Climate Extremes Workshop: May 16-17, 2018


This workshop took place at SAMSI, Research Triangle Park, NC


This workshop followed the CLIM Transition Workshop and focused on a more in depth discussion into climate extreme research.
**NOTE: Planning for this workshop is ongoing and more information will be posted as updates are made available.

Supporting Media

Printable Schedule
Speaker Abstracts

Wednesday, May 16, 2018
SAMSI in Research Triangle Park, NC.

Description Speaker Slides
Special Lecture: “Climate Extremes and Max-stable Processes” Raphaël Huser, KAUST
Climate and Weather Extremes
Historical Perspective on Hurricane Harvey Rainfall Ken Kunkel, NC Climate Center, Asheville
Extreme Values of Vertical Wind Speed in Doppler LIDAR ARM Measurements Charlotte Haley, Argonne
Employing a Multivariate Spatial Hierarchical Model to Characterize Extremes with Application to US Gulf Coast Precipitation Brook Russell, Clemson
The Dependence Between Extreme Precipitation and Underlying Indicators of Climate Change Richard Smith, UNC-Chapel Hill
Spatial Extremes
Max-Infinitely Divisible Models for Spatial Extremes Using Random Effects Ben Shaby, Penn State
Assessing models for estimation and methods for uncertainty quantification for spatial return levels Bo Li, University of Illinois
Decompositions of Dependence for High-Dimensional Extremes: Applied to Spatial Precipitation Extremes Yujing Jiang, Colorado State University
Spatial Modeling for Improving Estimates of Extreme Precipitation Statistics at Weather Stations Mark Risser, LBNL

Thursday, May 17, 2018
SAMSI in Research Triangle Park, NC.

Description Speaker Slides
Networks and Extremes
Networks and Extremes: Review and Further Studies Ansu Chatterjee, University of Minnesota
Network Analysis of Gulf Coast Extreme Precipitation Whitney Huang, SAMSI
Extreme Rainfall Events of Indian Monsoon: A Network-based Analysis Adway Mitra, ICTS; visiting SAMSI/UNC-Chapel Hill
Life Cycle of Extreme Events Revealed by Network Chen Chen, University of Chicago
New Models for Extremes
Semiparametric Density Estimation for Heavy Tailed Data Surya Tokdar, Duke
A Semiparametric Bayesian Clustering Model for Spatial Extremes Brian Reich, NC State University
Semiparametric Models for Densities that Have Flexible Tail Behaviors Michael Stein, University of Chicago
Extreme Value Theory and the Re-assessment in the Caribbean: Lessons from Hurricane Irma and Maria David Torres, University of Puerto Rico

Questions: email