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@tennlee tennlee commented Jun 7, 2025

This is work in progress to advance data pipelines which help to translate between weather timescales and climate timescales. Climate timescales are seemingly modelling typically at monthy duration, using a 360-day calendar which is new for me. ERA5 is a re-analysis product available (at high resolutions) at hourly resolution. The challenge is to work out how to relate these data sets and capture that in a pipeline. The existing tutorial on working with climate data approaches this but provides and incomplete solution with respect to presenting samples to an ML pipeline.

The work thus far enhances some of the pipeline code needed to do this. However, we need to add an aggregation process to the temporal retrieval which is used when accessing the ERA5 data.

I am putting the work in progress up as a pull request and will pose the question to some of the other collaborators as to how best to progress from here.



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name = "pyearthtools-models"
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This isn't relevant to this PR and was an accidental include

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tennlee commented Jun 7, 2025

@jennan @millerjoel I'd be interested in your take on this one, it's not clear exactly what to do next. I might take another run at it tomorrow. Do you have some CMIP5 data on hand to set up the same data archive and look at the problem together?

@nikeethr nikeethr marked this pull request as draft June 10, 2025 02:25
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