SoftwareApplication
identifier: 10.5281/zenodo.1051093
name: ece2cmor3
description: Process EC-Earth output to publish for CMIP6
description: * Process EC-Earth climate model output to CMIP6-compliant NetCDF files * Create EC-Earth output configurations from CMIP6 data requests * Explore what variables can be produced with EC-Earth * Support for atmosphere, ocean, land and chemistry sub-models * Parallel execution of cdo commands processing the atmospheric GRIB files ece2cmor3 is a python package that allows climate scientists to post-process raw EC-Earth climate model output to CMIP6-compliant, annotated NetCDF4 files with a few simple python scripts. The software is easily installed on your local HPC facility using Anaconda and makes efficiently use of multi-core machines by executing the post-processing in a parallel queue over variables (for the atmospheric data). Furthermore, ece2cmor3 contains various helper scripts to configure the EC-Earth namelists and extract EC-Earth-supported variables from a given data request.
code repository: https://github.com/EC-Earth/ece2cmor3
author: https://orcid.org/0000-0001-8367-1333
author: https://orcid.org/0000-0002-9983-6195
keywords: Optimized data handling
keywords: High performance computing
keywords: Big data
programming language: Jinja
programming language: Python
programming language: Shell
license:
  creative work: creativeWork
    name: Apache-2.0
reference publication: j.procs.2017.05.146
reference publication: escience.2018.00121

https://orcid.org/0000-0001-8367-1333
type: Person
given name: Gijs
family name: van den Oord
name: Gijs van den Oord
affiliation: Organization
  name: Netherlands eScience Center

https://orcid.org/0000-0002-9983-6195
type: Person
given name: Thomas
family name: Reerink
name: Thomas Reerink
affiliation: Organization
  name: Koninklijk Nederlands Meteorologisch Instituut

j.procs.2017.05.146
type: ScholarlyArticle
name: Parallel Post-Processing of the Earth Climate Model Output
pagination: 2473-2477
url: https://doi.org/10.1016%2Fj.procs.2017.05.146

escience.2018.00121
type: ScholarlyArticle
name: Post-Processing Strategies for the ECMWF Model
pagination: 401-401
url: https://doi.org/10.1109%2Fescience.2018.00121