TWO STUDIES OF STATISTICAL MODELING OF ENVIRONMENTAL EXTREMES
Colorado State University
In this talk, we will present two separate studies which analyze environmental extremes.
The first study uses two CESM initial condition ensembles to investigate potential changes in extreme precipitation under two climate change scenarios over the contiguous United States. We fit non-stationary generalized extreme value (GEV) models to annual maximum daily precipitation simulated from the 30-member “Large Ensemble” under the RCP8.5 scenario and a 15-member “Medium Ensemble” under the RCP4.5 scenario. We then compare impacts using the 1% annual exceedance probability level, which is the amount of daily rainfall with only a 1% chance of being exceeded in a given year. We also investigate a pattern scaling approach in which we produce predictive GEV distributions of annual precipitation maxima under RCP4.5 given only global mean temperatures for this scenario. We compare results from this less computationally intensive method to those obtained from our GEV model fitted directly to the CESM RCP4.5 output and find that pattern scaling produces reasonable projections. This study is part of a larger project on the Benefits of Reduced Anthropogenic Climate change (BRACE).
The second study examines the sensitivities of extreme ground-level ozone to meteorological drivers (e.g. air temperature) using quantile regression and a recently-developed method based on maximizing tail dependence. We will present a case study comparing the sensitivities for observed ozone to those we find in WRF-Chem output. Preliminary results show discrepancies between the relationships between the driving meteorological variables and ozone levels between the observations and the WRF-Chem output
Wednesday, June 1, 2016
Mesa Lab, Chapman Room
(Bring your lunch)