PCMDI > WCRP CMIP3 Model Output > Diagnostic Subprojects

PI:	Justin Sheffield
Institution:	Princeton University
Abstract:
Detection of climate change induced trends in water cycle variables is dependent upon the strength of the trend against the background variability. This is basically a signal to noise problem. We wish to investigate how detectability depends upon a number of factors including the range of potential trends as predicted by GCMs. Given the uncertainty in predictions of future climate change we will look at results from a number of GCMs, including ensembles where available, and see how this uncertainty translates into uncertainty in detection. The study will focus on monthly datasets of land surface variables, initially precipitation and temperature. This work will be undetaken solely at Princeton University under the direction of Prof. Eric F. Wood.
Publications:
Sheffield, J., and E. F. Wood, 2007: Projected Changes in Drought Occurrence under Future Global Warming from Multi-Model, Multi-Scenario, IPCC AR4 Simulations. Climate Dynamics. Submitted. Abstract. Edit. Add Publication