Closed katjaweigel closed 4 years ago
just a very general remark - maybe we should encourage developers (you guys here too) to include the actual physical process(es) that the recipes perform in their names, like here De Angelis makes me think of either the Formula 1 driver (Elio De Angelis) or the champagne (Angeli) :grin: - something for the @ESMValGroup/esmvaltool-developmentteam to debate+decide I reckon
I though we were supposed to name recipes based on the paper? But I was wondering if this is always a good idea, too. Not that much here, since I didn't know Elio De Angelis (sorry!), but the other recipe I'm working on I actually called "recipe_drought_events.yml", although the name following the paper would be "recipe_martin18.yml". But I think "Martin" is really a too frequent name?
Recipe reproducing (part of) the analysis of a given paper are named like the paper itself. I think we should not change this now that our papers are about to be finalized.
In the future, we might think about grouping the recipes by topics in subdirectories. I think there is already an issue with such suggestion or something along this line.
cool, makes sense then, but at least the diagnostics the recipes execute should have phenomenological names - it would be very useful to change these abstract paper-motivated recipe names once the paper gets published :beer:
apologies for trying to reinvent the wheel here - do we also have a list of recipes each diagnostic is run by? Ie in the diagnostic script itself, in its docstring
Short description of the diagnostic Recipe: recipe_deangelis15nat.yml Diagnostics: deangelis15nat/deangelisf1b.py deangelis15nat/deangelisf2ext.py deangelis15nat/deangelisf3f4.py
Reproducing figure 1b, 2, 3, 4 and extended data figure 1 and 2 from DeAngelis et al. (2015).
DeAngelis, A. M., Qu, X., Zelinka, M. D., and Hall, A.: An observational radiative constraint on hydrologic cycle intensification, Nature, 528, 249, 2015. This paper compares models with different schemes for water vapor short wave absorption with the observations. Schemes using pseudo-k-distributions with more than 20 exponential terms show the best results.
Branch and pull request Draft pull request #1576