Oocgcm Save
oocgcm is a python library for the analysis of large gridded geophysical dataset.
oocgcm
Out of core analysis tools for general circulation models in python.
This project provides tools for post-processing and analyzing output of general circulation models (based on the Arakawa C-grid) and gridded satellite data.
Our aim is to simplify the analysis of very large datasets of model output (~1-100Tb) like those produced by basin-to-global scale sub-mesoscale permitting ocean models and ensemble simulations of eddying ocean models by leveraging the potential of xarray and dask python packages.
The project is so far mostly targeting NEMO ocean model and gridded ocean satellite data (AVISO, SST, ocean color...) but we try to build a framework that can be used for other ocean models as well. The framework can also be used for C-grid atmospheric general circulation models.
Installation
git clone https://github.com/lesommer/oocgcm.git
cd oocgcm
python setup.py install
Status
The project is in pre-alpha phase. More information can be found on the project documentation and on the project wiki. Ideas, comments and contributions are welcome !!
Related projects
oocgcm project builds upon past experience with previous projects including :
A number of related projects based on xarray and dask python packages are available in the atmopshere/ocean/climate community. This include in particular:
More can be found on related projects on this discussion thread on xarray forum.
License
Copyright 2016, oocgcm Developers
Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.
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