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ESRL/PSD Seminar Series

Analysis of Non-stationary Spatio-Temporal Climatic Extremes

Linyin Cheng
Center for Hydrometeorology and Remote Sensing University of California, Irvine


Numerous studies show that climatic extremes have increased substantially in the second half of the 20th century. For this reason, analysis of extremes under a non-stationary assumption has received a great deal of attention. In this presentation, a new developed Non-stationary Extreme Value Analysis (hereafter, NEVA) software package will be presented for estimating stationary and non-stationary return levels, return periods, and risks of climatic extremes using Bayesian inference. It also offers the confidence interval and uncertainty bounds of estimated return levels, and non-stationary extreme value analysis using both constant and time varying exceedance probability methods, which make NEVA explicitly designed to facilitate analysis of extremes in the geosciences. Both stationary and non-stationary components of NEVA are validated for a number of case studies using empirical return levels. The results show that NEVA reliably describes extremes and their return levels. More applications using NEVA will be presented such as assessment for non-stationary return levels in CMIP5 multimodel simulations. Furthermore, the model can be used for non-stationary extreme value analysis of precipitation Intensity-Frequency-Duration (IDF) curves, which helps to improve our understanding of the potential climate-induced changes in the intensity, duration and frequency of heavy precipitation. Beyond the non-stationary univariate analysis, a new framework named empirical Bayes conditional extreme value analysis model will be presented to detect potential changes in hydrological cycle, and assess joint occurrence of extreme events.

Tuesday, June 4th
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