This is part of the labels / documentation for <a href='http://jcm.chooseclimate.org'>Java Climate Model</a><hr/>

#radfor		§This module calculates the total radiative forcing, as the sum of that from CO2, all the other greenhouse gases and aerosols(from @oghga ), solar variability and volcanos. It also distributes the forcing between the 4 surface boxes of the @heatflux module
  £§iobinfo ££radforintro ££radforco2 ££radforothgas ££radforaerosol ££radforsolvol ££radfordistrib  ££radforipcc ££radforfuture

#radforplot		§£^apptag This plot shows the forcing due to greenhouse gases, aerosols (sulphate and smoke), and external forcing (solar variablility, volcanos).   <li> ²The concept of "radiative forcing" is introduced later.²  <li> ²°adju You also have the option to stabilise forcing -see @stabrfdoc, @co2eq²
  £§graphinfo ££radforintro ££stabilisationrf  ££radforco2 ££radforothgas ££radforaerosol ££radforsolvol ££radfordistrib ££rftemp ££radforipcc

#rfco2d		§This is one of the parameters tuned to GCM predictions -see @gcmfit, @climodmenu. Its effect on temperature is not intuitive, because the temperature rise for CO2 doubling is already fixed by @climsens. That is divided by this parameter to get warming per forcing, which is applied to the forcing from all gases. So increasing this parameter effectively reduces the influence of other greenhouse gases, aerosols and solar variability, compared to CO2.

#sulfrf2000		§See @radforaerosol

#solarrf2000		§See @radforsolvol

#sv		§See @radforsolvol

#volcfac		§See @radforsolvol

#bcocwig		§See @radforaerosol

#HadA		§Added for UNFCCC model intercomparison exercise, assessing the Brazilian proposal

#4gas		§Option for UNFCCC model intercomparison exercise, assessing the Brazilian proposal -see @attribution

#radforintro		§

Radiative Forcing is a convenient concept for combining various influences on the heat balance of the earth. It refers to the change in instantaneous heating at the top of the troposphere, compared to the preindustrial climate. In response to radiative forcing, the earth's surface warms until the extra infra-red radiation it emits balances the extra incoming forcing.

² °glob For more explanation of the RF concept, see IPCCTAR WG1 Chapter six. ²

#radforco2		§RF For CO2 the radiative forcing is proportional to the logarithm of its concentration (this is due to the partial saturation of the absorption of infra-red by CO2, because its concentration is relatively high compared to other trace gases) .

CO2 rf = f x ln([CO2]/[CO2]prein)/ln(2)

 where f= @rfco2d (parameter in @heatflux  included in @gcmfit ) 

 Consequently doubling the CO2 concentration has the same warming effect, regardless of the baseline.

#radforothgas		§The other gas curve shows the sum of the radiative forcings from CH4, N2O, O3, CFCs and HFCs. Currently the radiative forcing from the other gases combined is almost as great as that from CO2. However methane and tropospheric ozone have much shorter atmospheric lifetimes than CO2, and so they become relatively less important in the longer term.  For more detail see @othgasplot, @fgasplot

#radforaerosol		§Sulphate aerosols and white smoke reflect sunlight and there have a cooling effect (negative radiative forcing), whilst black smoke (soot) absorbs sunlight and has a warming effect.

Sulphate gases also combine with water to form droplets of sulphuric acid, which act as condensation nuclei for cloud droplets, which then reflect even more sunlight. This is known as the "indirect" effect.

Since these droplets are then removed from the atmosphere as acid rain, their atmospheric lifetime is very short, so these effects are greatest in industrial regions. In developed countries, the cooling effect of aerosols was greatest in 1970s-1980s and is now declining due to attempts to reduce acid rain by using of cleaner fuels or putting "scrubbers" on chimneys.

The magnitude of the sulphate aerosol radiative forcing (especially the indirect effect) is very uncertain, so an adjustable parameter is provided for you to experiment with this. Try to get a good fit between the calculated and measured temperatures on the @glotempplot.

The radiative forcing from carbon aerosols is even less certain. In 2000 the radiative forcing (W/m2) was assumed to be:
  <table>
  <tr><td></td><td>Fossil Fuel</td><td>Biomass Burning</td></tr>
  <tr><td>White (organic)</td><td>-0.1</td><td>-0.4</td></tr>
  <tr><td>Black (soot)</td><td>+0.2</td><td>+0.2</td></tr>
  </table>

In the future, Bern-CC model simply scales these to CO emissions, whilst Wigley-Raper model assumes the fossil component scales with sulphate aerosols and the biomass part with "gross deforestation". By default the former is used, but the "BCOCWig" option (expert level) selects an approximation to the latter.   <li>See @oghga module for calculation formulae

#radforsolvol		§The direct impact of solar variability is rather small, however various mechanisms have been proposed which may amplify this. In @radforplot the curve from Hoyt and Schatten has been scaled to produce a forcing of 0.3W/m2 in 2000 compared to 1750 (as suggested by IPCCTAR-WG1-ch6).

As well as the regular eleven year sunspot cycle, there seems to be increased heating during the period 1910-1940, and a slight cooling thereafter. This helps to explain part of the shape of the historical temperature curve, but it cannot explain the particularly rapid warming since 1970 (See @glotempplot)

Since the magnitude of this effect is very uncertain, an adjustable parameter is provided for you to experiment with this.

In addition, the dust produced by major volcanic eruptions has a short term impact on global climate, the most recent example being Mt Pinatubo in 1991. These spikes are also visible in the carbon cycle, due to the feedback from temperature. However this forcing has no impact on the long term trends.

#radfordistrib		§It is assumed in @radforplot, that we can compare and sum the radiative forcing caused by various greenhouse gases, aerosols, and solar variability, which helps to illustrate the relative importance of various factors. However it must be emphasised that forcings with different regional distributions, cannot be considered to offset each other. For example, sulphate aerosols have a short lifetime so their cooling effect is felt mainly in industrialised areas of northern continents. Stratospheric ozone depletion is biased towards the polar regions. The effect of greenhouse gases may be greatest during winter nights, whilst the effect of increased solar activity may be greatest during summer days.

Some of these effects are considered by unevenly distributing the radiative forcing between the four surface boxes of the climate model (@heatflux). Try the @unif option to switch off this effect.

The distribution between the four surface boxes of the climate model is:   <li>Sulphate direct, black carbon aerosols: strong bias to north land   <li>Sulphate indirect, tropospheric ozone: weaker bias to north land   <li>Organic carbon aerosols (biomass burning): bias to south land   <li>Stratospheric ozone depletion: bias to south   <li>Other greenhouse gases, solar and volcano: evenly distributed.

#radforipcc		§If you select expert complexity level, and then click the button "ipccdata" (top panel) you will see circles superimposed on this plot, which show the data published in the IPCCTAR-WG1-SRES appendix. These should be comparable with the model calculations, when "no-policy SRES scenarios" is also selected from the mitigation menu. See @compareipcc for more information.

² °cogs Note: Two sets of circles are given for CO2 R.F., derived from Bern-CC and W/R models. To match these data you should move the @rfco2d parameter to 3.71. For some GCM-fits this parameter is lower, but then is offset by a higher climate sensitivity (see above and @glotempplot). ²

²Another set of circles corresponds to the sum of BC+OC aerosol forcing using the Wigley formula (see above). ²

²The @tarO3 parameter (@othgasplot) should also be selected.²

#radforfuture	¨fut		§Aircraft contrails, dust and albedo changes are mentioned in IPCC Chapter 6, but not in the tabulated data for SRES scenarios, consequently they are not included here.

However the effect of aircraft contrails and Ozone from NOx could be shown, based on scenarios in the IPCC special report on aviation.

The most challenging development, would be to include the varying effect of unevenly distributed forcings (@radfordistrib) on the regional climate impacts (@regcli).

#sulfind		§The indirect effect is caused by the cloud-seeding properties of acidic sulphate aerosols, which form very good cloud condensation nuclei .

#blackcarbon		§Black smoke - mainly from incomplete combustion of fossil fuel - warming efect

#orgcarbon		§Light coloured smoke -mainly from biomass burning following deforestation - this has a temporary cooling effect.

#aerosol		§see @radforaerosol

#natvar		§see @radforsolvol

#otherghg		§see @othgasplot for details