Monday, Nov 01, 2021 |
| 8:50am |
Lars Bildsten (KITP Director) |
Welcome[Video][CC] |
| 9:00am |
Steven Brunton (U Washington) |
Interpretable and Generalizable Machine Learning for Fluid Dynamics[Slides][Video][CC] |
| 9:45am |
Rose Yu (UC San Diego) |
Physics-Guided Deep Learning for Fluid Dynamics[Slides][Video][CC] |
| 10:30am |
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| 11:00am |
Laure Zanna (NYU) |
Machine Learning for Ocean Closures: Advances and Lessons[Video][CC] |
| 11:45am |
Pedram Hassanzadeh (Rice) |
Data-driven subgrid-scale modeling: Stability, extrapolation, and interpretation[Slides][Video][CC] |
| 12:30pm |
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| 2:00pm |
Jaideep Pathak (LBNL) |
Data-driven and data-assisted modeling for applications in fluid dynamics and geophysics[Video][CC] |
| 2:45pm |
Navid Constantinou (ANU) |
A data-driven approach for developing and calibrating a parameterization of the ocean mesoscale eddy fluxes[Slides][Video][CC] |
| 3:30pm |
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| 4:00pm |
Alistair Adcroft (Princeton) |
Towards using machine learning in real climate models[Slides][Video][CC] |
| 4:45pm |
Aneesh Subramanian (CU Boulder) |
Exploring physical and Machine Learning approaches for stochastic modeling and ensemble prediction of weather and climate[Video][CC] |
| 5:30pm |
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| 6:00pm |
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| 8:00pm |
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Tuesday, Nov 02, 2021 |
| 9:00am |
Gus Camps-Valls (U de València) |
Gaussianizing the Earth[Slides][Video][CC] |
| 9:45am |
Christian Lessig (U Magdeburg) |
Representation learning and custom loss functions for atmospheric data[Slides][Video][CC] |
| 10:30am |
|
| 11:00am |
Jakob Runge (DLR) |
Causal inference for Earth system sciences[Video][CC] |
| 11:45am |
Claire Monteleoni (CU Boulder) |
Deep Unsupervised Learning for Climate Informatics[Slides][Video][CC] |
| 12:30pm |
|
| 2:00pm |
Maike Sonnewald (Princeton) |
Revealing the Impact of Global Heating on the Meridional Overturning Circulation with transparent machine learning[Video][CC] |
| 2:45pm |
Bryan Kaiser (LANL) |
Objective discovery of dominant dynamical regimes[Slides][Video][CC] |
| 3:30pm |
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| 4:00pm |
Dorit Hammerling (Mines) |
Contained Chaos: Ensemble Consistency Testing for the Community Earth System Model[Video][CC] |
| 4:45pm |
Maria Molina (NCAR) |
Deep Learning for Subseasonal Global Precipitation Prediction[Slides][Video][CC] |
| 5:30pm |
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| 6:00pm |
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| 8:00pm |
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Wednesday, Nov 03, 2021 |
| 9:00am |
Elizabeth Barnes (Colorado State) |
Benefits of saying I Don't Know when analyzing and modeling the climate system with ML[Video][CC] |
| 9:45am |
Abigail S Bodner (NYU) |
Relating coastal sea level to its drivers in the interior[Slides][Video][CC] |
| 10:30am |
|
| 11:00am |
Henk Dijkstra (Utrecht U) |
Skillful El Nino prediction beyond predictability barriers[Video][CC] |
| 11:45am |
Duncan Watson-Parris (Oxford) |
Earth System Emulation[Video][CC] |
| 12:30pm |
|
| 2:00pm |
Tapio Schneider (Caltech) |
How to calibrate climate models with diverse data: an example from cloud parameterizations[Video][CC] |
| 2:45pm |
Robert Pincus (LDEO) |
Atmospheric radiation: using machine learning for the unknowable and uncomputable[Slides][Video][CC] |
| 3:30pm |
|
| 4:00pm |
Mike Pritchard (UCI) |
Lessons and outlook for ML parameterization of sub grid atmospheric physics from the vantage of emulating cloud superparameterization[Video][CC] |
| 4:45pm |
Aditi Sheshadri (Stanford) |
A deep learning parameterization of gravity wave drag coupled to an atmospheric global climate model[Video][CC] |
| 5:30pm |
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| 6:00pm |
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| 8:00pm |
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Thursday, Nov 04, 2021 |
| 9:00am |
Amy Mc Govern (Oklahoma) |
Using AI to Facilitate Environmental Justice: The Need for Ethical and Responsible AI for Weather and Climate[Video][CC] |
| 9:45am |
Antoine Blanchard (AIR Worldwide) |
Debiasing coarse-scale climate models using statistically consistent neural networks[Video][CC] |
| 10:30am |
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| 11:00am |
Jacquelyn Shelton
(Hong Kong Polytechnic U) |
Deep learning and energy models for fine dead wood segmentation[Video][CC] |
| 11:45am |
Katie Dagon (NCAR) |
Machine Learning and Earth System Modeling: from parameter calibration to feature detection[Slides][Video][CC] |
| 12:30pm |
|
| 2:00pm |
Donata Giglio (CU Boulder) |
Estimating Oxygen in the Southern Ocean using Argo Temperature and Salinity[Video] |
| 2:45pm |
Annalisa Bracco (Georgia Tech) |
Manifold learning as a tool to link AI/ML and climate dynamics[Slides][Video] |
| 3:30pm |
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