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

#heatflux		§This module calculates the global surface temperature change, considering the energy balance due to radiative forcing in four surface boxes (north, south, land, ocean), and the slow uptake of heat by a multilayer upwelling-diffusion ocean.
  £§iobinfo <hr>See also @glotempplot, @oceantempplot, @rftemp, @gcmfit ££udebmodel  ££climodfuture

#glotempplot		§£^apptag This plot shows the change in global average surafce temperature. Historical measured and proxy temperatures are shown for comparison.

² °clou Regional temperature changes can be much greater than the global averages shown here! -see @regclimap ²

² °emit You can also set a target temperature stabilisation curve, and calculate the emissions to attain it: see @stabtempdoc ²

² °glob °cogs See @udebmodel and @gcmfit for explanation of how the model works²

² °adju The ocean layer temperatures and ocean mixing parameters are shown in @oceantempplot  ²
  £§graphinfo
  ££rftemp  ££stabilisationtemp ££gcmfit

#tempav		§Model calculation

#tempproxy		§Proxy data from tree rings, corals, sediments, from 1750-1990 (from Mann et al, see @dataref)

#tempdata		§Measured thermometer data from 1860-2001(compiled by Jones et al, CRU, see @dataref)

#temptrend		§Trend of either measured or proxy data (7 year moving average)

#tempnl		§(calculated) difference from average depends on @lotr, @kns, @klo and @radfordistrib. Nl responds most rapidly to radiative forcing, but also has most of the cooling from sulphate aerosols.

#tempno		§as NL above, note that surface ocean temperature also depends on heat flux from below (see @oceantempplot)

#tempsl		§as NL above There is less land  in southern hemisphere, but also less aerosols

#tempso		§as NO above.

#climsens		§This parameter is one of the most important uncertainties. It is defined as the global average temperature rise caused by a doubling of CO2 concentration. The sensitivity takes into account the fast, physical feedback processes in the climate system, such as changes in water vapour, clouds, and snow albedo.

#lotr		§This parameter defines the ratio of warming of land compared to ocean at <i>equilibrium</i>. It is used, together with @climsens, to calculate the internal model parameters which determine the heat fluxes to space.

#kns		§Determines the rate of heat transfer between northern and southern surface boxes

#klo		§Determines the rate of heat transfer between land and sea boxes

#baseyear		§Temperature <i>change</i> is relative to temperature in a certain year. This parameter affects the plotted temperature curves (although the @heatflux calculations are always relative to 1750) . For the measured/proxy data, the baseline is averaged over five years (chosen year 2) to smooth odd peaks. This parameter also affects the @stabtempl, but note @heatflux  always calculates relative to 1750, and the temperatures on the @regclimap are always relative to 1961-90.

  °adju It is recommended to set the baseline to 1765, for understanding the effect of science model parameters, and to 1990 for comparison with IPCC predictions.

#climodmenu		§This affects a set of parameters of @heatflux module (shown on @glotempplot, @oceantempplot and @radforplot), based on the table in IPCCTAR WG1apx9.1
 See @gcmfit  for explanation.

#oceantempplot		§£^apptag This plot shows the change in temperature in each layer of the ocean, demonstrating the slow transfer of heat between surface and deep water.   <li>² @udebmodel explains more about the layers and factors affecting the mixing.²  <li>² °glob Deep ocean temperature is a major factor in sea-level rise -see @sealevelplot  ²  <li>² °adju Surface temperatures and parameters are shown in @glotempplot .
  £^interacs £^curves
  ² °cogs The curves simply correspond the temperature of each box in @heatflux .<li>Green-Cyan: South Ocean<li>Red-Pink: North Ocean
 There are 70 boxes: 35 North, and 35 South, the upper layers are each 49m deep, the lower layers 196m deep. ²
  £^scales
  £^controls £^menopts

These parameters are usually tuned to a GCM chosen from the @climodmenu, as explained in @gcmfit ²
  <hr>²°cogs Note that the initial temperature profile is set such that the model starts in steady state in 1750 (i.e. if there were no forcing, there would be no temperature change). This profile is calculated analytically by fixing the surface temperature, and helps to reveal unrealistic combinations of parameters. ²
  ££gcmfit

#psi		§The cold water which sinks around Greenland and Antarctica has a major influence on the deep ocean temperature. Since most of this cold salty water is formed near freezing ice, its temperature is always close to zero. This parameter determines the warming of this water, as a fraction of the warming of surface water elsewhere.

#teddydiff		§Affects the flux of heat from the surface to the deep ocean. Increasing this will cool the surface slightly, but warm the deep ocean, and consequently increase the sea-level rise due to thermal expansion.

#tmixlay		§Depth of the well-mixed surface ocean layer, above the thermocline.

#seaice		§Introduces a difference between air and water temperatures in high latitudes.

#tufbopt		§The rate of sinking of cold polar water (see @psi) may decrease as the surface temperature rises, due to stratification of the water column which weakens the thermohaline circulation.

#tnoupwell		§see @tufbopt

#uwbaserate		§see @tufbopt

#uwredfrac		§see @tufbopt

#udebmodel		§This is an efficient java implementation of the Wigley/Raper Upwelling-Diffusion Energy Balance (UDEB) model which was used to make many of the the smooth-curve plots in the IPCC-TAR WG1. Parameters are tuned to fit seven different GCM predictions, as described in IPCCTAR-WG1-Appx 9.1. The system of heat fluxes is resolved using an efficient eigenvector calculation method.
  ³Features of UDEB model³  <li>Four surface boxes: north & south, land & ocean   <li>In each box, the "lambda" values for calculating heat flux to space are derived from the prescribed equilibrium @climsens and @lotr parameters.   <li>Surface fluxes depend on @klo and @kns conductivities (these are fairly arbitrary, but have little impact on the global average temperature)   <li>Radiative forcing of aerosols and short-lived gases is unevenly distributed between boxes (e.g. most of the sulphate aerosol cooling is in the north-land box)   <li>Two 1-D Upwelling-Diffusion Oceans (north and south), connected only at surface:   <li>Fixed @teddydiff between layers (unlike carbon model).   <li>A high latitude downwelling "pipe" (rather than a separate box), for whose water temperature is a fixed fraction of the average temperature (@psi parameter).   <li>A @seaice parameter adjusts the water/air temperature ratio.   <li>The lag of the surface ocean warming also depends on the @tmixlay   <li>The rate of this downwelling/upwelling is reduced with temperature to account for changing thermohaline circulation (@tufbopt, @tnoupwell, @uwbaserate, @uwredfrac parameters).
  <hr>See also:<li>@eigenvec,<li>Raper et al 2001 and references therein (@references),<li>@compareipcc, IPCCTAR-WG1-Appx 9.1., IPCC technical paper (1997) describing an earlier version of this model.

#climodfuture	¨fut		§The next step from here, might be to investigate the possibility to develop an interactive java version of intermediate complexity models. The simplest of these is the Bern zonally averaged model with the 2.5D Ocean.

#rftemp		§You can see how well the climate model predictions match the historical data, as you adjust the balance of radiative forcing from greenhouse gases, sulphate aerosols, and solar variability, which have different patterns over time (see @radforplot)

The surface temperature follows changes in radiative forcing fairly rapidly, with some delay due to exchange of heat with the deeper ocean. Note that short spikes in forcing (e.g. from volcanos) affect the land temperatures more than the ocean. The deep ocean, and hence sea-level rise, responds much more slowly. See also @inertia

You can also observe that some forcings are distributed unevenly between the four surface boxes (expert level). For example, most of the sulphate is in the northen land box.

#gcmfit		§The credibility of a simple climate model depends on fitting the parameters to predictions from more sophisticated global climate models (GCMs). In IPCC-TAR seven GCMs were used for this purpose. This parameter fitting was carried out by Sarah Raper et al as described in IPCC-TAR WG1 Appx9.1 See @references, @compareipcc.
  °adju If you select the "expert" @complexitymenu level, you can see all the parameters changing together, as you choose different GCMs from @climodmenu. Surface flux (energy balance) parameters are shown in @glotempplot, ocean mixing parameters (affecting the inertia of the system) are in @oceantempplot. 
  You can also adjust these parameters individually, to understand the effect of each one (see also @heatflux module)