August 18th, 2025 - NEW : G2WS's first MVP
CCEM (version 7) will be made available as a stand-alone Web page.
G2WS (Geopolitical Global Warming Simulator) is a simple simulator that allows the user to experiment with the system dynamic model and see how it reacts (a) when you change the major system beliefs (the KNUs) (b) when you change the policies of the five geopolical blocks (US, EU, China, India, RestOfWord).
We are currently experimenting with a MVP (Minimum Viable Product), that is a public html file g2wsmvp
Warning : this is an ongoing experimentation, you may play with the Web page (clicking on the previous link) at your own risks.
the Web user interface code for G2WS is brand new and not fully tested
CCEM has much fewer bugs but is, by design, under construction and full of limitations. When playing with G2WS, one sees the limits very clearly (which is the purpose of exposing G2WS in an early stage).
G2WS exposes a few KNUs (known unknowns) that you may experiment with (using a slider) but some other key model parameters are still hidden. This will change in the future, as G2WS evolves towards a digital product.
To learn more about G2WS, read the tutorial.
July 17th, 2025
Version CCEM v7 was completed and released on GitHub.
For french readers, you may find a story about v7 in my last blog post.
CCEM v7 introduces a more detailed and better calibrated damage model, with damage types explicitly categorized and linked to temperature rise. The model includes:
Property damage (based on insurance data), with causes such as loods, hurricanes, heatwaves, and droughts
Loss of working hours, incapacitated workers, sickness, and mortality
Agricultural losses, with bibliographic updates
Impact on population dynamics, both the increase of death rates and the lowering of birth rates.
The damage function now follows a tree structure, enabling differentiated responses by damage type and zone. The model also includes IPCC AR6-based recalibration to better connect CO₂ levels with temperature and resulting impacts.
A major improvement in v7 is the explicit modeling of adaptation as a form of investment. Adaptation:
Reduces the effective damage from climate impacts
Follows a return-on-investment (RoI) logic, with zone-specific attenuation curves
Includes a cumulative benefit effect, highlighting the advantage of early investment
Is implemented via a new “KNU” (known unknowns) representing strategic beliefs
Adaptation costs and effects are integrated into the local optimization ("tactic") engine, and results (adaptation spending and avoided damages) are tracked and displayed. The model captures realistic deployment constraints and includes a notion of volume discounts.
3. Energy Transition
The transition model in CCEM v7 reflects updated thinking from recent literature, particularly Greg de Temmerman’s work:
Transition arcs between energy types now include efficiency gains, especially in electrification (Carnot principle)
Efficiency ratios are defined per transition, allowing precise modeling (e.g., fossil → electric transition with reduced final energy need)
Net effects include asymmetrical energy shifts (e.g., -100% fossil, +50% electricity)
A bug in previous models related to transition cost allocation has been fixed
In v7, CCEM replaces its former CO₂ concentration model with a TCRE-based warming function, linking cumulative anthropogenic emissions directly to temperature rise:
Based on recent IPCC guidance (AR6), this approach eliminates the need to model atmospheric concentration dynamics
Simplifies the climate feedback loop while maintaining sufficient realism
Aligns well with observed data over the last 40 years (e.g., ~54% of CO₂ emissions accumulating in atmosphere)
Supports new simulations for RCP 4.5 and RCP 6.0, with updated warming estimates (e.g., 2.7°C and 3.2°C respectively)
The optimization routine in CCEM has been significantly improved:
Previous local descent approaches have been replaced by sampling and nested search algorithms
New tools such as topt and toptp explore tactical parameter space more robustly, escaping local minima
Enables true Best Response calculations: finding the optimal tactic for one actor given the others’ strategies
Demonstrated for regions like Europe and China: responses differ depending on external transition behavior
Paves the way for Nash Equilibrium research in future CCEM v8
December 31st, 2024
First post about CCEM in my English blog "Biology of Distributed Information System":
this blog post presents:
Hello Future!, a great book about 2035 by Langdon Morris
a short update on CCEM v6 (cf. below)
A manifesto (EM3) that advocates the disclosure of energy hypotheses (beliefs) when presenting 21st century scenario produced from a model (IAM, SDEM, etc.)
A short narrative that describes part of the content of the FormAction presentation of December 4th, 2024.
December 4th, 2024
Presentation of CCEM to FormAction (on the invitation of Erik Grab) of a revised version of the DCAQ talk made in August : the slides are available on Slideshare.
This is the first presentation that used CCEM v6. The narrative is similar to the previous talk, but using constant dollars figures makes for a more compelling presentation.
CCEM v6 is now available on GitHub. Here is a short description of the main changes compared with v5:
The world in CCEM is divided into geopolitical blocks (also called zones). CCEM v6 has added India as a new zone, because of its size, its growing economy and its political strategy. CCEM has now five zones: Europe (27), USA, China, India and RoW (Rest of World).
The most significant change in CCEM v6 is the move from current to 2010 constant dollars to measure GDP. Switching to constant dollars changes the perspective significantly! First, as we show in Section 3, once you remove inflation, you see that energy density is progressing quite slowly over the past decades (with flat periods for some of the zones). Second, and most importantly, World GDP growth is very heterogenous: while US and China have been doing well for the past decade, Europe GDP has actually declined since 2010, a fate shared with “Rest of the Word” on average. Taking this perspective into account has required a significant overhaul of the economy (M4) model, with the introduction of “asset decay” (a feature that is borrowed from “Limit to Growth”) : if nothing is done, productive asset decline in time and their associated return slows down.
Dematerialization of the economy, that this the decline of energy density, has now a simpler but more robust model to accommodate the past 40 decades of historical data. CCEM distinguishes between “dematerialization” and “savings” (efficiency). Dematerialization captures the faster growth of “immaterial” economy (software, services, …) compared to “material” economy. Savings captures the possibility of doing the same economic activities with less energy through technology progress. CCEM works with two beliefs: the first one is an energy density trend that is projected from past data, the second one is a “savings” roadmap (part of the energy transition) where investments into new technology may reduce energy consumption at iso-activity. One way to think of it is that the first belief is the “business as usual” trend of energy density decline, whereas the second parameter is a possible political decision of investing into efficiency
Because 2024 has been used to study the impact of actual fossil fuel reserves and understand how net-zero scenarios could work, the energy supply equations of M1 (energy production model) have evolved to provide a more robust model of adaptation (to energy shortage, to energy abundance, to price increases) as to avoid oscillations (which were present in v4 and v5). Let us recall that energy prices in CCEM are a demand/supply signal and cannot reproduce the fluctuation observed in an open market.
CCEM now includes a set of feedback loops that link “pain” to the economy. Let us recall that pain is a synthetic KPI made of decline of GDP/person, shortages of energy, decline in food/person (using the proxy of wheat production), impacts of global warming. The first feedback loops says that productive labor hours will decline as pain rises (for a multiplicity of causes, such heatwaves, social unrest and strikes, loss of productivity because of engagement decline – a key issue when you listen to workforce sociologists, etc.). The second feedback loop says that pain will lower population growth (or accelerate its decline) both because mortality will increase and because the causes of “pain” will slow down the birth rate.
Ecological redirection is defined in the CCEM model as the portfolio of possible reactions that geopolitical blocks may take. Roughly speaking there are three groups of redirection implemented in CCEM v6: sobriety (voluntary energy consumption reduction through regulation), acceleration of energy transition (three parts: efficiency, renewable energy production and electrification) and taxes (both as carbon tax applied locally and as protectionist measures, such as Europe CBAM: Carbon Border Adjustment Mechanism).
To evaluate the efficiency of redirection, CCEM implements the concept of “Strategy” associated to each zone, which a cost function (evaluation function) that is defined independently for each zone as a combination of GDP growth, Pain minimization, global warming minimization (optional). To evaluate a time-series of future result, we introduce (classical with all IAMs that are defined as optimization problems, such as DICE) future discounting (future results – good or bad – are slightly less important than present ones). This way, long-term thinking (or the absence of) may be easily capture for each zone. The question of what a proper time discount should be is a very hot topic amongst futurists.
The code for searching the demand/supply equilibrium (see game.cl) has been improved through a dichotomic search. As a consequence CCEM v6 is significantly faster than CCEM v5.
KNUs have been introduced as "cones" (that is defined by 3 piecewise linear functions : median, min and max), preparing for randomization of beliefs that will be implemented in 2025.
August 30th, 2024
Another presentation of "A System Dynamics Model for Global Warming Impact, from Energy Transition to Ecological Redirection" was made to Michelin DCAQ summer university, with a focus about En-ROADS.
CCEM v5 released on GitHub. Here are CCEM v5 main changes compared to v4 (IAMES paper is based on v4, while the two last presentations are based on v5)
Change of energy unit : move to PWh from toe (ton of oil equivalent). This change was suggested by my colleagues from NATF, to reflect the 21st century move towards Electricity as the main energy vector. Note that many IAMs use EJ (exa joules) as their main energy unit.
GreenGrowth is a yearly roadmap (not based on prices) to represent possible acceleration and the political nature of the industrial roadmap.
Since electrification is a key KPI (part of a KNU = Key kNown Unknown), CCEM v5 computes the growth of electricity production to produce an approximate value for the electrification KPI
CCEM v5 implements a Feedback loop "less people -> less production", with a “AI factor” that reduces the impact (0 -> AI absorbs the reduction of workforce, or older non-productive people are more targeted). This is a new Key Known Unknown !
CCEM v5 uses a new, simpler CO2 concentration model, where a faction of emitted CO2 is absorbed (ocean, forrest, land ...) and the rest (54%) is added to the atmosphere
The previous model based on a fixed absorbtion capacity does not match the existing data
this rough approximation matches the Wikipedia page on the cycle of CO2 ...
building a better model will be a goal of CCEM v7.
Protectionism (import taxes, CBAM or public boycott) is now implemented: Each zone may decide to reduce import/export based on difference in CO2/Energy and CO2 taxes
Energy transition is a political decision (a factor from 0 to 100% = fastest possible transition based on belief)
Here is a crude roadmap of CCEM versions and how they fit into the global plan of producing "serious games".
GW2S stands for "Geopolitical Global Warming Simulation", it is meant to be similar to En-ROADS.
GW3S stands for "Geopolitical Game of Global Warming Simulation" : it extends GW2S with the game theoretical aspects using the GTES framework.
Note that the IAMES paper, "CCEM: A System Dynamics Earth Model for Capturing Beliefs Related to the Coupling of Energy, Economy and Global Warming", is now available on line as an IFACS publication.
June 24th, 2024
Presentation "A System Dynamics Model for Global Warming Impact, from Energy Transition to Ecological Redirection" to AXA IM
Video capture is available on Vimeo.
May 26th; 2024
Launch of this web site (http://modelccem.eu).
Stay tuned, this is "work in progress".
CCEM presentation to IAMES 2024
paper may be found here.