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Indicator Assessment

GHG emissions - outlook from MNP

Indicator Assessment
Prod-ID: IND-67-en
  Also known as: Outlook 008
Published 08 Jun 2007 Last modified 11 May 2021
24 min read
This page was archived on 12 Nov 2013 with reason: Content not regularly updated

The risk of inaction is high, with unabated emissions in the Baseline scenario1  leading to about a 37% and 52% increase in global emissions in the 2030 and 2050 respectively compared to 2005, with a wide range of impacts on natural and human systems. This unabated emission pathway could lead to high levels of global warming, with long-term average temperatures likely to be at least 4 to 6 C higher than pre-industrial temperatures. The costs of even the most stringent mitigation cases are in the range of a few percent of global GDP in 2050. Thus they are manageable, they are also feasible at limited cost, especially if policies are designed to start early to be cost-effective and to share the burden of costs across all regions.

 

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GHG emissions according to the baseline scenario

GHG Emission projections per capita by the world regions

Note: Figures include land use change and forestry.

GHG per GDP by world regions

Shares of GHG emissions per region

Note: Figures include land use change and forestry.

Change in GHG emissions compared to 2005

Impacts of policy scenarios on greenhouse gas emissions, 2000-2050

Policy scenarios compared to Baseline: GHG emissions, CO2 emissions and global temperature change, 2000-2050

Note: The Outlook Baseline uses the UN forecast of population growth to 2050 and estimates that global economic growth will be 2.4% per year (expressed in terms of purchasing power parity or PPP) on average to 2050

The principal gases associated with climate change are carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), which together accounted for over 99% of anthropogenic GHG emissions in 2005. CO2 is the dominant greenhouse gas, accounting for 64% of global emissions and about 83% of emissions from OECD countries in 2005, excluding land use and forestry emissions and removals. Including land use change and forestry increases the share of CO2 in 2005 to 76% globally and does not significantly change the share for the OECD. Hydrofluorocarbons (HFCs), perfluorocarbons (PFCs) and sulphur hexafluoride (SF6) account for less than 1% of total global anthropogenic GHG emissions, but they are growing quickly. All these greenhouse gases are subject to international obligations under the United Nations Framework Convention on Climate Change (UNFCCC), including national monitoring and reporting of emissions and removals of greenhouse gases.
Fossil fuel combustion is by far the largest global source of CO2 emissions, accounting for 66% of global GHG emissions in 2005. Of this, fossil fuel combustion in power generation is the most important source, and accounted for about one-quarter of all global GHG emissions in 2005. Electricity-related CO2 emissions are also a rapidly-growing source of GHGs, particularly in Asia, reflecting both increased electrification rates and the continued predominance of fossil-fired electricity. Global CO2 emissions from road transport are a significant contributor to global GHG emissions, at 11% of the total in 2005.

Trends in GHG emissions vary widely according to world region. Global anthropogenic GHG emissions (excluding CO2 emissions or uptake from land use change and forestry and from international bunkers) increased by 28% between 1990 and 2005.4 This increase was lower in OECD countries (+14%) than in BIC countries (Brazil, India, China), where emissions grew by about 70%. However, emissions in some countries - particularly those in Central and Eastern Europe - fell during the same period. Trends for OECD countries are broadly similar even if emissions or uptake from land use change and forestry are included, in which case OECD countries' emissions increased 10% over the period 1990-2005. BIC countries' emissions also increase even more (nearly 110%) if CO2 emissions from land use change and forestry are included.
However, between 1990 and 2005 there were also large variations in these trends within different OECD countries. Emissions in nine OECD countries increased by more than 20% in this period, and eight further OECD countries reported smaller increases. However, emissions in several other OECD countries have decreased since 1990, including Germany, Hungary, Finland, Norway, the Czech Republic and Slovakia, where 2005 emissions were between 67-80% of their 1990 value.

Policy scenarios:
Emission reductions are not only possible; they are also feasible at limited cost. Simulations made by MNP for the OECD Environmental Outlook compare Baseline (no new policy) projections for GHG emissions, global mean temperature and GDP increase with different policy cases of a phased-in carbon tax of USD 25 per tonne of CO2eq (see graph). Costs of a globally applied tax policy starting in 2008 would decrease GDP by only 1% below its "business as usual" level by 2050. Another more radical scenario involves phasing in a global tax to stabilise atmospheric GHG concentrations at 450 ppm CO2eq. This policy reduces climate impact substantially, but has more significant, though manageable, global costs. It is projected to reduce Baseline estimates of GDP by about 0.5% and 2.5% by 2030 and 2050 respectively, amounting to a loss of about 0.1 percentage point a year on average. Aggregate costs of global mitigation (% GDP), with all countries participating, would be lower in the OECD than in the BRIC and ROW countries, underscoring the need for burden-sharing in future agreements.

Table 1 shows growth in GHG and CO2 emissions for the Baseline and policy cases compared to 2000 emission levels. All of the policy cases, except the OECD 2008 tax, lead to significant emission reductions compared to 2000, with the 450 PPM case showing the greatest reductions in global GHG emissions (-39%), whereas the All 2008 tax case delivers about two-thirds of this emission reduction by 2050. Interestingly the Phased 2030 and Delayed 2020 tax cases significantly reduce emissions from the Baseline but do not deliver absolute emission reductions in 2050. The OECD 2008 tax shows significant reductions in OECD regions (-43%) yet the global emissions still grow by 38% compared to 2000 emission levels (Table 1). The spread of outcomes among these cases demonstrates the importance of full participation by all major emitters and early mitigation efforts if substantial emission reductions are to be achieved by 2050.

Note: The Outlook Baseline uses the UN forecast of population growth to 2050 and estimates that global economic growth will be 2.4% per year (expressed in terms of purchasing power parity or PPP) on average to 2050

1)The OECD Baseline Reference Scenario presents a projection of historical and current trends into the future. This Baseline indicates what the world would be like to 2030 if currently existing policies were maintained, but no new policies were introduced to protect the environment. It is an extension of current trends and developments into the future, and as such it does not reflect major new or different developments in either the drivers of environmental change or environmental pressures. A number of major changes are possible in the future, however, that would significantly alter these projections.

Because the Baseline reflects no new policies, or in other words it is "policy neutral", it is a reference scenario against which simulations of new policies can be introduced and compared. Simulations of specific policy actions to address key environmental challenges were run in the modelling framework. The differences between the Baseline projections and these policy simulations were analysed to shed light on their economic and environmental impacts.

Supporting information

Indicator definition

Definition:

This indicator illustrates the projected trends in anthropogenic greenhouse gas emissions in relation to the EU and Member State targets, using existing policies and measures and/or additional policies and/or use of Kyoto mechanisms. The greenhouse gases are those covered by the Kyoto Protocol (CO2, CH4, N2O, SF6, HFCs and PFCs), weighed by their respective global warming potential, aggregated and presented in CO2-equivalent units.

The indicator also provides information on emissions from the main greenhouse gas emitting sectors: energy supply and use (including energy industry, fugitive emissions, energy use by industry and by other sectors); transport; industry (processes); agriculture; waste and other (non-energy).

Model used: IMAGE

Ownership: Netherlands Environmental Assessment Agency (MNP)

Temporal coverage: 1990 - 2100 

Geographical coverage: OECD Europe: Andorra, Austria, Belgium, Denmark, Faeroe Islands, Finland, France, Germany, Gibraltar, Greece, Holy See, Iceland, Ireland, Italy, Liechtenstein, Luxembourg, Malta, Monaco, Netherlands, Norway, Portugal, San Marino, Spain, Svalbard and Jan Mayen; Eastern Europe: Albania, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Hungary, Macedonia, Poland, Romania, Slovakia, Slovenia, Yugoslavia; Former USSR: Armenia, Azerbaijan, Belarus, Estonia, Georgia, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Moldova, Russian Federation, Tajikistan, Turkmenistan, Ukraine, Uzbekistan; South Asia: Afganistan, Bangladesh, Bhutan, British Indian Ocean Territory, India, Maldives, Nepal, Pakistan, Sri Lanka; East Asia: China, Hong Kong, Democratic People's Republic of Korea, Republic of Korea, Macau, Mongolia, Taiwan; Canada, USA

Units

Million tonnes in CO2-equivalent or Gt in CO2-equivalent


 

Policy context and targets

Context description

Over a decade ago, most countries joined an international treaty -- the United Nations Framework Convention on Climate Change (UNFCCC) -- to begin to consider what can be done to reduce global warming and to cope with whatever temperature increases are inevitable. Recently, a number of nations have approved an addition to the treaty: the Kyoto Protocol. The Kyoto Protocol, an international and legally binding agreement to reduce greenhouse gases emissions world wide, entered into force on February 16th 2005. The 1997 Kyoto Protocol shares the Convention's objective, principles and institutions, but significantly strengthens the Convention by committing Annex I Parties to individual, legally-binding targets to limit or reduce their greenhouse gas emissions.

To date most countries in the Pan-European region ratified the Kyoto Protocol, notably:  Annex I: Belarus, Croatia,  Russian Federation, Ukraine, EU 27, Norway, Iceland, Liechtenstien, Switzerland. Non-Annex I countries: Albania, Armenia, Azerbaijan, Bosnia and Herzegovina, Georgia, Kyrgyzstan, Kazhakhstan, Former Yugoslavian Republic Macedonia, Montenegro, Republic of Moldova, Serbia, Tajikistan, Turkey,  Turkmenistan, and Uzbekistan.

31 countries and the EEC are required to reduce greenhouse gas emissions below levels specified for each of them in the treaty.  The Individual Targets for Annex I Parties are listed in the Kyoto Protocol's Annex B. These add up to a total cut in greenhouse-gas emissions of at least 5% from 1990 levels in the commitment period 2008-2012.

The EU Commission's Progress Report towards achieving the Kyoto objectives in the EU and the individual Member States is required under the EU Greenhouse Gas Monitoring Mechanism (Council Decision 280/2004/EC concerning a mechanism for monitoring Community GHG emissions and for implementing the Kyoto Protocol).

Targets

Pan European level
The majority of the countries in the Pan European region and the EEC are required to reduce greenhouse gas emissions below levels specified for each of them in the Kyoto Protocol.  The individual targets for Annex I Parties are listed in the Kyoto Protocol's Annex B. These should add up to a total cut in greenhouse-gas emissions of at least 5% from 1990 levels in the commitment period 2008-2012.

EU level

For the EU-15 Member States, the targets are those set out in Council Decision 2002/358EC in which Member States agreed that some countries would be allowed to increase their emissions, within limits, provided these are offset by reductions in others.

The EU-15 Kyoto Protocol target for 2008-2012 is a reduction of 8 % from 1990 levels for the basket of six greenhouse gases. For the new Member States, the candidate countries, other EEA member countries, and other Annex 1 countries the targets are included in the Kyoto Protocol.

Overview of national Kyoto targets (reduction from base year levels):




Kyoto Target 
2008-2012



Kyoto Target 
2008-2012
Austria -13% Luxembourg -28.0%
Belgium -7.5% Malta -
Bulgaria -8.0% Netherlands -6.0%
Croatia -5.0% Norway 1.0%
Czech Republic -8.0% Poland -6.0%
Cyprus - Portugal +27.0%
Denmark -21.0% Romania -8.0%
Estonia -8.0% Slovakia -8.0%
Finland 0% Slovenia -8.0%
France 0% Spain +15.0%
Germany -21.0% Sweden +4.0%
Greece +25.0% Turkey -
Hungary -6.0% United Kingdom -12.5%
Iceland -10.0% 15 old EU Member
States (EU15)
-8.0%
Ireland +13.0% Belarus 0
Italy -8.0% Russian Federation 0
Latvia -8.0% Ukraine 0
Liechtenstein -8.0%

Lithuania -8.0%

Non-Annex I countries are not bound to such commitments and do not expect reduction of the GHG emissions.

The post 2012 climate regime will look different compared to Kyoto. In March 2007, the Council of the European Union decided that the EU would make a firm independent commitment to achieving at least a 20 % reduction of greenhouse gas emissions by 2020 compared to 1990. On 23 January 2008 the European Commission put forward a package of proposals that will deliver on the European Union's ambitious commitments to fight climate change and promote renewable energy up to 2020 and beyond. In December 2008 the European Parliament and Council reached an agreement on the package that will help transform Europe into a low-carbon economy and increase its energy security. The Package sets a number of targets for EU member states with the ambition to achieve the goal of limiting the rise in global average temperature to 2 degrees Celsius compared to pre-industrial times including: GHG reduction of 20% compared to 1990 by 2020 (under a satisfactory global climate agreement this could be scaled up to a 30% reduction); 20% reduction in energy consumption through improved energy efficiency, an increase in renewable energy's share to 20% and a 10% share for sustainably produced biofuels and other renewable fuels in transport.

Other related goals and targets:

EU

- max global temperature rise of 2o (EC 6EAP and Councils), meaning global concentrations of less than 450 ppm CO2 equivalent

- for developed countries: 60 to 80% reductions in greenhouse gas emissions (2004 Environment Council)

- global CO2 emissions should decline after 2025, by as much as 50% of 1990 levels (EC 2006 Green paper on energy)

Related policy documents

 

Methodology

Methodology for indicator calculation

Projections of GHG emissions are produced can be calculated using the IMAGE Scenarios Model

Overview of the IMAGE Scenarios Model

The Integrated Model to Assess the Global Environment (IMAGE) developed by the National Institute for Public Health and the Environment (RIVM), is a dynamic integrated assessment modelling framework for global change. The main objectives of IMAGE are to contribute to scientific understanding and support decision-making by quantifying the relative importance of major processes and interactions in the society-biosphere-climate system. To accomplish this, IMAGE provides:

  • dynamic and long-term perspectives on the systemic consequences of global change
  • insights into the impacts of global change
  • a quantitative basis for analyzing the relative effectiveness of various policy options to address global change.

Components of IMAGE 2.2

In the IMAGE 2.2 framework the general equilibrium economy model, WorldScan, and the population model, PHOENIX, feed the basic information on economic and demographic developments for 17 world regions into three linked subsystems:

  • The Energy-Industry System (EIS), which calculates regional energy consumption, energy efficiency improvements, fuel substitution, supply and trade of fossil fuels and renewable energy technologies. On the basis of energy use and industrial production, EIS computes emissions of greenhouse gases (GHG), ozone precursors and acidifying compounds.
  • The Terrestrial Environment System (TES), which computes land-use changes on the basis of regional consumption, production and trading of food, animal feed, fodder, grass and timber, with consideration of local climatic and terrain properties. TES computes emissions from land-use changes, natural ecosystems and agricultural production systems, and the exchange of CO2 between terrestrial ecosystems and the atmosphere.
  • The Atmospheric Ocean System (AOS) calculates changes in atmospheric composition using the emissions and other factors in the EIS and TES, and by taking oceanic CO2 uptake and atmospheric chemistry into consideration. Subsequently, AOS computes changes in climatic properties by resolving the changes in radiative forcing caused by greenhouse gases, aerosols and oceanic heat transport.

Modelling approach of IMAGE 2.2

Historical data for the 1765-1995 period are used to initialise the carbon cycle and climate system. IMAGE 2.2 simulations cover the 1970-2100 period. Data for 1970-1995 are used to calibrate EIS and TES. Simulations up to the year 2100 are made on the basis of scenario assumptions on, for example, demography, food and energy consumption and technology and trade. Although IMAGE 2.2 is global in application, it performs many of its calculations either on a high-resolution terrestrial 0.5 by 0.5 degree grid (land use and land cover) or for 17 world regions (energy, trade and emissions).

Use of Scenarious

The objective of the IMAGE 2.2 model is to explore the long-term dynamics of global environmental change, in particular, dynamics related to climate change. This requires an image of how the world system could evolve. Future greenhouse gas emissions, for instance, are the result of complex interacting demographic, techno-economic, socio-cultural and political forces. Scenarios are alternative images of how the future might unfold. They form an appropriate tool in analyzing how driving forces may influence future emissions and in assessing the associated uncertainties.

Recently, the Intergovernmental Panel on Climate Change (IPCC) published a set of new scenarios in the Special Report on Emissions Scenarios (SRES) (IPCC, 2000). These scenarios are based on a thorough review of the literature, the development of narrative 'storylines' and the quantification of these storylines using six different integrated models from different countries.
This CD-ROM represents the IMAGE 2.2 elaboration of the SRES storylines. Contrary to the original SRES scenarios, the scenarios on this CD-ROM do not focus solely on emissions, but also describe the possible environmental impacts of these scenarios . It should, however, be clear that the scenarios on this CD-ROM represent only one of the many possible elaborations of the SRES scenarios. In this respect, they reflect the authors' interpretations and valuation of only a part of past and present events, behaviours and structures. So-called 'disaster' scenarios are not included and none of the scenarios include new explicit climate policies.
Summary of the scenarious presented in the table below:

 Storyline assumptions
 A1 family
 B1 family
 A2 family
 B2 family

Stabilizing population (9 billion in 2050)

Stabilizing population (9 billion in 2050)

Growing population (13.5 billion in 2100); slowdown in fertility decline with lower income

rowing population (10.5 billion in 2100); in some regions slowdown in fertility decline with lower income

lobalization, very high-growth high-tech

Globalization, high-growth high-tech

Focus on regional [cultural] identity; environment low-priority

Focus on regional [cultural] identity; local/regional environment high-priority; non-effective in global environmental issues

Market-based capital and labour allocation

Balanced government and market in [economic] development

-

-

Orientation on profits and [technological] opportunities
Convergence in regional income and rapid diffusion of technology; no trade barriers

Orientation on non-material quality of life aspects.
Convergence in income and rapid diffusion of resource-efficient technology

No convergence in regional income and slow diffusion of technology; trade barriers
In some regions poor functioning markets and institutions

Orientation on non-material quality of life aspects. Varied regional economic and technology developments

Top

 Energy system dynamics
 A1 family
 B1 family
 A2 family
 B2 family

Decline in energy-intensity due to innovations and high capital turnover rate

Strong focus on energy efficiency and sufficiency, service economy.

Low rate of energy efficiency innovations, due to trade barriers and capital scarcity

Focus on energy efficiency and sufficiency, service economy.

Preference for clean fuels and fast depletion cause fossil fuel prices to rise. This enables efficiency and zero-carbon options to penetrate, accelerated by learning-by-doing

Large preference for clean fuels and depletion cause fossil fuel prices to rise. This further accelerates efficiency and zero-carbon options to penetrate, accelerated by learning-by-doing

Coal use rises in many regions: seen as cheapest available fuel as oil and gas become more expensive/ unavailable. initially capital-intensive zero-carbon options penetrate in most regions only slowly

Preference for clean fuels and depletion cause fossil fuel prices to rise in some regions, inducing efficiency and zero-carbon options to penetrate, accelerated by learning-by-doing

Top

 Food system dynamics
 A1 family
 B1 family
 A2 family
 B2 family

Fast increase in the volume of trade in food and feed

Fast increase in the volume of trade in food and feed

Moderate increase in the volume of trade in food and feed

Moderate increase in the volume of trade in food and feed

Fast increase in food and livestock productivity

Fast increase in food and livestock productivity with high efficiency of fertilizer use

Slow increase in crop and livestock productivity

Moderate increase in food and livestock productivity

Fast increase in per capita consumption of livestock products as a result of GDP increase

Per capita consumption of livestock products is 10% lower than in A1 scenario in 2050 and 20% lower than in A1 in 2100

Slow increase in per capita consumption of livestock products as a result of GDP increase

Moderate increase in per capita consumption of livestock products as a result of GDP increase

The IMAGE 2.2 elaboration of the SRES scenario narratives and assumptions described in detail by IPCC (2000) is found on the main disc.

Methodology for gap filling

Historical data for the 1765-1995 period are used to initialise the carbon cycle and climate system. IMAGE 2.2 simulations cover the 1970-2100 period. Data for 1970-1995 are used to calibrate EIS and TES. Simulations up to the year 2100 are made on the basis of scenario assumptions on, for example, demography, food and energy consumption and technology and trade. Models are used for projections and gap fillings.

Methodology references

  • IMAGE 2.2 implementation of the SRES scenarios A comprehensive analysis of emissions, climate change and impacts in the 21st century. This CD-ROM allows the user to explore the implementation of the IPCC-SRES scenarios (A1B, A1T, A1F, A2, B1 and B2) with the IMAGE 2.2 model for the 1995-2100 period. In contrast to the original SRES scenarios, the scenarios on this CD-ROM do not focus solely on emissions but also describe the possible environmental impacts of these scenarios. The scenarios can be visualized, analyzed and compared with the IMAGE 2.2 User Support System (USS). Hence, the user cannot run the IMAGE 2.2 model. Documentation is provided on all the IMAGE submodels, scenario assumptions and indicators. Furthermore, a guided tour offers an introduction to the USS and the documentation. The scenarios presented on the main disc do not reflect the uncertainties in the climate system. Some of the major uncertainties in the causal chain of climate change center on the climate sensitivity and regional climate-change patterns. The scenarios are based on one value for the climate sensitivity (the median of the IPCC (2001) range), and on one default GCM run (HADCM2). To illustrate uncertainties in climate sensitivity and climate-change patterns, the following additional simulations were made: the main disc ( IMAGE team, 2001a ) provides IMAGE 2.2 runs with changed climate sensitivity for the A1F and B1 scenarios (A1F low, A1F high, B1 low, B1 high). These scenarios span the full range of emissions of the SRES scenarios and therefore adequately illustrate the uncertainty of different climate sensitivities. a supplementary disc ( IMAGE team, 2001b ) provides IMAGE 2.2 runs with five different climate-change patterns for the A1F, B1 and A2 scenarios to illustrate the uncertainties in SRES climate-change scenarios resulting from differences in GCMs. The GCMs used include: ECHAM4, CGCM1, GFDL-LR15-a, HADCM2 and CSIRO-MK2. Another supplementary disc (forthcoming) will deal with the IMAGE 2.2 implementation of mitigation scenarios and analyses of emission burdens with the FAIR model (in preparation, IMAGE team, RIVM-CD-ROM Publication 481508020).
 

Uncertainties

Methodology uncertainty

Many unknowns and uncertainties in the climate system are not reflected in the IMAGE scenarios. Some of the major uncertainties in the causal chain are the climate sensitivity and regional climate-change patterns. The direct effects of a changed climate are changes in carbon uptake by the biosphere and oceans and in the distribution and productivity of crops, as well as shifts in ecosystems. Indirectly, many other processes are influenced, which can lead to the concentrations of greenhouse gases in the atmosphere being built up differently and to different land-use patterns. IMAGE simulates the consequences of these changes in an integrated fashion, accounting for interactions and feedbacks. The outcome is thus not necessarily a linear function of climate sensitivity.

These climate uncertainties were addressed by providing additional simulations to illustrate the uncertainty in the climate sensitivity and in the regional climate-change patterns.

Climate sensitivity

Climate sensitivity refers to long-term (equilibrium) change in global mean surface temperature following a doubling of the atmospheric concentration in CO2 equivalents. According to IPCC, this climate sensitivity is between 1.5oC and 4.5oC. In earlier versions of IMAGE, the climate sensitivity generated by the climate model was 2.4oC. Due to the rigid structure of these earlier versions, we were unable to change this and assess the consequences of such a change.

In IMAGE 2.2 a simpler climate model MAGICC (see Upwelling-Diffusion Climate Model)   is incorporated, allowing to define the climate sensitivity. The default value for IMAGE runs is 2.5, which is the median value of the IPCC range (median differs from mean because the range is logarithmic).

To test the uncertainty related to the climate sensitivity, runs with respectively a low (1.5oC) and high (4.5oC) climate sensitivity were created. A pattern-scaling procedure is used to obtain regional and seasonal climate-change patterns using the calculated increase in global mean temperature.

Runs with changed climate sensitivity are provided for the A1F (A1F low, A1F high) and B1 (B1 low, B1 high) scenarios on the main disc (IMAGE team 2001a). These scenarios span the full range of the SRES emission scenarios and therefore adequately illustrate the uncertainty of different climate sensitivities.

Regional climate-change patterns

Climate-change patterns are not simulated explicitly in IMAGE. The global mean temperature increase, as calculated by IMAGE, is linked with the climate patterns generated by a general circulation model (GCM) for the atmosphere and oceans. This linking takes place using the standardized IPCC pattern-scaling approach (Carter et al., 1994) and additional pattern-scaling for the climate response to sulphate aerosols forcing (Schlesinger et al., 2000; see Geographical Pattern Scaling, GPS). GCMs are currently the best tools available for simulating the physical processes that determine global climate dynamics and regional climate patterns.

GCMs simulate climate over a continuous global grid with a spatial resolution of a few hundred kilometres and a temporal resolution of less than an hour.

Most GCMs agree on the global patterns of climate change:

  • temperature increases above land are faster than above the oceans
  • high latitudes warm up more sharply than low latitudes
  • winter warms up more sharply than summers
  • total precipitation increases with increasing temperature
  • maritime regions generally get wetter
  • continental regions could get dryer.

Regionally, however, there are large differences between the different GCMs, especially in precipitation-change patterns.

IMAGE 2.2 runs with five different climate-change patterns are provided on the supplementary disc (IMAGE team 2001b, RIVM CD-ROM publication 481508019) for the A1F, B1 and A2 scenarios. The aim of this material is to illustrate the uncertainties in SRES climate-change scenarios resulting from these differences in GCMs. The first two scenarios span the full range of the SRES emission scenarios, the latter being based on a highly different narrative with different demographic and socio-economic assumptions. The three scenarios therefore adequately illustrate the uncertainty of different climate patterns. Differences in the runs for each scenario indicate some of the uncertainty caused by regional variation in climate-change patterns (not the global mean).

The scenarios for five different GCM runs from the IPCC data centre were implemented, which comprised:

  • ECHAM4 of the Deutsches Klimarechenzentrum DKRZ in Germany
  • CGCM1 of the Canadian Centre for Climate Modelling and Analysis in Canada
  • GFDL-LR15-a of the Geophysical Fluid Dynamics Laboratory in the USA
  • HADCM2 of the Hadley Centre for Climate Prediction and Research in the UK
  • CSIRO-MK2 of Commonwealth Scientific and Industrial Research Organisation in Australia

Data sets uncertainty

Description of the date sets uncertainties is not found in the reference documentation.

Rationale uncertainty

In common with all attempts to describe future trends, the energy projections and GHG projections in the Outlook are subject to a wide range of uncertainties. The reliability of projections depends both on how well the model represents reality and on the validity of the assumptions it works under.

Data sources

Other info

DPSIR: Pressure
Typology: Performance indicator (Type B - Does it matter?)
Indicator codes
  • Outlook 008
EEA Contact Info info@eea.europa.eu

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