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Josh Lanham

(he/him)

Postdoctoral Researcher in Physical Oceanography

University of Cambridge — Department of Applied Maths and Theoretical Physics

About

I’m a postdoctoral researcher in Climate Science / Physical Oceanography at the University of Cambridge, Department of Applied Maths and Theoretical Physics. My work focuses on Southern Ocean and Atlantic water-mass dynamics, with particular interest in Antarctic Bottom Water, Circumpolar Deep Water, and shelf processes in the Bellingshausen Sea near the Antarctic Peninsula.

I combine observations (GO-SHIP, GLODAP, Argo, autonomous gliders), inverse methods, and machine learning to classify water masses and map their variability. I also work with data-assimilating and high-resolution models (ECCO/MITgcm) to study the processes that enable warm water to access ice shelves. Current projects include classifying Atlantic water masses from OMP-derived fractions, assessing poleward migration of CDW, and producing a global mapped transient tracer product using implicit neural networks.

If you’d like to collaborate, please get in touch. For an up-to-date list of publications, please see my Google Scholar.

Download CV

Education

PhD Physical Oceanography

University of Cambridge, Darwin College

MSc Applied Meteorology

University of Reading

BA Geography (First Class)

University of Oxford, Mansfield College

Research interests

Southern Ocean and Atlantic overturning circulation Antarctic Bottom Water and Circumpolar Deep Water variability Machine-learning classification of ocean water masses Inverse methods and OMP analysis Glider observations and Antarctic shelf processes Ocean–ice interactions and feedbacks near the Antarctic Peninsula

📚 My Research

I study large-scale overturning and water-mass pathways from the Atlantic to the Antarctic margin, with emphasis on:

Southern Ocean water masses: AABW formation/change; CDW variability and southern boundary shifts; shelf processes in the Bellingshausen Sea.
Classification & mapping: Training ensemble machine learning models to apply water-mass labels to Argo and model fields, integrating GO-SHIP/GLODAP/Argo with ECCO and MITgcm. Mapping transient tracer distributions with Neural Networks.
Gliders: Cross-over calibration/QC and workflow tooling for Slocum/Seaglider missions on the Antarctic shelf.

Featured Publications