Global hydrology modelling and uncertainty: Running multiple ensembles with a campus grid

61Citations
Citations of this article
77Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Uncertainties associated with the representation of various physical processes in global climate models (GCMs) mean that, when projections from GCMs are used in climate change impact studies, the uncertainty propagates through to the impact estimates. A complete treatment of this 'climate model structural uncertainty' is necessary so that decision-makers are presented with an uncertainty range around the impact estimates. This uncertainty is often underexplored owing to the human and computer processing time required to perform the numerous simulations. Here, we present a 189-member ensemble of global river runoff and water resource stress simulations that adequately address this uncertainty. Following several adaptations and modifications, the ensemble creation time has been reduced from 750 h on a typical single-processor personal computer to 9 h of high-throughput computing on the University of Reading Campus Grid. Here, we outline the changes that had to be made to the hydrological impacts model and to the Campus Grid, and present the main results. We show that, although there is considerable uncertainty in both the magnitude and the sign of regional runoff changes across different GCMs with climate change, there is much less uncertainty in runoff changes for regions that experience large runoff increases (e.g. the high northern latitudes and Central Asia) and large runoff decreases (e.g. the Mediterranean). Furthermore, there is consensus that the percentage of the global population at risk to water resource stress will increase with climate change. © 2010 The Royal Society.

Cite

CITATION STYLE

APA

Gosling, S. N., Bretherton, D., Haines, K., & Arnell, N. W. (2010). Global hydrology modelling and uncertainty: Running multiple ensembles with a campus grid. In Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences (Vol. 368, pp. 4005–4021). Royal Society. https://doi.org/10.1098/rsta.2010.0164

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free