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SMURPHS: Historical HadGEM3-GC3.1 scaled aerosol coupled ensemble

Latest Data Update: 2020-05-12
Status: Ongoing
Online Status: ONLINE
Publication State: Published
Publication Date: 2020-10-23
Download Stats: last 12 months
Dataset Size: 873 Files | 2TB


This dataset consists of 5x5 historical simulations (1850-2014) with HadGEM3-GC3.1 (Met Office Hadley Centre Global Coupled model General Circulation 3.1). This is an ensemble dataset, part of the Securing Multidisciplinary UndeRstanding and Prediction of Hiatus and Surge events (SMURPHS) project. The model version used here is a development version of the UK's submission to Coupled Model Intercomparison Project Phase 6 (CMIP6) and differs from the CMIP6 version in its treatment of prescribed ozone. This ensemble was designed to sample a range in plausible historical aerosol forcing, with the present-day aerosol effective radiative forcing ranging from -0.38 W/m2 to -1.5 W/m2, which spans a large range of the total aerosol effective radiative forcing presented in Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5).

The targeted aerosol forcings were achieved by applying a constant scaling factor in space and time to the standard historical CMIP6 historical AA and precursor emissions, namely organic and black carbon (fossil and biofuel) and sulfur dioxide (SO2) emissions. All other forcing agents follow historical CMIP6 emissions. The scalings were chosen such that the targeted aerosol forcings are approximately equally spaced:
- 0.2x scaling to give -0.38 W/m2
- 0.4x scaling to give -0.60 W/m2
- 0.7x scaling to give -0.93 W/m2
- 1.0x scaling to give -1.17 W/m2
- 1.5x scaling to give -1.50 W/m2.

The scalings required to reach the intended forcing values were determined from 5 10-year atmosphere-only time-slice runs for the year 2014 with pre-industrial sea-surface temperatures. Note that the 1x scaling is not strictly a ‘scaling’ but corresponds to the standard emissions. The configuration for the scaled aerosol simulations was derived from the 1x scaling simulations, therefore these are directly comparable with the only difference being the scaled aerosol emissions. Five simulations were performed for each scaling and the simulations cover the period 1850-2014. The same five initial conditions were used for each scaling sub-ensemble, and the first four correspond to the initial conditions selected for the four CMIP6 historical simulations. These were well spaced in a pre-industrial control simulation and sample different phases of internal variability in both the Pacific and Atlantic. We recommend only analysing data from 1900, as introducing the scaled aerosols in 1850 produces a small initial drift in the climate system. We estimate that most of this drift has been removed by 1900.

The reference paper for this dataset is Dittus et al., 2020. Please cite this paper when using the dataset. Dittus, A. J., Hawkins, E., Wilcox, L. J., Sutton, R. T., Smith, C. J., Andrews, M. B. and P. M. Forster, 2020: Sensitivity of historical climate simulations to uncertain aerosol forcing. In press, Geophysical Research Letters

Citable as:  Dittus, A.; Andrews, M.; Hawkins, E.; Smith, C.; Wilcox, L. (2020): SMURPHS: Historical HadGEM3-GC3.1 scaled aerosol coupled ensemble. Centre for Environmental Data Analysis, date of citation.
Abbreviation: Not defined
Keywords: SMURPHS, coupled, HadGEM3-GC3.1, aerosol, ensemble, historical


Previous Info:
No news update for this record
Previously used record identifiers:
No related previous identifiers.
Access rules:
Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence: When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data lineage:

The historical-0p2, historical-0p4, historical-0p7 and historical-1p5 ensemble members (20 in total), as well as the fifth member of historical-1p0, were run by Andrea Dittus. The historical-1p0 ensemble members were run by Martin Andrews. The data were post-processed by Andrea Dittus.

The data were passed from the project team to the Centre for Environmental Data Analysis for archival and distribution.

Data Quality:
The Centre for Environmental Data Analysis have done no quality control on the data as they are produced by the project team.
File Format:
Data are provided in NetCDF formats.

Process overview

This dataset was generated by the computation detailed below.

Development version of Met Office Hadley Centre (MOHC) HadGEM3-GC31-LL


All simulations in the historical scaled aerosol emissions ensemble were conducted with a development version of the HadGEM3-GC3.1-LL global climate model at N96-ORCA1 resolution, corresponding to 135 km resolution in mid-latitudes and 1º in the ocean (Williams et al., 2018). The low-resolution version of this model (used here) is documented in Kuhlbrodt et al. (2018). Information on the representation of aerosol processes and aerosol radiative forcing in this model can be found in Mulcahy et al. (2018).

The model is related to this model:

The only difference between the model version used here and the CMIP6 version linked above is in the treatment of prescribed ozone. In the development version (used for this dataset), there is a known issue that causes stratospheric ozone concentrations to occur in the upper troposphere as the tropopause rises with warming, causing a small amount of unphysical warming. This issue has been resolved in the UK's contribution to CMIP6 (Andrews et al., 2020 under review).

Input Description


Output Description


Software Reference


  • units: nm
  • var_id: wavelength
  • standard_name: radiation_wavelength
  • long_name: Radiation Wavelength 550 nanometers
  • units: Pa
  • var_id: psl
  • standard_name: air_pressure_at_mean_sea_level
  • units: K
  • standard_name: air_temperature
  • var_id: tasmin
  • units: 1
  • var_id: od550aer
  • standard_name: atmosphere_optical_thickness_due_to_ambient_aerosol_particles
  • units: 1
  • var_id: od550dust
  • standard_name: atmosphere_optical_thickness_due_to_dust_ambient_aerosol_particles
  • units: 1
  • standard_name: cloud_area_fraction
  • var_id: clt
  • units: m.s-1
  • standard_name: eastward_wind
  • var_id: ua
  • units: m
  • standard_name: geopotential_height
  • var_id: zg
  • units: m
  • standard_name: height
  • var_id: height
  • var_id: latitude_bounds
  • var_id: latitude_longitude
  • var_id: longitude_bounds
  • units: m.s-1
  • standard_name: northward_wind
  • var_id: va
  • var_id: pr
  • units: kg m-2 s-1
  • standard_name: precipitation_flux
  • units: Pa
  • long_name: pressure
  • var_id: plev
  • standard_name: relative_humidity
  • units: %
  • var_id: hurs
  • units: 1
  • standard_name: sea_ice_area_fraction
  • var_id: siconca
  • units: W m-2
  • standard_name: surface_downwelling_longwave_flux_in_air
  • var_id: rlds
  • units: W m-2
  • standard_name: surface_downwelling_shortwave_flux_in_air
  • var_id: rsds
  • units: K
  • standard_name: surface_temperature
  • var_id: ts
  • var_id: hfls
  • units: W m-2
  • standard_name: surface_upward_latent_heat_flux
  • units: W m-2
  • standard_name: surface_upward_sensible_heat_flux
  • var_id: hfss
  • units: W m-2
  • standard_name: surface_upwelling_longwave_flux_in_air
  • var_id: rlus
  • units: W m-2
  • standard_name: surface_upwelling_shortwave_flux_in_air
  • var_id: rsus
  • var_id: time_bnds
  • var_id: time_bounds
  • units: W m-2
  • standard_name: toa_incoming_shortwave_flux
  • var_id: rsdt
  • var_id: rlut
  • units: W m-2
  • standard_name: toa_outgoing_longwave_flux
  • var_id: rsut
  • units: W m-2
  • standard_name: toa_outgoing_shortwave_flux
  • units: kg m-2 s-1
  • var_id: evspsbl
  • standard_name: water_evapotranspiration_flux

Co-ordinate Variables

  • units: degrees_north
  • standard_name: latitude
  • var_id: latitude
  • units: degrees_east
  • standard_name: longitude
  • var_id: longitude
  • standard_name: time
  • var_id: time
Temporal Range
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Geographic Extent