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Python package associated with running the SalishSeaCast NEMO and other ocean models in near-real-time to produce daily nowcasts/forecasts

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Salish Sea NEMO Model Nowcast

License:Apache License, Version 2.0
Licensed under the Apache License, Version 2.0 Python Version Git on GitHub pre-commit The uncompromising Python code formatter Documentation Status Sphinx linkcheck pytest and test coverage analysis Codecov Testing Coverage Report CodeQL analysis Issue Tracker

The SalishSeaNowcast package is a collection of Python modules associated with running the Salish Sea NEMO model in a daily nowcast/forecast mode. The runs use as-recent-as-available (typically previous day) forcing data for the western boundary sea surface height and the Fraser River flow, and atmospheric forcing from the four-times-daily produced forecast results from the Environment Canada High Resolution Deterministic Prediction System (HRDPS) operational GEM 2.5km resolution model.

The runs are automated using an asynchronous, message-based architecture that:

  • obtains the forcing datasets from web services
  • pre-processes the forcing datasets into the formats expected by NEMO
  • uploads the forcing dataset files to the HPC or cloud-computing facility where the run will be executed
  • executes the run
  • downloads the results
  • prepares a collection of plots from the run results for monitoring purposes
  • publishes the plots and the processing log to the web

Documentation for the package is in the docs/ directory and is rendered at https://salishsea-nowcast.readthedocs.io/en/latest/.

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Licensed under the Apache License, Version 2.0

The Salish Sea NEMO model nowcast system code and documentation are copyright 2013-2021 by the Salish Sea MEOPAR Project Contributors and The University of British Columbia.

They are licensed under the Apache License, Version 2.0. http://www.apache.org/licenses/LICENSE-2.0 Please see the LICENSE file for details of the license.

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Python package associated with running the SalishSeaCast NEMO and other ocean models in near-real-time to produce daily nowcasts/forecasts

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