 |
<< Back to Subproject Details
- Pitman, A.J., and S.E. Perkins, 2007: Reducing uncertainty in selecting climate models. Quantification and Reduction of Predictive Uncertainty for Sustainable Water Resources Management (Proceedings of Symposium HS2004 at IUGG2007, Perugia, July 2007). IAHS Publ., 313, 3-15.
Deciding which climate models to use to assess the impact of
climate change on water resources is particularly difficult in environments
where precipitation dominates resource vulnerability. We show that assessing
climate models based on their simulation of mean precipitation provides little
guide to a model’s ability to simulate the more extreme events that affect
hydrological systems. In contrast, a probability density function based assessment
using daily climate model data provides a good basis for confidence in a
model’s ability to simulate the 95th rainfall percentile. We demonstrate that
climate models have useful skill in simulating observed probability density
functions over two regions of Australia, although the well-known bias of
excess rainfall at low rates remains common. We conclude by identifying
those climate models that produce the best basis for hydrological impacts
assessment over two regions of Australia.
Last Updated: 2007-12-13
<< Back to Subproject Details
|
|
