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Introduction Java Climate Model, Scenarios to limit global warming to 2°C, +> implications for Introduction Java Climate Model, Scenarios to limit global warming to 2°C, +> implications for Brazilian energy sector Presentation for COPPE-EPD 24 Aug 2011, Cenergia (+a few updates from later presentations) Dr Ben Matthews Université catholique de Louvain (UCL) Centre de recherche sur la Terre et le climat Georges Lemaître (TECLIM) in IVIG, COPPE 14 may - 25 august 2011 matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

 • • . . . who is this. . . ? 90 -93 • • . . . who is this. . . ? 90 -93 Univ Edinburgh - focus environmental chemistry +. . . 93 -00 Ph. D UEA Norwich - Air-Sea CO 2 Fluxes, catalysis marine algae + European Study of Carbon in Ocean Biosphere Atmosphere + project Qingdao Ocean Univ China + UNFCCC COP 2 (GCI) COP 3 Kyoto (SGR) • 01 -02 early development JCM • 02 -11 UCL-TECLIM (formerly ASTR - Louvain-la-Neuve Belgium) • now here in IVIG. . . (until mid august) Denmark DEA, Norway UNEP-GRID, Switzerland Univ-Bern + COP 6, 7. . . + projects CLIMNEG, ABCI + support to IPCC vice-chair, IPCC scenarios process + support European UNFCCC science expert groups (SBs, COPs 1416) + MATCH, project INFRAS (swiss), UNEP paper etc. matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

 • • Overview: Range climate models, introducing JCM Some specific issues • • • • Overview: Range climate models, introducing JCM Some specific issues • • • Historical contributions & Alternative metrics Global 2°C pathways Regional emissions, pledges, effort-sharing, equity new Energy module Demonstration JCM matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

 • • • (AO)GCMs - Global Climate (General Circulation) Models Various types of • • • (AO)GCMs - Global Climate (General Circulation) Models Various types of climate models (AO = coupled Atmosphere and Ocean) 3 D models based on real physics (box size about 0. 5°-2. 5°=> parameterised clouds, vegetation etc. ). GCMs evolve towards ESMs (Earth System Models) including coupled biogeochemical cycles and ecosystem responses. Include intrinsic variability. Running multi-century scenarios takes weeks of computation. RCMs - Regional Climate Models: 3 D models with higher resolution for regional impacts studies - better clouds, topography Focus on one region (eg NE Brazil) over short timescale (eg decade). “Nested” within GCM providing boundary conditions. EMICs - Earth-System models of Intermediate Complexity “ 2. 5 D” models first designed to study long paleoclimate timescales (eg glacial cycles), => much faster than GCMs, but incorporating nonlinear physical and biogeochemical feedbacks and “tipping points”. Useful for long-term future, especially sea-level rise. IAMs - Integrated Assessment Models Designed to explore wide range of mitigation scenarios / climate policy proposals. Simpler parameterised physics and carbon cycle, but better socio-economic projections, maybe including energy sector, land-use change, optimisation, equity etc. matthews@climate. be, JCM - Java Climate Model - model: www. climate. be/jcm / where does this fit ? jcm. ivig. coppe. ufrj. br began as interactive tool for global dialogue, evolved to be between IAMs and

Socioeconomic complexity Range of model complexities / specialities National energy planning models Future supercomputer Socioeconomic complexity Range of model complexities / specialities National energy planning models Future supercomputer clusters / cloud? complex IAMs (IMAGE, MESSAGE, AIM. . . ) JCM all-round, interactive simple IAMs (optimisation, game theory - eg RICE) ESMs (CLIMBER, Mo. Bi. Dic. . . ) algebraic models (old, for teaching) EMICs (>1000 yrs) (Had. EM, . . . ) GCMs RCMs (Had. CM, ECHAM, GISS. . . ) (Precis CCLM, . . . ) Physical complexity / resolution Fast (many scenarios) - Medium - Slow (few scenarios) Regional (+shortterm) matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

Model complexity <=> applications Complex 3 D models Intermediate Complexity Simple models (- eg Model complexity <=> applications Complex 3 D models Intermediate Complexity Simple models (- eg IPCC) Strengths Physical realism, High-resolution, variability Biogeochemical feedbacks, Long timescales (paleoclimate) Visualisation, Transparency Accessibility, Simplicity Weaknesses Slow, not flexible, few scenarios, few people can use Role in • Calibrating simpler Integrated models Assessme • Extreme events nt Reports Neither intuitive Lack physical Lack flexibility, nor realistic => basis Lost information hard to interpret - don’t use alone (esp. coupling) • Probabilistic • Explore options Risk analysis • Long-term (SLR) • Tipping points /risk-value choices • Stakeholder dialogue matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br Consensus Synthesis

Linking / intercalibrating models and scenarios So - for whole climate problem we need Linking / intercalibrating models and scenarios So - for whole climate problem we need a suite of models, not one Need to be consistent, inter-calibrated, with coherent scenarios • • IPCC (WG 1) new Representative Concentration Pathways GCMs => full range climate response => tune IAMs IPCC (WG 3) new socioeconomic scenario library (? ) incorporate into IAMs, compare diff sources / resolutions /timescales • both => Impacts and Adaptation (IPCC WG 2) + need iterative feedback => needs more time ! matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

Introducing Java Climate Model matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. Introducing Java Climate Model matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

Special focus of JCM • • Global Stabilisation Scenarios (2°C etc. ) - multi Special focus of JCM • • Global Stabilisation Scenarios (2°C etc. ) - multi gas, multi-indicator, flexible pathway shapes. . . - sensitivity to climate, & carbon cycle uncertainties - sharing of emissions / effort between countries Interactive tool for global dialogue - enable people to explore relative sensitivity to policy options and scientific uncertainties: “the ultimate integrated assessment model is the global network of human heads” • Core science copied from other models and IPCC reports. Fast, efficient implementation convenient for both: - interactive exploration useful for teaching - integration over uncertainty - risk analysis matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

Physical science of JCM • • • Bern carbon model including climate feedbacks and Physical science of JCM • • • Bern carbon model including climate feedbacks and ocean chemistry Atmospheric chemistry and radiative forcing calculated for >30 gases and aerosols UDEB climate model (parameters tuned to fit GCMs) Originally intended to be consistent IPCCTAR, mostly updated to AR 4 Speciality - inverse calculations to stabilise temperature matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

 • • • Regional Emissions Scenarios Regional data CO 2, CH 4, N • • • Regional Emissions Scenarios Regional data CO 2, CH 4, N 2 O, CO 2 eq, population, GDP, . . . Diverse region sets depending application Calculates by country 1750 -2050, by region thereafter (=> 2300+) Calculates LUC emissions from biome changes Originally - top-down sharing, convergence, depending population, GDP, etc. Recently - added “pledges” to 2020 + gradual participation approach thereafter matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

Other applications of JCM • • Historical Contributions to climate change (ACCC/MATCH) + focus Other applications of JCM • • Historical Contributions to climate change (ACCC/MATCH) + focus historical landuse change with IVIG (revisit? compare “carbon space”, “equitable access to sustainable development? ”) Aviation scenarios incl climate impact cirrus clouds/other gases (ABCI) (comparison short/long-lived gases - reapply to issue GWP, GTP ? ) • Economic analyses - sensitivity to scenarios and integration over regions, wealth, time, and uncertainty/risk (Climneg 2 project) matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

 • • Overview: Range climate models, introducing JCM Some specific issues • • • • Overview: Range climate models, introducing JCM Some specific issues • • • Historical contributions & Alternative metrics Global 2°C pathways Regional emissions, pledges, effort-sharing, equity new Energy module in JCM Demonstration JCM matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

Historical contributions / Alternative metrics • • Link to COPPE - IVIG was via Historical contributions / Alternative metrics • • Link to COPPE - IVIG was via MATCH Special focus on historical contributions from land-usechange matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

=> Integrating over time / gases • MATCH/ACCC - historical contributions to CC • => Integrating over time / gases • MATCH/ACCC - historical contributions to CC • Future contributions of different gases - technically similar still relevant in equity discussions (comparing e. g. Indian proposal “carbon space”) Impact of each ton CO 2 / other gas changes with time, * lifetime/decay in atmosphere => changing climate impact * technology evolution => changing contribution to sustainable development question, - alternatives to GWP for comparing short/long-lived gases - depends impact of most concern (eg biodiversity vs sea-level rise) - also depends reference scenario - e. g. 2°C not constant concns - => We should consider new metrics, not only GTP + calculate tables differences variants, write joint paper input IPCC-AR 5 ? matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

=> Integrating over time / gases (contd. . . ) • Original “Brazilian-proposal” • => Integrating over time / gases (contd. . . ) • Original “Brazilian-proposal” • • Transparent “Policymaker model” good concept (but now computer-tools can replace algebra) “Double integral” was misleading, - Atmosphere has little heat capacity to accumulate warming, - Second integral applies to deep ocean + ice-melt => Sea-level rise, not surface Temperature Revised Brazilian proposal JM+GM-F, and more recent presentations (eg UNFCCC workshop 2009) • • • Still greatly over-estimated duration of temperature response, + why exclude other gases + LUC ? => misleading results now help delay / excuses by China etc. GWP is different issue - not only temperature in one year • • compromise to integrate all impacts including rate of warming, SLR, regional. . . not constructive to tell UNFCCC that IPCC all wrong. . . matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

Global 2°C stabilisation pathways • • • Policy compromise to interpret UNFCCC Article 2 Global 2°C stabilisation pathways • • • Policy compromise to interpret UNFCCC Article 2 European Policy since 1996, global policy since 2009 (Copenhagen / Cancun) But is it enough to avoid dangerous impacts ? What does this imply for emissions pathways? What is acceptable risk of passing this level? Stabilisation under uncertainty First 2°C probabilistic analysis with JCM in 2003 Pathway Shape New pathways (Swiss INFRAS project) UNEP “Gap” report and other recent papers matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

2°C Stabilisation under uncertainty - 2003 Example below from presentation of Matthews & Van. 2°C Stabilisation under uncertainty - 2003 Example below from presentation of Matthews & Van. Ypersele at WCCC 2003 Moscow, also to EU strategy Firenze. Shifting from concentration to temperature target shifts the burden of uncertainty from impacts to mitigation matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

JCM: 2°C / 1. 5°C pathways after the 2020 pledges No ra Ca pi JCM: 2°C / 1. 5°C pathways after the 2020 pledges No ra Ca pi vea d ice t: m el t! matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

Relating temperature - concentration Global average temperature rise above preindustrial (for best-guess model parameters) Relating temperature - concentration Global average temperature rise above preindustrial (for best-guess model parameters) CO 2 equivalent concentration Including all GHG gases and aerosols Dotted lines – CO 2 only (from Java Climate Model – jcm. ivig. coppe. ufrj. br or jcm. climate. be)

Relating concentration - emissions CO 2 equivalent concentration Solid lines - including all GHG Relating concentration - emissions CO 2 equivalent concentration Solid lines - including all GHG gases and aerosols Dotted lines – CO 2 only CO 2 equivalent emissions Solid lines – All gases + LUC Dotted lines – Fossil CO 2 only (from Java Climate Model – jcm. ivig. coppe. ufrj. br or jcm. climate. be)

UNEP “Gap” report, EGSci paper (Cancun) Both apply probabilistic approach (>66% chance <2°C), compare UNEP “Gap” report, EGSci paper (Cancun) Both apply probabilistic approach (>66% chance <2°C), compare many IAM scenarios Key message: 2020 pledges are not enough, about half-way there. If emissions peak higher, they decline at unfeasible rates later. matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

UNEP “Gap” 2010 matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. UNEP “Gap” 2010 matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

Conclusion EGSci 2010 • The Copenhagen Pledges are indeed a first step in the Conclusion EGSci 2010 • The Copenhagen Pledges are indeed a first step in the right direction, but are by themselves not enough for the reductions we need by 2020. • Instead further steps are necessary to enhance these pledges in a binding agreement to bring 2020 emissions to a level that does not burden future generations with potentially unfeasible emission reduction rates. • This document was commissioned and is now provided with the intent to inspire and assist in discussions working towards a post-2012 climate agreement. “Scientific Perspectives after Copenhagen” December 1 st, 2010 Cancún, Mexico

Regional emissions, pledges, effort-sharing, equity • • • Current emissions distribution 2020 Pledges / Regional emissions, pledges, effort-sharing, equity • • • Current emissions distribution 2020 Pledges / NAMAs Peaking Historical contributions, vs feasibility Equity matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

CO 2 Emissions (per capita) 1990, 2000, 2010 Bars: width: population, height CO 2 CO 2 Emissions (per capita) 1990, 2000, 2010 Bars: width: population, height CO 2 per capita, area CO 2 lower part Energy CO 2 upper part Land-Use CO 2 (white = negative) Africa Brazil W. Europe China USA Brazil China Brazil USA (2010 is estimate based on 2009 data, extrapolation energy intensity trends)

Copenhagen Pledges / NAMAs 2020 + percapita emissions 1990 -2020 Copenhagen Pledges / NAMAs 2020 + percapita emissions 1990 -2020

CO 2 Emissions/GDP (intensity) - 2005 and 2020 matthews@climate. be, model: www. climate. be/jcm CO 2 Emissions/GDP (intensity) - 2005 and 2020 matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

2050 emissions and peaking • • Cancun mandate to COP 17, Durban 2011: to 2050 emissions and peaking • • Cancun mandate to COP 17, Durban 2011: to agree 2050 global emissions goal and peaking timeframe - crucial to give signal for longterm infrastructure investments global total constrains China more obviously than Brazil of course, peaking is earlier in some countries than others. . . integral of emissions may be better indicator for avoiding 2°C matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

CO 2 eq Peaking later in developing countries 2°C stabilisation scenario, global peak 2020, CO 2 eq Peaking later in developing countries 2°C stabilisation scenario, global peak 2020, CO 2 eq includes energy+LUC CO 2, CH 4, N 2 O China USA India CFCs Africa Russia Brazil

CO 2 Peaking later in developing countries 2°C stabilisation scenario, global peak 2020, energy CO 2 Peaking later in developing countries 2°C stabilisation scenario, global peak 2020, energy CO 2 only China India USA Africa Russia

CO 2 eq per capita (same 2°C scenario) 2°C stabilisation scenario, global peak 2020, CO 2 eq per capita (same 2°C scenario) 2°C stabilisation scenario, global peak 2020, CO 2 eq includes energy+LUC CO 2, CH 4, N 2 O

Historical contribution to temperature rise, per capita (including emissions of CO 2 (energy+LUC), CH Historical contribution to temperature rise, per capita (including emissions of CO 2 (energy+LUC), CH 4, N 2 O, since 1890, for same 2°C scenario)

Emissions Pathways 2020 -2050 Per capita CO 2 emissions (left) and rate of decline Emissions Pathways 2020 -2050 Per capita CO 2 emissions (left) and rate of decline %/year (right) Scenario -50% wrt 1990 by 2050, multiple participation / sharing criteria matthews@climate. be, model: www. climate. be/jcm,

 • • Equity Issues The greatest inequity is in the distribution of climate • • Equity Issues The greatest inequity is in the distribution of climate change impacts - think first about the most vulnerable countries /regions In UNFCCC, “Equity” has become “excuses” (for China). . . ? Emphasis historical responsibility / “Equitable Access to Common Atmospheric Space” => delay action => greater warming => greater inequity • • => How to broaden the equity debate? Include both mitigation + impacts Interpret “Equitable Access to Sustainable Development”? Global 2050 target - Annex 1 target => implied developing country limit? Equal per capita: Ax 1 approx -86% wrt 1990 by 2050 if global -50% (European position: Ax 1 -80 to -95%) matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

JCM Energy module (under development): • To use JCM to calculate projection for Brazilian JCM Energy module (under development): • To use JCM to calculate projection for Brazilian energy sector • How to differentiate extra reductions by sector / fuel ? • Not only energy supply - what about changing demand? - need sectoral energy module ( JCM regional shares module only based on political / equity criteria ) - shift towards lower-carbon energy, some options cheaper / more capacity energy efficiency, buildings, transport infrastructure planning etc. Relation energy / land-use change? - distribution of effort energy vs LUC, implications of biofuels for landuse, capacity. . . matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

JCM Energy module - Characteristics: BUT. . . For pathways avoiding 2°C warming, need JCM Energy module - Characteristics: BUT. . . For pathways avoiding 2°C warming, need long-term global perspective • Timescale climate stabilisation at least 150 years, and global emissions reductions >>50% • => Essential to consider investment in infrastructure, with learning • Extrapolation of trends can’t capture this, nor can “equilibrium” model or MAC (power plants, new transport networks, buildings and planning. . . ) approach => disequilibrium / dynamic partial-equilib / agent based approach • Need all regions, all sectors to get global total (and hence climate, 2°C. . . ) + global trade => fossil fuel prices, energy intensive goods, technology transfer, carbon market Too much for a few weeks. . . matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

JCM Energy module - Progress: • • Incorporated data to JCM from IEA- WEO JCM Energy module - Progress: • • Incorporated data to JCM from IEA- WEO 2010 (16 regions, 3 scenarios, , various fuels+renewables) Created energy-data module to view / explore these scenarios Start to develop dynamic model - start Electricity sector, convenient investment cost data (IEA) + technical potentials (SRREN) - considered challenges Transport sector - ? ? how to acccount for buildings, construction, energy intensive goods. . • More time needed to complete. . . matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

JCM Energy module - IEA scenarios: Example IEA 450 Scenario Regional CO 2 Emissions, JCM Energy module - IEA scenarios: Example IEA 450 Scenario Regional CO 2 Emissions, Energy Sources (TPED) matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

 • • JCM Energy module - Electricity: Regional capacities starting from IEA data, • • JCM Energy module - Electricity: Regional capacities starting from IEA data, Capacity investment depends expected price Investment costs from IEA (with learning), regional technical potentials from SRREN, . . . • Very sensitive to interest rates, as well as carbon price etc. • To add: Efficiency, dynamic learning, CCS, Extra capacity for peak demand. . . Electricity Production, Costs, CO 2 Emissions matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

JCM Energy module - Transport: • • Transport: more challenging to get data on JCM Energy module - Transport: • • Transport: more challenging to get data on investments. . . Substitution of fuels is not enough for whole world, (dominant in western hemisphere - but rest of world is building railways. . . ) Must consider modal shifts (road, air. . . => rail, ships. . . ) but modal shift not yet accounted for in most models (eg IEA 2009 shifts scenario - arbitrary - not efficient allocation investments) needs more time. . . matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

Contributions to CENPES project • • • Meetings / course / demonstrations / website. Contributions to CENPES project • • • Meetings / course / demonstrations / website. . . Energy module of JCM - focus on longterm => infrastructure investments - done electricity, started transport, - buildings + industry + trade & feedbacks to complete. . . need more time - when done - illustrate sensitivity parameters + feedbacks inc prices, explore “needs-based” / feasibility approach to sharing effort Sensitivity Analysis 2°C - postponed => quick. . . in general Brazilian energy emissions per capita low ( << China) => poorly constrained by equity-based approach, unless LUC rises again matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

To develop here: sensitivity analysis 2°C=> Brazilian energy - what makes most difference? inverse To develop here: sensitivity analysis 2°C=> Brazilian energy - what makes most difference? inverse calculation, automated to explore many variantssector • Starting from 2°C stabilisation scenarios (various pathway shapes - approaching 2°C faster or slower) • + Varying physical climate parameters => Concentrations GHGs (climate sensitivity, ocean mixing, aerosols etc. - probabilistic weighting of sets as 2003 ? ) • + Varying carbon cycle parameters => Global CO 2 emissions (ocean sink, CO 2 fertilisation, climate feedback on soil respiration, etc. ) • + Varying sharing of national emissions /effort => Brazilian emissions (convergence, gradual participation, . . . starting from pledges + higher and lower? ) • + Varying distribution between sectors => Brazilian energy sector (uncertainty in LUC will make a big difference for Brazil) matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

 • • • Incorporate new IPCC RCP scenarios and GCM results, To develop • • • Incorporate new IPCC RCP scenarios and GCM results, To develop later. . . to test and re-calibrate physical climate system, feedbacks. . . Bottom-up socioeconomic scenarios, demographics, local data. . . + compare / connect scenarios in new IPCC socioeconomic scenario library? 1. 5°C scenarios? (decline after peak - interest many countries) Alternative metrics for integrating gases (GWP, GTP etc. ) Synthesis of regional & sectoral impacts of climate change - new functions based on AR 5 WG 2? • Re-develop optimisation module • Simpler versions for teaching, for smaller screens, . . . ? • for cost-effective solutions / re-calibration ? Recall concept democratisation of climate science-policy interface: matthews@climate. be, assessment model is the global network of human model: www. climate. be/jcm / “ultimate integrated jcm. ivig. coppe. ufrj. br heads”

 • • Overview: Range climate models, introducing JCM Some specific issues • • • • Overview: Range climate models, introducing JCM Some specific issues • • • Historical contributions & Alternative metrics Global 2°C pathways Regional emissions, pledges, effort-sharing, equity new Energy module Demonstration JCM matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

JCM - Demonstration recent updates on IVIG site: belgian site: jcm. ivig. coppe. ufrj. JCM - Demonstration recent updates on IVIG site: belgian site: jcm. ivig. coppe. ufrj. br www. climate. be/jcm matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

Hints for using JCM • • If problem with “launch” button, can try zip Hints for using JCM • • If problem with “launch” button, can try zip package note page about issues with java (+ tell me) be patient on first startup - wait while loading data Unfold tree => modules => plots, parameters right-click on plots => stack, table, save. . . right-click on curve-sets in tree => variants, more plots parameters only appear if they are useful increase complexity level => more options If strange result try: Reset “scientific” parameters Read how-to-use pages and “help-on-click” doc matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br

Introduction Java Climate Model, Scenarios to limit global warming to 2°C, +> Implications for Introduction Java Climate Model, Scenarios to limit global warming to 2°C, +> Implications for Brazilian energy sector Obrigado - Perguntas ? * Range climate models * Historical contributions & Alternative metrics * Global 2°C pathways * Regional emissions, effort-sharing, equity * Energy module * Intro / Demo JCM Dr Ben Matthews matthews@climate. be recent updates on IVIG site: belgian site: jcm. ivig. coppe. ufrj. br www. climate. be/jcm matthews@climate. be, model: www. climate. be/jcm / jcm. ivig. coppe. ufrj. br