Abdullah Al Fahad, Ph.D.

My passion lies in working with numerical models and Atmospheric Physics, specifically utilizing programming tools to analyze vast amounts of data and identify patterns. I possess a keen interest in researching large-scale atmospheric circulation, as well as exploring seasonal to decadal variations in large-scale atmospheric properties, and investigating the climate's response to external factors such as anthropogenic and natural sources. In Fall 2020, I graduated with a Ph.D. in Climate Dynamics from George Mason University, and in December 2020, I joined NASA GSFC at the Global Modeling and Assimilation office.

My Current research at NASA includes: Air-Sea-Ice interaction, Climate model development, High resolution climate modeling, Annual to decadal climate prediction. My current project at Goddard focuses on developing and analyzing a novel prototype, property-conserving, ocean-ice-atmosphere model, and data assimilation system based on the Goddard Earth Observing System Model (GEOS) in conjunction with the adjoint-model capabilities of the Massachusetts Institute of Technology general circulation model (MITgcm). The resulting data assimilation system and an inferred solution will be used to study inter-annual to decadal prediction and predictability in the coupled system.

Tools I use/used in my research-

Models: GEOS, MITgcm, CESM, WRF.
Programming Language: Python, MATLAB, R, NCL, GrADS, Latex, C, bash scripting.
Machine Learning: Scikit-learn, Deep Learning, Keras, Tensorflow, RNN (LSTM, GRU), kNN.

Email: afahadabdullah@gmail.com; a.fahad@nasa.gov

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