"Dask and the ocean death zones" - Lessons from a real life earth science workflow with a ‘fullish’ pangeo stack

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Julius Busecke \\ Columbia University Dask and the ocean death zones Lessons from a real life earth science work f low with a ‘fullish’ pangeo stack

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Oxygen Minimum Zones (OMZs) in the global ocean

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GROWING OXYGEN MINIMUM ZONES IMPACT BOTH LOCAL ECOSYSTEMS AND THE GLOBAL CLIMATE

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The OMZ expands into the thermocline Preprint Link Busecke et al., submitted to AGU Advances Thermocline Intermediate Waters Deep

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The OMZ expands into the thermocline Preprint Link Busecke et al., submitted to AGU Advances Thermocline Intermediate Waters Deep

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Density Framework • Dynamically consistent vertical coordinates are key! Depth Depth Coordinates Density Coordinates Potential Density

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Density Framework • Dynamically consistent vertical coordinates are key! • xgcm handles this task very e ff iciently. 🙏 numba + dask + xarray Depth Depth Coordinates Density Coordinates Potential Density

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Wait, this was not complicated!

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The full stack work f low Transform into density coordinates

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The full stack work f low Model output Clean up naming/metadata etc Remove Control Run Drift Combine variables Interpolate Grids Calculate additional variables (potential density, apparent oxygen utilization, etc.) Remove mixed layer + bottom values Add/recalculate grid metrics Transform into density coordinates

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Model output Clean up naming/metadata etc Remove Control Run Drift Add/recalculate grid metrics The full stack work f low

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Model output Clean up naming/metadata etc Remove Control Run Drift Add/recalculate grid metrics The full stack work f low

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Model output Clean up naming/metadata etc Remove Control Run Drift Add/recalculate grid metrics The full stack work f low

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Combine variables Calculate additional variables (potential density, apparent oxygen utilization, etc.) Remove mixed layer + bottom values Interpolate Grids Credit: Raphael Dussin The full stack work f low

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Combine variables Calculate additional variables (potential density, apparent oxygen utilization, etc.) Remove mixed layer + bottom values Interpolate Grids Mixed Layer Masked Full data The full stack work f low

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Combine variables Calculate additional variables (potential density, apparent oxygen utilization, etc.) Remove mixed layer + bottom values Interpolate Grids The full stack work f low

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.compute()

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.compute()

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.compute()

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.compute() In the end I had to write out small time steps in a for loop 😭. Not pretty but it worked 😬

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What have I learned?

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You are all awesome!

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HPC Cloud Laptop

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😍 HPC Cloud Laptop

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Dont combine datasets if you don’t have to!

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Persistent Pain Points Maybe not “embarrassingly” parallel, but it “should still work”. Not able to pin down a single step in the pipeline that provokes failure. Its usually just the “whole thing” that fails. Using dask vs understanding dask. Can the transition be easier for xarray daskers?

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Going Forward

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Lets get more science work f lows in the cloud! Going Forward

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Lets get more science work f lows in the cloud! • Use-cases for complex dask work f lows Going Forward

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Lets get more science work f lows in the cloud! • Use-cases for complex dask work f lows • Awesome for reproducible science. Going Forward

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Lets get more science work f lows in the cloud! • Use-cases for complex dask work f lows • Awesome for reproducible science. • Need: Derived data products in the cloud. Going Forward

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Interested in more of the science? Check out our preprint! Interested in working with CMIP6 data? PANGEO-CMIP6 Questions? Comments? Feedback? Let me know! @JuliusBusecke jbusecke julius@ldeo.columbia.edu