The University of Southampton
University of Southampton Institutional Repository

GENIE: Grid enabled integrated earth system model

GENIE: Grid enabled integrated earth system model
GENIE: Grid enabled integrated earth system model
An understanding of the astonishing and, as yet, unexplained natural variability of past climate is an essential pre-requisite to increase confidence in predictions of long-term future climate change. GENIE is a new Grid-enabled modelling framework that can compose an extensive range of Earth System Models (ESMs) for simulation over multi-millennial timescales, to study ice age cycles and long-term human induced global change. Grid technology is a key enabler for the flexible coupling of constituent models, subsequent execution of the resulting ESMs and the management of the data that they generate.
15-16
Price, Andrew
f4db9dfc-23b6-4c11-8da6-bbf0ee35d6d5
Lenton, Tim
2e73ba9a-99c0-43be-bda3-1e769206d72d
Cox, Simon
4fe1de98-4843-4d45-9143-3369b6b9a241
Valdes, Paul
1d96598c-56b8-4582-bc4a-e5618309641b
Shepherd, John
f38de3ac-eb3b-403f-8767-c76be68d8bf2
The GENIE Team
Price, Andrew
f4db9dfc-23b6-4c11-8da6-bbf0ee35d6d5
Lenton, Tim
2e73ba9a-99c0-43be-bda3-1e769206d72d
Cox, Simon
4fe1de98-4843-4d45-9143-3369b6b9a241
Valdes, Paul
1d96598c-56b8-4582-bc4a-e5618309641b
Shepherd, John
f38de3ac-eb3b-403f-8767-c76be68d8bf2

Price, Andrew, Lenton, Tim, Cox, Simon, Valdes, Paul and Shepherd, John , The GENIE Team (2005) GENIE: Grid enabled integrated earth system model. ERCIM News, 61, 15-16.

Record type: Article

Abstract

An understanding of the astonishing and, as yet, unexplained natural variability of past climate is an essential pre-requisite to increase confidence in predictions of long-term future climate change. GENIE is a new Grid-enabled modelling framework that can compose an extensive range of Earth System Models (ESMs) for simulation over multi-millennial timescales, to study ice age cycles and long-term human induced global change. Grid technology is a key enabler for the flexible coupling of constituent models, subsequent execution of the resulting ESMs and the management of the data that they generate.

Full text not available from this repository.

More information

Published date: 2005

Identifiers

Local EPrints ID: 23521
URI: https://eprints.soton.ac.uk/id/eprint/23521
PURE UUID: 5c3db9eb-d0a8-4d9a-931e-9d42073fdac1
ORCID for John Shepherd: ORCID iD orcid.org/0000-0002-5230-4781

Catalogue record

Date deposited: 20 Mar 2006
Last modified: 15 Mar 2019 01:37

Export record

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×