For a fuller description of the paper itself, go to the end of this web page.

Each simulation published in this paper corresponds to a unique 5 or 6 character code on the web pages.

The following table lists the name of the simulation as used in the paper, and the corresponding code name

The webpage gives you the ability to examine the published simulations, but you can also download the raw (netcdf) files to perform your own analysis. Detailed instructions on how to use the webpages and access the data can be found here: Using_BRIDGE_webpages.pdf

You can have make you own analysis and plots by going here

Simulation Name as in Paper | Simulation name on web pages |
---|---|

PI_1 | xnvea |

PI_2 | xnveb |

PI_3 | xnvec |

PI_4 | xnved |

PI_5 | xnvee |

PI_6 | xnvef |

PI_7 | xnveg |

PI_8 | xnveh |

PI_9 | xnvei |

PI_10 | xnvej |

PI_11 | xnvek |

PI_12 | xnvel |

PI_13 | xnvem |

PI_14 | xnven |

PI_15 | xnveo |

PI_16 | xnvep |

PI_17 | xnveq |

PI_18 | xnver |

PI_19 | xnves |

PI_20 | xnvet |

PI_21 | xnveu |

PI_22 | xnvev |

PI_23 | xnvew |

PI_24 | xnvex |

PI_25 | xnvey |

PI_26 | xnvez |

PI_27 | xnveA |

PI_28 | xnveB |

PI_29 | xnveC |

PI_30 | xnveD |

PI_31 | xnveE |

PI_32 | xnveF |

PI_33 | xnveG |

PI_34 | xnveH |

PI_35 | xnveI |

PI_36 | xnveJ |

PI_37 | xnveK |

PI_38 | xnveL |

PI_39 | xnveM |

PI_40 | xnveN |

PI_41 | xnveO |

PI_42 | xnveP |

PI_43 | xnveQ |

PI_44 | xnveR |

PI_45 | xnveS |

PI_46 | xnveT |

PI_47 | xnveU |

PI_48 | xnveV |

PI_49 | xnveW |

PI_50 | xnveX |

PI_51 | xnveY |

PI_52 | xnveZ |

PI_53 | xnve0 |

PI_54 | xnve1 |

PI_55 | xnve2 |

PI_56 | xnve3 |

PI_57 | xnve4 |

PI_58 | xnve5 |

PI_59 | xnve6 |

PI_60 | xnve7 |

PI_61 | xnve8 |

PI_62 | xnvfa |

PI_63 | xnvfb |

PI_64 | xnvfc |

PI_65 | xnvfd |

PI_66 | xnvfe |

PI_67 | xnvff |

PI_68 | xnvfg |

PI_69 | xnvfh |

PI_70 | xnvfi |

PI_71 | xnvfj |

PI_72 | xnvfk |

PI_73 | xnvfl |

PI_74 | xnvfm |

PI_75 | xnvfn |

PI_76 | xnvfo |

PI_77 | xnvfp |

PI_78 | xnvfq |

PI_79 | xnvfr |

PI_80 | xnvfs |

PI_81 | xnvft |

PI_82 | xnvfu |

PI_83 | xnvfv |

PI_84 | xnvfw |

PI_85 | xnvfx |

PI_86 | xnvfy |

PI_87 | xnvfz |

PI_88 | xnvfA |

PI_89 | xnvfB |

PI_90 | xnvfC |

PI_91 | xnvfD |

PI_92 | xnvfE |

PI_93 | xnvfF |

PI_94 | xnvfG |

PI_95 | xnvfH |

PI_96 | xnvfI |

PI_97 | xnvfJ |

PI_98 | xnvfK |

PI_99 | xnvfL |

PI_100 | xnvfM |

PI_101 | xnvfN |

PI_102 | xnvfO |

PI_103 | xnvfP |

PI_104 | xnvfQ |

PI_105 | xnvfR |

PI_106 | xnvfS |

PI_107 | xnvfT |

PI_108 | xnvfU |

PI_109 | xnvfV |

PI_110 | xnvfW |

PI_111 | xnvfX |

PI_112 | xnvfY |

PI_113 | xnvfZ |

PI_114 | xnvf0 |

PI_115 | xnvf1 |

PI_116 | xnvf2 |

PI_117 | xnvf3 |

PI_118 | xnvf4 |

PI_119 | xnvf5 |

PI_120 | xnvf6 |

PI_121 | xnvf7 |

PI_122 | xnvga |

PI_123 | xnvgb |

PI_124 | xnvgc |

PI_125 | xnvgd |

PI_126 | xnvge |

PI_127 | xnvgf |

PI_128 | xnvgg |

PI_129 | xnvgh |

PI_130 | xnvgi |

PI_131 | xnvgj |

PI_132 | xnvgk |

PI_133 | xnvgl |

PI_134 | xnvgm |

PI_135 | xnvgn |

PI_136 | xnvgo |

PI_137 | xnvgp |

PI_138 | xnvgq |

PI_139 | xnvgr |

PI_140 | xnvgs |

PI_141 | xnvgt |

PI_142 | xnvgu |

PI_143 | xnvgv |

PI_144 | xnvgw |

PI_145 | xnvgx |

PI_146 | xnvgy |

PI_147 | xnvgz |

PI_148 | xnvgA |

PI_149 | xnvgB |

PI_150 | xnvgC |

This archive contains the climatologies of 150 member perturbed parameter ensemble of pre-industrial, mid-Holocene and 2xCO2 simulations with a modified version of HadAM3.

Name | Hopcroft et al |
---|---|

Brief Description | This archive contains the climatologies of 150 member perturbed parameter ensemble of pre-industrial, mid-Holocene and 2xCO2 simulations with a modified version of HadAM3. |

Full Author List | Peter O. Hopcroft and Paul J. Valdes and William Ingram |

Title | Using the mid-Holocene greening of the Sahara to narrow acceptable ranges on climate model parameters |

Year | 2021 |

Journal | Geophysical Research Letters |

Volume | 48(6) |

Issue | |

Pages | e2020GL092043 |

DOI | 10.1029/2020GL092043 |

Contact's Name | Peter O. Hopcroft |

Contact's email | p.hopcroft@bham.ac.uk |

Abstract | During the early to mid-Holocene vegetation expanded to cover much of the present-day Sahara. Although driven by the different orbital configuration, general circulation models have largely failed to simulate the required rainfall increase. One possible explanation is the presence of systematic biases in the representation of atmospheric convection that could also impact future projections. We employ a Bayesian method to learn from an ensemble of present day and mid-Holocene simulations that vary parameters in the convection, boundary layer and cloud schemes. We show that the 'Green' Sahara rainfall can be \peter{reproduced} by %increasing convective mixing in the upper troposphere and reducing it near the surface, increasing mixing between convective plumes and the environment in the upper troposphere relative to lower down, introducing a new approach to this long-standing discrepancy. This does not appreciably impact the present day simulation but it alters the precipitation response to elevated CO2. Developing parameterisation schemes using only historical observations is necessary, but we show that palaeoclimate changes can provide powerful additional constraints for model improvement. |