TY - JOUR
T1 - Service-oriented environments for dynamically interacting with mesoscale weather
AU - Droegemeier, Kelvin K.
AU - Brewster, Keith
AU - Xue, Ming
AU - Weber, Daniel
AU - Gannon, Dennis
AU - Plale, Beth
AU - Reed, Daniel
AU - Ramakrishnan, Lavanya
AU - Alameda, Jay
AU - Wilhelmson, Robert
AU - Baltzer, Tom
AU - Domenico, Ben
AU - Murray, Donald
AU - Ramamurthy, Mohan
AU - Wilson, Anne
AU - Clark, Richard
AU - Yalda, Sepideh
AU - Graves, Sara
AU - Ramachandran, Rahul
AU - Rushing, John
AU - Joseph, Everette
AU - Morris, Vernon
N1 - Funding Information:
partment of Physics and Astronomy at Howard University, codirector of the NOAA/Howard University Center for Atmospheric Sciences, and principal investigator on several research grants from NASA, NOAA, and NSF. He has a PhD in physics from the State University of New York, Albany. Contact him at [email protected].
Funding Information:
LEAD is a large information technology research grant funded by the US National Science Foundation under the following cooperative agreements: ATM-0331594 (University of Oklahoma), ATM-0331591 (Colorado State University), ATM-0331574 (Millersville University), ATM-0331480 (Indiana University), ATM-0331579 (University of Alabama in Huntsville), ATM03-31586 (Howard University), ATM-0331587 (University Corp- oration for Atmospheric Research), and ATM-0331578 (University of Illinois, Urbana-Champaign, with a subcontract to the University of North Carolina).
PY - 2005/11
Y1 - 2005/11
N2 - The construction of Linked Environments for Atmospheric Discovery (LEAD) system, which addresses the challenges needed to create a framework for predicting the atmosphere, is discussed. LEAD's complex array of services, applications, interfaces, and local and remote computing, networking, and storage resources are assembled by users in workflows to study mesoscale weather as it evolves. LEAD lets users query for and acquire information, simulate and predict weather by using numerical atmospheric models, assimilate data and analyze data and model output. A reliability-monitoring toolkit complements the performance-monitoring infrastructure. It helps LEAD use reliability data to make scheduling decisions, anticipate likely failures, and take action.
AB - The construction of Linked Environments for Atmospheric Discovery (LEAD) system, which addresses the challenges needed to create a framework for predicting the atmosphere, is discussed. LEAD's complex array of services, applications, interfaces, and local and remote computing, networking, and storage resources are assembled by users in workflows to study mesoscale weather as it evolves. LEAD lets users query for and acquire information, simulate and predict weather by using numerical atmospheric models, assimilate data and analyze data and model output. A reliability-monitoring toolkit complements the performance-monitoring infrastructure. It helps LEAD use reliability data to make scheduling decisions, anticipate likely failures, and take action.
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U2 - 10.1109/MCSE.2005.124
DO - 10.1109/MCSE.2005.124
M3 - Review article
AN - SCOPUS:28244451273
SN - 1521-9615
VL - 7
SP - 12
EP - 27
JO - Computing in Science and Engineering
JF - Computing in Science and Engineering
IS - 6
ER -