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Xgcm (https://xgcm.readthedocs.io/en/latest/) and xmitgcm (https://xmitgcm.readthedocs.io/en/latest/) provide good tutorials on this matter of post-processing the outputs in Python.
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<div>Best,</div>
<div>Takaya<br>
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<div>On Nov 25, 2024, at 8:38 AM, 박주룡 <itts9904@snu.ac.kr> wrote:</div>
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Dear MITgcm Team,</div>
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I hope this email finds you well.</div>
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While exploring tools for my research and studies, I came across the MITgcm code, and I am truly impressed by its capabilities and the effort that has gone into its development. I am eager to learn more about it and apply it to my work.</div>
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I recently ran the <code style="box-sizing: initial; margin: 0px; padding: 0px; border: 0px; vertical-align: baseline; text-decoration-skip-ink: none; font-size: inherit; font-family: monospace;">tutorial_global_oce_latlon</code> example from the verification
cases, and it seems to have executed successfully, producing the expected output files. However, I would like to request guidance on how to proceed with post-processing these results.</div>
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Specifically, I am interested in visualizing fields such as velocity using Python and <code style="box-sizing: initial; margin: 0px; padding: 0px; border: 0px; vertical-align: baseline; text-decoration-skip-ink: none; font-size: inherit; font-family: monospace;">MITgcmutils</code>.
Could you kindly provide any example scripts or references that could help me get started with this type of analysis?</div>
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Your assistance would be greatly appreciated as I work to better understand and utilize the output data from MITgcm simulations.</div>
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Thank you for your time and support. I look forward to your response.</div>
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Best regards,</div>
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<strong id="nameOrg" style="font-size: 13px; letter-spacing: -1px;">박주룡</strong><span id="nameEng" style="font-size: 11px;"> JURYONG PARK</span><br>
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