toy model

[aaronspring]

s2dverification, similar to climpred but written in R, has a toy model to test expected behaviour of skill (dependence of number of inits, members) on synthetic data. nice-to-have

References

• Manubens, Nicolau, Louis-Philippe Caron, Alasdair Hunter, Omar Bellprat, Eleftheria Exarchou, Neven S. Fučkar, Javier Garcia-Serrano, et al. “An R Package for Climate Forecast Verification.” Environmental Modelling & Software 103 (May 1, 2018): 29–42. https://doi.org/10/gc9wzk.
• Weigel, A. P., M. A. Liniger, and C. Appenzeller. “Can Multi-Model Combination Really Enhance the Prediction Skill of Probabilistic Ensemble Forecasts?” Quarterly Journal of the Royal Meteorological Society 134, no. 630 (2008): 241–60. https://doi.org/10/bg2hkm.

[bradyrx]

Are you supposed to know exactly what correlations, etc. should come out from it for testing functions? Or is it just a way to generate feasible prediction data to plug into functions? (as opposed to doing np.random.rand for instance).

[aaronspring]

just a way to generate feasible prediction data to plug into functions

[aaronspring]

https://xclim.readthedocs.io/en/latest/notebooks/sdba.html