Our projects

LEAP - Learning the Earth with Artificial Intelligence and Physics

Learning the Earth with Artificial Intelligence and Physics (LEAP) is an NSF Science and Technology Center (STC) launched in 2021.

Oct 24, 2021

M²LInES - Multiscale Machine Learning In Coupled Earth System Modeling

M²LInES is a large international collaborative project with the goal of improving climate projections, using scientific and interpretable Machine Learning to capture unaccounted physical processes at the air-sea-ice interface.

Jan 24, 2021

M²LInES - Multiscale Machine Learning In Coupled Earth System Modeling

CPT - Ocean Transport and Eddy Energy

The Climate Process Team (CPT) aims to implement, assess, improve, and unify recent work on energetically-consistent ocean eddy momentum and tracer parametrizations in ocean-only and coupled climate models to improve model fidelity.

Dec 31, 2020

CPT - Ocean Transport and Eddy Energy

Climate Variability

In addition to its role played in heat and carbon uptake, the large-scale ocean circulation in the Atlantic is an important driver of European climate variability on interannual and decadal timescales.

Nov 30, 2020

Data Science & Climate

We work on data-driven methods to undertand and predict climate. The tools we use range from probabilistic models informed by data to machine learning algorithms (e.g., neural networks). Some of our data-driven work include:

Nov 30, 2020

Data Science & Climate

We observe and predict a range of extremes events in precipitation, sea level, and air or ocean temperatures. Some of these events are rare but are of large amplitudes. Sampling their statistics and undertanding their dynamical drivers are important for climate detection, attribution and adaption.

Nov 30, 2020

Mentoring + DEI Activities

Selected programs that we participate in and might be of interest to our community NYU CDS Undergraduate Research Program (CURP) in partnership with the National Society of Black Physicists (NSBP); Unlearning Racism in Geoscience (URGE); Mentoring Physical Oceanography Women to Increase Retention (MPOWIR); NYU Proud to be First.

Nov 30, 2020

Ocean Turbulence

Ocean mesoscale eddies strongly affect the strength and variability of ocean jets such as the Gulf Stream. The spatial scales of eddies are too small to be resolved in climate models and hence their effects on the large-scale circulation need to be parametrized.

Nov 30, 2020

Oceans in Climate Change

The oceans are a major sink of heat and carbon, able to delay climate change. The role of ocean heat uptake remains central in quantifying both the magnitude and timescale of the local and global climate response to forcing.

Nov 30, 2020

Oceans in Climate Change

Climate projections are subject to three sources of uncertainties: initial condition, model and scenario. Our research is concerned with the first two kinds of errors. Specifically, how do the lack of ocean observations, the chaotic nature of the climate system and the poor representation of subgrid turbulent processes impact predictions on intra-seasonal to centennial timescales.

Nov 30, 2020

Predictability