The AMPERE project was a collaborative effort among 22 institutions in Europe, Asia and North America that started in February 2011 and concluded in January 2014. The AMPERE results have improved our understanding of possible pathways toward medium- and long-term climate targets at the global and European levels and provided insights into the cost implications of policy delay, technology availability and unilateral action in a fragmented international policy landscape. AMPERE was funded by the European Union Seventh Framework Programme (FP7) under grant agreement no. 265139. AMPERE stands for "Assessment of Climate Change Mitigation Pathways and Evaluation of the Robustness of Mitigation Cost Estimates". The research was divided into five work packages, which focused on the following research questions.

  • WP1 – Representation of the climate system for mitigation pathways: What amounts of future emissions are consistent with specific long-term climate targets?
  • WP2 – Delayed policy action and path dependency in energy systems: How do short-term climate policies impact the achievability of long-term climate targets? What is the role of different technologies and their innovation in meeting long-term climate targets?
  • WP3 – The implications of internationally fragmented climate policy: What are the economic implications and climate benefits of unilateral mitigation by a first mover followed by delayed global action?
  • WP 3 + 4 – Model diagnostics and validation: Why do model responses to carbon pricing differ, and what can be learned about the differences in mitigation cost estimates between models? What model validation approaches are appropriate for energy-economy and integrated assessment models of climate change?
  • WP5 – Decarbonisation scenarios for Europe: What are the costs and benefits of potential European Union climate targets for 2030 and 2050, and what are the roles of different technologies?

AMPERE scenario data were used in a series of research papers, which were published in a special issue of Technological Forecasting and Social Change as well as other journals. In addition, the results were used in the 5th Assessment Report of Working Group III of the IPCC.

The project was coordinated by the Potsdam Institute for Climate Impact Research (Project chair: Ottmar Edenhofer; Project Director: Elmar Kriegler). The steering committee of the project included Detlef van Vuuren (Universiteit Utrecht), Keywan Riahi (IIASA), Pantelis Kapros (ICCS) and Valentina Bosetti (FEEM). Further information is available on the AMPERE project website.

Contents of the Database

The database, operated by the International Institute for Applied Systems Analysis (IIASA) for the AMPERE consortium, hosts the model results for work packages 2, 3, and 5, as well as the results from the model diagnostics project. Definitions of the variables used in the respective work packages are listed here. Each set of results can be accessed in separate database views, which are organized as follows.

WP2+3 (Work Packages 2 and 3)

The results for work packages 2 and 3 are combined in the WP2+3 view. Nine models (DNE21+, GCAM, IMACLIM, IMAGE, MERGE-ETL, MESSAGE, POLES, REMIND, and WITCH) participated in WP2, which explored (a) implications of short-term emission targets for the cost and feasibility of long-term climate goals; (b) the role of technology for the attainability of climate targets; and (c) technology diffusion in integrated assessment models compared with successful examples of technology diffusion in the past.

Eleven models (DNE21+, GCAM, GEM-E3, IMACLIM, IMAGE, MERGE-ETL, MESSAGE, POLES, REMIND, and WITCH, and WorldScan) participated in WP3. These teams (a) conducted modelling comparisons to assess unilateral action by a first mover pursuing strong climate policy despite lack of global participation before 2030, as well as staged accession by the rest of the world to a global climate regime after 2030. In addition, WP3 performed (b) a comparison of 21st century emission drivers in the model study scenarios with historical trends.

PLEASE NOTE: The WP3 results were also used by WP5 in an ex-post analysis of the specific impacts on Europe of unilateral EU first mover action. For this purpose, the European model NEMESIS also calculated the WP3 scenarios. NEMESIS data for the EU region are thus included in this database even though NEMESIS data were not used for WP3, but rather were only used for WP5.

More information on the scenarios, objectives, and assumptions for these work packages can be found in their study protocols: WP2 and WP3. An overview of the findings of WP2 is provided by Riahi et al. (2014) and an overview of the findings of WP3 is provided by Kriegler et al. (2014).

WP5 (Work Package 5)

The results for work package 5 are in the WP5 view. Seven energy-economy models (GAINS, GEM-E3, Green-X, NEMESIS, PRIMES, TIMES-PanEU and WorldScan) participated in WP5, which addressed questions regarding (a) the role of interim emission targets, limitations in technological options, and path dependency for the achievement of the European decarbonisation target for 2050; (b) the impact of unilateral European climate policy on different economic sectors; and (c) the possibility of economic advantages arising from technological advances in clean energy producing sectors due to European climate policy. The analysis of the impacts of unilateral European climate policy was based on data from the WP3 scenarios.

More information on the scenarios, objectives, and assumptions for this work package can be found in the study protocol for WP5. The findings related to the role of emission targets, technology options and path dependency for European decarbonisation is provided by Capros et al. (2014).


The results for the model diagnostics project are in the Diagnostics view. AMPERE performed diagnostic exercises that identified distinct classes of models that differ in their responses to climate policy scenarios. The diagnostic analysis focused on the AMPERE models with global coverage but also compared the global results with regional results, including those of the EU model PRIMES. The diagnostic work developed a rough model classification scheme as well as a set of diagnostic indicators.

More information on the scenarios, objectives, and assumptions for the model diagnostics project can be found in the diagnostics study protocol. An overview of the findings of the AMPERE diagnostics study is provided by Kriegler et al. (2014).


The information supplied on this site or parts thereof may be freely used for non-commercial and educational purposes. Data from this site is for informational purposes only. Information from this site may be reproduced and used with proper acknowledgment of the following sources, depending on whether the information is based on WP2, WP3, WP5, or diagnostic data:

WP2: Riahi et al. (2014): Locked into Copenhagen Pledges - Implications of short-term emission targets for the cost and feasibility of long-term climate goals, Technological Forecasting and Social Change, online first, DOI: 10.1016/j.techfore.2013.09.016.

WP3: Kriegler et al. (2014): Making or breaking climate targets: The AMPERE study on staged accession scenarios for climate policy, Technological Forecasting and Social Change, online first, DOI: 10.1016/j.techfore.2013.09.021.

WP5: Capros et al. (2014): EU Decarbonisation pathways, Climate policy delays, Energy Roadmap, EU Energy Policy, Technological limitations, Energy Strategy Reviews 2(3-4), 231-245, DOI: 10.1016/j.esr.2013.12.007.

Diagnostics: Kriegler et al. (2014): Diagnostic indicators for integrated assessment models of climate policies, Technological Forecasting and Social Change, online first, DOI: 10.1016/j.techfore.2013.09.020.

Individual documents on this webpage may have different copyright conditions than IIASA; these conditions will be noted in the respective documents. Views or opinions expressed herein do not necessarily represent those of IIASA, its National Member Organizations, or other supporting institutions.

Participating Institutions

The AMPERE consortium is comprised of 22 institutions, including some of the most recognized integrated assessment and energy modeling teams from Europe, Asia, and the United States. The project benefited from the capabilities of 17 energy-economy and integrated assessment models, which have unique structures and functions. The diversity of these models increased the robustness of insights since it allowed the identification of areas of uncertainty where model results differ as well as areas where models from across the spectrum concur.

  1. Potsdam Institute for Climate Impact Research (PIK), Germany (Coordinator WP3 and diagnostic study)
  2. International Institute for Applied Systems Analysis (IIASA), Austria (coordinator WP2)
  3. Institute of Communication and Computer Systems (ICCS), Greece (coordinator WP5)
  4. Fondazione Eni Enrico Mattei (FEEM), Italy
  5. Utrecht University, Netherlands
  6. Centraal Planbureau (CPB), Netherlands
  7. Centre for European Policy Studies (CEPS), Belgium
  8. Centre National de la Recherche Scientifique (CNRS-LEPII), France
  9. Climate Analytics, Germany
  10. Enerdata, France
  11. ERASME Université Paris I, France
  12. NDRC Energy Research Institute (ERI), China
  13. EU Joint Research Centre, Institute for Prospective Technological Studies (IPTS), Belgium
  14. Indian Institute of Management Ahmedabad (IIM-A), India
  15. Met Office Hadley Centre, UK
  16. National Institute for Environmental Studies (NIES), Japan
  17. Paul-Scherrer-Institut (PSI), Switzerland
  18. Research Institute of Innovative Technology for the Earth (RITE), Japan
  19. Société de mathématiques appliqués aux sciences humaines - CIRED, France
  20. University of Stuttgart, Institute for Energy Economics and the Rational Use of Energy (IER), Germany
  21. Vienna Technical University, Energy Economics Group (EEG), Austria
  22. External partner: Pacific Northwest National Laboratory (PNNL) Joint Global Change Research Institute (JGCRI), USA

Database Tutorial


A short tutorial on the use of the web database can be found below. If you experience technical problems with this database, please contact the AMPERE Database Administrator.

The Navigation tabs

At the upper end of the browser window are three navigation tabs that provide different ways of viewing the data in the web database. These three tabs are described in more detail in the following section.

Sectors tab

The Sectors tab allows the user to select multiple variables from a single scenario and region. This view is most useful for displaying a set of variables from one sector (e.g., all fuel types of industrial final energy consumption). If the variables can be added in a meaningful way (e.g., different fuel types of one sector), a stacked area graph is shown. If this is not possible (e.g., for different fuel prices), a line graph is displayed. In case variables with different units are selected, a warning is issued on the y-axis label of the graph in red. Please note that it is necessary to mark a variable name (highlighted in blue) in addition to selecting variables for the graph on the right hand side to be updated (see also the description under (3.) Variables below).

Series tab

The Series tab allows selecting a single variable from multiple scenarios and regions. The preview graph on the right is always a line graph and is most useful for comparing trends across different scenarios (and models) in one or multiple regions.

Scatter tab

The Scatter tab allows one to look at the relationship between two variables. One can select one variable from the navigation tree for the x-axis and another variable for the y-axis. It is also possible to examine growth rates and per capita, per GDP, and per final or primary energy values.

Common Features of the Sectors, Series, and Scatter tabs

In all three view tabs the following selections can be made in the navigation bars on the upper left-hand side of the browser window:

(1.) Regions: In the upper left area of the screen is a field named Regions. Depending on the tab (see above), you may select one or multiple regions for which the data is shown on the screen. See Region definitions for a description of each region.

(2.) Scenarios: This field includes the list of scenarios from which one or more scenarios can be selected. In addition to scenarios, historical and base year data is included for some variables and can be compared with scenario results. Note that only some emission and energy variables are included in the historical data.

(3.) Variables: This field includes a list of the variables that can be selected within the database. Note that, in the Sectors tab, one must not only select one or multiple variables, but also mark a variable name (highlighted in blue) in order for the graph on the right hand side to be updated. It is not important which variable or variable category is marked to initiate the graph update.

The Chart Preview on the upper right-hand side of the browser window shows the graph of the selected data (variable + scenarios + regions). In addition, the horizontally oriented Query Results area in the middle of the screen shows the data in tabular format.

It is possible to export the data either into Excel or two different graphical formats (PNG = portable network graphics, SVG = scalable vector graphics). In order to do so, select one of the options in the Output Options window at the bottom of the browser window. The field titled Notes shows additional information or explanatory text for the selected variables. The availability of notes is still under development and the contents depend on input from modeling teams.

Download tab

The Download tab allows you to download a data snapshot of the respective work package in either MS Access or CSV format. To do so, you will have to provide your name and email address, so that we can inform you in case of updates (e.g. error corrections in the underlying database).

Region definitions

The consolidated results in the WP2+3 view are shown at regional aggregations of the World, five macro regions, the seven individual countries/regions with large economies that are commonly used in scenario analysis, and two subsets of the European Union (EU15 and EU12). WP5 focused only on the EU so includes only the 27-member EU region. The Diagnostics view includes the World, five macro regions, and four of the countries/regions with large economies (the 27-member EU, China, India, and the United States). These regions are defined as follows.

Aggregation on the five region level

OECD90 = Includes the OECD 90 countries.
Australia, Austria, Belgium, Canada, Denmark, Fiji, Finland, France, French Polynesia, Germany, Greece, Guam, Iceland, Ireland, Italy, Japan, Luxembourg, Netherlands, New Caledonia, New Zealand, Norway, Portugal, Samoa, Solomon Islands, Spain, Sweden, Switzerland, Turkey, United Kingdom, United States of America, Vanuatu

Reforming Economies (REF) = Countries from the Reforming Economies of Eastern Europe and the Former Soviet Union.
Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Cyprus, Czech Republic, Estonia, Georgia, Hungary, Kazakhstan, Kyrgyzstan, Latvia, Lithuania, Malta, Poland, Republic of Moldova, Romania, Russian Federation, Slovakia, Slovenia, Tajikistan, TFYR Macedonia, Turkmenistan, Ukraine, Uzbekistan, Yugoslavia

Asia (ASIA) = Includes most Asian countries with the exception of the Middle East, Japan and Former Soviet Union states.
Afghanistan, Bangladesh, Bhutan, Brunei Darussalam, Cambodia, China, China Hong Kong SAR, China Macao SAR, Democratic People's Republic of Korea, East Timor, India, Indonesia, Lao People's Democratic Republic, Malaysia, Maldives, Mongolia, Myanmar, Nepal, Pakistan, Papua New Guinea, Philippines, Republic of Korea, Singapore, Sri Lanka, Taiwan, Thailand, Viet Nam

Middle East and Africa (MAF) = Includes the countries of the Middle East and Africa.
Algeria, Angola, Bahrain, Benin, Botswana, Burkina Faso, Burundi, Cameroon, Cape Verde, Central African Republic, Chad, Comoros, Congo, Cote d'Ivoire, Democratic Republic of the Congo, Djibouti, Egypt, Equatorial Guinea, Eritrea, Ethiopia, Gabon, Gambia, Ghana, Guinea, Guinea-Bissau, Iran (Islamic Republic of), Iraq, Israel, Jordan, Kenya, Kuwait, Lebanon, Lesotho, Liberia, Libyan Arab Jamahiriya, Madagascar, Malawi, Mali, Mauritania, Mauritius, Morocco, Mozambique, Namibia, Niger, Nigeria, Oman, Qatar, Reunion, Rwanda, Saudi Arabia, Senegal, Sierra Leone, Somalia, South Africa, Sudan, Swaziland, Syrian Arab Republic, Togo, Tunisia, Uganda, United Arab Emirates, United Republic of Tanzania, Western Sahara, Yemen, Zambia, Zimbabwe

Latin America (LAM) = Includes the countries of Latin America and the Caribbean.
Argentina, Bahamas, Barbados, Belize, Bolivia, Brazil, Chile, Colombia, Costa Rica, Cuba, Dominican Republic, Ecuador, El Salvador, Guadeloupe, Guatemala, Guyana, Haiti, Honduras, Jamaica, Martinique, Mexico, Netherlands Antilles, Nicaragua, Panama, Paraguay, Peru, Puerto Rico, Suriname, Trinidad and Tobago, Uruguay, Venezuela

Seven individual countries/regions commonly used in scenario analysis

Brazil = Federative Republic of Brazil
China = People's Republic of China
India = Republic of India
EU = European Union (27 member countries) = sum of EU15 and EU12 (see below)
Japan = State of Japan
Russia = Russian Federation
USA = United States of America

European Union countries and country groups

EU15 = European Union 15 (15 member states of the EU before the enlargement on 1st May 2004)
Austria, Belgium, Denmark, Finland, France, Germany, Greece, Ireland, Italy, Luxembourg, Netherlands, Portugal, Spain, Sweden, United Kingdom

EU12 = European Union 12 (12 new member states)
Bulgaria, Cyprus, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Romania, Slovakia, Slovenia



With respect to information available from this webpage, neither IIASA nor any of its employees make any warranty, expressed or implied, including warranties of merchantability and fitness for a particular purpose, nor does IIASA assume any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, product, or process disclosed, nor does IIASA represent that its use would not infringe upon privately owned rights. The software is provided on an 'as is' basis and IIASA disclaims all liability of any kind whatsoever arising out of the use, or inability to use, the databases and all information and data contained within them. Parts of the pages or the complete model might be extended, changed or partly or completely deleted without separate announcement.

Referrals and links

This website may contain advice, opinions and statements from external websites. Hyperlinks to non-IIASA Internet sites do not imply any official endorsement of, or responsibility for, the opinions, ideas, data or products presented at these locations nor guarantee the validity of the information provided. The sole purpose of links to other sites is to indicate further information available on related topics.

AMPERE Database, 2014
Available at: https://tntcat.iiasa.ac.at/AMPEREDB/

Responsible for this page: AMPERE Database Administrator