📘 Bo-Wen Shen · Research Portfolio

Nonlinear dynamics | Chaos & predictability | Weather & Climate modeling | AI-enhanced frameworks
🏛️ San Diego State University · Mathematics & Statistics 🌍 Applied Mathematics · Nonlinear Data Analysis 💻 High‑end Computing · Global NWP & Climate
🌀 1. Chaotic dynamics signature contribution
Extended Lorenz models to unveil coexisting chaotic and non‑chaotic attractors — a paradigm shift in weather predictability. Formalized “three kinds of butterfly effects” and multistability in high‑dimensional systems.
Is Weather Chaotic? Coexistence of Chaos and Order within a Generalized Lorenz Model
Bulletin of the American Meteorological Society (BAMS) · 2021 · Vol. 102, E148–E158
coexisting attractorsmultistabilityfeatured insight
Three Kinds of Butterfly Effects Within Lorenz Models
Encyclopedia · 2022 · 2(3), 1250–1259
Lorenz 1963/1969sensitivityreview
A Review of Lorenz’s Models from 1960 to 2008
International Journal of Bifurcation and Chaos (IJBC) · 2023 · 33(10), 2330024 (Feature Article, Editor’s Pick 2024)
comprehensive reviewpredictability
Coexistence of Chaotic and Non‑Chaotic Orbits in a New Nine‑Dimensional Lorenz Model
CHAOS 2018 ¡ Springer Proceedings in Complexity ¡ 2019
9D Lorenzorbit coexistence
One Saddle Point and Two Types of Sensitivities Within the Lorenz 1963 and 1969 Models
Atmosphere ¡ 2022 ¡ 13(5), 753
saddle‑point dynamicsfinite predictability
🌊 2. Nonlinear wave & quantum dynamics KdV · solitons · homoclinic links
Bridges Lorenz‑type chaos with solitary waves, KdV equation, homoclinic orbits and quantum tunneling. Formulated the novel KdV‑SIR model for epidemic waves.
Homoclinic Orbits and Solitary Waves within the non‑dissipative Lorenz Model and KdV Equation
International Journal of Bifurcation and Chaos ¡ 2020 ¡ 30, 2050257
solitonshomoclinic connection
A KdV‑SIR Equation and Its Analytical Solutions: An Application for COVID‑19 Data Analysis
Chaos, Solitons & Fractals ¡ 2023 ¡ 113610 (with W. Paxson)
epidemic wavesanalytical KdV‑SIR
From Airy’s Equation to the Non‑dissipative Lorenz Model: Turning Points, Quantum Tunneling, and Solitary Waves
Encyclopedia ¡ 2025 ¡ 5(4), 208
quantum analogyWKB ¡ turning points
Solitary Waves, Homoclinic Orbits, and Nonlinear Oscillations within the non‑dissipative Lorenz Model, the inviscid Pedlosky Model, and the KdV Equation
CHAOS 2020 ¡ Springer ¡ 2021
unified wave perspective
🤖 3. AI / ML / Deep Learning transformers · AI weather limits
Pioneering the integration of Transformer architectures with generalized Lorenz models for downscaling/upscaling. Examines fundamental predictability limits of AI‑based weather prediction.
Exploring Downscaling in High‑Dimensional Lorenz Models Using the Transformer Decoder
Machine Learning and Knowledge Extraction (MAKE) · 2024 · 6, 2161–2182
Transformer decoderdownscalingLorenz‑96‑like
Butterfly Effects and Finite Predictability in AI‑Based Weather Prediction
ESS Open Archive (submitted to GRL) ¡ 2025 ¡ with R. Pielke Sr., X. Zeng
AI weather modelschaos theorypredictability horizon
A Brief Review of AI‑Enhanced Modeling Framework
Wikipedia (History of numerical weather prediction) ¡ 2024 ¡ contributed entry
AEMFcommunity resource
Introduction to Foundation Models for Mathematical Programming ¡ Course Materials Math340
San Diego State University ¡ 2025 ¡ http://doi.org/10.13140/RG.2.2.24063.32169
educationfoundation models
⚙️ 4. High‑performance & scientific computing PEEMD · scalability · NASA supercomputing
Developed Parallel Ensemble Empirical Mode Decomposition (PEEMD) and advanced multi‑scale modeling frameworks on NASA Columbia/Discover. Scalability improvements for global climate simulations.
Parallel Implementation of the Ensemble Empirical Mode Decomposition (PEEMD) and Its Application for Earth Science Data Analysis
Computing in Science & Engineering (CiSE) · 2017 · 19(5), 49–57
PEEMDmulticore/parallel
Improving the NASA Multiscale Modeling Framework’s Performance for Tropical Cyclone Climate Study
Computing in Science & Engineering · 2013 · 15(5), 56–67
MMF scalabilityNASA supercomputers
Cross‑Platform Performance of a Portable Communication Module and the NASA Finite Volume General Circulation Model
International Journal of High Performance Computing Applications · 2005 · 19: 213–223
fvGCMportability
Petascale Computing: Impact on Future NASA Missions (Book chapter)
Chapman & Hall / CRC Press ¡ 2007 ¡ with R. Biswas, M.J. Aftosmis, C. Kiris
petascalefuture HPC
🌎 5. Climate modeling & analysis global mesoscale · hurricanes · predictability limits
Global‑scale simulations of hurricane genesis (Sandy, Katrina, Nargis), African easterly waves, MJO interactions. Recent work on tipping points, energy‑balance models and the two‑week predictability barrier.
Genesis of Hurricane Sandy (2012) Simulated with a Global Mesoscale Model
Geophysical Research Letters ¡ 2013 ¡ 40, DOI:10.1002/grl.50934
Hurricane Sandyglobal mesoscale
African Easterly Waves in 30‑day High‑resolution Global Simulations: A Case Study during the 2006 NAMMA Period
Geophysical Research Letters ¡ 2010 ¡ 37, L18803
AEW30‑day hindcast
Tipping, Bifurcation, and Regime Shifts in Nonlinear Energy‑Balance Models
International Journal of Bifurcation and Chaos ¡ 2026 ¡ 36(6), 2630014 (Feature Article)
climate tippingEBM
Exploring the Origin of the Two‑Week Predictability Limit: A Revisit of Lorenz’s Predictability Studies in the 1960s
Atmosphere ¡ 2024 ¡ 15(7), 837 (podcast featured)
predictability limitLorenz 1960s
Predicting Tropical Cyclogenesis with a Global Mesoscale Model: Hierarchical Multiscale Interactions During the Formation of Tropical Cyclone Nargis (2008)
J. Geophys. Res. ¡ 2010 ¡ 115, D14102
Cyclone Nargismultiscale
📖 Editorial & synthesis leadership special issues · books
Special Issue on 50th Anniversary of the Metaphorical Butterfly Effect since Lorenz (1972)
MDPI Atmosphere ¡ 2023 ¡ edited with R.A. Pielke Sr., X. Zeng ¡ 336 pp, ISBN 978-3-0365-8911-4
Butterfly Effects (Physics Today, Weatherwise) – magazine & public outreach
2024 ¡ Physics Today 77(9), 10; Weatherwise, DOI:10.1080/00431672.2024.2329521
Lorenz’s View on the Predictability Limit · Encyclopedia & Video entry
2023 · Encyclopedia 3(3), 887–899 + video summary
The Dual Nature of Chaos and Order in the Atmosphere (Editor’s Choice)
Atmosphere 2022 · 13(11), 1892 · with Pielke, Zeng, Cui, Faghih‑Naini, Paxson et al.
⚡ Impact synthesis · Prof. Shen’s research uniquely bridges deterministic chaos → nonlinear waves/KdV → AI downscaling → global climate simulations. His generalized Lorenz hierarchy reveals coexisting order & chaos, reshaping predictability theory. The Transformer‑Lorenz framework opens new data‑driven pathways for Earth system prediction.

📚 Based on Prof. Shen’s publication listing (bwshen.sdsu.edu) and archived content as of April 2026.