RCP Database (version 2.0):

The RCP database aims at documenting the emissions, concentrations, and land-cover change projections of the so-called "Representative Concentration Pathways" (RCPs). Information about the RCPs and the scenario development process for the IPCC AR5 can be found in the IPCC Expert Meeting Report on New Scenarios and Moss et al. (2010).
For a draft work plan summarizing the data exchange between the Integrated Assessment and Climate Modeling community see also the "Representative Concentration Pathways (RCPs) Draft Handshake". The final RCPs have been documented in a Special Issue of Climatic Change that was published in November 2011 (Climatic Change, Volume 109, Issue 1-2). The overview paper (van Vuuren et al, 2011) of the Special Issue summarizes the main achievements. Further description of the RCP can be found below.

Version 2.0 of the database includes harmonized and consolidated data for three of the four RCPs. This comprises emissions pathways starting from identical base year (2000) for BC, OC, CH4, Sulfur, NOx, VOC, CO and NH3. In addition, harmonized well-mixed GHG emissions of the RCPs have been added for the period 2005 to 2100. Radiative forcing and concentrations of GHGs are given for the RCPs up to the year 2100, and are extended for climate modeling experiments to 2300 (ECPs). Wherever available, historical information is provided back to the year 1850. Recent updates include historic and future land-cover information as well as emissions and concentrations data for additional sources: Click here for CMIP5 recommended data.

Initial emissions datasets were made publicly available on May 26, and were extended December 1 to cover harmonized data for all GHGs and concentrations. We ask users to register in order to receive information about further developments and updates of the database (download is thus only possible after registration).

The data provided for the RCPs is extensive - and has undergone several procedures to assure quality and consistency, to harmonize regional base year emissions to recent inventories, and to downscale the projections to 0.5 x 0.5 degree. However, if errors are found or questions remain regarding the data or their use please inform the individual modeling teams and the contact persons provided below.

To prevent misuse of the RCPs, we have provided guidance on the limits and uses of the RCPs below (see "Characteristics and Guidance").

Contacts

We encourage users to send comments on the current database to:

RCP 2.6 (IMAGE): Detlef van Vuuren (detlef.vanvuuren@pbl.nl)
RCP 4.5 (MiniCAM): Allison Thomson (Allison.Thomson@pnl.gov)
RCP 6.0 (AIM): Toshihiko Masui (masui@nies.go.jp)
RCP 8.5 (MESSAGE): Keywan Riahi (riahi@iiasa.ac.at)
 
Base year emissions inventories:
Jean-Francois Lamarque (lamar@ucar.edu) and
Steve Smith (ssmith@pnl.gov)
 
Land-use data harmonization:
Louise Parsons Chini (lchini@umd.edu) and
George C. Hurtt (gchurtt@umd.edu)


Description of the RCPs

The RCP database aims at documenting the emissions, concentrations, and land-cover change projections of the so-called "Representative Concentration Pathways" (RCPs). The Representative Concentration Pathways are based on selected scenarios from four modeling teams/models (NIES/AIM, IIASA/MESSAGE, PNNL/MiniCAM, and PBL/IMAGE). The RCPs are meant to serve as input for climate and atmospheric chemistry modeling as part of the preparatory phase for the development of new scenarios for the IPCC's Fifth Assessment Report and beyond. Further documentation can be found in the IPCC Expert Meeting Report on New Scenarios (Noordwijkerhout report) and the "Representative Concentration Pathways (RCPs) Draft Handshake".

Characteristics and guidance

The RCPs are not new, fully integrated scenarios (i.e., they are not a complete package of socioeconomic, emissions, and climate projections). They are consistent sets of projections of only the components of radiative forcing that are meant to serve as input for climate modeling, pattern scaling, and atmospheric chemistry modeling. As such, they jump-start the scenario development across research communities from which uncertainties about socioeconomic, climate, and impact futures can be explored. They thus constitute just the beginning of the parallel process of developing new scenarios for the IPCC's fifth Assessment Report. By doing so, the RCPs aim at providing a consistent analytical thread across communities.

The RCPs are named according to their 2100 radiative forcing level as reported by the individual modeling teams. The radiative forcing estimates are based on the forcing of greenhouse gases and other forcing agents - but does not include direct impacts of land use (albedo) or the forcing of mineral dust.

The RCPs are not forecasts or boundaries for potential emissions, land-use, or climate change. They are also not policy prescriptive in that they were chosen for scientific purposes to represent the span of the radiative forcing literature at the time of their selection and thus facilitate the mapping of a broad climate space. They therefore do not represent specific futures with respect to climate policy action (or no action) or technological, economic, or political viability of specific future pathways or climates.

The RCPs are four independent pathways developed by four individual modeling groups. The socioeconomics underlying each RCP are not unique; and, the RCPs are not a set or representative of the range of potential assumptions. For instance, the RCPs with lower radiative forcing (RCP 6.0, RCP 4.5 and RCP 2.6) are not derived from those with higher radiative forcing (RCP 8.5, or even RCP 6.0). The differences between the RCPs can therefore not directly be interpreted as a result of climate policy or particular socioeconomic developments. Any differences can be attributed in part to differences between models and scenario assumptions (scientific, economic, and technological). This is in particular relevant for scenario elements that are only indirectly coupled to the radiative forcing targets such as land use/land cover and air pollutant emissions.

The extension of the scenarios beyond 2100 will be done using simple algorithms intended for use as pathways to drive long-term earth-system simulation experiments and is not the result of integrated assessment analysis or modeling.


Information on individual RCPs

RCP 2.6:

The RCP 2.6 is developed by the IMAGE modeling team of the Netherlands Environmental Assessment Agency. The emission pathway is representative for scenarios in the literature leading to very low greenhouse gas concentration levels. It is a so-called "peak" scenario: its radiative forcing level first reaches a value around 3.1 W/m2 mid-century, returning to 2.6 W/m2 by 2100. In order to reach such radiative forcing levels, greenhouse gas emissions (and indirectly emissions of air pollutants) are reduced substantially over time. The final RCP is based on the publication by Van Vuuren et al. (2007).

The IMAGE-team responsible for developing the RCP 2.6 are:

Detlef P. van Vuuren, Elke Stehfest, Jasper van Vliet, Michel den Elzen, Angelica Mendoza-Beltran, Morna Isaac, Sebastiaan Deetman, Rineke Oostenrijk and Tom Kram.

RCP 4.5:

The RCP 4.5 is developed by the MiniCAM modeling team at the Pacific Northwest National Laboratory's Joint Global Change Research Institute (JGCRI). It is a stabilization scenario where total radiative forcing is stabilized before 2100 by employment of a range of technologies and strategies for reducing greenhouse gas emissions. The scenario drivers and technology options are detailed in Clarke et al. (2007). Additional detail on the simulation of land use and terrestrial carbon emissions is given by Wise et al (2009).

The MiniCAM-team responsible for developing the RCP 4.5 are:

Allison Thomson, Katherine Calvin, Steve Smith, Page Kyle, April Volke, Pralit Patel, Sabrina Delgado, Ben Bond-Lamberty, Marshall Wise, Leon Clarke and Jae Edmonds

RCP 6.0:

The RCP 6.0 is developed by the AIM modeling team at the National Institute for Environmental Studies (NIES), Japan. It is a stabilization scenario where total radiative forcing is stabilized after 2100 without overshoot by employment of a range of technologies and strategies for reducing greenhouse gas emissions. The details of the scenario are described in Fujino et al. (2006) and Hijioka et al. (2008).

The AIM-team responsible for developing the RCP 6.0 are:

Toshihiko Masui, Yasuaki Hijioka, Sawako Ishiwatari, Tsuguki Kinoshita, Ken'ichi Matsumoto, Toru Nozawa, and Mikiko Kainuma in collaboration with Etsushi Kato at Japan Agency for Marine-Earth Science and Technology (JAMSTEC).

RCP 8.5:

The RCP 8.5 is developed by the MESSAGE modeling team and the IIASA Integrated Assessment Framework at the International Institute for Applies Systems Analysis (IIASA), Austria. The RCP 8.5 is characterized by increasing greenhouse gas emissions over time representative for scenarios in the literature leading to high greenhouse gas concentration levels. The underlying scenario drivers and resulting development path are based on the A2r scenario detailed in Riahi et al. (2007).

The MESSAGE-team responsible for developing the RCP 8.5 are:

Keywan Riahi, Volker Krey, Shilpa Rao, Vadim Chirkov, Cheolhung Cho, Peter Kolp, Nebojsa Nakicenovic in collaboration with colleagues from other IIASA Programs: Janusz Cofala, Guenther Fischer, Arnulf Gruebler, Georg Kindermann, Zbigniew Klimont, Peter Rafaj, Wolfgang Schoepp


Information on Harmonization of RCP Land-Use Data

The future land-use projections from each RCP were harmonized to ensure a smooth transition from the historical land-use data (from HYDE 3.1: http://www.pbl.nl/hyde ) and to compute the associated secondary (recovering) land area and all land-use transitions. The harmonized data represents fractional land-use patterns and underlying land-use transitions annually for the past (1500-2005) and the RCPs (2005-2100) at 0.5? x 0.5? resolution. This includes transitions between cropland, pasture, primary land and secondary (recovering) land, including the effects of wood harvest and shifting cultivation, as well as land-use changes and transitions from/to urban land. More information is available at: http://luh.unh.edu.

The land-use harmonization team are:

George Hurtt, Louise Parsons Chini, and Steve Frolking.


A short tutorial on the use of the database

Click on the tabs on the top of the page (red text fields) to enter the database. The “Compare” tab includes the data of all RCPs, and permits data comparisons at the global as well as the level of 5 regions.

The “Spatial” tab lists the spatial data of all RCPs, and permits online browsing and downloading the gridded data sets.

The “Download” tab lists the available bulk downloads (regional as well as spatial data) on a per RCP basis. Please note that before downloading from the RCP database you have to register by providing your email address. We kindly ask you to (optionally) provide your name, country and organization as well.

After entering the database the following selections can be made in order to visualize the data on the screen, or to download the data to Excel:

(1) Regions: In the upper left area of the screen is a field named “Regions”. You may select one or multiple regions for which the data is shown on the screen

(2) Scenarios: This field includes the list of scenarios (RCPs) from which one or more scenarios can be selected.

(3) Variables: In this field the variables can be selected for which the data is shown on the screen. Note that while it is possible to select multiple regions or scenarios, just one variable at a time can be shown on the screen. Each time a new variable is selected the screen is updated automatically..

The Chart Preview on the right shows the graph of the selected data (variable + scenarios + regions). In addition, the window “Query Results” shows the data in tabular format.

It is possible to export the data either into Excel or two different graphical formats. In order to do so, select one of the options in the “Output Options” window.

The field titled “Notes” shows additional information or explanatory text for the selected variables.


Region definitions

The consolitated results in the database are shown at regional aggregations of 5 regions. The regions are defined as:

Aggregation on the 5 region level

OECD90 = Includes the OECD 90 countries, therefore encompassing the countries included in the regions Western Europe (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, Turkey, United Kingdom), Northern America (Canada, United States of America) and Pacific OECD (Australia, Fiji, French Polynesia, Guam, Japan, New Caledonia, New Zealand, Samoa, Solomon Islands, Vanuatu) .

REF = Countries from the Reforming Ecomonies region (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 = The countries included in the regions China + (China, China Hong Kong SAR, China Macao SAR, Mongolia, Taiwan) , India + (Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, Sri Lanka) and Rest of Asia (Brunei Darussalam, Cambodia, Democratic People's Republic of Korea, East Timor, Indonesia, Lao People's Democratic Republic, Malaysia, Myanmar, Papua New Guinea, Philippines, Republic of Korea, Singapore, Thailand, Viet Nam) are aggregated into this region.

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

LAM = This region includes the Latin American countries (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).


Citation

Please use the following references for the scenario data presented in the RCP Database:

RCP 2.6:

  • van Vuuren, D., M. den Elzen, P. Lucas, B. Eickhout, B. Strengers, B. van Ruijven, S. Wonink, R. van Houdt, 2007. Stabilizing greenhouse gas concentrations at low levels: an assessment of reduction strategies and costs. Climatic Change, doi:10.1007/s/10584-006-9172-9.

RCP 4.5:

  • Clarke, L., J. Edmonds, H. Jacoby, H. Pitcher, J. Reilly, R. Richels, 2007. Scenarios of Greenhouse Gas Emissions and Atmospheric Concentrations. Sub-report 2.1A of Synthesis and Assessment Product 2.1 by the U.S. Climate Change Science Program and the Subcommittee on Global Change Research. Department of Energy, Office of Biological & Environmental Research, Washington, 7 DC., USA, 154 pp.
  • Smith, S.J. and T.M.L. Wigley, 2006. Multi-Gas Forcing Stabilization with the MiniCAM. Energy Journal (Special Issue #3) pp 373-391.
  • Wise, MA, KV Calvin, AM Thomson, LE Clarke, B Bond-Lamberty, RD Sands, SJ Smith, AC Janetos, JA Edmonds. 2009. Implications of Limiting CO2 Concentrations for Land Use and Energy. Science. 324:1183-1186. May 29, 2009.

RCP 6.0:

  • Fujino, J., R. Nair, M. Kainuma, T. Masui, Y. Matsuoka, 2006. Multi-gas mitigation analysis on stabilization scenarios using AIM global model. Multigas Mitigation and Climate Policy. The Energy Journal Special Issue.
  • Hijioka, Y., Y. Matsuoka, H. Nishimoto, M. Masui, and M. Kainuma, 2008. Global GHG emissions scenarios under GHG concentration stabilization targets. Journal of Global Environmental Engineering 13, 97-108.

RCP 8.5:

  • Riahi, K. Gruebler, A. and Nakicenovic N.: 2007. Scenarios of long-term socio-economic and environmental development under climate stabilization. Technological Forecasting and Social Change 74, 7, 887-935.

Please use the following references for the historical projections and inventory data presented in the RCP Database:

Grassland and forest fire emissions:

  • For the "year 2000" climatology please refer to the following publication:
    Van der Werf, G., J. T. Randerson, L. Giglio, G. J. Collatz, P. S. Kasibhatla, and A. F. Arellano Jr. (2006), Interannual variability in global biomass burning emissions from 1997 to 2004, Atmos. Chem. Phys., 6, 3423?3441.
  • For the 1960-2000 RETRO inventory use:
    Schultz, M.G., A. Heil, J.J. Hoelzemann, A. Spessa, K. Thonicke, J. Goldammer, A.C. Held, J.M. Pereira, M. van het Bolscher (2008), Global Wildland Fire Emissions from 1960 to 2000, Global Biogeochem. Cyc., doi:10.1029/2007GB003031.
  • The reference for the 1850-1960 period is the following:
    Mieville, A., C. Granier, C. Liousse, B. Guillaume, F. Mouillot, J.F. Lamarque, J.M. Gr?goire, G. P?tron (2009), Emissions of gases and particles from biomass burning during the 20th century using satellite data and an historical reconstruction, Atmospheric Environment, submitted.
Please note that emissions over the 1850-2000 period have been harmonized to "year 2000 climatology" emissions.

International shipping emissions:

Ship emission totals for the year 2000 are taken from Table 3 of Eyring et al. (2009).
Historical CO2 ship emission totals from 1850 to 2000 are based on the Second International Maritime Organization (IMO) GHG Study (Buhaug et al., 2009).
Historical non-CO2 shipping emission totals are scaled backwards in time by using the IMO CO2 emission time series.
References:

  • Buhaug, ?., J. J. Corbett, ?. Endresen, V. Eyring, J. Faber, S. Hanayama, D. S. Lee, D. Lee, H. Lindstad, A.Z. Markowska, A. Mjelde, D. Nelissen, J. Nilsen, C. P?lsson, J. J. Winebrake, W.?Q. Wu, and K. Yoshida, Second IMO GHG study 2009; International Maritime Organization (IMO) London, UK, March, 2009.
  • Eyring, V., I. S. A. Isaksen, T. Berntsen, W. J. Collins, J. J. Corbett, O. Endresen, R. G. Grainger, J. Moldanova, H. Schlager, and D. S. Stevenson, Transport impacts on atmosphere and climate: Shipping, Atm. Env., doi:10.1016/j.atmosenv.2009.04.059, 2009.

Aviation emissions:

  • Lee et al. (2009) in preparation (QUANTIFY Scenarios)
    Developed from the approach of Lee, D.S., et al., Aviation and global climate change in the 21st century, Atmospheric Environment (2009), doi:10.1016/j.atmosenv.2009.04.024

Sulfur emissions of all other sectors:

  • For historical and year 2000 sulfur emissions of all sectors except the ones listed above please refer to:
    Smith et al. (2009) in preparation; updated from Smith, Steven J., Pitcher, H., and Wigley, T.M.L. (2001) Global and Regional Anthropogenic Sulfur Dioxide Emissions. Global and Planetary Change 29/1-2, pp 99-119 Smith, Steven J, Robert Andres, Elvira Conception and Josh Lurz (2004) Sulfur Dioxide Emissions: 1850-2000 (JGCRI Report. PNNL-14537).

Black and organic carbon emissions of all other sectors:

  • For historical and year 2000 black and organic carbon emissions of all sectors except the ones listed above please use:
    Updated from: Bond, T.C., E. Bhardwaj, R. Dong, R. Jogani, S. Jung, C. Roden, D.G. Streets, S. Fernandes, and N. Trautmann (2007), Historical emissions of black and organic carbon aerosol from energy-related combustion, 1850-2000, Glob. Biogeochem. Cyc., 21, GB2018, doi:10.1029/2006GB002840,
    with new emissions factors developed in collaboration with C. Liousse

NOx, CO, CH4 and NMVOC emissions of all other sectors:

  • Lamarque, J.F., Bond, T.C., Eyring, V., Granier, C., Heil, A., Klimont, Z., Lee, D., Liousse, C., Mieville, A., Owen, B., Schultz, M.G., Shindell, D., Smith, S.J., Stehfest, E., Van Aardenne, J., Cooper, O.R., Kainuma, M., Mahowald, N., McConnell, J.R., Naik, V., Riahi, K., Van Vuuren, D.P., 2010. Historical (1850-2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: Methodology and application. Atmospheric Chemistry and Physics Discussions 10, 4963-5019.

Please use the following references for the land-use/cover history and harmonization presented in the RCP Database:

  • Hurtt, G.C., Chini, L.P., Frolking, S., Betts, R., Feddema, J., Fischer, G., Goldewijk, K.K., Hibbard, K., Janetos, A., Jones, C., Kinderman, G., Kinoshita, T., Riahi, K., Shevliakova,E., Smith, S., Stehfest, E., Thomson, A., Thornton, P., vanVuuren, D., and Y.P. Wang. 2009. Harmonization of global land-use scenarios for the period 1500-2100 for IPCC-AR5. iLEAPS Newsletter 7:6-8.


Acknowledgements

Collaborators during the RCP scenario process.

This list is intended as an indication of the range of scientists and institutions involved in the production of the RCP scenarios. Individuals listed here have participated in a variety of ways, ranging from preliminary planning discussions to substantial work on the scenarios, underlying research, or foundational data sets. No implication in terms of attribution or responsibility should be implied from this document.

(Preliminary list in alphabetical order)

RCP Scenario Process

Jae Edmonds (15)
Kathy Hibbard (6)
Yasuaki Hijioka (11)
Sawako Ishiwatari (11)
Mikiko Kainuma (11)
Etsushi Kato (26)
Tom Kram (16)
Martin Manning (4)
Toshihiko Masui (11)
Ken'ichi Matsumoto (11)
Jerry Meehl (6)
Richard Moss (15)
Nebojsa Nakicenovic (14)
Toru Nozawa (11)
Keywan Riahi (14)
Steve Rose (1)
Steven J Smith (15)
Ron Stouffer (3)
Allison Thomson (15)
Detlef vanVuuren (16)
and John Weyant (2)

Historical Emissions Development

Tami Bond (8)
Janusz Cofala (14)
Veronika Eyring (9)
Claire Granier (7,8)
Angelika Heil (10)
Mikiko Kainuma (11)
Zbigniew Klimont (14)
Jean-Francois Lamarque (5,6)
David Lee (12)
Catherine Liousse (13)
Aude Mieville (7)
Keywan Riahi (14)
Martin Schultz (10)
Steven J Smith (15)
David Stevenson (17)
and John Van Aardenne (18)

Land-Use Scenarios History and Harmonization

Richard Betts(21)
Louise P. Chini (27)
Johannes Feddema (22)
Steve Frolking (19)
Kees Klein Goldewijk (16)
George C. Hurtt (27)
Chris Jones (21)
Tsuguki Kinoshita (11)
Keywan Riahi (14)
Elena Shevliakova (20)
Steven J Smith (15)
Elke Stehfest (16)
Allison Thomson (15)
Peter Thornton (23)
Detlef van Vuuren (16)
and Yingping Wang (24)

RCP Future Emissions Scenarios Development

IIASA (14): Keywan Riahi, Volker Krey, Shilpa Rao, Vadim Chirkov, Cheolhung Cho, Peter Kolp, Nebojsa Nakicenovic, Janusz Cofala, Guenther Fischer, Arnulf Gruebler, Georg Kindermann, Zbigniew Klimont, Peter Rafaj, Wolfgang Schoepp
JGCRI (15): Allison Thomson, Katherine Calvin, Steve Smith, Page Kyle, April Volke, Pralit Patel, Sabrina Delgado, Ben Bond-Lamberty, Marshall Wise, Leon Clarke and Jae Edmonds
NIES (11): Mikiko Kainuma and Toshihiko Masui et al. (to be updated)
PBL (16): Detlef P. van Vuuren, Elke Stehfest, Jasper van Vliet, Michel den Elzen, Angelica Mendoza-Beltran, Morna Isaac, Sebastiaan Deetman, Rineke Oostenrijk and Tom Kram.

Concentration Calculations and Data

Malte Meinshausen (25)
Keywan Riahi (14)
Steve Smith (15)
Detlef van Vuuren (16)

RCP web-database

Peter Kolp (14)
Keywan Riahi (14)

1) Electric Power Research Institute, Washington, DC, USA
2) Department of Management Science and Engineering, Stanford University, Stanford, CA
3) Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey, USA
4) NZ Climate Change Research Institute, Victoria University of Wellington, Wellington, NZ
5) NOAA Earth System Research Laboratory, Chemical Sciences Division, Boulder, CO, USA; Cooperative Institute for Research in Environmental Sciences, University of Colorado at Boulder, Colorado, USA
6) National Center for Atmospheric Research, Boulder, Colorado, USA
7) Laboratoire Atmospheres, Milieux, Observation Spatiales, CNRS UMR 8190, Paris, France; Universite Pierre et Marie Curie, Paris, France
8) University of Illinois, Urbana-Champaign, IL, USA
9) Deutsches Zentrum fuer Luft- und Raumfahrt, Oberpfaffenhoffen, Germany
10) Forschungszentrum, Juelich, Germany
11) National Institute for Environmental Studies, Japan
12) Manchester Metropolitan University, Manchester, UK
13) Laboratoire d'Aerologie, Toulouse, France
14) International Institue for Applied Systems Analysis, Laxenburg Austria
15) Pacific Northwest National Laboratory, Joint Global Change Research Institute, College Park, MD, USA
16) Netherlands Environmental Assessment Agency, Bilthoven, Netherlands
17) University of Edinburgh, Edinburgh, UK
18) Joint Research Center, Ispra, Italy
19) Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824
20) Princeton/GFDL, Princeton, NJ
21) Met Office Hadley Centre, Exeter, UK
22) University of Kansas, Lawrence, KS
23) Oak Ridge National Lab, Oak Ridge, TN
24) CSIRO, Australia
25) Potsdam Institute for Climate Impact Research (PIK), Germany
26) Japan Agency for Marine-Earth Science and Technology, Japan
27) University of Maryland, College Park, MD, USA


RCP Database, 2009
Available at: http://www.iiasa.ac.at/web-apps/tnt/RcpDb


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