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Reproducible IPCC Science Using Pangeo Tools in the Cloud

Reproducible IPCC Science Using Pangeo Tools in the Cloud

AMS Annual Meeting 2023

Try it out yourself with the live [demo code](https://github.com/jbusecke/presentation_ams_2023). If you want to find out more check our [working group documentation](https://pangeo-data.github.io/pangeo-cmip6-cloud/)and the [pangeo community](https://pangeo.io).

Julius Busecke

January 10, 2023
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  1. Reproducible IPCC Science Using Pangeo Tools in the Cloud AMS

    2023 | | Julius Busecke
  2. Who am I? Physical Oceanographer Studies the role of ocean

    currents for the climate and ecosystems. Senior Sta ff Associate - Columbia University Manager, Data and Compute - NSF LEAP STC Core-Maintainer of xgcm Core-Maintainer of xMIP Maintainer of the Pangeo CMIP6 data Pangeo Fan, User, and Member
  3. Source: https://www.un.org/en/global-issues/climate-change

  4. None
  5. Observations

  6. Observations Models Models

  7. Observations Models Models Theory 🧑🔬📚🌍 Understanding more about our planet

  8. 8 Credit: NASA's Goddard Space Flight Center

  9. 8 Credit: NASA's Goddard Space Flight Center

  10. 8 Credit: NASA's Goddard Space Flight Center https://earthdata.nasa.gov/eosdis/cloud-evolution SWOT NISAR

  11. Increasing Resolution and Complexity

  12. Climate Science: A global distributed effort

  13. Download Clean and Combine Crunch the data Interpret Results

  14. None
  15. Download Clean and Combine Crunch the data Interpret Results ⏳💸🚫

  16. Download Clean and Combine Crunch the data Interpret Results

  17. Download Clean and Combine Crunch the data Interpret Results

  18. Download Clean and Combine Crunch the data Interpret Results

  19. Download Clean and Combine Crunch the data Interpret Results

  20. Download Clean and Combine Crunch the data Interpret Results ❌

  21. CMIP6 Cloud Dataset • Pangeo partnered with ESGF and Google

    Cloud to provide a new public dataset • > 1 PB and counting • Data stored in Zarr format • Google provides free hosting in GCS • Mirrored on AWS https://pangeo-data.github.io/pangeo-cmip6-cloud/
  22. E ff icient and fast access to arrays in object

    store Easy parallelization -> fast iteration on analysis Flexible scienti f ic data structure Crowd Sourced Cleaning + Combining Your favorite code to analyze/interpret 🎁
  23. https://github.com/jbusecke/present a tion_ a ms_2023 Demo

  24. None
  25. https://medium.com/pangeo/easy-ipcc-part-1-multi- model-datatree-469b87cf9114

  26. Start exploring CMIP6 data now!

  27. If you run into issues with CMIP data please check

    out xMIP!