53 citations · 188 across the 20 of their papers we have counts for
9 papers · 1 filter
Surface temperature extremes produced by huge machine learning hindcasts of summer 2023
Mark Risser, Ankur Mahesh, William D. Collins +6
The summer of 2023 brought record-breaking heat extremes across the globe. In this work, we investigate how much worse these extremes might have become, given identical large-scale…
Granger causal inference for climate change attribution
Mark D. Risser, Mohammed Ombadi, Michael F. Wehner
Climate change detection and attribution (D&A) is concerned with determining the extent to which anthropogenic activities have influenced specific aspects of the global climate sys…
Explaining the unexplainable: leveraging extremal dependence to characterize the 2021 Pacific Northwest heatwave
Likun Zhang, Mark D. Risser, Michael F. Wehner +1
In late June, 2021, a devastating heatwave affected the US Pacific Northwest and western Canada, breaking numerous all-time temperature records by large margins and directly causin…
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…
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…
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…
Spatially-Dependent Multiple Testing Under Model Misspecification, with Application to Detection of Anthropogenic Influence on Extreme Climate Events
Mark D. Risser, Christopher J. Paciorek, Daithi Stone
The Weather Risk Attribution Forecast (WRAF) is a forecasting tool that uses output from global climate models to make simultaneous attribution statements about whether and how gre…
Nonstationary Spatial Prediction of Soil Organic Carbon: Implications for Stock Assessment Decision Making
Mark D. Risser, Catherine A. Calder, Veronica J. Berrocal +1
The Rapid Carbon Assessment (RaCA) project was conducted by the US Department of Agriculture's National Resources Conservation Service between 2010-2012 in order to provide contemp…
Quantifying the effect of interannual ocean variability on the attribution of extreme climate events to human influence
Mark D. Risser, Daithi A. Stone, Christopher J. Paciorek +2
In recent years, the climate change research community has become highly interested in describing the anthropogenic influence on extreme weather events, commonly termed "event attr…