Climate Scientist at NASA GSFC · Dynamical Physics × Generative AI

“Big whorls have little whorls, which feed on their velocity.
And little whorls have lesser whorls, and so on to viscosity.”
— Lewis Fry Richardson

Abdullah Al Fahad, Ph.D.

Climate Scientist · NASA Goddard Space Flight Center, Global Modeling and Assimilation Office

About

I build forecasting systems where dynamical physics meets generative AI. At NASA GSFC's Global Modeling and Assimilation Office, I co-develop the GEOS-MITgcm coupled atmosphere–ocean model and combine it with PyTorch diffusion and flow-matching models for coupled Earth-system prediction. As Principal Investigator of a NASA-funded project, I pair AI with physics to diagnose, correct, and improve forecast skill from weather, subseasonal-to-seasonal, and decadal timescales.

I earned my Ph.D. in Climate Dynamics from George Mason University in 2020. My research spans coupled model development and adjoint data assimilation, kilometer-scale "Nature Run" simulations for satellite observing-system experiments, and generative machine learning for downscaling, bias correction, and probabilistic ensembles — turning physics into decision-ready products for extreme weather and climate risk.

That work runs end to end, from model development to forecasts people can act on. Weather2Grid is a live experimental forecast that converts official, numerical, and AI weather guidance into calibrated county-level power-outage risk for emergency managers, with the meteorological and impact-model uncertainty reported separately. SURMA-Flow assimilates rain-gauge and satellite observations through a score-guided rectified-flow model to produce BRISHTI-05, a 30-member daily 5-km precipitation reanalysis over Bangladesh. Alongside them sit a global flow-matching ensemble emulator, kilometer-scale hybrid downscaling, and multi-hazard catastrophe-risk layers used by government agencies and commercial insurance and energy partners.

Skills

Models & NWP

GEOS / MITgcmWRFCESMGFS & ECMWFCMIP5/6/7Ensemble & downscaling

Data Assimilation & Optimization

Adjoint methodsCoupled initializationOSSEsGreen's functionsBayesian / GP optimization

Machine Learning & AI

PyTorch (CUDA)DiffusionFlow matchingSuper-resolutionGraphCast / GNNsBias correction & XAI

Geospatial & Data

Xarray / DaskGDAL / RasterioQGIS / ArcGISNetCDF / GRIB / ZarrSatellite & radar

Programming & HPC

PythonFortran (MPI)SQLMATLAB / RAWSLinux HPC & GPUDocker / Git