Climate & Ocean Physics

Understanding, Modeling, Predicting

Laure Zanna

Laure Zanna

Professor of Mathematics & Atmosphere/Ocean Science [she/her]

Courant Institute, NYU

+ Center for Data Science (Affiliated)

Overview

Our group aims to advance the fundamental understanding of ocean dynamics and its role in the climate system in order to improve climate change projections. Our team has worked on a wide range of topics including global and regional sea level rise, ocean decadal predictions, the representation of ocean turbulence in climate models, and uncertainty quantification for seasonal predictions. Recently, we have been particularly interested in the role of the ocean dynamics in shaping patterns of ocean heat and carbon storage under climate change, and in the development of physics-aware machine learning models to deepen our understanding of climate processes and their representation in climate models.

[formal bio] Laure Zanna is a Professor in Mathematics & Atmosphere/Ocean Science at the Courant Institute, New York University. Her research focuses on the dynamics of the climate system and the main emphasis of her work is to study the influence of the ocean on local and global scales. Prior to NYU, she was a faculty member at the University of Oxford until 2019, and obtained her PhD in 2009 in Climate Dynamics from Harvard University. She was the recipient of the 2020 Nicholas P. Fofonoff Award from the American Meteorological Society “For exceptional creativity in the development and application of new concepts in ocean and climate dynamics”. She currently serves as an editor for the Journal of Climate.

Interests

  • Ocean Dynamics
  • Climate Change
  • Machine Learning/Data Science
  • Ocean Warming & Sea Level

Education

  • PhD in Climate Dynamics, 2009

    Harvard University

  • MSc in Environmental Sciences, 2003

    Weizmann Institute of Science

  • BSc in Atmospheric Physics, 2001

    Tel Aviv University

Our Team

Researchers

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Abigail Bodner [she/her]

Postdoc [starting Summer 2021]

GFD, Turbulence, Sea Level, Machine Learning

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Arthur Guillaumin [he/him]

Postdoc

Statistics, Machine learning, Physics Applications

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Elizabeth Yankovsky [she/her]

Postdoc

Model parameterization, Turbulence, Mesoscale & submesoscale dynamics

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Emily Newsom [she/her]

Postdoc

Transient climate change, Ocean heat uptake, Global ocean circulation, Atmosphere-ocean dynamics

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Mike Byrne

Marie Curie Fellow

Atmospheric Dynamics

Students

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Andrew Brettin [he/him]

PhD Student

Sea Level, Coastal ocean dynamics, Extreme events

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Aurora Basinski

PhD Student

Tracer distribution, Ocean carbon uptake, Conceptual models

Projects

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Climate Process Team

Climate Process Team

CPT Ocean Transport and Eddy Energy

Climate Variability

Climate Variability

Processes leading to variability

Data Science & Climate

Data Science & Climate

Harnessing Data and Machine Learning

Extreme Events

Extreme Events

Temperature, Ocean Velocities & Sea Level Extremes

Ocean Turbulence

Ocean Turbulence

Understanding and Parameterizing Turbulence

Oceans in Climate Change

Oceans in Climate Change

Understanding the role of ocean dynamics in climate

Predictability

Predictability

Understanding Uncertainty

Probabilistic Climate Predictions

Probabilistic Climate Predictions

Designing Ocean Model Ensembles

Sea Level

Sea Level

Global and Regional Projections

TICTOC

TICTOC

Transient tracer-based Investigation of Circulation and Thermal Ocean Change

UKFAFMIP

UKFAFMIP

Addressing the Grand Challenge of regional sea level change prediction

Contact