RFMIP-ERF

Inferring effective radiative forcing from global model integrations

The first goal of RFMIP is to investigate the effective radiative forcing (ERF) across climate models and to understand the reasons for inter-model differences. The effective radiative forcing includes rapid adjustments in the troposphere such as the changes in clouds and vertical temperature structure, in addition to the well-known stratospheric adjustment that occurs in response to an abrupt change in greenhouse gas forcing. Rapid adjustments are distinct from climate feedbacks, which scale with changing near-surface air temperature. Rapid adjustments, including those driven by cloud changes, can be determined using radiative kernels.

As a minimum, a group of six 30-year fixed sea-surface temperature model runs will be requested from each modelling group (table 1). ERF will be diagnosed as the difference in net top-of-atmosphere radiative flux between each experiment and the model’s pre-industrial control run. Fixing sea-surface temperatures and sea-ice conditions suppresses climate feedbacks and allows ERF to be diagnosed as the difference in top-of-atmosphere (TOA) radiation fluxes between each experiment and the piClim-control run (Forster et al., 2016).

Sea surface temperatures and sea ice from a monthly climatology covering at least 30 years of a pre-industrial control run of the same model are to be used for all time slice and transient integrations. These should be prescribed according to the AMIP protocols, whereby interpolated daily data are generated preserving the prescribed monthly averaged field.

To understand the evolution of ERF over the 1850-2014 period, we also request transient simulations where forcing agents (greenhouse gases, aerosols, land-use changes, solar and volcanoes; table 2) vary to match the best-estimate historical forcing. Again, sea-surface temperatures and sea-ice are to be fixed at the pre-industrial level, to diagnose ERF as the difference of TOA fluxes. Beyond 2014, forcing timeseries are to be taken from SSP2-4.5.

In RFMIP-ERF-HistAer and RFMIP-ERF-Aer, ozone concentrations should be fixed at pre-industrial values. In concentration-based models, the concentrations of ozone should be fixed, and in emissions-based models, the ozone in the radiation code should be fixed. As solar and volcanic forcings affect stratospheric ozone, this effect will be included in the hist-nat integration of DAMIP. To get a consistent ERF estimate modelling groups should include the same dataset in the RFMIP-ERF-HistNat experiment. David Plummer, in collaboration with Michaela Hegglin, has kindly agreed to develop prescribed ozone datasets for DAMIP hist-nat, which account for solar and volcanic effects and that data will be published on input4MIPs in due course. Therefore, we suggest that modelling centres using models without coupled chemistry wait until the prescribed ozone datasets are available before commencing these experiments.

It has come to our attention that the piClim-anthro and piClim-ghg experiments are described differently in ES-Doc. Please follow the guidelines on this website. Clarifications, but where the protocol agrees with ES-Doc, are given in orange. – CS, 8 April 2019 (update 23 May 2019).

Table 1: Present-day time-slice simulations

Experiment title Experiment description Years Major purposes
piClim-control Pre-industrial conditions 30 Baseline for model-specific effective radiative forcing (ERF) calculations
piClim-anthro Present-day (2014) anthropogenic forcing (well-mixed greenhouse gases, aerosols, ozone and land-use). Note: use present-day ozone concentrations 30 Quantify present day (2014) total anthropogenic ERF
piClim-ghg Present-day (2014) non-ozone (well-mixed) greenhouse gases. Note: use present-day well-mixed GHG concentrations, not pre-industrial as mentioned on ES-Doc. To confirm, pre-industrial ozone to be used for this experiment 30 Quantify present-day (2014) ERF by non-ozone greenhouse gases
piClim-aer Present-day (2014) aerosols (ozone fixed at pre-industrial concentrations) 30 Quantify present-day (2014) ERF by aerosols (ozone fixed at pre-industrial)
piClim-lu Present-day (2014) land-use 30 Quantify present-day (2014) ERF by land-use changes.
piClim-4xCO2 CO2 concentrations set to 4 times pre-industrial 30 Quantify ERF of 4 × CO2

Table 2: Historical (1850-2014)/SSP2-4.5 (2015-2100) transient simulations

Experiment title Experiment description Start End Major purposes
piClim-histall Time-varying forcing from all agents 1850 2100 Diagnose transient ERF from all agents
piClim-histnat Time-varying ERF from volcanoes, solar (including spectral) variability, etc. 1850 2100 Diagnose transient natural ERF
piClim-histghg Time-varying ERF from non-ozone (well-mixed) greenhouse gases 1850 2100 Diagnose transient ERF from non-ozone greenhouse gases
piClim-histaer Time-varying ERF from aerosols (ozone fixed at pre-industrial concentrations) 1850 2100 Diagnose transient ERF from aerosols (ozone fixed at pre-industrial)