july retro add

Author: IamShubhamGupto

content/news/2407Gentine.md

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+---
+date: 2024-07-02T09:29:16+10:00
+title: "Sampling Hybrid Climate Simulation at Scale"
+heroHeading: ''
+heroSubHeading: 'Sampling Hybrid Climate Simulation at Scale to Reliably Improve Machine Learning Parameterization'
+heroBackground: ''
+thumbnail:  'images/news/2407Gentine.png'
+images: ['images/news/2407Gentine.png']
+link: 'https://doi.org/10.22541/essoar.172072688.86581349/v1'
+---
+
+Machine-learning (ML) models could enhance climate simulations by accurately representing small-scale processes like turbulence and convection. However, it's unclear if better standalone (offline) performance leads to better integrated (online) performance in climate models. In this preprint, researchers, including **Pierre Gentine**, conducted extensive experiments with 2,970 hybrid simulations, finding that reducing offline error generally improves online accuracy, but some decisions can destabilize the model. Key improvements include incorporating memory, training on diverse climates, converting moisture input to relative humidity, and avoiding certain error metrics. This study answers crucial questions about ML design for parameterizations in climate modeling, paving the way for more reliable and efficient simulations.

content/news/2407Reichl.md

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+---
+date: 2024-07-01T09:29:16+10:00
+title: "Improved Equatorial Upper Ocean Vertical Mixing"
+heroHeading: ''
+heroSubHeading: 'Improved Equatorial Upper Ocean Vertical Mixing in the NOAA/GFDL OM4 Model'
+heroBackground: ''
+thumbnail:  'images/news/2407Reichl.png'
+images: ['images/news/2407Reichl.png']
+link: 'https://doi.org/10.22541/essoar.170785794.47537760/v1'
+---
+
+Deficiencies in how upper ocean mixing is modeled cause biases in climate simulations, affecting ocean heat uptake and ENSO predictions. To address this, researchers evaluated different mixing models, To address this, researchers evaluated different mixing models, in this [study](https://doi.org/10.22541/essoar.170785794.47537760/v1) led by **Brandon Reichl**, using detailed simulations and applied improvements to NOAA/GFDL's OM4 ocean model. Enhancements to the model's mixing were informed by observational data and led to more accurate diurnal mixing, ocean currents, and upper ocean temperature profiles. The improved model better represents tropical ocean dynamics, leading to more accurate climate predictions. **Alistair Adcroft** also contributed to the research.