Root Mean Square Error (RMSE) between observed and modelled patterns of variability.

Tool to compute the RMSE between the observed and modelled patterns of variability obtained through classification and their relative relative bias (percentage) in the frequency of occurrence and the persistence of each mode.

Authors

• Veronica Torralba (BSC, Spain; None)
• Neven Fuckar (BSC, Spain; None)
• Nicola Cortesi (BSC, Spain; https://orcid.org/0000-0002-1442-9225)
• Virginie Guemas (BSC, Spain; https://orcid.org/0000-0002-6340-3558)
• Alasdair Hunter (BSC, Spain; https://orcid.org/0000-0001-8365-3709)
• Nuria Perez-Zanon (BSC, Spain; None)
• Nicolau Manubens (BSC, Spain; https://orcid.org/0000-0002-0114-508X)

Maintainers

• No maintainer available (Unseen University; None)

Projects

• Copernicus Climate Change Service 34a Lot 2 (MAGIC) project

References

• Neven S. Fučkar, Virginie Guemas, Nathaniel C. Johnson, François Massonnet, and Francisco J. Doblas-Reyes. Clusters of interannual sea ice variability in the northern hemisphere. Climate Dynamics, 47(5-6):1527–1543, nov 2015. URL: https://doi.org/10.1007%2Fs00382-015-2917-2, doi:10.1007/s00382-015-2917-2.

Weather_Regime

Compute modes of variability.

Weather Regime: Main

Data files

• Predicted modes of variability | download | references | extra data citation | provenance
• Reference modes of variability | download | references | extra data citation | provenance
• Root Mean Squared Error between reference and future projected patterns | download | references | extra data citation | provenance

Files

main_log.txt | main_log_debug.txt | recipe_modes_of_variability.yml | figures | data