Metadata-Version: 2.1
Name: forecast-clarify
Version: 0.1.1
Summary: Local sea surface temperature weekly forecasts based on local statistics (seasonal cycle, week-to-week persistence) and coarse-resolution dynamical forecasts
Home-page: https://github.com/olewu/forecast_clarify
Author: Climate Futures, Clarify
Author-email: owul@norceresearch.no, odd.gunnar@clarify.io
License: MIT
Classifier: Development Status :: 5 - Production/Stable
Classifier: Topic :: Scientific/Engineering
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: License :: OSI Approved :: MIT License
Requires-Python: >=3.6
Description-Content-Type: text/markdown
License-File: LICENSE.txt
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: requests
Requires-Dist: xarray
Requires-Dist: scikit-learn (==1.1.2)

forecast_clarify
==============================
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Local water temperature (3m) weekly forecasts based on local statistics (seasonal cycle, week-to-week persistence) from NorKyst800 (2006 - 2022).

Forecasts can be created for all [BarentsWatch Sites](https://www.barentswatch.no/). Model parameters at these sights are derived from the closest grid points in the high-resolution ocean model ROMS, run in the NorKyst800 set-up (described in [Asplin et al., 2020](https://link.springer.com/article/10.1007/s10236-020-01378-0)).

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<p><small>Project based on the <a target="_blank" href="https://github.com/jbusecke/cookiecutter-science-project">cookiecutter science project template</a>.</small></p>
