Ancillary Information on refD1 Forcings
The required forcings, largely following datasets produced for the historical period of CMIP6 up to 2014 and then SSP2-4.5 for 2015 – 2018, are detailed in the refD1 experimental description. Here, a bit of additional information is provided on particular datasets that deviate from the standard CMIP6 recommendations.
Near-surface methane concentration
A slightly modified time series for the near-surface methane mixing ratio has been recommended for refD1 over the period 2015 – 2018. This data has been created by scaling the original SSP2-4.5 methane data by a globally constant scaling factor to bring the year-to-year changes in methane in line with more recent observations given in the annual WMO GHG bulletin and the NOAA/ESRL Global Monitoring Laboratory Atmospheric Greenhouse Gas Index. A comparison of the global average CO2, CH4 and N2O near-surface concentrations from the different Tier 1 and 2 CMIP6 SSPs against these observations for 2012 – 2019, can be found here.
The netCDF file of annual average, global and hemispheric mean methane near-surface concentrations for 2015 – 2019 is available here. Monthly global and hemispheric means are available here. While monthly means with 15° latitude bands can be found here and monthly means with 0.5° latitude resolution are here.
The python script that was used to modify the original v1.2.1 SSP 2-4.5 methane data files can be found here.
Ozone Depleting Substances
The WMO-2018 scenario of global-average near-surface mixing ratios was based on observations up to the beginning of 2017, with projected values used for subsequent years. To more accurately reflect the recent behaviour of different ODSs, flask network observations from NOAA ESRL were used to extend the WMO-2018 time series for 2017 – 2018 for CFC-11, CFC-12, CCl4, HCFC-22 and CH3Cl. For convenience, the original WMO-2018 time series was also extrapolated backwards from 1955 to 1949. A comparison of the original WMO-2018 baseline scenario and the revised time series for the REF-D1 simulation can be found here, and the python script that was used to revise the WMO-2018 time series can be found here.
Quasi-Biennial Oscillation
The time series of equatorial zonal winds to be used for introducing, or constraining, a QBO for the historical hindcast simulations has been extended from the dataset produced for CCMI-1. The python script that was used to extend the dataset using the Singapore winds from FUB can be found here, and plots of the CCMI-1 and the extended time series can be found here.
Ancillary information for the scenario forcings
Quasi-Biennial Oscillation
For modelling groups that do not internally generate a QBO, we ask that zonal winds in the QBO domain are relaxed towards a prescribed timeseries of monthly average zonal winds for the entire 1960 – 2100 period. A figure detailing the construction of the extended timeseries from observations and the full timeseries can be found here. A compressed tar file (.tgz) of the input files and programs to produce the extended QBO timeseries can be found here.