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StableClim

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DataCite Commons2025-12-16 更新2025-04-16 收录
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https://adelaide.figshare.com/articles/dataset/StableClim/12197976/2
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<b>StableClim V1.0.1</b><br><br>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.<br>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.<br>The naming convention for the results of the global and regional regressions is:<br>StableClim_&lt;<i>scenario</i>&gt;_&lt;<i>var</i>&gt;.RDS<br>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.<br><br>The naming convention for the ensemble mean monthly data is:StableClim_MonthlyEnsemble_&lt;<i>scenario</i>&gt;_&lt;<i>var</i>&gt;.nc<br>and for the regression files:<br>StableClim_Regression_&lt;<i>scenario</i>&gt;_&lt;<i>var</i>&gt;.nc<br>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).<br>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. <br><br>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.<br><br><b>Change log:</b><br><i>2020-08-04 - Updated to StableClim v 1.0.1</i> <br>- Climate change thresholds had been incorrectly calculated during bootstrapping. The thresholds have now been bootstrapped correctly and updated as appropriate.<br>- CSV files for global and regional regressions are now also provided in a gzip archive [<i>GlobalRegionalThresholdsRegressions.tar.gz</i>].<br>- An R tutorial is now provided [<i>StableClim-Tutorial.pdf</i>] which shows how to extract, subset, plot, and calculate pattern scaled trends from the data contained in StableClim.<br><br>
提供机构:
The University of Adelaide
创建时间:
2020-04-26
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