Forcings in GISS Climate Models

We summarize here forcing datasets used in GISS global climate models over the years. Note that the forcings are estimates that may be revised as new information or better understandings of the source data become available. We archive both our current best estimates of the forcings, along with complete sets of forcings used in specific studies. All radiative forcings are with respect to a specified baseline (often conditions in 1850 or 1750).

Forcings can be specified in a number of different ways. Traditionally, forcings have been categorized based on specific components in the radiative transfer calculation (concentrations of greenhouse gases, aerosols, surface albedo changes, solar irradiance, etc.). More recently, attribution of forcings have been made via specific emissions (which may have impacts on multiple atmospheric components) or by processes (such as deforestation) that impact multiple terms at once (e.g., Shindell et al., 2009).

Additionally, the definition of how to specify a forcing can also vary. A good description of these definitions and their differences can be found in Hansen et al. (2005). Earlier studies tend to use either the instantaneous radiative imbalance at the tropopause (Fi), or very similarly, the radiative imbalance at the Top-of-the-Atmosphere (TOA) after stratospheric adjustments — the adjusted forcing (Fa). More recently, the concept of an 'Effective Radiative Forcing' (Fs) has become more prevalent, a definition which includes a number of rapid adjustments to the imbalance, not just the stratospheric temperatures. For some constituents, these differences are slight, but for some others (particularly aerosols) they can be significant. Note however that because of the internal variability inherent in the ERF calculation (a 30 year simulation with fixed sea ice and sea surface temperature), the uncertainty for the smaller forcings is significant (+/- 0.08W/m2, 95% CI).

In order to compare radiative forcings, one also needs to adjust for the efficacy of the forcing relative to some standard, usually the response to increasing CO2. This is designed to adjust for particular geographical features in the forcing that might cause one forcing to trigger larger or smaller feedbacks than another. Applying the efficacies can then make the prediction of the impact of multiple forcings closely equal the net impact of all of them. This is denoted Fe in the Hansen description. Efficacies can depend on the specific context (i.e. they might be different for a very long term simulation, compared to a short term transient simulation) and don't necessarily disappear by use of the different forcing definitions above.

Quantifiying the actual forcing within a global climate model is quite complicated and can depend on the baseline climate state. This is therefore an additional source of uncertainty. Within a modern complex climate model, forcings other than solar are not imposed as energy flux perturbations. Rather, the flux perturbations are diagnosed after the specific physical change is made. Estimates of forcings for solar, volcanic and well-mixed GHGs derived from simpler models may be different from the effect in a GCM. Forcings from more heterogeneous forcings (aerosols, ozone, land use, etc.) are most often diagnosed from the GCMs directly.

Forcings in the CMIP6 Simulations

Discussions of the CMIP6 forcings are available in Miller et al. (2021) for the E2.1 models. We also provide the single forcing calculations for the E2.2 models which have an extended model top and higher vertical resolution which predominantly impacts stratospheric ozone effects. Additionally, we provide some information related to forcing variants in the CMIP6 simulations.

Historical forcings from the E2.1 model (f2 variant)
Fig. Effective radiative forcing (ERF) at the top-of-the-atmosphere (W/m2) in the E2.1-G (f2) model. Time-series are provided for all forcings together, just natural forcings, and greenhouse gas (GHG) and aerosols separately, encompassing the historical times series (1850-2014) and SSP2-4.5 (2015-2100). Data download.
Single forcings for E2.1 model (f2 variant) Comparison in forcings between E2.1 NINT (f2) and OMA
Fig. (a) Single forcing ERF (W/m2) in the E2.1-G (f2) model for years 2000 and 2014, and compared to E2-R (CMIP5). (b) Forcings for 2 and 4xCO2. (c) Comparison between single forcings in the NINT and OMA versions of E2-1-G.

The ERF (Fs) for year 2000 and year 2014 for each historical forcing can be downloaded here (E2.1, f2), here (E2.1 OMA), and here (E2.2).

Forcings in the CMIP5 Simulations

Fig 2. from Miller et al. (2014) (updated)
Fig. Instantaneous radiative forcing at the tropopause (W/m2) in the E2-R NINT ensemble. (a) Individual forcings and (b) Total forcing, along with the separate sums of natural (solar, volcanic and orbital) and anthropogenic forcings. (Updated: 3/12/2016)

Calculations and descriptions of the forcings in the GISS CMIP5 simulations (1850-2012) can be found in Miller et al. (2014). Data for these figures are available here and here. (Note the iRF figure and values were corrected on 3/12/2016) to account for a missing forcing in the 'all forcings' case. Fig. 4 in Miller et al (2014) was also updated). Snapshots of the ERF (Fs) and adjusted forcings (Fa) from these simulations. Note that the forcings from 2000 (or 2005 in some cases) are extrapolations taken from the RCP scenarios, and the real world has diverged slightly from them.

Further estimates of the responses, including temperatures and the ocean heat content changes, and efficacies are available in the supplementary material associated with Marvel et al. (2016).

Forcings in Hansen et al. (2011)

The following chart of forcings from 1880-2011 is taken from Hansen et al. (2011):

Line plot of separate radiative forcings, 1880-2011   Line plot Net forcing, 1880-2011

Data is updated from the CMIP3 studies below (e.g., Hansen et al. 2007a, b) and extended to 2011 using assumptions outlined in the paper. The separate radiative forcing data (Fe) are available here (Net forcing). The figures are also available as PDFs here and here.

Forcings in the CMIP3 simulations

The following chart of forcings from 1750-2000 is taken from Hansen et al. (2005):

Bar chart showing changes in climate forcings in units of Watts per meter-squared.

Figure is also available in PDF format. (Source: Figure 28 of Hansen et al. (2005). More details, including maps and time series of individual forcings are available on the Efficacy web pages.

Forcings in Hansen et al. (1988)

Although no longer an up-to-date study, the original forcings used in the first transient GISS climate model simulations (Hansen et al., 1988) are occasionally of historical interest. The specific scenarios for the three model runs (A, B, and C, 1958-2050) can be downloaded here, along with the effective forcing (Fe). The global mean temperature responses to 2020 are also available.

Further Details and Various Future Scenarios

Paleo-Climate Forcings

GISS models are often used to assess skill in capturing key paleo-climate eras or events. The forcings for these simulations include atmospheric composition, natural drivers but also changes in land-ocean masks and orography. (TBD)

Contacts

Please address scientific inquiries about these data to Makiko Sato, Andrew Lacis, Reto Ruedy or Gavin Schmidt.

References

Hansen, J., I. Fung, A. Lacis, D. Rind, S. Lebedeff, R. Ruedy, G. Russell, and P. Stone, 1988: Global climate changes as forecast by Goddard Institute for Space Studies three-dimensional model. J. Geophys. Res., 93, 9341-9364, doi:10.1029/JD093iD08p09341.

Hansen, J., M. Sato, R. Ruedy, et al., 2005: Efficacy of climate forcings. J. Geophys. Res., 110, D18104, doi:10.1029/2005/JD005776. (See also Efficacy webpages).

Hansen, J., M. Sato, R. Ruedy, et al., 2007: Climate simulations for 1880-2003 with GISS modelE. Clim. Dyn., 29, 661-696, doi:10.1007/s00382-007-0255-8.

Hansen, J., M. Sato, P. Kharecha, and K. von Schuckmann, 2011: Earth's energy imbalance and implications. Atmos. Chem. Phys., 11, 13421-13449, doi:10.5194/acp-11-13421-2011.

Marvel, K., G.A. Schmidt, R.L. Miller, and L. Nazarenko, 2016: Implications for climate sensitivity from the response to individual forcings. Nature Clim. Change, early on-line, doi:10.1038/nclimate2888.

Miller, R.L., G.A. Schmidt, L.S. Nazarenko, et al, 2015: CMIP5 historical simulations (1850-2012) with GISS ModelE2. J. Adv. Model. Earth Syst., 6, no. 2, 441-477, doi:10.1002/2013MS000266.

Miller, R.L., G.A. Schmidt, L. Nazarenko, et al, 2021: CMIP6 historical simulations (1850-2014) with GISS-E2.1. J. Adv. Model. Earth Syst., 13, no. 1, e2019MS002034, doi:10.1029/2019MS002034.

Nazarenko, L., G.A. Schmidt, R.L. Miller, et al., 2015: Future climate change under RCP emission scenarios with GISS ModelE2. J. Adv. Model. Earth Syst., 7, no. 1, 244-267, doi:10.1002/2014MS000403.

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This page was written by Dr. Makiko Sato and Dr. Gavin Schmidt. (Last modified: 2018-06-26)