ECMWF | Reading | 28-29 November 2017
Workshop description
Python has become increasingly popular in processing environmental data, including the handling of weather forecast, climate and oceanographic data. In recent years the Python eco-system has greatly improved its handling of large multi-dimensional data with the development of Pandas, Xarray and links to machine learning frameworks. Jupyter notebooks are now a popular interface for scientists to exchange their work in Python.
ECMWF invited developers of Python frameworks in the field of environment data to a two day workshop. The workshop assessed the current status of Python packages around the world through presentations of developments. Participants were able to join discussions on how interoperability between different packages can be achieved and how efforts between different developments can be harmonised.
Presentations
| Setting the scene Baudoin Raoult (ECMWF) |
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| xarray: N-D labeled arrays and datasets in Python Stephan Hoyer (Google Research) |
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| Python based Data Science on Cray platforms Rob Vesse (Cray Inc) |
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| Python in the Copernicus Climate Change Service context Cedric Bergeron (ECMWF) |
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| Metview and Python - what they can do for each other Iain Russell (ECMWF) |
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| A common data model approach to NetCDF and GRIB data harmonisation Alessandro Amici (B-Open) |
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| MetPy: Community-driven Meteorological Analysis Tools in Python Ryan May (University Corporation for Atmospheric Research / Unidata) |
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| MetWork, an open source meteorological framework to build our projects of tomorrow Fabien Marty (Météo-France) |
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| EPyGrAM: A Python package to handle meteorological fields from various formats Alexandre Mary (Météo-France) |
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| SciTools: our history in a nutshell Bill Little and Philip Elson (Met Office) |
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| CliMAF (Climate Model Assessment Framework) Jérôme Servonnat (LSCE – IPSL) |
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| ESMValTool and PRIMAVERA: making climate metrics available for everyone Javier Vegas-Regidor (Barcelona Supercomputing Center) |
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| Birdhouse: Tools to support Web Processing Services in Climate Science Carsten Ehbrecht (DKRZ) |
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| The Community Intercomparison Suite (CIS): an open-source toolbox Duncan Watson-Parris (University of Oxford) |
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| Pytroll: Open Source, Community Driven Earth Observation Data Processing in Python Martin Raspaud (SMHI) |
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| Operational satellite image generation with Pytroll Panu Lahtinen (FMI) |
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| Unifying verification through a Python-wrapped Suite of Tools Tara Jensen (NCAR) |
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Leif Denby (University of Leeds) |
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| Working Groups Conclusions | |