Welcome...
… to the web pages of the GENIE Earth-system model. GENIE is the brainchild of a cadre of Earth-system modelers based mostly at the Universities of Bristol, East Anglia, Southampton and the Open University. However, the network of contributors to the model and members of the currently funded GENIEfy project spread much further afield.
For help with installing and running GENIE, you might want to try the wiki; and to engage with the users and developers of GENIE, why not join the GENIEfy Network, right here on researchpages.net (you’ll need to sign up first).
Our objectives are to develop, evolve and continually support a Grid-based computing framework which will allow us to:
- flexibly couple together state-of-the-art components to form a unified Earth System Model (ESM)
- execute the resulting ESM across a computational Grid
- share the distributed data produced by simulation runs
- provide high-level open access to the system, creating and supporting virtual organisations of Earth System modellers
The Domain of GENIE
The GENIE project’s aim is to build simplified and faster-running models of the Earth’s climate system, and make them easier to use and more widely available to other people who want & need to use them. State-of-the-art climate models (such as the excellent Hadley Centre model) work on quite detailed scales in both space and time, and are consequently big and slow, and cannot be used to simulate more than a few centuries of climate on anything other than a super-computer, and even so may take months to give results. We aim to model the climate for many thousands of years, because the climate of the Earth has undergone major and dramatic climate changes (including ice ages) in the past, over periods of many thousands (and even millions) of years, and we need to understand these so that we can model future climate with more confidence. And we aim to do this using more widely available computers (including top-end PCs) so that more scientists who are not computer experts can explore their ideas. To build such models which run thousands of times faster, we have to work with coarser grids, giving us less detailed results, and also use simplified versions of the physical, chemical and biological processes which interact to control the climate. The price of this is that we expect less accurate results, but we can afford to do large numbers of runs to compare the results, and so find out how much simplification we can tolerate, and how accurate the answers are, which is almost impossible with the big models.
