papers

Publications (8)

stat.AP2021

Estimating Concurrent Climate Extremes: A Conditional Approach

Whitney K. Huang, Adam H. Monahan, Francis W. Zwiers

Simultaneous concurrence of extreme values across multiple climate variables can result in large societal and environmental impacts. Therefore, there is growing interest in underst…

math.PR2017

How close are time series to power tail Lévy diffusions?

Jan Gairing, Michael A. Högele, Tania Kosenkova +1

This article presents a new and easily implementable method to quantify the so-called coupling distance between the law of a time series and the law of a differential equation driv…

physics.ao-ph2023

Algorithmic Hallucinations of Near-Surface Winds: Statistical Downscaling with Generative Adversarial Networks to Convection-Permitting Scales

Nicolaas J. Annau, Alex J. Cannon, Adam H. Monahan

This paper explores the application of emerging machine learning methods from image super-resolution (SR) to the task of statistical downscaling. We specifically focus on convoluti…

stat.AP2021

Nonstationary seasonal model for daily mean temperature distribution bridging bulk and tails

Mitchell Krock, Julie Bessac, Michael L. Stein +1

In traditional extreme value analysis, the bulk of the data is ignored, and only the tails of the distribution are used for inference. Extreme observations are specified as values…

math.NA2019

Joint state-parameter estimation of a nonlinear stochastic energy balance model from sparse noisy data

Fei Lu, Nils Weitzel, Adam H. Monahan

While nonlinear stochastic partial differential equations arise naturally in spatiotemporal modeling, inference for such systems often faces two major challenges: sparse noisy data…

physics.ao-ph2019

Machine Learning for Stochastic Parameterization: Generative Adversarial Networks in the Lorenz '96 Model

David John Gagne, Hannah M. Christensen, Aneesh C. Subramanian +1

Stochastic parameterizations account for uncertainty in the representation of unresolved sub-grid processes by sampling from the distribution of possible sub-grid forcings. Some ex…

stat.ME2022

Teleconnected warm and cold extremes of North American wintertime temperatures

Mitchell L. Krock, Adam H. Monahan, Michael L. Stein

Current models for spatial extremes are concerned with the joint upper (or lower) tail of the distribution at two or more locations. Such models cannot account for teleconnection p…

math.PR2015

Stochastic averaging of dynamical systems with multiple time scales forced with α-stable noise

William F. Thompson, Rachel A. Kuske, Adam H. Monahan

Stochastic averaging allows for the reduction of the dimension and complexity of stochastic dynamical systems with multiple time scales, replacing fast variables with statistically…