JULIUS BUSECKE* SEP 24 CMIP6 IN THE CLOUD: A PROTOTYPE TO BREAK BARRIERS AND ACCELERATE COLLABORATION *THANKS TO MY COLLABORATORS, ESPECIALLY CHARLES STERN!

WHO AM I? M²LInES jbusecke juliusbusecke.com @JuliusBusecke @[email protected] @codeandcurrents.bsky.social 🌊 Climate Scientist Ocean transport of Heat, Carbon Oxygen Impact of small scale processes on global climate variability. 🤓Developer/Data Nerd Pangeo CMIP6 Cloud Data xMIP/xGCM 🤝 Open Science Advocate Manager for Data and Computation - NSF- LEAP Lead of Open Research - m2lines

No content

https://edition.cnn.com/ https://www.wsj.com

By running large numerical simulations of the planet! HOW DO WE KNOW WHAT WILL HAPPEN?

"THE INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE (IPCC) IS THE UNITED NATIONS BODY FOR ASSESSING THE SCIENCE RELATED TO CLIMATE CHANGE." WWW.IPCC.CH/

"THE INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE (IPCC) IS THE UNITED NATIONS BODY FOR ASSESSING THE SCIENCE RELATED TO CLIMATE CHANGE." WWW.IPCC.CH/

"THE INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE (IPCC) IS THE UNITED NATIONS BODY FOR ASSESSING THE SCIENCE RELATED TO CLIMATE CHANGE." WWW.IPCC.CH/ Comparing Simulations to observations

"THE INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE (IPCC) IS THE UNITED NATIONS BODY FOR ASSESSING THE SCIENCE RELATED TO CLIMATE CHANGE." WWW.IPCC.CH/ Comparing Simulations to observations Future Predictions

"THE INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE (IPCC) IS THE UNITED NATIONS BODY FOR ASSESSING THE SCIENCE RELATED TO CLIMATE CHANGE." WWW.IPCC.CH/ Comparing Simulations to observations Future Predictions Emission Scenarios

"THE INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE (IPCC) IS THE UNITED NATIONS BODY FOR ASSESSING THE SCIENCE RELATED TO CLIMATE CHANGE." WWW.IPCC.CH/ Comparing Simulations to observations Future Predictions Emission Scenarios Model Spread (Uncertainty)

COUPLED MODEL INTERCOMPARISON PROJECT The objective of CMIP is to better understand past, present and future climate changes arising from natural, unforced variability or in response to changes in radiative forcing in a multi-model context. [...] 1000s of individual simulations - 20PB data More use-cases and opportunities to explore

- Many 100.000s of individual datasets - Each dataset is identi fi ed by a unique id, consisting of 'facets' - Facets are part of CMIP controlled vocabulary (https://wcrp-cmip.github.io/CMIP6_CVs/) CMIP DATA https://wcrp-cmip.org/cmip-data-access/#access-routes CMIP Cycle MIP activity Modelling Center Model Code Experiment/forcing scenarios Ensemble member Output Variable Model Grid CMIP6.ScenarioMIP.NOAA-GFDL.GFDL-CM4.ssp585.r1i1p1f1.Omon.thetao.gn mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version di ff erent simulations components of a single simulation example MIP table used

- Many 100.000s of individual datasets - Each dataset is identi fi ed by a unique id, consisting of 'facets' - Facets are part of CMIP controlled vocabulary (https://wcrp- cmip.github.io/CMIP6_CVs/) - Variable names are standardized using the CMOR (https:// cmor.llnl.gov/) library. CMIP DATA https://wcrp-cmip.org/cmip-data-access/#access-routes CMIP Cycle MIP activity Modelling Center Model Code Experiment/forcing scenarios Ensemble member Output Variable Model Grid CMIP6.ScenarioMIP.NOAA-GFDL.GFDL-CM4.ssp585.r1i1p1f1.Omon.thetao.gn mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version di ff erent simulations components of a single simulation example MIP table used https://wcrp-cmip.org/map/#map_of_modelling_centres_and_esgf_nodes

- Many 100.000s of individual datasets - Each dataset is identi fi ed by a unique id, consisting of 'facets' - Facets are part of CMIP controlled vocabulary (https://wcrp- cmip.github.io/CMIP6_CVs/) - Variable names are standardized using the CMOR (https:// cmor.llnl.gov/) library. CMIP DATA https://wcrp-cmip.org/cmip-data-access/#access-routes CMIP Cycle MIP activity Modelling Center Model Code Experiment/forcing scenarios Ensemble member Output Variable Model Grid CMIP6.ScenarioMIP.NOAA-GFDL.GFDL-CM4.ssp585.r1i1p1f1.Omon.thetao.gn mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version di ff erent simulations components of a single simulation example MIP table used https://wcrp-cmip.org/map/#map_of_modelling_centres_and_esgf_nodes

CMIP DATA https://wcrp-cmip.org/cmip-data-access/#access-routes CMIP Cycle MIP activity Modelling Center Model Code Experiment/forcing scenarios Ensemble member Output Variable Model Grid CMIP6.ScenarioMIP.NOAA-GFDL.GFDL-CM4.ssp585.r1i1p1f1.Omon.thetao.gn mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version di ff erent simulations components of a single simulation example MIP table used

CMIP DATA https://wcrp-cmip.org/cmip-data-access/#access-routes CMIP Cycle MIP activity Modelling Center Model Code Experiment/forcing scenarios Ensemble member Output Variable Model Grid CMIP6.ScenarioMIP.NOAA-GFDL.GFDL-CM4.ssp585.r1i1p1f1.Omon.thetao.gn mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version di ff erent simulations components of a single simulation example MIP table used Hingray and Saïd 2014

CMIP DATA https://expearth.uib.no/?page_id=28 CMIP Cycle MIP activity Modelling Center Model Code Experiment/forcing scenarios Ensemble member Output Variable Model Grid CMIP6.ScenarioMIP.NOAA-GFDL.GFDL-CM4.ssp585.r1i1p1f1.Omon.thetao.gn mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version di ff erent simulations components of a single simulation example MIP table used - Variable names are standardized using the CMOR (https://cmor.llnl.gov/) library.

- Data is distributed via the Earth System Grid Federation (ESGF) - Federation of public sector data centers hosting CMIP data (and more) on their servers. - Licensed, public, free - Data nodes serve netcdf fi les primarily to download. ESGF

- Reality: Large institutions create mirrors of parts of the archive, restricted to employees (data fortresses) - Large overhead, requires both expertise, time and funds - Individual access/data cleaning approaches might be incompatible, hindering reusability/reproducibility - E ff ectively limits conducting climate science to large legacy orgs CMIP DATA: CHALLENGES ESGF Custom Code Custom Code Custom Code University Lab Industry ❌ ✋🚫

ANALYSIS-READY CLOUD-OPTIMIZED (ARCO) DATA

ANALYSIS-READY CLOUD-OPTIMIZED (ARCO) DATA Analysis-Ready: • Think in “Datasets/ Datacubes” not “ fi les” and "folders" • Rich Metadata Cloud Optimized: Chunked appropriately for analysis Rich metadata Everything in one dataset object

ANALYSIS-READY CLOUD-OPTIMIZED (ARCO) DATA Analysis-Ready: • Think in “Datasets/ Datacubes” not “ fi les” and "folders" • Rich Metadata Cloud Optimized: • E ffi cient cloud native access • Integration with data science and ML ecosystem

CMIP6 CLOUD DATA ESGF Ingestion Pipeline A single data repository in the cloud serves all use cases Everybody rolls their own Custom Code Custom Code Custom Code University Lab Industry ❌ ✋🚫 Storage Provided by Google as Public Dataset

CMIP6 CLOUD DATA A single data repository in the cloud serves all use cases Collaborative and agile Research Inclusive Education on real climate data Fast Iteration - Lower Barrier of Entry Portable Methods and Results not just for Academia

CMIP6 CLOUD DATA A single data repository in the cloud serves all use cases Collaborative and agile Research Inclusive Education on real climate data Portable Methods and Results not just for Academia Fast Iteration - Lower Barrier of Entry

CMIP6 CLOUD DATA A single data repository in the cloud serves all use cases Collaborative and agile Research Portable Methods and Results not just for Academia Inclusive Education on real climate data Fast Iteration - Lower Barrier of Entry

CMIP6 CLOUD DATA A single data repository in the cloud serves all use cases Portable Methods and Results not just for Academia Collaborative and agile Research Inclusive Education on real climate data Fast Iteration - Lower Barrier of Entry

CMIP6 CLOUD DATA A single data repository in the cloud serves all use cases Collaborative and agile Research Inclusive Education on real climate data Fast Iteration - Lower Barrier of Entry Portable Methods and Results not just for Academia

DEMO

DEMO

DEMO

MORE INFO? I ❤ QUESTIONS jbusecke juliusbusecke.com @JuliusBusecke @[email protected] @codeandcurrents.bsky.social https://github.com/leap-stc/cmip6-leap-feedstock https://pangeo-data.github.io/pangeo-cmip6-cloud/