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).

Transcript

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
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
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
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!