A New Generation of Climate Models
<p>As we embark on the third year of <a href="https://m2lines.github.io/" rel="noopener ugc nofollow" target="_blank">M²LInES</a>, we want to share our progress and what comes next.</p>
<p><strong>M²LInES’ mission is to improve coupled climate models by reimagining physics model development through innovative use of data and AI.</strong> We aim to accelerate the pace of climate model development by learning physics from data with scientific machine learning, and ultimately enhance climate model fidelity and reliability for future projections.</p>
<p>As we continue to develop and generalize AI-enhanced models of ocean, sea-ice, and atmospheric processes from data, we can now begin to assess their impact on the large-scale climate in a suite of global model configurations.</p>
<p>Climate models are known to have stubborn biases <em>(model error relative to observations)</em> due to incorrect representations of unresolved physics. We can now demonstrate in <strong>GFDL OM4</strong>, <strong>Global Ocean and Sea Ice Model at 1/4 degree horizontal resolution:</strong></p>
<p><a href="https://medium.com/@lz1955/a-new-generation-of-climate-models-aefd851d47bd">Website</a></p>