Seminar at SMU Delhi
July 19, 2011 (Tuesday) ,
3:30 PM at Webinar
Speaker:
Snigdhansu Chatterjee,
University of Minnesota, USA
Title:
A statistical study of climate change: analysis of temperature records of Arctic seawater data
Abstract of Talk
We analyze a dataset on seawater pattern over the last few decades.
For specificity, we restrict attention to temperature measures in the
Arctic Ocean region for this talk. Our goal is to investigate whether
there is a significant change of pattern in the Arctic Ocean seawater
temperature, thus detecting climate change, after accounting for the
systematic factors like location, depth, season, and the temporal and
spatial dependence pattern of the observations. We do not explicitly
model the spatio-temporal dependency pattern of the observations, but
treat it as an extremely high dimensional nuisance parameter, and use
techniques for estimation and inference that are insensitive to it. We
use nonparametric curve fitting for weakly dependent observations to
model different functions of seawater temperature, and then perform
sequential tests to detect whether the function under consideration
has changed its pattern from previous time-points. A complex
resampling-based robustness study is used to decide whether the
changes detected are chance aberrations. Finally, we separate the data
in two parts based on observation-time, and use a block bootstrap
based scheme to compare temperature patterns in the two regimes. The
block-bootstrap based technique elicits probabilities that are the
equivalents of size, power and $p$-value of our sequential testing
procedure, under reasonable assumptions. The methodology used in this
paper is applicable for any sequence of dependent observations on the
climate, and unlike many other climate studies does not rely on
computer simulated deterministic outputs, nor use of indirect
historical data, nor rely on technical assumptions like linearity,
Gaussian nature of random variables, specific dependency patterns, and
so on. This work is jointly done with Qiqi Deng and Jie Xu.