Correspondence to IPCC-TAR predictions

SRES data | Differences | Links | Base

This web model uses an efficient java implementation of simple carbon and climate models with the same specification as used to generate many of the smooth-curve plots used within the IPCC-TAR report.

Therefore, if we give it the same input (emissions or stabilsation scenarios), and use the same sets of model parameters (ocean mixing, climate sensitivity, etc.), we should get the same output (CO2 concentration or emissions, radiative forcing, temperature, sea-level) as IPCC. This can be checked, by comparing with specific plots and data from IPCC-TAR, as explained below.

Experts can also check that the model behaves as they would expect, by experimenting with many possible combinations of parameters. For this purpose switch the version (top panel menu) to "expert" mode, and you will see more curves and controls.

See also:

  • Features of each plot
  • How each module works
  • About simple climate models

    IPCCTAR-WG1-SRES data

    The SRES appendix at the end of IPCC-TAR WG1 report contains useful tables of data, giving IPCC predictions of CO2 concentration, radiative forcing, temperature and sea-level rise for the 6 SRES marker scenarios. To help you check the correspondence, this data may be superimposed as small circles on the plots.

    To see this, you should do the following:

  • Press the reset button (top), to get the default set of model parameters.
  • Choose "SRES no-climate-policy scenarios" from the Mitigation menu (top)
  • Select "expert" from the complexity menu (top)
  • Press the "IPCC-data" button (top)
  • Select a plot to check (CO2 Concentration, Radiative Forcing, Temperature, Sea-level)
  • Select a scenario from the SRES menu (top)

    The circles should then appear, you should see a good fit to the curves generated by the model. (Of course, the data will not correspond, if you adjusted the model parameters since pressing the reset button!)

    There are also some important technical points to consider when making comparisons:

  • The IPCC data for temperature and sealevel correspond to the average of the seven GCMs (see Climate Model). You can use the GCM-fit menu on the temperature plot to cycle through the range of models. HadCM3 is now the default option and is quite close to the average, however the difference between models varies between scenarios and is greater for sea-level.
  • The concentration / radiative forcing data come from the Bern-CC Model and the temperature/ sealevel from the Wigley/Raper model, except that:
  • The total RF is from the WR model
  • CO2 RF is shown for both models. However, in the WR Model, the parameter "Radiative Forcing for CO2 doubling" varies with the GCM-fit, whereas in the Bern-CC model this was fixed at 3.71 W/m2. You must set this parameter, to check the CO2 RF data.
  • These two models used quite different formulae for RF from carbon aerosols. The default (Bern-CC) option scaled to CO emissions is consistent with IPCC Chapter 6 and SRES tables. However you should select the BCOCWig option when comparing temperature / sealevel / total rf. Data is shown for the total of BC+OC according to the WR. The BCOCWig option gives an approximate fit only.
  • The circles are adjusted, if you move the temperature baseline year.
  • The baseline year for sealevel rise is 1990 in the data and 1750 in JCM, so the circles are adjusted accordingly.
  • Circles are not shown in the emissions plots, since the emissions are taken directly from SRES data tables.
  • You can also choose the older scenario IS92A, but data is not available for all quantities. Also it had to be scaled down to match current emissions, and different models may make different assumptions about this.
  • See also Known Differences with IPCC Calculations (below), especially regarding the biosphere sink

    For more info see also:

  • SRES scenarios.
  • Carbon Plot
  • Radiative Forcing Plot
  • Temperature Plot
  • Sealevel Plot
  • WG1 SRES appendix data tables

    Known differences in calculation methods

    Mathematical Method

    JCM uses an eigenvector calculation method rather than direct integration, combined with an iteration of the ramp-function for non-linear fluxes. This method finds the exact analytical solution, given the assumption that the non-linear fluxes change linearly within one timestep. The method used by Bern-CC and WR models is different but the difference should be almost negligible.
  • Eigenvector Method

    Terrestrial Biosphere sink

    The carbon cycle model used here is an older version of the Bern model which uses the same "HILDA" ocean as the Bern-CC model, but a simpler 4-box terrestrial biosphere (as used in IPCC SAR). The Bern-CC (TAR) model incorporates a more sophisticated dynamic vegetation model including several plant types and many grid cells, each with different temperature and precipitation derived from GCM predictions. The temperature feedback tends to lower the biosphere sink (and hence increase the concentration) towards the end of this century.

    It is planned to develop a fast implemention of the dynamic vegetation model within JCM.

  • See Carbon Module

    Climate-Carbon feedback

    In this web model, the carbon cycle and climate are directly coupled to achieve the feedback from temperature to carbonate chemistry in the surface ocean. In the IPCC calculations, different models were used for the carbon cycle and temperature. Although both Bern-CC and WR model include some climate-carbon feedbacks, these two models were not directly coupled as they are here. This may result in slight differences, however direct coupling should be preferable.

    Sea-level rise due to ice-melt

    The calculations here are based on simple formulae, parameterised to fit data in Chapter 11 of IPCC-TAR-WG1 (the glacier formula is adapted from that used in the SAR).

    Links into IPCC-TAR:

    Note, when comparing curves, always be careful regarding the baseline for temperature and sea-level rise ( see below).

    General links

  • IPCC-TAR Online at GRID Arendal
  • IPCC Homepage
  • JCM References Page

    Stabilisation scenarios

    The formulae for defining the target curve towards a particular stabilisation level is derived from the original formulae in the IPCC technical paper of Enting et al 1994 (referred to as "S" "WG1" in IPCC-TAR-SYR). The "WRE "curves are a variant of this with a delayed start, following the IS92A business-as-usual scenario for the first few years.

    In JCM, stabilisation curves start from 2000 (current emissions), whereas the originals started from 1990. As current emissions lie significantly below the IS92A projections, these have been scaled down to fit the current level.

    For more information see:

  • Mitigation /Stabilisation scenarios,
  • IPCC-TAR-SYR Figure SPM6
  • WG1 TS Fig 25 WRE stabilisation curves & implied emissions

    Radiative forcing

    The contributions of the minor greenhouse gases and aerosols were derived from figures and data in
  • Chapter 6 of TAR-WG1
    Various contribtions to RF
  • WG1 TS Fig 9
  • SYR main part Fig 2-2 (not yet available online)
  • WG1 Ch6 Fig 6-6
    Solar and volcano forcing history
  • WG1 Ch6 Fig 6-8
    Useful data table
  • WG1 Ch6 Table 6-11

    Temperature projections

    Explaining the climate model parameters
  • WG1 Ch9 Appendix 9.1

    SRES temperatures

  • SYR SPM3 -SRES projections (not yet available online)
  • WG1 TS Fig 22
  • WG1 Ch9 Fig 9-14
  • WG1 Ch9 Fig 9-15
    WRE temperatures
  • WG1 TS Fig 26
  • WG1 Ch9 Fig 9-16
  • WG1 Ch9 Fig 9-17

    Sea level rise


    SRES sea-level
  • WG1 TS Fig 22
  • WG1 Ch11 Fig 11-12
    Note various other plots and tables in
  • Chapter 11 of TAR-WG1,
    Note also WG1 Ch 11 fig 11-9 (uncertainty in different contributions to sea-level)

    Timescales of response

    Will add later link to Q5 of IPCC SYR regarding timescales of response, once equivalent plots are set up in JCM.
  • Note especially SPM5 -timescales of response (not yet available online)

    Units and baselines

    The zero-point for reporting temperature rise is arbitrary ! Climate modellers usually start by assuming a steady-state in the preindustrial era (typically 1750 or 1765), which thus defines the zero point. Those investigating historical data tend to use the 1960-1990 average as a baseline, to smooth out temporary fluctuations, but acknowledging that the best data comes from the recent past. Whereas people comparing future scenarios often want to to know the change from the present (typically 2000). So, be very careful to compare like with like! The same applies to sea-level rise. See:
  • Temperature Plot
  • Sealevel Plot

    Most scientists report CO2 emissions in Gt Carbon, to allow for easy transformation to/from fossil fuel, bicarbonate ions in seawater, wood, soil, etc, whilst others report Gt CO2, including the weight of the oxygen atoms (Note 1 Gt= 1 billion tons = 1 Pg, and 1 Gt CO2 = (44/12)* Gt C). Also, sometimes people refer instead to Gt CO2-equivalent (CO2-e) which includes other greenhouse gases scaled using global warming potentials

  • How much is a GtC?