Data

StableClim

Adelaide University
Brown, Stuart C. ; Wigley, Tom M.L. ; Otto-Bliesner, Bette L ; Fordham, Damien
Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]
ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25909/5ea59831121bc&rft.title=StableClim&rft.identifier=10.25909/5ea59831121bc&rft.publisher=The University of Adelaide&rft.description=StableClim V1.0.1Dataframes 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:StableClim__.RDSwhere 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__.ncand for the regression files:StableClim_Regression__.ncwhere 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.Change log:2020-08-04 - Updated to StableClim v 1.0.1 - Climate change thresholds had been incorrectly calculated during bootstrapping. The thresholds have now been bootstrapped correctly and updated as appropriate.- CSV files for global and regional regressions are now also provided in a gzip archive [GlobalRegionalThresholdsRegressions.tar.gz].- An R tutorial is now provided [StableClim-Tutorial.pdf] which shows how to extract, subset, plot, and calculate pattern scaled trends from the data contained in StableClim.&rft.creator=Brown, Stuart C. &rft.creator=Wigley, Tom M.L. &rft.creator=Otto-Bliesner, Bette L &rft.creator=Fordham, Damien &rft.edition=2&rft_rights= https://creativecommons.org/licenses/by/4.0/&rft_subject=Palaeoclimatology&rft_subject=Ecological impacts of climate change and ecological adaptation&rft_subject=StableClim&rft_subject=TraCE-21ka&rft_subject=RCP&rft_subject=CMIP5&rft_subject=climate change&rft_subject=Ecological Impacts of Climate Change&rft.type=dataset&rft.language=English Access the data
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Full description

StableClim V1.0.1

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:
StableClim_<scenario>_<var>.RDS
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:
StableClim_Regression_<scenario>_<var>.nc
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.


Change log:
2020-08-04 - Updated to StableClim v 1.0.1
- Climate change thresholds had been incorrectly calculated during bootstrapping. The thresholds have now been bootstrapped correctly and updated as appropriate.
- CSV files for global and regional regressions are now also provided in a gzip archive [GlobalRegionalThresholdsRegressions.tar.gz].
- An R tutorial is now provided [StableClim-Tutorial.pdf] which shows how to extract, subset, plot, and calculate pattern scaled trends from the data contained in StableClim.

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Subjects
CMIP5 | Ecological Impacts of Climate Change | Ecological impacts of climate change and ecological adaptation | Palaeoclimatology | RCP | StableClim | TraCE-21ka | climate change |

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Identifiers
ACN 633 798 857