Center for Atmosphere-Ocean Science
The Center for Atmosphere Ocean Science is a unit of the Department of Mathematics, within the Courant Institute of Mathematical Sciences at New York University. A cornerstone of the Center is our PhD in Atmosphere Ocean Science and Mathematics, a companion to the department’s PhD in Mathematics.
News & Research
Centennial response of Greenland’s three largest outlet glaciersJan. 5, 2021
David Holland and colleagues have used historical photographs to extend the climate record of ice loss in Greenland back beyond the modern satellite era to almost a century and a half ago. The study significantly improves the temporal resolution of ice loss during that period showing a complex multi decadal pattern of increased and lessened loss rates. Read More
Heat and carbon coupling reveals ocean warming due to circulation changesSept. 23, 2020
Laure Zanna and Ben Bronselaer developed a new method to analyze the global uptake of heat and carbon in the ocean. Their results show that ocean warming patterns will increasingly be influenced by simple uptake of atmospheric warming, making them easier to predict. This is in contrast to the past 60 years, over which time circulation changes have been viewed as key factors in shaping ocean warming patterns. Read More
Statistical forecasting of the El Nino Southern OscillationFeb. 25, 2020
CAOS researchers Xinyang Wang and Dimitris Giannakis in collaboration with Joanna Slawinska of University of Wisconsin-Milwaukee have developed a data-driven technique for statistical forecasting of the El Nino Southern Oscillation (ENSO), based on a combination of kernel methods for machine learning with techniques from operator-theoretic ergodic theory. Read More
Untangling waves and vortices from limited observationsFeb. 6, 2020
CAOS researchers H. Wang and O.Bühler have developed a numerically robust algorithm to decompose the 1-D energy spectra obtained from ship/aircraft data sets. This work is featured in Focus on Fluids by Journal of Fluid Mechanics. Read More
Predicting fluids flows from Lagrangian drifter observationsOct. 30, 2019
Courant researchers M. A. Mohamad and A. J. Majda studied how Lagrangian observations can be used to recover Eulerian properties of a fluid flow using data assimilation techniques. They show how exact and approximate algorithms, which combine observations with a model, can be used to predict Eulerian properties of the flow field.
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