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Activity Number: 32
Type: Contributed
Date/Time: Sunday, August 9, 2015 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics and the Environment
Abstract #316433
Title: Quantifying Distributional Changes Daily Surface Temperature Observations
Author(s): Martin Tingley*
Keywords: Quantile regression ; surface temepratures ; climate change ; climate extremes

Characterizing how the magnitude and frequency of extreme climate events are changing, and will continue to change due to anthropogenic forcing of the climate system, is currently a major challenge for the climate sciences. While the current warming trend is certainly contributing to the recent increase in warm temperature extremes and decrease in cold extremes, far less is understood about the contribution of possible changes in the variability about the central tendency. These issues are explored via a quantile regression analysis of daily maximum and minimum temperature observations from over 3000 North American weather stations, allowing trends in the center of the temperature distribution to be disentangled from trends in other aspects of the distribution. Data reduction strategies are then discussed, with a focus on quantifying departures of the intercept quantile functions from normality, and departures of the slope quantile functions from linear transformations of normally distributed variables.

Authors who are presenting talks have a * after their name.

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