How To Use CMIP6 Data
CMIP6 data takes some getting used to. There are a lot of concepts to learn before being able to truly put it into action. That’s ok! We’re going to orient you so you don’t feel lost, and then we’re going to set you on a path towards being a climate science superstar at your company.
In short, CMIP6 is the output of thousands of runs of supercomputer simulations at dozens of labs around the world. These simulations start in, say, the year 1850 and then simulate clouds and oceans and carbon cycles and industrial output under different sets of assumptions running all the way forward to, say, the year 2100. As they go along, they output the values of dozens of variables, like near-surface temperature, or rate of precipitation, or ice thickness, or snow coverage, all separately for every square on Earth they’re simulating.
The complete output of all these models is simply too large to deal with, and is often only the kind of data actual climate scientists care about anyway (e.g. “cfadLidarsr532” for “CALIPSO Scattering Ratio”, anyone?). So, we’ve captured a much smaller subset of data that mere mortals can interpret and we’ve made it available right here, in Snowflake.
Take a pick from the sections below to get started. If you don’t know what to pick, just start at the beginning and work your way down. It reads like an adventure novel, we promise.
- What is CMIP6, anyway?
- What actual variables do you have available?
- What's the fast track to getting started?
- What are the actual tables?
- Dealing with geographies
- Ok, show me some example queries
- There are some caveats to the data you should definitely be aware of
Interested? Please email us at info@pollen.io to get started.
