activity
20162019
most citedApplication of Deep Convolutional Neural Networks for Detecting Extreme Weather in Climate Datasets

316 citations · 455 across the 9 of their papers we have counts for

collaborators

9 papers

stat.AP2019

The effect of geographic sampling on evaluation of extreme precipitation in high resolution climate models

Mark D. Risser, Michael F. Wehner

Traditional approaches for comparing global climate models and observational data products typically fail to account for the geographic location of the underlying weather station d…

stat.AP2019★ 15 cited

Detected changes in precipitation extremes at their native scales derived from in situ measurements

Mark D. Risser, Christopher J. Paciorek, Travis A. O'Brien +2

The gridding of daily accumulated precipitation -- especially extremes -- from ground-based station observations is problematic due to the fractal nature of precipitation, and ther…

stat.AP2018★ 37 cited

A probabilistic gridded product for daily precipitation extremes over the United States

Mark D. Risser, Christopher J. Paciorek, Michael F. Wehner +2

Gridded data products, for example interpolated daily measurements of precipitation from weather stations, are commonly used as a convenient substitute for direct observations beca…

stat.ME2017

A Nonparametric Method for Producing Isolines of Bivariate Exceedance Probabilities

Daniel Cooley, Emeric Thibaud, Federico Castillo +1

We present a method for drawing isolines indicating regions of equal joint exceedance probability for bivariate data. The method relies on bivariate regular variation, a dependence…

cs.DC2017★ 5 cited

An Assessment of Data Transfer Performance for Large-Scale Climate Data Analysis and Recommendations for the Data Infrastructure for CMIP6

Eli Dart, Michael F. Wehner, Prabhat

We document the data transfer workflow, data transfer performance, and other aspects of staging approximately 56 terabytes of climate model output data from the distributed Coupled…

stat.ME2017

Quantifying statistical uncertainty in the attribution of human influence on severe weather

Christopher J. Paciorek, Dáithí A. Stone, Michael F. Wehner

Event attribution in the context of climate change seeks to understand the role of anthropogenic greenhouse gas emissions on extreme weather events, either specific events or class…