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Activity Number: 168 - SPEED: Environmental Statistics Methods and Applications, Part 1
Type: Contributed
Date/Time: Monday, July 29, 2019 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics and the Environment
Abstract #305034 Presentation
Title: Impact of ENSO and NAO on Extreme Monthly Precipitation of the USA
Companies: Spelman College
Keywords: ENSO; NAO; large-scale climate indices; Extreme precipitation

Changes in extreme precipitation are associated with changes in their probability distributions and the characteristics of quantiles derived from fitted distributions. In this study, the Bayesian linear quantile regression method is employed to analyze spatiotemporal trends of monthly extreme precipitation in the United States and its association with ENSO and NAO as large-scale climate indices. Monthly total maximum precipitation over the period of 65 years (1950 -2014) for 1108 sites was used for the analysis. Our results show that changes in upper quantiles of the distributions of the extreme precipitation have occurred in the Southeastern United States and at a much higher rate. ENSO has a negative effect on the coastal area while the positive effect on inland while the effect of NAO has otherwise for the USA. Such results are particularly useful for water managers who are more concerned with extreme values rather than the average one. Our study has significant implication in environmental and infrastructural assessment as well as disaster risk management.

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