Modeling centers around the world are now
releasing data from simulations with the next generation of climate models, the
Coupled Model Intercomparison Project Phase 6 (CMIP6). For three days in
October, thirty UW climate science graduate students and postdocs got together to
see what they could learn about future climate change from these new
simulations. We combined efforts with CMIP6 hackathons at two other institutes,
the National Center for Atmospheric Research (NCAR) in Boulder, Colorado and
the Lamont-Doherty Earth Observatory in Palisades, New York. It was a test in
working together remotely, which is increasingly a focus for climate scientists
trying to limit their CO2 emissions from travel.
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UW climate scientists analyzing climate model data in Python. |
Besides studying the new climate
projections, an overarching goal was for all participants to use a common set
of Python tools for accessing and analyzing the CMIP6 data. These tools allow
users to quickly access and analyze CMIP6 data on cloud storage, without
downloading all of the data themselves. This facilitates reuse of analysis code
across projects and makes the resulting science more reproducible. In
particular, we worked with xarray, a Python package for working with labeled multi-dimensional
datasets, dask, a Python package for parallelizing
analysis, and intake-esm, a Python package developed by Pangeo to
streamline access to CMIP6 data that is stored on NCAR’s supercomputer and on the
Pangeo Cloud Data Catalog. Pangeo is a community promoting open, reproducible, and scalable
science that also develops some Python software.
Highlights from the UW group include a public-facing
web tool for visualizing local CMIP6 climate projections, an investigation of
how much of Southern Ocean surface waters are sinking into the deep ocean in
different CMIP6 models and how this affects climate, an analysis of how well
CMIP6 models can simulate observed Pacific Ocean temperature changes over the
last 50 years, an investigation of projected changes in the position of the
Gulf Stream, and an investigation of projected changes in Antarctic sea ice. While
these projects, as expected, were not completed after just 3 days, there is now
momentum amongst the participants to continue working on them, to continue
learning Python, and to work towards making our science more open and
reproducible.
Public code repositories for the Hackathon
projects can be found on Github:
Anyone interested in trying out these CMIP6 analysis tools
for themselves can access the Pangeo hackathon
template on which these projects are based or contact me for more information.
The UW CMIP6 Hackathon was made possible
by funding from the University of Washington Program on Climate Change and the
Department of Atmospheric Sciences, as well as by support from the NCAR
and Lamont CMIP6 Hackathons,
which were funded by US CLIVAR, Ocean Carbon & Biogeochemistry, the
National Science Foundation, NASA, and the National Ocean and Atmospheric
Administration Modeling, Analysis, Predictions and Projections Program.
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