Francesco Muschitiello
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About
Reconstructing and predicting climate change – from polar ice and the Atlantic overturning to global wildfire – using data, models and machine learning.
Research Area
I am a climate scientist and paleoceanographer studying how –and how fast– the Earth system changes across timescales, from ice ages to the decades ahead. The ocean and cryosphere store most of the climate system’s heat and carbon and hold some of its most dangerous tipping points. My group reconstructs and predicts how the ocean, ice, carbon cycle and climate extremes behave by combining deep-sea and polar archives, satellite and instrumental data, climate-model simulations, and data science (Bayesian inference, machine learning).
Working with partners (Italy’s CNR, Australia’s IMAS, and the British Antarctic Survey) we study the Arctic and Southern Ocean, and Antarctic margins (sea ice, deep-sea circulation, ice sheets), the Atlantic overturning circulation (AMOC) and its approach to tipping, the ocean’s role in regulating atmospheric CO₂, and global wildfire in a warming climate. A central aim is to break the “language barrier” between climate models and observations, developing quantitative tools that test the models we rely on for future projections.
As part of the Cambridge Centre for Climate Repair’s executive team, I also develop physically-informed, Earth-observation methods to quantify carbon removal. Students gain transferable, in-demand skills like scientific computing, machine learning, Bayesian inference, Earth-system modelling, through their research complemented by my EarthLab training network. Fieldwork is also possible.
Project Interests
I seek individuals with strong computing skills interested in addressing global climate problems. Possible directions:
(1) Polar oceans (Arctic & Antarctic) – sea ice, circulation and ice-sheet dynamics, from the last century to past glacial cycles; fieldwork possible.
(2) The Atlantic overturning (AMOC) – reconstructing and predicting its variability; early-warning indicators for tipping under Greenland melt and Arctic sea-ice loss.
(3) Global wildfire – empirical models of burnt area, size and intensity, benchmarked with Earth observations and paleo-records.
(4) Benchmarking climate models against the poorly-observed deep ocean – ML-corrected ocean reanalyses, carbon storage, heat uptake.
(5) Climate repair – quantifying permanence and additionality of nature-based and ocean carbon removal.