Merge pull request #105 from johannag126/master

add Feb news

Author: johannag126

content/news/.DS_Store

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+---
+date: 2025-02-04T09:29:16+10:00
+title: "Learning Machine Learning with Lorenz-96"
+heroHeading: ''
+heroSubHeading: 'Learning Machine Learning with Lorenz-96'
+heroBackground: ''
+thumbnail:  'images/news/Jupyterbook-session.jpg'
+images: ['images/news/Jupyterbook-session.jpg']
+link: 'https://m2lines.github.io/L96_demo/intro.html'
+---
+Photo (credit: Will Chapman):  students at the Future Earth Research School on data driven modeling using the M²LInES book for their group project!
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+The M²LInES team is proud to share this **[article](https://doi.org/10.21105/jose.00241)** and **[Jupyter Book](https://m2lines.github.io/L96_demo/intro.html)** published in the Journal of Open Science Education (JOSE) and led by Dhruv Balwada. Developed by our team, it aims to introduce Machine Learning (ML) methods to climate scientists and also climate modeling to machine learning experts. The book presents **a wide range of ML applications for climate modeling, focusing on hybrid AI+Physics methods using the Lorenz-96 model**. We hope this book can be used as a pedagogical tool for self-learning, a reference manual, or for teaching modules in an introductory class on ML or hybrid climate modeling.
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content/news/2502Jupyterbook.md

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+---
+date: 2025-02-04T09:29:16+10:00
+title: "Youtube channel to learn data science with M²LInES Carlos Fernandez Granda"
+heroHeading: ''
+heroSubHeading: 'Youtube channel to learn data science with M²LInES Carlos Fernandez Granda'
+heroBackground: ''
+thumbnail:  'images/news/2502YTCarlos.png'
+images: ['images/news/2502YTCarlos.png']
+link: 'https://www.youtube.com/@cfgranda/playlists'
+---
+If you are looking for clear material to understand statistics, probabilities, and mathematical tools for data science, check out the **[Youtube Channel](https://www.youtube.com/@cfgranda/playlists)** of Carlos Fernandez-Granda where he shares recordings of his lectures at NYU!

content/news/2502YTCarlos.md

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+---
+date: 2025-02-04T09:29:16+10:00
+title: "New study addressing artifacts near coastlines caused by out-of-sample predictions"
+heroHeading: ''
+heroSubHeading: 'New study addressing artifacts near coastlines caused by out-of-sample predictions'
+heroBackground: ''
+thumbnail:  'images/news/2502Zhangetal.png'
+images: ['images/news/2502Zhangetal.png']
+link: 'https://doi.org/10.48550/arXiv.2411.01138'
+---
+This [study](https://doi.org/10.48550/arXiv.2411.01138), led by Cheng Zhang, improves machine-learned models for simulating ocean mesoscale eddies **by addressing artifacts near coastlines caused by out-of-sample predictions using convolutional neural networks (CNN)**. Comparing two different strategies for treating Boundary Conditions (BCs) in CNN models - zero and replicate padding - they show that replicate padding significantly reduces these artifacts, enhancing the accuracy and stability of ocean modeling near complex coastal regions.

content/news/2502Zhang.md

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  Links to our past newsletters are below.
 ### 2025
+* 02/04/2025 - [M²LInES newsletter - February 2025](https://mailchi.mp/382387c99943/m2lines-feb2025-2)
 
 * 01/02/2025 - [M²LInES newsletter - January 2025 - Happy new year!](https://mailchi.mp/9d6e3eddad27/m2lines-jan2025)