF (Weather Research and Forecasting) simulations. In a similar way, multiple Regional Ocean Modeling System (ROMS) or WRF/ROMS simulations can be carried out. Metadata and the resulting large volumes of data will then be made available for further study and for educational purposes using analysis, mining, and visualization services. Initial coupling of the ROMS and WRF codes has been completed and parallel I/O is being implemented for these models. Management of these activities (services) are being enabled through Grid workflow technologies (e.g. OGCE). LEAD (Linked Environments for Atmospheric Discovery) is a recently funded 5-year, large NSF ITR grant that involves 9 institutions who are developing a comprehensive national cyberinfrastructure in mesoscale meteorology, particularly one that can interoperate with others being developed. LEAD is addressing the fundamental information technology (IT) research challenges needed to create an integrated, scalable 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. A transforming element of LEAD is Workflow Orchestration for On-Demand, Real-Time, Dynamically-Adaptive Systems (WOORDS), which allows the use of analysis tools, forecast models, and data repositories 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 LEAD efforts are primiarly directed at mesoscale meteorology, the IT services being developed has general applicability to other geoscience and environmental science. Integration of traditional and new data sources is a crucial component in LEAD for data analysis and assimilation, for integration of (ensemble mining) of data from sets of simulations, and for comparing results to observational data. As part of the integration effort, LEAD is creating a myLEAD metadata catalog service: a personal metacatalog that extends the Globus MCS system and is built on top of the OGSA-DAI system developed at the National e-Science Center in Edinburgh, Scotland.
UR: http://www.ncsa.uiuc.edu/Expeditions/MEAD
DE: 6339 System design
DE: 4500 OCEANOGRAPHY: PHYSICAL
DE: 3300 METEOROLOGY AND ATMOSPHERIC DYNAMICS
SC: Special Focus: Advances in Data Acquisition, Management, Analysis and Display [SF]
MN: 2004 AGU Fall Meeting