93 citations · 746 across the 53 of their papers we have counts for
5 papers · 1 filter
Data-driven transition path analysis yields a statistical understanding of sudden stratospheric warming events in an idealized model
Justin Finkel, Robert J. Webber, Edwin P. Gerber +2
Atmospheric regime transitions are highly impactful as drivers of extreme weather events, but pose two formidable modeling challenges: predicting the next event (weather forecastin…
Ensemble Markov chain Monte Carlo with teleporting walkers
Michael Lindsey, Jonathan Weare, Anna Zhang
We introduce an ensemble Markov chain Monte Carlo approach to sampling from a probability density with known likelihood. This method upgrades an underlying Markov chain by allowing…
Rare Event Sampling Improves Mercury Instability Statistics
Dorian S. Abbot, Robert J. Webber, Sam Hadden +2
Due to the chaotic nature of planetary dynamics, there is a non-zero probability that Mercury's orbit will become unstable in the future. Previous efforts have estimated the probab…
Approximating matrix eigenvalues by subspace iteration with repeated random sparsification
Samuel M. Greene, Robert J. Webber, Timothy C. Berkelbach +1
Traditional numerical methods for calculating matrix eigenvalues are prohibitively expensive for high-dimensional problems. Iterative random sparsification methods allow for the es…
Learning forecasts of rare stratospheric transitions from short simulations
Justin Finkel, Robert J. Webber, Dorian S. Abbot +2
Rare events arising in nonlinear atmospheric dynamics remain hard to predict and attribute. We address the problem of forecasting rare events in a prototypical example, Sudden Stra…