Research & Development
From the Navier–Stokes equations to generative neural networks — coupled dynamical models, data assimilation, and physics-ML, developed into operational products for climate-risk decisions.
Research: Earth-system science
Development: operational products
Dynamical Modeling
Data Assimilation
Physics-ML & Generative AI
Extreme Events & Climate Risk
Interactive
One research program, two engines
My projects live on a continuum between pure dynamical physics and pure machine learning. The most powerful tools sit in the middle — ML constrained by physics, and physics accelerated by ML. Click a dot to explore each project.
⚙ Dynamical Physics
Machine Learning 🧠
Science
Research highlights
Dynamical · OSSE
Global Kilometer-Scale GEOS/ECCO Nature Run
Co-developed and executed a global coupled atmosphere–ocean simulation at kilometer scale (C1440-LLC2160) — a digital-twin "truth" dataset for satellite observing-system simulation experiments, pre-launch sensor evaluation, and extreme-event reconstruction, produced on petabyte-scale HPC.
Scientific Data (2026)GRL (2022)
Dynamical · Coupled Modeling
GEOS-MITgcm NWP-to-Decadal Prediction System
Co-led development of NASA's modular coupled prediction system spanning weather to decadal horizons: Fortran/MPI coupling architecture, dynamically balanced initialization, adjoint data assimilation, and legacy-kernel optimization for 30% higher HPC throughput.
+30% throughputJ. Climate (in review)
Hybrid Physics-ML
Green's-Function, Adjoint & Bayesian Parameter Optimization
Two physically interpretable strategies for tuning Earth-system models: Green's-function response maps with Gaussian-process multi-fidelity search, and ocean-adjoint gradients transferred into coupled GEOS-MITgcm experiments.
−75% calibration cost10× throughput+40% accuracy
Hybrid Physics-ML · NASA PI
NOAA FIM Model Bias Correction for Extreme Monsoon Forecasts
Principal Investigator of a NASA-funded project correcting a persistent systematic error in NOAA's FIM model to improve forecasts of extreme South Asian monsoon precipitation — combining tendency-error diagnosis, explainable AI, and generative bias correction.
NASA GMAO Core (2026)CRPS · RMSE · ACC verified
Hazard ScienceDynamical
Monsoon Extremes & Bay of Bengal Tropical Cyclones
A connected research program on flood-producing monsoon rainfall and the environmental drivers of Bay of Bengal cyclones under climate change — including the finding that climate change quadruples flood-causing extreme monsoon events in Bangladesh and Northeast India.
4× extreme events (QJRMS 2024)J. Climate (2023)
Research → Operations
Development & products
Hybrid Physics-ML
Dynamical-AI Kilometer-Scale Downscaling & Reanalysis
Hybrid WRF + diffusion/flow-matching pipelines that downscale MERRA-2/MERRA-21C global reanalysis to 3-km and site-specific wind, solar, moisture, and flood products — supporting NASA fire modeling and a 2025-selected NASA project on downscaled-projection uncertainty.
3-km CONUS reanalysis~1000× faster inference
ML · Generative
Global Probabilistic S2S Flow-Matching Emulator
Dynamical-model-informed stochastic flow matching for global subseasonal forecasting: generates 1,000+ physically realistic ensemble members in seconds for tail-probability and extreme-event analysis, without running a numerical model at inference.
1,000+ members in secondsAIES (submitted)
ML · Foundation Model
AirCast-SR: Atmospheric Super-Resolution
Co-developed a foundation model for kilometer-scale atmospheric super-resolution via latent consistency diffusion — a standalone learned pathway to high-resolution fields when full regional dynamical downscaling is impractical.
arXiv preprint (2026)
Climate Risk · Applied
Multi-Hazard Climate & Catastrophe-Risk Engine
Probabilistic hazard information for tropical cyclones, floods, extreme precipitation, heat, and renewable-energy resources: GEOS/WRF/CMIP ensembles fused with generative scenarios, river-flow and inundation mapping, and geospatial exposure layers for government and commercial insurance and energy partners.
1,000+ climate scenariosDecision-ready risk layers
Software · Education
Open-Source Tools & Workforce Development
AOESpy (Python climate-analysis library), ClimBuntu (a preconfigured Linux environment for climate research), and an open Climate Data Science & Modeling curriculum — used internationally and for mentoring 5+ students and interns.
Used internationally5+ mentees
Publications
2026Fahad, A. A., Molod, A., Wargan, K., Menemenlis, D., Heimbach, P., Trayanov, A., … & Coy, L. Northern Hemisphere stratospheric temperature response to external forcing in decadal climate simulations. Atmospheric Chemistry and Physics, 26(1), 647–663.
2026Menemenlis, D., Molod, A., Hill, C. N., Trayanov, A., Strobach, E., Campin, J. M., … (incl. Fahad, A. A.). The GEOS/ECCO C1440-LLC2160 Coupled Atmosphere-Ocean Simulation Dataset. Scientific Data.
2024Fahad, A. A., et al. Climate Change Quadruples Frequency of Flood-Causing Extreme Monsoon Rainfall Events in Bangladesh and Northeast India.
QJRMS.
doi:10.1002/qj.4645
2023Fahad, A. A., Reale, O., Molod, A., Sany, T. A., Ahammad, M. T., & Menemenlis, D. The Role of Tropical Easterly Jet on the Bay of Bengal's Tropical Cyclones: Observed Climatology and Future Projection.
Journal of Climate, 36, 5825–5840.
doi:10.1175/JCLI-D-22-0804.1
2022Strobach, E., Klein, P., Molod, A.,
Fahad, A. A., Trayanov, A., Menemenlis, D., & Torres, H. Local Air-Sea Interactions at Ocean Mesoscale in Western Boundary Currents.
Geophysical Research Letters, 49.
doi:10.1029/2021GL097003
Preprints & under review
2026Fahad, A. A., & Singh, M. Dynamical-Model-Informed Stochastic Flow Matching for Global Probabilistic Subseasonal Forecasting of Means and Extremes. Artificial Intelligence for the Earth SystemsSubmitted
2026Fahad, A. A., Singh, M., Barahona, D., Darmenov, A., & Molod, A. A Physics-ML Multi-Fidelity Strategy for Earth System Model Parameter Optimization: A QG Proof-of-Concept. Artificial Intelligence for the Earth SystemsSubmitted
2026Fahad, A. A., Molod, A., Menemenlis, D., Zhang, H., & Trayanov, A. Minimizing the Initial Shock: The Mechanics of Dynamically Balanced Coupled Initialization in GEOS-MITgcm Subseasonal-to-Seasonal Forecasts. Journal of ClimateIn review
2026Luitel, S., Singh, M., Durkee, J., Fahad, A. A., et al. AirCast-SR: A Foundation Model for Kilometer-Scale Atmospheric Super-Resolution via Latent Consistency Diffusion. arXiv preprintPreprint
2026Menemenlis, D., Zhang, H., Carroll, D., Fahad, A. A., & Heimbach, P. Coupled Model Optimization Using an Ocean-Only Adjoint. Part I. JAMESSubmitted
2026Molod, A., et al. (incl. Fahad, A. A.). Simulation of the Equilibrium of the GEOS-S2S-3 Coupled Model for Seasonal Prediction. JAMESSubmitted
2026Molod, A., et al. (incl. Fahad, A. A.). GEOS-S2S-3: NASA's Coupled Assimilation and Sub/Seasonal Forecast System. JGR: AtmospheresSubmitted
Earlier peer-reviewed
2023Cramwinckel, M. J., Burls, N.,
Fahad, A. A., Knapp, S., … & Inglis, G. N. Global and Zonal-Mean Hydrological Response to Early Eocene Warmth.
Paleoceanography and Paleoclimatology, 38.
doi:10.1029/2022PA004542
2021Fahad, A. A., Singh, B., Kamal, M., Ahmed, T., Kibria, M., & Chowdhury, N. R. The Role of Local Topography and Sea Surface Temperature on Summer Monsoon Precipitation over Bangladesh and its Surrounding Regions.
International Journal of Climatology.
doi:10.1002/joc.7490
2021Fahad, A. A., & Burls, N. J. The Influence of Direct Radiative Forcing versus Indirect Sea Surface Temperature Warming on Southern Hemisphere Subtropical Anticyclones.
Climate Dynamics.
doi:10.1007/s00382-021-06006-1
2021Fahad, A. A., Burls, N. J., Swenson, E. T., & Straus, D. M. The influence of South Pacific Convergence Zone heating on the South Pacific Subtropical Anticyclone.
Journal of Climate, 34(10), 3787–3798.
doi:10.1175/JCLI-D-20-0509.1
2021Simpson, I. R., McKinnon, K., Davenport, F., Tingley, M., Lehner, F.,
Fahad, A. A., & Chen, D. Emergent constraints on the large scale atmospheric circulation and regional hydroclimate: do they still work in CMIP6?
Journal of Climate.
doi:10.1175/JCLI-D-21-0055.1
2020Fahad, A. A., Burls, N. J., & Strasberg, Z. How will southern hemisphere subtropical anticyclones respond to global warming? Mechanisms and seasonality in CMIP5 and CMIP6 model projections.
Climate Dynamics.
doi:10.1007/s00382-020-05290-7
2019Burls, N. J., Blamey, R. C., Cash, B., Swenson, E. T.,
Fahad, A. A., Bopape, M.-J., Straus, D., & Reason, C. J. C. Cape Town "Day Zero" drought and Hadley Expansion.
npj Climate and Atmospheric Science, 2(1), 27.
doi:10.1038/s41612-019-0084-6
2019Swenson, E. T., Straus, D. M., Snide, C. E., &
Fahad, A. A. The Role of Tropical Heating and Internal Variability in the California Response to the 2015/16 ENSO Event.
Journal of the Atmospheric Sciences.
doi:10.1175/JAS-D-19-0064.1
Leadership
Funded research
PIImproving Forecast Skill of Extreme South Asian Summer Monsoon Precipitation in NASA's Seasonal Prediction System by Correcting a Persistent Systematic Error in Coupled Models. NASA HQ-directed GMAO Core, 2026.
Co-IGlobal Km-Scale Reanalysis for Assessing Uncertainties in Downscaled Climate Projections with Applications to End-Users. NASA ROSES RSIR, selected 2025.
Co-ISatellite perspectives of convective organization in equatorial Pacific coupled feedbacks and atmospheric river genesis. NASA ROSES PMMCCST, selectable 2024.
Co-IIntegrated GEOS and ECCO earth system modeling and data assimilation to advance seasonal-to-decadal prediction. NASA ROSES MAP, selected 2023.
PIThe influence of tropical diabatic heating on subtropical anticyclones and the storm tracks — using NASA products to constrain and correct model bias. GMU College of Science Research Grant, 2020.
Also: Co-Lead, WCRP CMIP7 Data Analysis Young Scientist Group (2023–present) · Peer reviewer for Nature Climate Change, Journal of Climate, Climate Dynamics, Journal of Hydrometeorology, and Weather, Climate, and Society.
Origins
Doctoral research
My Ph.D. (George Mason University, 2020, advised by Dr. Natalie Burls) investigated what controls the strength, seasonality, and future of subtropical anticyclones — the great high-pressure systems over the subtropical oceans that shape rainfall, drought, and marine climate in both hemispheres. Using CESM experiments, CMIP5/6 ensembles, and dynamical diagnostics, I showed how tropical diabatic heating, direct CO₂ radiative forcing, and indirect SST warming each imprint on the anticyclones and the storm tracks — mechanisms that now inform my model bias-correction work at NASA. This program also contributed to the Cape Town "Day Zero" drought study and emergent-constraint assessments of CMIP6 circulation projections.