93 citations · 746 across the 53 of their papers we have counts for
10 papers · 1 filter
Missing the Butterfly and Predicting the Past: Features or Bugs of Accurate AI Weather Models?
Pedram Hassanzadeh, Weidong Li, Y. Qiang Sun +4
AI weather prediction (AIWP) models rival physics-based models, yet the sources of their unexpected forecast accuracy and the degree of their physical fidelity remain unclear. Here…
AI-boosted rare event sampling to characterize extreme weather
Amaury Lancelin, Alex Wikner, Laurent Dubus +5
Weather extremes pose major societal risks, especially in a changing climate, but due to their rarity, they are difficult to study using limited observations or complex climate mod…
Can AI weather models predict out-of-distribution gray swan tropical cyclones?
Y. Qiang Sun, Pedram Hassanzadeh, Mohsen Zand +3
Predicting gray swan weather extremes, which are possible but so rare that they are absent from the training dataset, is a major concern for AI weather models and long-term climate…
Using Explainable AI and Transfer Learning to understand and predict the maintenance of Atlantic blocking with limited observational data
Huan Zhang, Justin Finkel, Dorian S. Abbot +2
Blocking events are an important cause of extreme weather, especially long-lasting blocking events that trap weather systems in place. The duration of blocking events is, however,…
Revealing the statistics of extreme events hidden in short weather forecast data
Justin Finkel, Edwin P. Gerber, Dorian S. Abbot +1
Extreme weather events have significant consequences, dominating the impact of climate on society. While high-resolution weather models can forecast many types of extreme events on…
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…
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…
Path properties of atmospheric transitions: illustration with a low-order sudden stratospheric warming model
Justin Finkel, Dorian Abbot, Jonathan Weare
Many rare weather events, including hurricanes, droughts, and floods, dramatically impact human life. To accurately forecast these events and characterize their climatology require…
Maximizing simulated tropical cyclone intensity with action minimization
David A. Plotkin, Robert J. Webber, Morgan E O'Neill +2
Direct computer simulation of intense tropical cyclones (TCs) in weather models is limited by computational expense. Intense TCs are rare and have small-scale structures, making it…
Practical rare event sampling for extreme mesoscale weather
Robert J. Webber, David A. Plotkin, Morgan E O'Neill +2
Extreme mesoscale weather, including tropical cyclones, squall lines, and floods, can be enormously damaging and yet challenging to simulate; hence, there is a pressing need for mo…