2020-05-06T05:11:09Z (GMT) by
Dataframes for the results of the global and regional regressions under pre-industrial, past, and historical/RCP conditions are stored as data.tables in named lists in a compressed RDS format.
The gridded datasets have been created as NetCDF files. A geopackage containing the aggregated IPCC regions and the Wallace zoogeographic regions and realms can also be found in the ‘gpkg’ folder within StableClim.
The naming convention for the results of the global and regional regressions is:
where scenario is the name of the scenario (piControl, past, spliced historical), and var represent either global and regional regression thresholds for the pre-industrial control simulation, or the slopes for global/regional temperature regressions for the past and historical/RCP data.
The naming convention for the ensemble mean monthly data is:StableClim_MonthlyEnsemble_<scenario>_<var>.nc
and for the regression files:
where scenario is the name of the scenario (past, spliced historical RCP 2.6 – RCP 8.5), and var is pr (precipitation) or ts (air temperature).
The monthly ensemble temperature and precipitation have the following dimensions – 72 x latitude, 144 x longitude, 3012 x months. The units for the monthly ensembles are pr = mm/day, ts = °C.
Each of the regression files contains three record variables: (1) = Trend, (2) = Variability, (3) = Signal:Noise ratio. These record variables have the following dimensions – 72 x latitude, 144 x longitude, and year [20,902 for the past, 251 for the historical/RCP]. Units for the regressions are pr = mm/year, ts = °C/year.
Multi-model median estimates of trend, variability, and SNR are available on request. Regressions on bias corrected datasets for the past and historical/RCP simulations, and files for bias-correcting the multi-model ensemble monthly data can be generated on request.