This PR implements a set of benchmarking recipes for comparison of different metrics (RMSE, bias, correlation, EMD) calculated for a given model simulation to the results from an ensemble of (model) datasets:
Documentation for the benchmarking recipes is available in [recipes/recipe_benchmarking.rst](), the documentation for monitoring and model evaluation have been updated to include the diurnal cycle plots.
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Description
This PR implements a set of benchmarking recipes for comparison of different metrics (RMSE, bias, correlation, EMD) calculated for a given model simulation to the results from an ensemble of (model) datasets:
For this, the existing monitoring diagnostics monitoring/monitor.py and monitor/multi_datasets.py have been extended.
The new diurnal cycle plot has also been added to the following existing recipes:
Documentation for the benchmarking recipes is available in [recipes/recipe_benchmarking.rst](), the documentation for monitoring and model evaluation have been updated to include the diurnal cycle plots.
Note for testing
The benchmarking recipes require the new preprocessor functions local_solar_time and distance_metric and the extended version of preprocessor resample_hours.
Checklist
It is the responsibility of the author to make sure the pull request is ready to review. The icons indicate whether the item will be subject to the 🛠 Technical or 🧪 Scientific review.
New or updated recipe/diagnostic