Professional Profile
Chaos, predictability, and tipping dynamics.
Dr. Bo-Wen Shen is an Associate Professor in the Department of Mathematics and Statistics at San Diego State University. His work connects generalized Lorenz models, butterfly effects, finite predictability, climate tipping processes, and AI-assisted prediction.
Lorenz modelschaos, order, attractors
Predictabilitybutterfly effects, SDIC
Climate systemstipping, modeling, AI
Research at a glance
Butterfly effectsThree meanings, multiscale predictability, and the difference between metaphors and mechanisms.
Generalized Lorenz modelsLow-order and nonlinear systems that reveal coexistence of chaos and order.
Weather and climate modelingHigh-end computing, mesoscale simulations, and predictability limits.
Climate tipping dynamicsBifurcation, delayed transition, domino cascades, and mechanism-based diagnostics.
Selected Highlights
- Generalized Lorenz ModelsIJBC, JAS, NPD, Atmosphere
- A Review of Lorenz’s Models from 1960 to 2008IJBC Feature Article
- The Dual Nature of Chaos and OrderBAMS, Atmosphere
- SDIC, Ill-Conditions, and Finite PredictabilityAtmosphere
- Three Kinds of Butterfly EffectsOutstanding Contributor Award
- Butterfly EffectsPhysics Today
- The Two-Week Predictability HypothesisFeature Paper
- Recent Advances in Prediction with AI ModelsEncyclopedia
- 30-day Simulations of African Easterly WavesAGU GRL
- Downscaling Through AI Transformer ModelsMAKE
- A Global Mesoscale Modelfeatured in Science
- Climate Tipping DynamicsIJBC Feature Paper
- Unified Framework: Lorenz Model and Nonlinear Schrödinger EquationChaos 2021 / IJBC
- Homoclinic Orbits, Solitary Waves, and Quantum TunnelingIJBC / CSF
Covers, features, and media
