| 9:00-9:15 |
Ryan Abernathey, Columbia University / LDEO |
Introduction |
| 9:15-9:30 |
Spencer Hill, UCLA & Caltech |
"infinite-diff" and "animal-spharm": xarray-based finite differencing and spherical harmonics |
| 9:30-9:45 |
Spencer Clark, Princeton University |
The other "aospy": automated climate data analysis and management |
| 9:45-10:00 |
Daniel Rothenberg, MIT |
A Pythonic Approach to Simplifying Climate Data Analysis Pipelines |
| 10:00-10:15 |
Phillip Wolfram, Los Alamos National Lab |
Climate analysis at exascale |
| 10:15-10:30 |
Jeremy McGibbon, University of Washington |
Lessons from Model Code |
| 10:30-11:00 |
coffee break |
|
| 11:00-11:15 |
Julien Le Sommer, CNRS |
What data-structures and utilities are needed for leveraging dask and xarray for the analysis ocean model output? |
| 11:15-11:30 |
Guillaume SERAZIN, IRD/LEGOS, Toulouse, France |
Filtering ocean dataset using dask and xarray |
| 11:30-11:45 |
Joy Monteiro, Stockholm University |
Data management à la GOAT |
| 11:45-12:00 |
Joe Hamman, University of Washington & NCAR |
xarray applications in hydroclimatology |
| 12:00-12:15 |
Brian Rose, University at Albany |
Climlab: a Python toolkit for interactive, process-oriented climate modeling |
| 12:15-12:30 |
Kevin Paul, NCAR |
A Brief Survey of Python Efforts & Interests at the National Center for Atmospheric Research |
| 12:30-1:30 |
lunch |
|
| 1:30-1:45 |
Matthew Rocklin, Continuum Analytics |
Dask |
| 1:45-2:00 |
Stephan Hoyer, Google Research |
Developer level APIs for xarray |
| 2:00-3:00 |
group discussion |
|
| 3:00-4:00 |
test drive someone else's package |
|
| 4:00-5:00 |
group discussion |
|