Computer Science – Computational Engineering – Finance – and Science
Scientific paper
2007-12-13
Computer Science
Computational Engineering, Finance, and Science
Scientific paper
Understanding the earth's climate system and how it might be changing is a preeminent scientific challenge. Global climate models are used to simulate past, present, and future climates, and experiments are executed continuously on an array of distributed supercomputers. The resulting data archive, spread over several sites, currently contains upwards of 100 TB of simulation data and is growing rapidly. Looking toward mid-decade and beyond, we must anticipate and prepare for distributed climate research data holdings of many petabytes. The Earth System Grid (ESG) is a collaborative interdisciplinary project aimed at addressing the challenge of enabling management, discovery, access, and analysis of these critically important datasets in a distributed and heterogeneous computational environment. The problem is fundamentally a Grid problem. Building upon the Globus toolkit and a variety of other technologies, ESG is developing an environment that addresses authentication, authorization for data access, large-scale data transport and management, services and abstractions for high-performance remote data access, mechanisms for scalable data replication, cataloging with rich semantic and syntactic information, data discovery, distributed monitoring, and Web-based portals for using the system.
Bernholdt David
Bharathi Shishir
Brown David
Chanchio Kasidit
Chen Meili
No associations
LandOfFree
The Earth System Grid: Supporting the Next Generation of Climate Modeling Research does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with The Earth System Grid: Supporting the Next Generation of Climate Modeling Research, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and The Earth System Grid: Supporting the Next Generation of Climate Modeling Research will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-661719