Dataset Open Access

Dataset for: Wood et al Role of sea surface temperature patterns for the Southern hemisphere jet stream response to CO2 forcing

Wood, Tom; McKenna, Christine; Chrysanthou, Andreas; Maycock, Amanda

This is a dataset of output from version 4 of the Reading Intermediate Global Circulation Model (IGCM4) that was used in the article Wood et al (2020) 'Role of sea surface temperature patterns for the Southern hemisphere jet stream response to CO2 forcing' published in Environmental Research Letters (https://doi.org/10.1088/1748-9326/abce27).

To isolate the role of sea surface temperature (SST) patterns for the Southern Hemisphere circulation response in the abrupt-4xCO2 experiments in CMIP5 and CMIP6, we perform experiments using IGCM4.

Five 120-year long simulations were performed following a 5-year spin-up period. In the control simulation (CTRL) we prescribe an annually repeating cycle of climatological monthly mean SSTs using the multi-model mean (MMM) of the ‘ts’ field for the first 200 years of the CMIP5 piControl simulations. Following the CMIP6 protocol (Eyring et al., 2016), greenhouse gas (CO2, CH4, and N2O) concentrations are set at preindustrial (year 1850) values and ozone is prescribed as a zonally averaged monthly mean preindustrial climatology.

In two perturbation simulations (4xCO2-FULLCMIP5 and 4xCO2-FULLCMIP6) the same boundary conditions are used as in CTRL, but with an annually repeating cycle of climatological monthly mean SST anomalies added using the MMM ‘ts’ field for either the CMIP5 or CMIP6 FAST (years 4-10) responses. In both the 4xCO2-FULLCMIP5 and 4xCO2-FULLCMIP6 simulations CO2 is quadrupled from its preindustrial concentration. This enables a like-for-like comparison with the CMIP5 and CMIP6 abrupt-4xCO2 simulations. Two further perturbation simulations (SHET-onlyCMIP5 and SHET-onlyCMIP6) are used to isolate the effect of differences in SH extratropical SST patterns alone. In both simulations CO2 is kept at preindustrial values, and CTRL SSTs are used with the SST anomalies from either 4xCO2-FULLCMIP5 or 4xCO2-FULLCMIP6 added poleward of 18°S. Similarly to McCrystall et al. (2020), the SST anomalies are smoothed between 18°S and 29°S using a cosine squared weighting function with weights of 0 at 18°S and 1 at 29°S. This minimizes sharp gradients in SST across the tropical-extratropical boundary.

To enable a clean determination of the effects of SST patterns alone, in all perturbation simulations we keep sea ice fixed at preindustrial values by only adding SST anomalies where the MMM sea ice concentration in the CMIP5 piControl simulations is less than 15% (i.e., equatorward of the sea ice edge). Furthermore, to remove the effect of differences in the change in global mean SST, the SST anomalies in each CMIP model are normalised by the respective global mean SST anomaly and then scaled to a global mean value of 2.2 K (the pooled MMM of CMIP5 and CMIP6). The CMIP6 FAST SST anomalies are added to the CMIP5 preindustrial control SSTs, so as to isolate the effect of differences in the fast SST responses between CMIP5 and CMIP6, and not the effect of differences in the base state.

Files (16.3 GB)
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T_IGCM4_4xCO2_FULL_CMIP5_mon_1.nc
md5:0ebc332b969aebc983683cd8bd588665
802.3 MB Download
T_IGCM4_4xCO2_FULL_CMIP5_mon_2.nc
md5:1c9ea6a6268abc4e3b737cc22d063b2a
815.7 MB Download
T_IGCM4_4xCO2_FULL_CMIP6_mon_1.nc
md5:a392c3856b0fdc734fd6393128c39329
802.3 MB Download
T_IGCM4_4xCO2_FULL_CMIP6_mon_2.nc
md5:50d62e1536e45901d1f56a84baf5616d
815.7 MB Download
T_IGCM4_CTRL_mon_1.nc
md5:4b93de6e064fbbbf8736852ba2fbd153
668.6 MB Download
T_IGCM4_CTRL_mon_2.nc
md5:028a7aa520ff4d5f4eaa2fbd408521ce
949.4 MB Download
T_IGCM4_SHET_only_CMIP5_mon_1.nc
md5:b15718902eddde563a40836e794be509
802.3 MB Download
T_IGCM4_SHET_only_CMIP5_mon_2.nc
md5:cd7ac3a91e58ea5b5d1881b1428d0496
815.7 MB Download
T_IGCM4_SHET_only_CMIP6_mon_1.nc
md5:a7ab0d6fe84799306b1deed32c3ae93b
802.3 MB Download
T_IGCM4_SHET_only_CMIP6_mon_2.nc
md5:bdb4c3b85012f625b6c4a8e9ad52e461
815.7 MB Download
Ts_IGCM4_4xCO2_FULL_CMIP5_mon.nc
md5:362d87e0a490dee2c9efa38d0a7ba0f0
47.8 MB Download
Ts_IGCM4_4xCO2_FULL_CMIP6_mon.nc
md5:4695872d15b7ccab5df4ed83c0368122
47.8 MB Download
Ts_IGCM4_CTRL_mon_1.nc
md5:192714f707b0b459d20424ade1fd8a20
19.8 MB Download
Ts_IGCM4_CTRL_mon_2.nc
md5:66bbdbe0ef2c2ac8c9d6fb218754acff
28.1 MB Download
ts_mon_clm_input_for_4xCO2-FULL_CMIP5_IGCM4_experiment_T42.nc
md5:918729a0942546fda9ca30bb16f714a4
811.6 kB Download
ts_mon_clm_input_for_4xCO2-FULL_CMIP6_IGCM4_experiment_T42.nc
md5:00983a6ea848ff7c1b26a2fa3d9b85ef
811.6 kB Download
ts_mon_clm_input_for_CTRL_IGCM4_experiment_T42.nc
md5:8caf5deee72a1eac62974c7a955eb60a
418.4 kB Download
ts_mon_clm_input_for_SHET-only_CMIP5_IGCM4_experiment_T42.nc
md5:bcfd1a5a5e2756180efed10c294a90ac
811.6 kB Download
ts_mon_clm_input_for_SHET-only_CMIP6_IGCM4_experiment_T42.nc
md5:e4e38a1167ac48bdb983133da392316a
811.6 kB Download
U_IGCM4_4xCO2_FULL_CMIP5_mon_1.nc
md5:e12e275930c6febd9a21307248174d29
802.3 MB Download
U_IGCM4_4xCO2_FULL_CMIP5_mon_2.nc
md5:7f5d02ca5adffc507804aefd20f49c75
815.7 MB Download
U_IGCM4_4xCO2_FULL_CMIP6_mon_1.nc
md5:d5f19eaff9c5a980d7b3bb9f3201cc79
802.3 MB Download
U_IGCM4_4xCO2_FULL_CMIP6_mon_2.nc
md5:1e14b13a2c344f3bf2660bd1fdd2ae5a
815.7 MB Download
U_IGCM4_CTRL_mon_1.nc
md5:a76964eac81c8bdd0c31668ca4fdeb1f
668.6 MB Download
U_IGCM4_CTRL_mon_2.nc
md5:1ef5544442cdfaaa87fba53bd3db51e2
949.4 MB Download
U_IGCM4_SHET_only_CMIP5_mon_1.nc
md5:30f92b6d790a860edc62132f68cd32a1
802.3 MB Download
U_IGCM4_SHET_only_CMIP5_mon_2.nc
md5:85ea306e7e9dae8452651e8723fe78fe
815.7 MB Download
U_IGCM4_SHET_only_CMIP6_mon_1.nc
md5:3fea04043cf542bb71d29f9f0bc8053d
802.3 MB Download
U_IGCM4_SHET_only_CMIP6_mon_2.nc
md5:d89086ff98ff66d6fbbf801aa4806188
815.7 MB Download
  • doi:10.5194/gmd-8-1157-2015

  • https://doi.org/10.1088/1748-9326/abce27

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