Annual Report 2008.pdf - SAMSI

SAMSI
madar@post.tau.ac.
“Bayesian Model Selection for The Farlie-Gumbel-Morgenstern Family.”
Suppose we have two General Extreme Value random variables. We wish to find a copula
structure that explains their joint behavior. As a first step, we consider the Farlie-Gumbel-
Morgenstern family of copulas, and offer some bayesian model selection to it.
Elizabeth Shamseldin
University of North Carolina, Chapel Hill
shamseld@email.unc.edu
“Downscaling Extremes: A Comparison of Extreme Value Distributions in Point-Source and
Gridded Precipitation Data”
There is substantial empirical and climatological evidence that precipitation extremes have
become more extreme during the twentieth century, and that this trend is likely to continue as
global warming becomes more intense. However, understanding these issues is limited by a
fundamental issue of spatial scaling: that most evidence of past trends comes from rain gauge
data, whereas trends into the future are produced by climate models, which rely on gridded
aggregates.
To study this further, we have fitted the Generalized Extreme Value (GEV) distribution to the
right tail of the distribution of both rain gauge and gridded events. The rain gauge data come
from a network of 5,873 U.S. stations, and the gridded data from a well-known re-analysis model
(NCEP) and on climate model runs from NCAR's Community Climate System Model (CCSM).
The results of this modeling exercise confirm, as expected, that return values computed from rain
gauge data are typically higher than those computed from gridded data. The main contribution
of this paper is the development of a family of regression relationships between the two sets of
return values that also take spatial and temporal variations into account. Based on these results,
we now believe it is possible to project future changes in precipitation extremes at the pointlocation
level based on results from climate models.
XVII. Program on Random Media Waves and Imaging Workshop
Schedule
Thursday, January 31, 2008
Radisson Hotel RTP
8:00 - 9:00 Registration and Continental Breakfast
Imaging and Inverse Problems Session
9:00 - 9:50 Margaret Cheney, Rensselaer Polytechnic Institute
Waveform Design for Radar Detection and Imaging