CM3 Dev-Eval Working group meeting minutes
Date: Tuesday 9 December at 10:30 am
Participants: @cbull, @jemmajeffree, @paocorrales, @RachelLaw, @ctychung, @kieranricardo, @MartinDix, @clairecarouge, @DeepashreeDutta, @Dietmar_Dommenget, @paulleopardi, @lachlanswhyborn, @sofarrell, @zoegillett27, @MATTENGLAND, @ShayneM, @heidi, @ClaireT, @gab563, @HIMADRI_SAINI, @ezhilsabareesh8, @lishx, @JulieA
Chair: @kieranricardo
Minutes: @spencerwong
Coord: @cbull
Agenda:
- shout-out props for Figures from: @Harun_Rashid @DeepashreeDutta @ctychung @DeepashreeDutta
- quick summary of workflow options for contributions: see [here] for instructions for contributing scripts and notebooks to the repository, and reach out if you have any questions!
- summary of the dev-eval meetings (Nov 19, Dec 3)
- community contributions
- offer support (breakout room?) to people wanting to get involved / could set aside 10 minutes at end of meeting to answer questions.
Updates from the last CM3 technical development meeting:
Minutes from the last technical development meeting are available here
- Currently investigating issues with the Arctic sea ice. Both CM3 and OM3’s Arctic sea-ice is ~2x larger than observations and CM2, but the causes may be different. OM3 has an issue with stuck ice, which isn’t as prevalent in CM3. Other possible causes are differences in bottom melt, issues with where the winds are pushing the ice, meltpond differences, and possible CICE stability issues.
- @ezhilsabareesh8’s updates to the bathymetry have successfully resolved the Baltic salinity drift.
- Work going into updating the UM version to 13.8. This will allow for the full set of GC5 central parameter changes to be copied over, which should reduce the radiative imbalance.
- @CharlesTurner’s virtualised dataset significantly speeds up accessing the CM3 atmospheric data. Issues have come up applying this approach to the CM2 runs, and we are currently trying to work around this.
GitHub issue links:
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@ctychung: Monthly mean precipitation and surface temperature
The precipitation maps show that the model still has a double ITCZ bias, though precipitation in the Western Pacific may be slightly better in CM3 than CM2. Surface temperatures show several differences between the two models, especially in the northern hemisphere and over Antarctica.
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@ctychung: ENSO and IOD power spectra
We may need more data for a reliable power spectrum, however the amplitude of the spectrum is much higher for CM2 compared to both CM2 and HadISST. Likewise, Niño3.4 standard deviation is almost twice that from observations.
Using the Planton Matrix was raised as a useful way to compare CM3’s ENSO against other models.
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@DeepashreeDutta: Comparison of cloud radiative effect (CRE) between ACCESS-CM3, ACCESS-CM2, and CERES observations
Zonal mean cloud radiative effects are roughly similar for CM2, CM3 and CERES observations, though CM3 shows some improvements compared to CM2. Maps show similar biases in many areas for both models, though CM3 may perform slightly better for high clouds, with reduced RMS error. CRE also looks better in CM3 compared to ESM1.5/1.6.
It was noted that the total CRE is too negative while the total TOA radiation imbalance is too positive, and improving the CRE alone may worsen the radiation imbalance. Comparison with other CMIP models was raised, and it’s likely that the errors in CM3 are within the range from other models.
GitHub issue links to OM3 figures for CM3:
Community figures
Harun Rashid
@Harun_Rashid
today I’d like to briefly talk about the ENSO power spectrum (slide 4) and the ENSO diagnostics table (slide 5). The table compares various ENSO diagnostics computed from the latest CM3 run with those calculated from observations, ACCESS-CM2 and other CMIP6 model simulations.
These figures also showed a high ENSO amplitude, and the fact that the Niño3.4 peak is higher than the Niño3 peak in the power spectrum suggested that it occurs too far to the west.
The run length is 37 years, with seven years of data missing
The simulation was done in August by Kieran at ACCESS-NRI
Please paste here and include a caption!
Discussion
Timeline for new experiments:
Work is underway to upgrade the UM version to 13.8, incorporate the GC5 Central parameter changed (including cloud tuning), and incorporate changes from the latest release of OM3. The plan is to start a new run in January which includes these changes.
CMORisation
The ad-hoc nature of the current analysis was discussed, and it was noted that this may have to change each time that the model is updated. The long term strategy is to have CMORised output, and to create analysis scripts that work seamlessly across runs and models. Progress is being made, including using CMOR names for OM3 output, however there is still work with the MED team to be done.
