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Merge pull request #92 from IamShubhamGupto/master
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‎content/news/2401Pavel.md‎

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date: 2024-01-02T09:29:16+10:00
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title: "Data-driven equation discovery ocean model by Pavel"
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title: "Data-driven equation discovery ocean model"
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heroHeading: ''
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heroSubHeading: 'Data-driven equation discovery ocean model by Pavel'
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heroSubHeading: 'Data-driven equation discovery ocean model'
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thumbnail: 'images/news/2401Pavel.png'
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images: ['images/news/2401Pavel.png']

‎content/news/2402Bhouri.md‎

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date: 2024-02-03T09:29:16+10:00
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title: "Stress-testing the coupled behavior of hybrid physics-machine simulations by Bhouri"
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title: "Stress-testing the coupled behavior of hybrid physics-machine simulations"
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heroHeading: ''
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heroSubHeading: 'Stress-testing the coupled behavior of hybrid physics-machine learning climate simulations on an unseen, warmer climate'
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‎content/news/2404Qu.md‎

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date: 2024-04-02T09:29:16+10:00
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title: "Joint Parameter and Parameterization Inference by Yongquan Qu"
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title: "Joint Parameter and Parameterization Inference"
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heroSubHeading: 'Joint Parameter and Parameterization Inference with Uncertainty Quantification through Differentiable Programming'
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‎content/news/2408Bonan.md‎

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date: 2024-08-03T09:29:16+10:00
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title: "Constraints imply limited future weakening of AMOC"
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heroSubHeading: 'Constraints imply limited future weakening of AMOC'
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thumbnail: 'images/publications/btsz_2024.png'
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images: ['images/publications/btsz_2024.png']
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link: 'https://www.researchsquare.com/article/rs-4456168/v1'
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---
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Climate models show varied predictions for the weakening of the Atlantic meridional overturning circulation (AMOC) this century. Researchers, including **Laure Zanna** and CliMA members, reduced this uncertainty by linking AMOC strength to the meridional density difference and overturning depth. They found that models with a deeper present-day overturning predict greater weakening due to less stratified North Atlantic waters. Using observational data, they estimate a modest AMOC weakening of about 4 Sv by century's end, regardless of emissions. The [study](https://www.researchsquare.com/article/rs-4456168/v1) highlights that inaccuracies in current ocean stratification models lead to exaggerated predictions of AMOC weakening.

‎content/news/2408Gorman.md‎

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date: 2024-08-02T09:29:16+10:00
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title: "Bringing Statistics to Storylines!"
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heroHeading: ''
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heroSubHeading: 'Rare Event Sampling for Sudden, Transient Extreme Events'
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thumbnail: 'images/news/2408Gorman.png'
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images: ['images/news/2408Gorman.png']
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link: 'https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024MS004264'
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Accurately modeling extreme weather events is a major goal in climate science and weather risk management. High-resolution computational models provide precise data but are costly for capturing rare events. This [study](https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2024MS004264) focuses on localized, short-lived events like heavy precipitation. The researchers, including **Paul O’Gorman**, developed a more efficient method for sampling these events by combining adaptive multilevel splitting (AMS) and “ensemble boosting.” The new approach, tested on the Lorenz-96 model, improved the sampling of extreme events by a factor of 10. This method helps efficiently simulate sudden, transient weather extremes, advancing efforts to model these events in atmospheric models.

‎content/news/Newsletters/_index.md‎

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Links to our past newsletters are below.
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### 2024
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* 08/05/2024 - [M²LInES newsletter - August 2024](https://mailchi.mp/673f0ae414a1/m2lines-august2024)
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* 07/22/2024 - [M²LInES newsletter - July 2024](https://mailchi.mp/f28e00f28543/m2lines-july2024)
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* 06/14/2024 - [M²LInES newsletter - June 2024](https://mailchi.mp/d978696aa4f1/m2lines-june-2024)

‎content/publications/_index.md‎

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‎content/team/AlexisBarge.md‎

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promoted: true
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Website:
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tags: [Machine Learning, Climate Model Development, Coupling]
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tags: [Machine Learning, Climate Model Development, Coupled Physics]
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‎content/team/Laure-Zanna.md‎

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Website: https://zanna-researchteam.github.io/
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weight: 1
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tags: ['Ocean', 'Climate', 'Machine Learning']
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tags: ['Ocean', 'Climate Model Development', 'Machine Learning']
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‎static/images/news/2408Gorman.png‎

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