Dataset Open Access

Data used to create figures in the ACP Letters manuscipt "The value of remote marine aerosol measurements for constraining radiative forcing uncertainty" by Regayre et al. (2020)

Leighton Regayre

This dataset was created from perturbed parameter ensembles (PPEs) using the HadGEM-UKCA atmospheric composition climate model. All data needed to reproduce figures in the Regayre et al. (2020) ACP Letters article "The value of remote marine aerosol measurements for constraining radiative forcing uncertainty" are included. Other output from the PPEs can be obtained by contacting the lead author.

The following data are included here:

  • CCN measurement data degraded to match the model-measurement comparison resolution.
  • Unconstrained and constrained CCN0.2 output from the PPE used to make Figure 1. These compressed files contain 48 .dat files. Each .dat file contains the PPE mean, variance and 95% creidble interval data. Files are named consecutively, containing data from 90oS to 90oN at 0oE, then continuing Eastward. When combined, these files provide data for each latitude/longitude pair at the N48 spatial resolution.
  • A zip file of an netcdf file containing 26-dimensional data for parameter values, used to create the sample of 1 million model variants from our statistical emulators of model output.
  • A zip file containing a folder of files made of one million ones and zeros that indicate the retention/rejection criteria from applying our constraint methodology for various constraint combination scenarios, for each model variant. A value of 1 indicates the model variant was retained. Data in these files is in the same order as the unconstrained sample file of parameter values.
  • Compressed files containing global, annual mean RFaci and ERFaci values for the unconstrained set of one million model variants. The compressed netcdf files contain RF (ERF), RFaci (ERFaci) and RFari (ERFari) values.
Files (294.3 MB)
Name Size
CCN0p2_ppe_constrained_apr.zip
md5:ea830156516562132c69230ed53f90f6
267.5 kB Download
CCN0p2_ppe_constrained_dec.zip
md5:d10c1967c8bd8e1ff4c239e49c0680cb
267.5 kB Download
CCN0p2_ppe_constrained_feb.zip
md5:a79243a56177887f93b45a185382db61
268.0 kB Download
CCN0p2_ppe_constrained_jan.zip
md5:a996a65934ff43da66787959807aa4e1
267.8 kB Download
CCN0p2_ppe_constrained_mar.zip
md5:1b287aec6b545d06a34b49ecb5bdd05b
268.0 kB Download
CCN0p2_ppe_unconstrained_apr.zip
md5:59b006f49f51ae5e6e9c76fa3ecd08ae
264.6 kB Download
CCN0p2_ppe_unconstrained_dec.zip
md5:9d042053d0bea90824a7025857092c2e
531.2 kB Download
CCN0p2_ppe_unconstrained_feb.zip
md5:13a7b355d879c43751b0c711ec09a71b
532.3 kB Download
CCN0p2_ppe_unconstrained_jan.zip
md5:10ad759ea46cdcbd899f7dc19e22f68e
530.5 kB Download
CCN0p2_ppe_unconstrained_mar.zip
md5:1db885376452d7530bcdabb4fc674294
532.4 kB Download
Degraded_CCN_data_ACESPACE.dat
md5:c314c4ac89db2fb0da70627d80ba9628
15.5 kB Download
Global_annual_mean_unconstrained_ERF_data.zip
md5:3d25a52da6da903c67303e53be93ded0
49.9 MB Download
Global_annual_mean_unconstrained_RF_data.zip
md5:639c0851bd12baaeb0fdfd51e5ff8992
42.6 MB Download
million_model_variant_sample_parameter_values.zip
md5:f4d5ec23a7589beafeac287ad1ffbca9
197.4 MB Download
Retain_reject_criteria_from_applying_constraints.zip
md5:1c63d2e6dea68df7b20e615a15431ce0
659.5 kB Download
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