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

#mainmenu		¨oldJCM4 addJCM5		§£%updatedoc
----
@welcome
@howuse (read this first!)
----
@aboutjcm
@tech
----
@docsearch, @doclist
 £§usehelpmode
----
@jcm_root (the package tree, containing...)<ul>	
<li>@jcm, 
<li>@jcm.mod </ul>
---- 
=== £`jcm.mod===
@jcm.mod.obj
@jcm.mod.soc
@jcm.mod.luc
@jcm.mod.carbon
@jcm.mod.ogas
@jcm.mod.cli
@jcm.mod.reg
----
**(OLD JCM4 Documentation to be updated)**
=== Cross Cutting / Overview Topics===
@intro
@emitcc 
@science 
@applications

#mmccot		¨oldJCM4		§<nobr>€€emit @emitcc </nobr>
<nobr>€€glob @science </nobr>
<nobr>€€clou @impacts  </nobr>

#mmusejcm		¨oldJCM4		§<nobr>€€about @about </nobr>
<nobr>€€tech @tech </nobr>
<nobr>€€teach @applications</nobr>

#mmpartjcm		¨oldJCM4		§<nobr>€€pan @pan </nobr>
<nobr>€€mod @mod </nobr>
<nobr>€€root @comp </nobr>

#mod		¨oldJCM4		§Link to old JCM4 page about modules
In JCM5 see @jcm.mod, @module

#pan		¨oldJCM4 addJCM5		§Old link to a JCM4 doc page about panels.
In JCM5, @plots are not fixed by code, but created on demand from @qtsets in @modules, the relevant documentation is therefore in modules (see @jcm.mod)

#applications		¨oldJCM4 addJCM5		§Note this is old documentation from JCM4, to be updated

Learning and dialogue
@teaching  

Presentations
@confpres 
 @linkpres
   @moscow  

Brazilian Proposal
@attribution (<a href="http://unfccc.int/program/mis/brazil/index.html" target="_new">UNFCCC website</a>  ) 

Investigate New Stabilisation Scenarios
@stabtempdoc
@stabrfdoc
@art2 

Integrated assessment / Uncertainty analysis
using new @scripting facility
e.g. @stabtemp2cscript 
 @probabilistic  <!-- add later impacts DDC and climnegIA -->
  ££jcmmirror

#jcmmirror		¨oldJCM4		§<li>JCM is part of UNEP's Climate Portal <a target="_new" href="http://climatechange.unep.net/jcm">climatechange.unep.net</a>  <li>Another copy is at of <a href="http://climate.unibe.ch/jcm" target="_new"> University of Bern Klima Umwelt Physik</a>   <li>New versions appear first on the homesite <a target="_new" href="http://jcm.chooseclimate.org">  jcm.chooseclimate.org </a>
  See also @develop.

#teaching		¨oldJCM4		§JCM has already been used for student courses in universities in several countries, including:  <li>Climate-negotiation role-play in UCL, Louvain-la-Neuve (Belgium)  <li>Climate change distance-learning course in Open University (UK)  <li>Courses about the Carbon-Climate system in LLN, University of Bern (Switzerland), and University of East Anglia (UK)  <li>University of Waterloo FES, Canada  <li>Interest was expressed for use in university courses in US and Italy
  <hr>
  The experience with students so far is very positive - they often learn to use JCM much faster than professors (!), and even those who are not experts on climatic topics ask sophisticated questions demostrating a thorough exploration of the issues, processes and uncertainties, which can inspire new developments in the model.
  More links/resources will be be added here soon
  <hr>
  The new @scripting feature will help in tailoring for future courses (by recording demonstrations) and could also be used as a format for sharing results.
  The long-term vision is to connect groups of students across the web, to have a real debate between people in all corners of the world. See also @dialogue
  Do you have a suggestion of how this could be developed further? Please get in touch (@contact)

#about		¨oldJCM4 addJCM5		§

#philosophy		¨oldJCM4		§%%[Note: this page dates from the earliest versions of JCM, in 2001, but remains relevant today]%%
££approaches ££uncertcope ££whobau
</ul>

#approaches		¨oldJCM4		§Whilst on tour demonstrating this web model,
  the author has observed that the questions people ask
  vary depending on different philosophical approaches to the climate problem.
  This page is provided to help us see various points of view.

If the default setup of the model shows a stabilisation scenario,
  some people ask "but you seem to predict a rather low temperature increase, do you think it's realistic that emissions will just fall like that?, and are especially upzzled why adjusting the ocean mixing rate (for example) should change the emissions but not the temperature. On the other hand, if the default setup shows an SRES scenario, others might say "why do you want emissions to increase like that?, or even ?I tried to adjust the temperature, but it doesn't work, I thought the aim was to stabilise the climate".

Essentially, some are thinking "where are we going, is it a problem, should we deviate?", whilst others ponder "what is the best destination, and hence the course towards it?".

The former are looking  forwards from the present, from cause to effect, and tend to emphasise "baseline" <i>predictions</i>, whereas the latter are trying to look backwards from the future, from effect to cause, trying to find a <i>problem-solving</i> framework.

You may find the @flowchart helpful. Which way do you prefer the arrows to go?

Note that this JCM, like the IPCC, considers both approaches, reviewing both
  @sres and @stabilisation scenarios. However if you ask me simply 'so what's your prediction of climate change', I will reply - that's our choice -what do you want to do (and maybe later -what risks are acceptable to you)? Hence the name ?chooseclimate? (see also @concept). But to have a real choice, we have to reach a common understanding among all all citizens who share the same atmosphere.

In climate science, those who work with sophisticated but slow Global Circulation Models can only  make forward-looking <i>predictions</i> based on a small set of pre-defined scenarios,
  whereas  those who work with simple models (such as this one) are able to use them for "inverse" (backwards) calculations or within "Integrated Assessment" frameworks, eventually intending to seek the "optimum" solution.

The former might emphasise @uncertainty in the models, whilst the latter try to make policy-relevant analysis now, anticipating the  @inertia in the system.

Both approaches pose technical problems:
  Predictions from socioecnomic models tend to diverge wildly in the future, and so cannot be extended for long enough timescales to show the effect of slowly-responding processes such as sea-level rise.  Whereas inverse calculations can define a stable future, but tend to diverge more when calculating pathways away from the present (particularly if we choose a target later in the cause-effect chain -see @uncertburden).

Imagine on a ship, the lookout high in the "crows nest" has a better view than the navigator below decks, but the latter has a chart covering greater distances, including changing currents and underwater obstacles. So they may give contradictory advice to the helmsman who, knowing that the ship is heavy to steer, has to find the best compromise!

The problem-solving approach also assumes that it is possible to make an effective science-driven global agreement limiting greenhouse gas emissions, i.e. that the UN Climate Convention will achieve it's aim as expressed in Article 2 (see @stabilisation). Those who project current trends might be more pessimistic about this,
  and prefer to emphasise developing technology to enable us to reduce emissions later if necessary, or to adapt to climate change (see @stabpathways).

  In practice, we need a mixture of both prediction and problem-solving approaches, as discussed below.

#uncertcope		¨oldJCM4		§In the IPCC TAR Synthesis Report, the answer to the first question
  regarding the application of science to the challenge posed by article 2 of the UN Climate Convention,
  emphasises that 
  <i>"Climate change decision making is essentially a sequential process under general uncertainty"</i>.
  This implies that we should try to make some decisions now rather than wait for perfect knowledge, but be prepared to adapt them later as the science evolves.   <li>see @ipcclinks

Rather than either fixed stabilisation pathways or no-climate-policy "scenarios",
  we could investigate "strategies" incorporating deliberate climate-policy feedbacks, which are robust in response to unexpected changes, working by "geocybernetics" or @fuzzycontrol rather than either forward or "inverse" calculations. The structure of this model has been designed with this in mind.

This process may be aided by the development of "intermediate complexity" climate system models, that are sufficiently complex to reveal non-linear surprises and regional impacts, but fast enough to be used in an Integrated Assessment problem-solving framework.

However,  models are only useful if more people understand how they work, and the ultimate ?integrated assessment model? remains the global network of human heads. This web model is developed as a window into these processes, to enable more people to become involved. It may also enable feedback between people, to provide the @dialogue, which must accompany any decision-making process.

Generally, experts tend to assume that other fields are simpler than their own. Consequently, natural scientists emphasise possible non-linear climate surprises, and suggest that we change human behaviour to avoid such risks, whereas social scientists point out how difficult that is, and might be more optimistic about adaptation or technological solutions.

However there is a fundamental difference between uncertainty in natural science, and in social science. Regarding for example, the @heatflux sensitivity, we can try to find out more about it, but we can't change it (unless you consider ?climate engineering...?). This does not apply to discovering which of the SRES "worlds" we inhabit (see @aboutsres)! This is a philosophical question, the old debate between "fate" and "free-will". The traditional academic system encourages scientists (of all disciplines) to be rather fatalistic, which can frustrate policymakers and the public.   

See also @uncertainty, @uncertburden

#whobau		¨oldJCM4		§We should be especially careful regarding the use of terminology which implicitly assumes a particular approach to the problem.

Regarding the distribution of future emissions, people emphasising the eventual "destination" tend to speak in terms of sharing <i>"rights"</i> to use the limited <i>"resource"</i> of the atmosphere in a sustainable way, whilst those emphasising current trends tend to speak of <i>"burden-sharing"</i> considering the <i>"mitigation effort"</i> to reduce emissions from a projected <i>"baseline"</i>.

Regarding impacts, perhaps we should remember that for many people, especially farmers or indigenous peoples depending on sustainable ecosystems, as well as for other species of life with which we share this planet, the business-as-usual <i>"baseline"</i> could be considered to be no anthropogenic climate change, the <i>"burden"</i> to be externally imposed climate impacts, and the <i>"effort"</i> to be adaptation!

%%A related issue arises in economic studies, regarding the difference between "willingness to pay" to avoid change, and "willingness to accept" compensation for it. Regarding the latter, in the UNFCCC process small island states request compensation for lost territory, whilst OPEC request compensation for lost oil revenues!%%  
See also @equity

#equity		¨oldJCM4		§We all have to share the same atmosphere: Emissions from one place reach the other side of the world in about a month, although they may remain there influencing the climate for hundreds of years. So climate policy requires a long-term, global agreement. Yet such an agreement will not be implemented effectively unless it also seen to be equitable, for most people of the world, considering many different perspectives of justice. Much mistrust in the global climate negotiations has come about because participants have focussed on only one type of equity (most relevant to their situation), and failed to recognise the perspectives of other groups.

Several types of climate (in)equity may be explored using JCM, following the links below:
  <h4>Responsibility for climate change</h4> This question is being explored under the auspices of the 'Brazilian proposal'. See also:<li>@attributeplot,<li>@responsibility,<li>@attribution
  <h4>Distribution of future emissions quotas</h4>  Should the concept be to share the 'burden' of reducing emissions, or to share 'rights' to use the atmosphere?  See also:<li>@distribplot,<li>@distribution,<li>@convergence
  <h4>Distribution of climate change impacts</h4> This may be the biggest inequity, as the poorest (warmest and most vulnerable) countries are likely to suffer the greatest  impacts. However patterns of regional impacts are still very uncertain, and methods of comparing and aggregating them rather controversial. See also:<li>@regclimap,<li>@regcli,<li>@impacts
  <h4>Distributions over time (Intergenerational equity)</h4>  Both physical and human parts of the climate system have a large inertia due, for example, to slow mixing of heat and carbon in the ocean, and slow changes in infrastructure, technology and lifestyle. So actsions now affect the legacy we leave for our grandchildren and beyond. See also:  <li>@inertia,<li>@stabpathways
  <h4>Other issues</h4>  <li>Coping with uncertainty requires additional effort, but who has to bear this depends on the type of policy targets chosen: see @uncertburden  <li>We should beware of loaded terminology: see @whobau  <li>We also share this planet with many other species, who also deserve a stable future climate and habitat. Interactions between climate change and biodiversity are complex and not yet considered in JCM, but should not be forgotten.
  <hr>
See also @equity

#concept		¨oldJCM4		§The original @oldconcept page dates from 2001
See also 
@dialogue

#oldconcept		¨oldJCM4		§<i>Abstract for IGBP Global Change Open Science Conference Amsterdam 1013 July 2001
  (which also included @oldfuture) </i>
  <hr>
  As we share a common atmosphere, safely controlling our global greenhouse experiment requires the cooperation and engagement of citizens worldwide. This requires better public understanding, at least of the scale of the problem, the slow time responses, and the relative importance of various scientific uncertainties and policy, technological and lifestyle choices. Yet even simple climate models illustrating these factors seem mysterious, even among climate policymakers.

  The Java Climate Model aims to help bridge that gap, by enabling anybody on the web to experiment with climate models and policy options. Parameters are adjusted simply by dragging graphical controls with a mouse in a web browser, causing an instant response in several linked plots (including regional and per-capita emissions, carbon cycle, radiative forcing, global temperature, sea-level, regional climate maps, etc.) Thus the human-carbon-climate system is presented in a dynamic, mechanical way, so it?s easy to see ?cause and effect? by ?playing? with parameters. This is not another "data visualiser" but a complete model, yet fast and compact (downloadable in a few seconds, then also working offline).

  To enhance credibility, the core calculation implements the same simple upwelling-diffusion carbon-cycle and climate models (fitted to AOGCM results), as used to make many of the smooth-curve plots in the recently published IPCC TAR (WG1). Although these U-D box models are conceptually simple, it has nevertheless been challenging to develop an instant response to moving controls. This was achieved using an efficient but exact eigenvector-matrix calculation method, originally developed by Jesper Gunderman for DEA-CCAT's earlier online web model. To check the accurate fit to the IPCC predictions, the SRES data tabulated in the report may be plotted alongside the model curves.

  All model calculations are within one timestep loop, therefore climate-carbon and other biogeochemical feedbacks are easily incorporated. Deliberate climate-emissions policy feedbacks or "geocybernetics" may also be investigated. Despite efforts to explain models, many policymakers don't trust predictions and prefer to respond after observed changes. Some problems with a responsive approach to climate control are illustrated by formulae adjusting emissions according to recent temperature trends. The slow response from emissions to impacts leads to oscillations, exacerbated by misleading effects of temporary aerosol cooling. Nevertheless specified targets may be approached this way.

  The Java model is also intended to enable feedback between people worldwide, and to broaden the discussion beyond english-speaking experts.

  Therefore the code structure is internationalised, making it easy to translate all the labels and pop-up information into any language (including Chinese) This may also be useful within the UNFCCC context.

  The model shown here is more an evolving ?proof of concepts? than a finished product,
  Therefore much further development is anticipated. Please read @future

#dialogue		¨oldJCM4		§Steering our global ship to identify and  avoid "dangerous anthropogenic interference in the climate system" (@art2) requires balancing many risk and value judgements. Computer models may help provide a quantitative framework to help resolve the effects of complex interacting processes. Yet these models remain a mysterious "black box" to all but a few experts, whilst to effectively implement any global agreement requires the active engagement of many citizens around the world. So we need some "democratisation" of climate science, as the ultimate  "integrated assessment model" will remain the global network of human heads.

  The Java Climate Model is designed to assist this dialogue, by enabling anybody to explore both mitigation policy options and scientific uncertainties simply by adjusting parameter controls with a mouse in a model launched from a web browser. The instant response on linked plots helps to demonstrate cause and effect, and the sensitivity to various assumptions, risk and value judgements.  

Moreover the code is  internationalised for easy @translation into many languages, and the model is compact and fast, considering users with slower computers and connections (@howfast). 
JCM has already been applied to both teaching and policy: 
@teaching 
@applications. 

The eventual aim is to link people from around the world to debate our future climate  choices across the web -  @remotecontrol  describes some technical experiments towards this aim.

  See also 
@future, 
@localtolocal,
@equity

#localtolocal		¨oldJCM4		§To engage people, we need to tell them how local emissions which they can influence, can change local impacts which affect them directly. Completing this loop, upscaling and downscaling via vast global natural and human systems (we have to assume some cooperation) is a challenge for any model, especially a fast interactive online tool. Currently JCM combines regional emissions and socio-economic data from the SRES scenarios (@aboutregions), with climate impact maps from a range of GCMs. (@regclimap), but this is still rather statistical and abstract. Eventually, plug-in modules should be developed which illustrate much more tangibly future climate impacts and specific actions  to reduce them.

#future		¨fut		§Main developments anticipated in @JCM6  <ul>
<li>Any chain is only as strong as its weakest link, this is especially true of integrated  assessment tools such as JCM. Therefore we should focus particularly on @impacts, see also @regclifuture 

<li>The core science modules of JCM, based on IPCC-TAR, need to be updated: see @AR4update

<li>The @aviashipemit and @aviationforcing modules will  be developed further, to contribute to the project "Avaiation and Belgian Climate Policy"

<li>@scripting (for probabilistic applications etc.)  will be made easier in @JCM6, using new capabilities of Java6, see @javafuture

<li>  Recalling that the ultimate aim of JCM is to help provide a @dialogue,
  continued effort will be made with @translation and applications for @teaching.  
</ul>

Can you help? Please get in touch (@contact)


<hr>
Below are some very old @JCM4 pages about future work (some of which may be already completed! - to be checked)
<ul>
<li>@carbonfuture  
<li>@oghgafuture  
<li>@radforfuture  
<li>@climodfuture 
 <li>@sealevelfuture
<li>@peoplefuture  
<li>@uncertfuture
<hr>
<li>@oldfuture, 
<li>@localtolocal
 </ul>
----
Taking a really long-term view, we might also consider adapting JCM: <ul>
<li>As a tool within a @globref, recalling the original vision of //chooseclimate.org//
<li>As a @climategame, recalling that people learn best by trial and error, and can spend a lot of time playing games! 
 </ul>

#oldfuture		¨fut		§<i>Note: This page dates from summer 2001!</i>

  The model shown here is more an evolving 'proof of concept' than a finished product, and much further development is anticipated.

  Many more variants on policy proposals are envisaged. Modules will be developed in-situ during the evolving global climate negotiations over the next few months, in response to suggestions. Although the current focus is on details of 'flexible mechanisms', we need long-term global proposals in order to calculate the climate impact, and should consider defining 'strategies' rather than fixed 'scenarios', in order to be robust against uncertainties.

  The networking features of Java could enable distributed groups to interact with the same model over the internet, using shared parameters as a quantitative framework for science or policy discussion. Thus the java model encourages direct dialogue between different stakeholder groups, rather than via experts, and enables citizens to balance risks, values and equity from various viewpoints.

  The technique for coding 'remote control' might also be applied to construct educational demonstration sequences in response to 'frequently asked questions'.

  The regional climate impact map already shown, illustrates the importance of thinking beyond global average figures, and many more plots could be developed with more sophisticated scaling. Dynamic graphics illustrating local and sectoral impacts should also be developed.

  The rapid response of the core science modules suggests that more sophisticated calculations are possible -eventually moving towards intermediate complexity models. It is particularly important to include more biogeochemical feedbacks, especially when extending the model over longer timescales. Suggestions are welcome regarding feedback parameters or model structures.

  The flexible modular code structure (which will be partly "open source") encourages development of additional "plug-in" components. These may eventually be linked to larger '3rd generation Integrated Assessment models' which are also expected to share modules across the web.

  So there is much potential, and any ideas for cooperation would be most welcome.

#acknow		¨oldJCM4		§Many people have helped during development of JCM 
(see also @develop).
  ££acknowmain 
<hr>
££acknowsupport 
<hr>
££acknowtranslate 
<hr>
££acknowmodels

#acknowmain		¨oldJCM4		§%%(in chronological order)%%
<li>Jesper Gunderman and Peter Laut (<nobr><a href="http://www.dea-ccat.dk" target="_new">DEA-CCAT Copenhagen</a> </nobr>), who provided the vital "break" inviting me to work with them in Copenhagen, and explaining their methods for solving the models.

<li>Brian Lucas, Lawrence Hislop, Aake Bjorke, and many others in <nobr><a href="http://www.grida.no" target="_new"> UNEP/GRID Arendal</a></nobr>, for a great working experience and insight in design and communications.

<li>Fortunat Joos (<nobr> <a href="http://www.climate.unibe.ch" target="_new"> KUP Bern</a> </nobr>), and many others in Bern, for sharing much insight into carbon/chemistry/climate models, also Jose Romero (BUWAL) for enthusiastic support of this project.

<li>Jean-Pascal van Ypersele (<nobr><a href="http://www.climate.be" target="_new"> UCL Louvain-la-neuve</a></nobr>), for support and encouragement for the longer-term development of JCM, and building bridges between research, policymaking and education.

<li>Christiano Pires de Campos (<nobr><a href="">IVIG, Rio de Janerio</a></nobr>)  for developing  @jcm.luc,  and for  much inspiration during all our work together here in UCL-ASTR in 2005,

</ul>

<hr>
 Acknowledgements due also to colleagues in Global Commons Insitute for introducing me to climate policy, to friends in Edinburgh who helped me during spring 2001, and to many others who gave ideas and encouragement regarding the model. 
Not least, I thank friends in many places, who helped this "nomad with a laptop" to feel at home and to escape the computer occasionally to enjoy the real world!

#acknowtranslate		¨oldJCM4		§Much thanks to the following  who helped to translate the JCM4 model labels (most recent first): <ul> <li>Martine Vanderstraaten (Flemish/Nederlands)  <li>Theres Grau (Deutsch)  <li>Jose Corcho Alvarado (Español)  <li>Phillipe Rekacewicz & Gilles Delaygue (Français)  <li>Suraje Dessai (Português)  <li>Nikolai Denisov (Russian)  <li>Petter Neumann (Norsk)  <li>Jesper Gunderman (Dansk)</ul>
<hr> Some parts of french documentation were also translated by students at UCL 

  Can you help with another language?  See @translation, @contact

#acknowsupport		¨oldJCM4		§Financial support in developing JCM is acknowledged, from
<ul>
<li>Belgian Science-Policy (BELSPO) via UCL-ASTR, for <ul>
<li>ClimNeg II project (2003-2005)
<li>Aviation Belgian Climate Impacts project (2006-2009)
<li>Support for assistance with IPCC work (2005+)
</ul>
<li>Swiss Government (BUWAL)  (2002)
<li>EnergiMiljoradet (Danish Council for Sustainable Energy)   (2001)
<li>Danish Energy Agency  (2001)
<li>UNEP-GRID (overheads in Arendal)
</ul>

#acknowmodels		¨oldJCM4		§As JCM aims to reproduce IPCC predictions, it incorporates formulae from many research groups.
  Although "simple" carbon/climate models can be described with relatively few boxes/equations, the validity of such "conceptual" models depends on the careful tuning of the parameters, to capture the response of more complex GCMs, or to match historical measurements.
  This is not an easy task, and these models have taken years to develop.

  So, the effort that has gone into the original models, should also be acknowledged, particularly the Bern model used for the carbon-cycle / chemistry in JCM, and the Wigley-Raper model used for the temperature / sea-level.

  Many sources of data are also acknowledged, particularly from RIVM's Image model used for the socioeconomic data, from CDIAC for national emissions data, and from IPCC-DDC for regional climates.

See @references for more detail

#contact		¨oldJCM4		§<h2>Dr Ben Matthews</h2>
<img src="../backpic/BenSevillavSmall.jpg" align=right>
//(a picture of me attending a recent scenarios workshop in Sevilla)//
<hr>
To contact me email <i>
<-{blue matthews AT climate.be}-

  I am now working at UCL-ASTR:
  <a href="http://www.climate.be" target="_new">Institut d'Astronomie et de Géophysique</a> Georges Lemaître
  Université Catholique de Louvain
  Louvain la Neuve, Belgium 1348

  <hr>
Many others contributed to development of JCM, 
  see @develop 
note also @acknowtranslate

#topmenu		¨oldJCM4 addJCM5		§@back+€€back @forward+€€forward @docsearch+€€search  ..... @mainmenu+€€home   @welcome+€€intro @howuse+€€tool   @aboutjcm+€€jcmb @tech+€€tech @jcm_root+€€root   ..... @jcm.mod.obj+€€sres @jcm.mod.socio+€€popu @jcm.mod.regemit+€€emit @jcm.mod.luc+€€luc @jcm.mod.carbon+€€carbon @jcm.mod.ogas+€€othgas @jcm.mod.cli+€€temp @jcm.mod.regimp+€€clou @jcm.mod.resp+€€point

#usehelpmode		¨oldJCM4 addJCM5		§%%€€adju Note: to quickly find relevant documentation for any £`package, £`module, £`param, or £`qtset, enable the documentation @filter in a @jcmtree %%