The RCP greenhouse gas concentrations and their extensions from 1765 to 2300
We present the greenhouse gas concentrations for the Representative Concentration Pathways (RCPs) and their extensions beyond 2100, the Extended Concentration Pathways (ECPs). These projections include all major anthropogenic greenhouse gases and are a result of a multi-year effort to produce new scenarios for climate change research. We combine a suite of atmospheric concentration observations and emissions estimates for greenhouse gases (GHGs) through the historical period (1750–2005) with harmonized emissions projected by four different Integrated Assessment Models for 2005–2100. As concentrations are somewhat dependent on the future climate itself (due to climate feedbacks in the carbon and other gas cycles), we emulate median response characteristics of models assessed in the IPCC Fourth Assessment Report using the reduced-complexity carbon cycle climate model MAGICC6. Projected ‘best-estimate’ global-mean surface temperature increases (using inter alia a climate sensitivity of 3°C) range from 1.5°C by 2100 for the lowest of the four RCPs, called both RCP3-PD and RCP2.6, to 4.5°C for the highest one, RCP8.5, relative to pre-industrial levels. Beyond 2100, we present the ECPs that are simple extensions of the RCPs, based on the assumption of either smoothly stabilizing concentrations or constant emissions: For example, the lower RCP2.6 pathway represents a strong mitigation scenario and is extended by assuming constant emissions after 2100 (including net negative CO2 emissions), leading to CO2 concentrations returning to 360 ppm by 2300. We also present the GHG concentrations for one supplementary extension, which illustrates the stringent emissions implications of attempting to go back to ECP4.5 concentration levels by 2250 after emissions during the 21st century followed the higher RCP6 scenario. Corresponding radiative forcing values are presented for the RCP and ECPs.
A set of scenarios known as Representative Concentration Pathways (RCPs) has been adopted by climate researchers to provide a range of possible futures for the evolution of atmospheric composition (Moss et al. 2008; Moss et al. 2010). These RCPs complement and, for some purposes, are meant to replace earlier scenario-based projections of atmospheric composition, such as those from the Special Report on Emissions Scenarios (SRES; Nakicenovic and Swart 2000). The RCPs are being used to drive climate model simulations planned as part of the World Climate Research Programme’s Fifth Coupled Model Intercomparison Project (CMIP5) (Taylor et al. 2009) and other comparison exercises. The four RCPs are based on multi-gas emission scenarios which were selected from the published literature (Fujino et al. 2006; Smith and Wigley 2006; Clarke et al. 2007; Riahi et al. 2007; van Vuuren et al. 2007; Hijioka et al. 2008; Wise et al. 2009) and updated for release as RCPs (Masui et al. 2011; Riahi et al. 2011; Thomson et al. 2011; van Vuuren et al. 2011b). Because they were produced by four different Integrated Assessment Models (IAMs), there are some inconsistencies in the relationships between emissions and concentrations that could complicate the interpretation of the climatic consequences of the four different scenarios. Furthermore, although concentrations drive traditional coupled atmosphere-ocean climate models, CMIP5 also includes simulations by Earth System Models (ESMs) with a full representation of the carbon cycle. These ESMs are optionally driven by prescribed emissions of carbon dioxide. The CMIP5 exercise, therefore, requires a set of historical and future pathways for both concentrations and emissions (see Appendix 1), ideally produced by a single model. Starting from these standardised concentration datasets, forthcoming CMIP5 intercomparisons will allow our understanding of the relationship between emissions and concentrations to be re-defined.
Historical mixing ratios of GHG concentrations used to extend RCP concentrations back in time
Historical mixing ratios
Data up to 1832 from Law Dome Ice Core data (Etheridge et al. 1998b) in its 75 year smoothed version a. For 1832 through 1958 the Law Dome 20-year smoothed data are used. This Keeling MLO record(Keeling and Whorf 2004) b is used over 1959 to 1981 with 0.59 ppm subtracted. 0.59 ppm is the mean difference between the Keeling MLO dataseries and the NOAA/ESRL/GMD global estimates over 1982–1986 (Conway et al. 1994)c. The global NOAA/ESRL/GMD data in 1982 and adjusted MLO values are the same at 340.56 ppm. Global NOAA data for 1980 and 1981, but these are not used because they are less consistent with MLO than for subsequent years. From 1982 to 2008, CO2 concentrations were extended with NOAA global-mean datapoints (Conway et al. 1994)c.
Observations up to 1850 are taken from the Law Dome Ice Core data (Etheridge et al. 1998a)d; beyond 1850, the data compilation for the NASA GISS model was usede: this data compilation uses concentration estimates over 1850–1980 from Etheridge et al. (1998a) followed thereafter by data from: NOAA/ESRL/GMD (Dlugokencky et al. 1994) for the period 1984 to 2003. From 2004 to 2008, the mixing ratios are taken from the flask data results from the NOAA ESRL Global Monitoring Divisionf.
Nitrous Oxide (N2O) average mixing ratio data up to 1850 data is taken from Flückiger et al. (2002) in its smoothed version using a 300 year cutoff spline; thereafter, from 1850 onwards, the data compilation by NASA GISS team is usedg. This includes the N2O measurements by Machida et al. (1995) from 1850 to 1977 and NOAA/ESRL/GMD Flask Datah over 1978–1999. From 2000 to 2008, our historical dataseries are sourced from the NOAA/ESRL/GMD In-Situ measurement data provided by G.S. Dutton, T.M. Thompson, J.W. Elkins and B.D. Halli
Historical C2F6 mixing ratios are determined from firn air as presented n Worton et al. (2007), Fig. 2b, which includes model results over 1940 to 2001; before 1940, we linearly interpolated to zero levels in 1900.
An initial pre-industrial mixing ratio of 35 ppt is assumed until 1922, based on Worton et al. (2007) and Deeds et al. (2008). From 1940 to 2003, the mixing ratio is determined from firn air, as provided in Worton et al. (2007). In between, from 1922 to 1940 estimates are based on model results which assume a constant rate of increase.
Based on Culbertson et al. (2004), Table 1 (interpolated end-of-year values between 1978 and 1996); linear interpolation to zero from 1978 to 1970 and linear extrapolation from 1996 to 2000 to attain the average RCP value.
SF6 is regularly measured at multiple NOAA/ESRL/GMD sites and by different techniques. We base our 1961–2008 estimate on a record from firn air, flasks, and in situ instruments from Butler et al. (1999); Geller et al. (1997), and from Peters et al. (2004), linearly interpolated back to zero from 1960 to 1950.
Taken directly from the WMO Stratospheric Ozone Assessment A1 scenario, starting in 1950 (Daniel et al. 2007). These mixing ratio histories are derived using results from global atmospheric measurements, analyses from firn air, archived air, and industrial production and bank data (Montzka et al. 1996a; Butler et al. 1999; Prinn et al. 2000; Metz et al. 2005; Clerbaux et al. 2007). Pre-1950 estimates were loosely based on AFEAS production data and consistent with the 1950 values for CFC-11, CFC-12, CFC-114, and CCl4. Pre-1950 emissions were designed such that 1950 concentration values are matched under the default lifetimes. For example, a linear ramp up of emissions from 1938 to 1950 of HCFC-22 emissions has been assumed to match 1950 concentration value (0.95 ppt). For CH3Br and CH3Cl, a pre-industrial value of 5.8 and 480 ppt is assumed, respectively.
The harmonized GHG concentration and emissions time series recommended for CMIP5 (Taylor et al. 2009) can be obtained from the RCP database website (RCP Database 2009) available at http://www.iiasa.ac.at/web-apps/tnt/RcpDb and the CMIP5 portal (PCMDI 2009) at http://cmip-pcmdi.llnl.gov/cmip5/. Extended GHG datasets until 2500 (for use in very long-term experiments), and further background information on the generation of the harmonized GHG concentration time series are provided at: http://www.pik-potsdam.de/`mmalte/rcps/.
This paper is structured as follows. First, we discuss the general approach taken to derive GHG concentration data for the RCPs in Section 2.1. Historical GHG concentrations from 1765 to 2005 are discussed in Section 2.2. The harmonization of the emissions from the IAMs is covered in Section 2.3, the assumptions used to calculate concentrations and forcing time series for the RCPs over the 21st century are discussed in Section 2.4. The extension of the RCPs beyond 2100 is discussed in Section 3. Section 4 presents the resulting GHG concentration time series for the RCPs. Section 5 discusses the results, including the inverse emission calculations for the extensions, and Section 6 concludes.
2.1 General approach
Each of the IAM teams can, in principle, provide both emissions and concentration data. However, each of the models uses different historical and base year data for the recent past (years 2000–2005). In order to ensure a smooth transition in the climate model runs from the historical period into the future, a harmonization step for emissions was performed here. Furthermore, it was decided that a single model version of MAGICC (e.g. Wigley and Raper 2001; Wigley et al. 2009; Meinshausen et al. 2011a) should be used to produce a more consistent estimate of concentrations and carbon feedbacks, rather than basing the RCPs on a variety of different model versions. GCAM that produced RCP4.5 (Thomson et al. 2011), for example, uses MAGICC5.3, as does AIM that contributed RCP6 (Masui et al. 2011). MESSAGE that produced RCP8.5 (Riahi et al. 2011) uses an updated version of MAGICC4.2, and IMAGE that produced RCP2.6 (Van Vuuren et al. 2011b)1 uses MAGICC6 except for its carbon cycle. Thus, as a second harmonization step, we apply a single climate and carbon cycle treatment, using the latest version 6 of MAGICC (Meinshausen et al. 2011a, b)2 to derive concentrations and inverse emissions for the RCPs.
By design, this study is concerned with providing a ‘reference’ starting point for further analysis in model intercomparison exercises rather than providing a detailed uncertainty analysis of the cause-effect chain from emissions to concentrations and global-mean temperatures. We hence limited this documentation to a detailed description of the chosen assumptions in deriving the RCP’s GHG concentrations, which can serve as the starting point for multi-model ensemble analysis in the future. A detailed description of the cause-effect chain as included in MAGICC6 can be found elsewhere (Meinshausen et al. 2011a), including a representation of uncertainties (Wigley and Raper 2002; Meinshausen et al. 2009).
2.2 Historical concentrations
For comparing climate model outcomes with historical climate observations, it is ideal if atmosphere-ocean general circulation models (AOGCMs) are driven with observations of the historical atmospheric composition. Such a comparison can be helpful for assessing the skill of climate models, or to determine the human-contribution to climate change. Building on current literature, and with the help of a number of experts, we compiled a consolidated set of 20th century global and annual mean GHG concentrations. Specifically, we compiled concentrations of carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), eight different hydrofluorocarbons (HFCs, namely HFC-23, HFC-32, HFC-43-10mee, HFC-125, HFC-134a, HFC-143a, HFC-227ea, and HFC-245fa), three perfluorocarbons (PFCs, namely CF4, C2F6, and C6F14), and SF6, as well as concentrations of 16 ODSs (CFC-11, CFC-12, CFC-113, CFC-114, CFC-115, Carbon Tetrachloride, Methyl chloroform, HCFC-22, HCFC-141b, HCFC-142b, Halon-1211, Halon-1202, Halon-1301, Halon-2402, CH3Br, CH3Cl). Building on this database of historical observations, we recommend sets of pre-industrial control run concentrations, depending on whether the historical ‘20th century’ run starts in 1765, or 1850 (or any year in between). Concentrations over this 1765 to 1850 period are constant for the halogenated gases with natural sources, i.e., CF4, CH3Br and CH3Cl, with 35 ppt, 5.8 ppt and 480 ppt, respectively. However, the recommended concentrations for the long-lived GHGs, CO2, CH4, and N2O show a small increase over that period, starting from the levels 278.1 ppm, 721.9 ppb, and 273.0 ppb in 1765 and increasing to 284.7 ppm, 791.0 ppb, 275.4 ppb in 1850, respectively. The concentrations were compiled based upon data available as of mid-2009 (see Table 1).
2.3 Harmonization of emissions
The harmonization of GHGs, tropospheric ozone precursors and aerosol emissions to common historical levels is necessary as IAMs do not necessarily start with the same historical emissions inventories, which is a disadvantage for comparisons of the scenarios’ future climate effects. There are several reasons that different IAM scenarios do not share the same historical emissions: besides the uncertainty in the historical record, different IAMs 1) do not include the same set of human activities that lead to emissions, 2) smooth short-term fluctuations differently and/or 3) assume different emissions factors from emissive processes. In addition, the actual ‘real world’ activity levels and emissions factors are inherently uncertain. The most appropriate harmonization method depends on the reasons that underlie the differences in historical emission levels. Given the many different sectors and emissions factors in the IAMs, a simple and transparent approach is followed here.
Reactive gas and aerosol emissions have been harmonized to year 2000 levels in a separate exercise in the RCP creation process (Lamarque et al. 2010; Smith et al. 2011; Granier et al. 2011), namely for sulfate oxides (SOx), carbon monoxide (CO), non-methane volatile organic compounds (NMVOC), nitrogen oxides (NOx), black carbon (BC), organic carbon (OC), ammonia (NH3), and also for methane (CH4) because of its role in atmospheric chemistry. Here, we extend this harmonization of the reactive gas emissions to year 2005 by using the average growth rates in RCP8.5, RCP4.5, and RCP2.6.3 This harmonization, therefore, enforces consistency among all RCP scenarios over 2000–2005 period.
Harmonization emission values
Harmonized global Emissions
Fossil & Ind. CO2
Marland et al. (2008)
Scale until 2050b
The recent emission increase until 2008 and stagnation in 2009 have not been used to harmonize RCP emissions, partially because RCPs are not meant to reflect short term fluctuations, partly because 2010 emissions are likely to be close to the harmonized RCP values.
RCP scenarios and Houghton (2008)
Shift until 2030b
2000 is average across RCP2.6, RCP4.5, and RCP8.5 with post-2000 growth rates from Houghton (2008)
Lamarque et al. (2011)
Scale until 2050b
For 2001–2005, the average growth rate across the RCP2.6, RCP4.5 and RCP8.5 scenario is assumed
RCP IAM emission scenarios
Scale until 2050b
Simple average across original IAM emissions for RCP2.6, RCP4.5 and RCP8.5
Smith et al. (2011)
Scale until 2050b
For 2001–2005, the average growth rate across the RCP2.6, RCP4.5 and RCP8.5 scenario is assumed
Lamarque et al. (2011)
Inverse emission estimatea
Scale until 2100b
In order to match the observed mixing ratio record (Worton et al. 2007) a nearly constant 12 kt emission is necessary (as the concentration increase is close to linear). For 2000–2005, using average growth rate of RCP2.6, RCP4.5 and RCP8.5.
Inverse emission estimatea
This emission rate is necessary to match the 0.1 ppt constant mixing ratio increase observed by (Worton et al. 2007).
EDGAR4 (EC-JRC and PBL 2009)
RCP2.6 is the only RCP reporting C6F14 with 1.6kt in year 2000. The lower EDGAR4 data was assumed for harmonization.
Inverse emission estimatea
Taken from original RCP2.6
RCP2.6 is the only RCP reporting HFC-32 emissions.
Average of SRES B1 & A2
As no data was reported in RCP scenarios, the average across SRES B1 & A2 emissions have been assumed. RCP2.6, RCP4.5 and RCP6 follow the stabilizing SRES B1 emissions and RCP8.5 follows A2 emissions.
Inverse emission estimatea
Inverse emission estimatea
Inverse emission estimatea
Inverse emission for 2000 to match observed atmospheric mixing ratios measured by Culbertson et al. (2004) with 2001-2005 emission growth rate taken as average from RCP2.6, RCP4.5 and RCP8.5.
EDGAR4 (EC-JRC and PBL 2009)
As for HFC-245fa, recent observations (Laube et al. 2010) suggest smaller actual emissions.
RCP4.5 original data
RCP4.5 derived their HFC-245fa emissions based on a later set of EMF-22 data than RCP2.6 or RCP8.5. Note that this is substantially higher than recently observed (Vollmer et al. 2006), although the latter implies higher rates of increase.
Inverse emission estimatea
Inverse emission estimate based on a constant lifetime of 3200 years and observed mixing ratios. Based on Butler et al. (1999) and Geller et al. (Geller et al. 1997), and Peters et al. (Peters et al. 2004).
We employ a harmonization process whereby the original IAM emission data is adjusted to the common 2000–2005 values and these adjustments are phased out afterwards. Specifically, the longer term RCP emission levels are identical to those of the original IAM emissions from 2050 onwards. In between, from 2005 to 2050, a multiplier, i.e., the ratio between RCP harmonized emission levels and original IAM emissions in 2005, is linearly relaxed back to 1 until 2050 (c.f. Van Vuuren et al. 2008).
Exceptions to this approach are applied for land-use related CO2 emissions and some fluorinated gases. Land-use related CO2 emissions turn negative in some regions, which is why we chose to apply an additive shift of emissions rather than a multiplier. The difference between original IAM emissions and the harmonized levels in 2005 is added to the original IAM data and this offset is linearly reduced to zero by 2030. A scaling factor rather than an offset until 2050 could have resulted in more pronounced negative emissions even in the case of an upward adjustment in 2005.
For fluorinated gases, the SRES scenarios used an external set of emissions (Fenhann 2000). In contrast, the IAMs producing the RCP scenarios now include fluorinated gas emissions in their modeling frameworks. For some fluorinated gas species, updated information on their trends is available, which causes IAMs to project markedly different future emissions compared to SRES. Some IAMs, however, include only a few aggregate fluorinated gas categories. This leads to somewhat artificially narrowed spreads for some fluorinated gas projections.
The net effect of the harmonization procedure for the long-lived GHGs and ODSs is in some years moderate, but is generally small and negligible in the long-term. Over all years, the highest upward shift in GWP-weighted (100 year time horizon) (IPCC 1996) aggregate emission levels is 11.5% for the RCP6 scenario, which is due to a substantial upward shift of landuse CO2 emissions from 1.3 to 4.4 GtCO2/yr in year 2005 (+226%). A 4.1% upward adjustment of the RCP2.6 scenario in 2005 resulted as well from the harmonization of landuse CO2 emissions from 2.8 to 4.4 GtCO2/yr in year 2005, in addition to small upward corrections of CH4 and fluorinated gases (see Fig. 2). Harmonization reduced the RCP8.5 emissions slightly, by 2.1% in 2005. The aggregate emission levels of RCP4.5 faced a small upward shift by 2.1% in 2005. By construction, the harmonization procedure had only negligible effects on post-2050 emission levels (<0.3%) given that only a few fluorinated gases were adjusted after 2050.
Note that these induced shifts of emission levels are within the uncertainty of current emission estimates. Nevertheless, due to the cumulative effect on radiative forcing levels for long-lived gases, the harmonization procedure will result in slightly different concentration and temperature projections (which is intended as part of increasing the comparability between the different scenarios). To ensure a smooth transition of concentrations from historical runs for shorter-lived substances, the harmonization is an essential step for consolidating the scenarios from four different IAMs for a climate model inter-comparison. Otherwise, a consistent comparison of the resulting climate consequences across the scenarios would be hindered.
Some other limitations of the harmonized emissions arose. The ODS projections (WMO 2007) do not incorporate the effects of the accelerated HCFC phase-out accepted by the Parties to the Montreal Protocol in 2007. In the absence of specific mitigation policies, this acceleration would be expected to lead to somewhat lower future HCFC emissions (Velders et al. 2007). and higher HFC emissions (Velders et al. 2009). Furthermore, NF3 (as well as several less abundant fluorinated gas compounds) are not included in the RCPs even though they may have small positive radiative forcing effects (Prather and Hsu 2008; Prather and Hsu 2010).
2.4 Calculation of GHG concentrations
In most of the experiments for the CMIP5 intercomparison exercise, AOGCMs and ESMs will be driven by historical and future GHG concentrations, not emissions, as shown in Appendix 1 and further described in Taylor et al. (2009). We derive concentrations from the harmonized emissions with a single model, MAGICC6, in order to ensure consistency between and within the different RCPs. Although various versions or parts of MAGICC are used in many IAMs (see above), we chose MAGICC not as a model in its own right, but because of its ability to closely emulate the full range of C4MIP carbon cycle and CMIP3 AOGCMs (Meinshausen et al. 2011a). We now summarize the various gas-cycle parameterizations, before providing more detail on the chosen carbon cycle and climate response settings. Our assumptions regarding non-GHG forcing agents are detailed in Appendix 2.
MAGICC uses gas-cycle parameterizations of different complexity to project concentrations and radiative forcing for CO2, CH4, N2O,3 PFCs, 8 HFCs, SF6 and 16 ODSs (see listing of individual species in Section 2.2). For CO2, MAGICC includes a global carbon cycle model with three land carbon pools, an ocean carbon scheme, and multiple temperature-dependent terrestrial and oceanic fluxes, as well as a parameterization for the CO2 fertilization effect. The model is designed to closely emulate higher complexity carbon cycle models regarding seven aggregated carbon pools and fluxes, as well as atmospheric CO2 concentrations, as described in detail in Meinshausen et al. (2011a). The model does not yet include a nitrogen cycle or interactions between the carbon cycle and nitrogen cycle – reflecting the state of carbon cycle models in C4MIP in 2006 (Friedlingstein et al. 2006). The chosen carbon cycle calibration is further described below.
For projecting CH4 and N2O concentrations, parameterizations from Ehhalt et al. (2001) are used—including simplified temperature-dependent tropospheric OH-chemistry parameterizations. Both CH4 and N2O lifetime includes a dependency of its lifetime on its own abundance. Further details regarding how these processes are treated in MAGICC6 can be found in Meinshausen et al. (2011a). Stratospheric sinks for all fluorinated gases and ODSs are assumed to become enhanced slightly with rising global mean temperatures (15% per degree Celsius warming) leading to shorter lifetimes at higher warming levels—due to a strengthening Brewer-Dobson circulation (Butchart and Scaife 2001). As the lifetime of CH4, tropospheric OH-related sinks of flourinated gases are made dependent on the parameterized changes in the OH abundances.
Previous applications of MAGICC6 have not used a single set of best-estimate parameters to calculate concentrations, radiative forcings and global mean temperatures from prescribed emissions, but instead used an array of parameter sets to project a range of climate responses by emulating CMIP3 GCMs (Meehl et al. 2005) and to project a range of CO2 concentrations by emulating C4MIP carbon cycle models (Friedlingstein et al. 2006) as described in Meinshausen et al. (2011a). Alternatively, historically constrained joint distributions of parameters were used (Meinshausen et al. 2009). To calculate a single set of concentrations for driving climate models (the motivation for the design of the RCPs), we need a single “best” set of model parameters for MAGICC. Many temperature projections will ultimately be produced by the CMIP5 models. However, the importance of having a ‘best-estimate’ future temperature projection within MAGICC6 is that many gases’ concentrations are influenced by temperature or climate feedbacks.
We chose parameters for MAGICC6 that would closely reflect the median of the distribution in global-mean temperature projections that is spanned when emulating the GCMs and carbon cycle models that took part in CMIP3 and C4MIP, respectively. Specifically, we chose an emulation of the C4MIP Bern-CC carbon cycle model (Joos et al. 2001) as ‘best-estimate’ for the carbon cycle behavior. This is both because the Bern-CC model (and earlier versions of this model) has been used for the consolidated concentrations of IPCC SRES scenarios presented in the Third Assessment Report (see Appendix II in Houghton et al. 2001) and because the projected CO2 concentrations from the Bern model are roughly in the middle of the range of C4MIP results (Friedlingstein et al. 2006).
For obtaining a ‘best-estimate’ climate response (which in turn influences concentrations), the intention is to have a set of climate parameters (such as climate sensitivity, vertical ocean diffusivity, etc.) that resembles the median of the AOGCMs that took part in CMIP3. We first emulated 19 of the CMIP3 AOGCMs by using calibrated MAGICC parameters, which span a climate sensitivity range between 1.9 K and 5.7 K (see Table B3 in Meinshausen et al. 2011a). We ran these emulations for the SRES A1B, B1 and A2 and ‘Constant year 2000 concentration’ scenarios, taking into account a complete set of radiative forcing agents (including e.g. indirect aerosol effects). In these emulations, we used the default Bern-CC emulation setting for the MAGICC carbon cycle. We then took the median for each scenario across these 19 global mean temperatures and ocean heat uptake time-series. Thereby, we created pseudo-AOGCM datasets, to which a standard least-squares optimization routine could calibrate a “best” set of 10 climate parameters of MAGICC. This is the same procedure as described in Meinshausen et al.(2011a), except that we fix the climate sensitivity at its best-estimate value of 3 K (Meehl et al. 2007; Knutti and Hegerl 2008). This fixed climate sensitivity is very close to the average of 2.88 K from emulating AOGCM CMIP3 models without a fixed climate sensitivity (see Table 4 in Meinshausen et al. 2011a).
Apart from deriving the default MAGICC climate response parameter set for creating the RCPs, one additional amendment has been implemented in MAGICC6 to serve this RCP process. Inverse emissions are now routinely calculated for all 31 considered GHGs (CO2, CH4, N2O, 3 PFCs, 8 HFCs, SF6 and 16 ODSs). This is of interest when concentration time-series are prescribed for designing the ECPs. For CO2, these inverse emissions can be compared to the allowable emissions derived from ESMs in the course of CMIP5.
3 Post-2100 extension
The RCPs and their simple extension rules beyond 2100 assumed for all GHGs.
RCP scenario 2005-2100
Extension 2100 to 2300
Constant emissions after 2100.
Smooth transition towards concentration stabilization level after 2150 achieved by linear adjustment of emissions between 2100 and 2150.c
Constant emissions after 2100, followed by a smooth transition to stabilized concentrations after 2250 achieved by linear adjustment of emissions after 2150.b
Supplementary Extension SCP6to4.5
Adjustment of emissions after 2100 to reach RCP4.5 concentrations levels in 2250 and thereafter.
Generally, there are three options for the design of a simple extension (with multiple combinations of these possible): I) the forcing and concentrations can simply be kept constant (as done for the SRES scenarios in CMIP3 and assessed by the IPCC Forth Assessment Report, AR4), II) emissions can be adapted over time, e.g. to yield a smooth stabilization at another level than where concentrations are in year 2100, or III) emissions can be kept constant. The two intermediate scenarios RCP4.5 and RCP6 are extended by concentration stabilization, albeit with stabilization achieved in 2150 to avoid discontinuities in the implied emissions. For the lowermost RCP, RCP2.6, emissions were kept constant after 2100. The extension of the highest RCP, RCP8.5, represents a mixture of constant emissions until 2150 and constant concentrations after 2250 (see Table 3). As a result of now including a low mitigation pathway RCP2.6 and due to these extension choices, the ECPs span a much wider range of post-2100 forcing pathways than considered in previous studies, such as CMIP3 assessed in IPCC AR4.
Several alternative extensions were considered for each RCP. For RCP8.5, the full range of possible extensions ranged from a constant forcing that results from simply keeping concentrations constant after 2100 to very high levels that result from assuming that emissions stay constant until 2300. After consultations with the respective expert groups an intermediate extension was selected. This extension avoids a possible discontinuity in emissions trends (that would arise from keeping concentrations constant), and avoids issues of resource availability that a higher extension might raise. Keeping emissions constant would have resulted in CO2 concentration of around 3000 ppm by 2300. The adopted RCP8.5 extension (ECP8.5) leads to a CO2 stabilization after 2250 at roughly 2000 ppm, or more than 7-times pre-industrial CO2 concentrations. The total forcing of this ECP8.5 is hence approximately twice as high as the next highest ECP (ECP6) (see Fig. 4 below). This high forcing for ECP8.5 is significantly above the highest forcing level that was considered in CMIP3 on the basis of IPCC SRES scenarios (i.e., approximately 700 ppm in A1B).
Another alternative extension was considered for RCP2.6, as one may question whether negative emissions can be sustained over very long time periods (in view of finite CO2 storage capacity). An alternative extension, in which emissions would converge back to zero between 2,150 and 2,200, would lead to CO2 concentration of about 380 ppm rather than 360 ppm by 2300. However, in consultation with experts it was concluded that a continuation of the 2100 emission levels cannot be excluded for reasons of physical constraints of sequestration & storage options and would better reflect the character of the RCP2.6 pathway.
Similar to this SCP6to4.5 extension, we considered an alternative ECP6 extension with comparatively less stringent post-2100 emission reductions, basically assuming that the RCP2.6 emissions path is followed 100 years later, i.e., in the 22nd century. Specifically, 2020–2100 RCP2.6 emission trajectories were assumed for 2120 to 2200—with linear interpolation between 2100 RCP6 and the extension by 2120. We kept emissions constant after 2200. Following that alternative, radiative forcing would have declined to 4.5 W/m2 only 350 years later, i.e., by 2450.
The conclusion from this alternative RCP6 extension and our SCP6to4.5 supplementary extension is that once high 21st century emissions increase radiative forcing levels to 6 W/m2, it seems very difficult to return to lower levels quickly. Any 4.5 W/m2 overshoot scenario of the sort considered here will imply higher global warming levels for considerable periods of time, i.e., centuries,—and rests on the assumption that stringent post-2100 emission reductions are feasible. A similar conclusion could be drawn for extensions that connect RCP8.5 to ECP6 or RCP4.5 to ECP3-PD long-term concentration levels5.
For the fluorinated gases within the basket of gases that are controlled under the Kyoto Protocol (HFCs, PFCs, and SF6), projections are inherently uncertain, as new applications are constantly being developed (apart from the fact that new fluorinated compounds are designed). For the purpose of designing the SCP6to4.5 extension, a question arises how to bridge the gap between the lower ECP6 fluorinated gas concentration levels towards the higher ECP4.5 ones. Partly because this gap is very small, only 2% in terms of the total radiative forcing difference between ECP6 and ECP4.5, and partly for simplicity, we modify only the emissions of the representative forcing agent HFC-134a in order to ramp up the aggregate forcing from HFCs, PFCs, and SF6.
4 Results: RCP GHG concentrations
This section presents the resulting GHG concentrations for the RCPs and ECPs, as well as the aggregate total radiative forcing. Total radiative forcing here includes all anthropogenic forcing agents as listed in Table 2.12 in IPCC AR4 WG1 (Forster et al. 2007), including—inter alia—direct and indirect aerosol forcings. See Appendix 2 for assumptions in regard to non-GHG forcings.
GHG concentrations for pre-industrial, historical, RCP and ECP/SCPs
GHG Forcing Agent (Unit)
HFCs, PFCs, SF6 (ppt HFC-134a-eq) a
ODS (ppt CFC-12-eq) a
HFCs, PFCs, SF6 (HFC-134a-eq ppt)
ODS (CFC-12-eq ppt)
RCP4.5 and RCP6 are both stabilization scenarios, with constant concentrations after 2150. By stabilizing CO2 concentrations at 543 ppm, RCP4.5 comes very close to a doubling of pre-industrial CO2 concentration (278 ppm)—and is hence only slightly higher than the SRES B1 scenario and its constant extension after 2100 with 540 ppm CO2 (see Bern-CC (reference) case in Appendix II.2.1 in Houghton et al. 2001). The RCP6 scenario stabilizes 200 ppm higher, at 752 ppm CO2 (see Fig. 5).
5.1 Ensemble results compared to our default concentration and temperature projections
In the above text we selected a specific (‘best-estimate’) set of MAGICC parameters to use in producing a standard set of RCP concentrations. Starting from the harmonized emissions, we can also produce concentrations (and forcing and temperature projections) using 19 individual CMIP3 climate and 9 C4MIP carbon cycle emulations. How does our default set of results compare with the distribution of results from these 171 (=19 × 9) cases?
In summary, our default carbon cycle/climate model settings are shown to reflect well the median emulated responses of both the AOGCM and carbon cycle response. The implied relation between emissions and concentrations may, of course, change with the next generation of models. It will be useful to compare the climate and carbon-cycle responses from the next round of climate model experiments with those presented here, which are, necessarily, calibrated to existing model experiments. The allowable CO2 emissions for these pathways could, for example, be lower (or higher) than those found here, if positive carbon cycle feedbacks were higher (or lower) in the CMIP5 generations of ESMs compared with C4MIP models. Similarly, including a nitrogen cycle in the MAGICC and other carbon cycle models will affect future forward and inverse projections (Thornton et al. 2007, 2009).
5.2 Inverse emissions for the long-term extension pathways
The extensions of the RCPs and the generation of the supplementary pathway were made using the simple rules given in Table 3. While these extensions are simply thought experiments, we examine here the implied emissions from the SCP6to4.5 scenario to illustrate some key points relevant to future long-term scenarios. The inverse emissions that correspond to this overshoot scenario imply a period of substantial net negative CO2 emissions of -13.9 GtCO2/year—between 2150 and 2230 (see Fig. 3). This value is larger in magnitude than the negative emissions level in the RCP2.6 scenario (−0.93 GtC/yr = −3.41GtCO2/yr), but there are scenarios in the literature that imply similarly negative emission levels already by 2100. For example, Calvin et al. (2009) show scenarios with slightly larger negative emissions levels by 2100 of -10 to -15 GtCO2/year in 2095. In addition to sustained net negative emissions in SCP6to4.5, the reduction rates assumed between 2100 and 2150 are rather substantial, similar to the steepest segments of RCP4.5 and RCP2.6 – but extended over a longer time period.
As highlighted in Fig. 3a, CO2 emissions for the SCP6to4.5 have to be reduced below the RCP4.5 emissions by approximately the same amount as the extra cumulative emissions that were emitted during the 21st century by RCP6. On the timescales of interest here, CO2 does not have finite lifetime (Archer and Brovkin 2008), but is simply being re-distributed between the different active carbon pools. This is largely why cumulative CO2 emissions are a crucial quantity for long-term temperature and atmospheric concentration responses (Kheshgi et al. 2005; Allen et al. 2009; Matthews et al. 2009). For this reason, cumulative emissions for the RCP4.5-ECP4.5 pathway and the RCP6-SCP6to4.5 pathway are roughly of the same size (see Fig. 3b).
For other long-lived GHGs such as N2O, the need to compensate for initially higher emissions with lower emissions later on is still apparent, although cumulative N2O emissions are a bit higher under the SCP6to4.5 pathway compared to RCP4.5-ECP4.5 —even though both paths ultimately stabilize at the same N2O concentration levels by design (see Fig. 3 e&f). For CH4, with its much shorter atmospheric lifetime (Forster et al. 2007), the ultimate concentration depends almost solely on emissions over the final few decades rather than on long-term cumulative emissions.
The challenge this study faces is to synthesize gas-cycle and climate response characteristics from a broad body of literature into a single-best set of data and model parameters to produce a common starting point for future model intercomparison exercises. By design, we therefore do not intend to fully represent uncertainties, but rather seek to produce concentration scenarios that reflect ‘middle-of-the-road’ carbon cycle and climate model responses, representative of the IPCC AR4 state of knowledge. While some parts of our approach can thereby be based on recent intercomparison exercises, in particular C4MIP and CMIP3, other assumptions relate to earlier community efforts, such as the OxComp workshop (Ehhalt et al. 2001). Uncertainties pertaining to future OH concentrations, CH4 lifetimes, N2O concentrations or the effect of the inclusion of a nitrogen cycle will result in different ‘reference’ pathway recommendations if this exercise were to be repeated in a couple of years from now. Furthermore, uncertainties arise as well from second-order effects of tropospheric ozone and aerosols, for example. To the extent that our non-GHG modeling assumptions deviate from current generation chemistry modeling results (see e.g. Lamarque in this issue for a comparison of tropospheric ozone levels), indirect effects via global-mean temperature and gas-cycle feedbacks will impact derived GHG concentrations presented here, although this indirect second-order effect is likely limited.
Regarding the RCP extensions, we reiterate that these ECPs are highly stylized and are not the result of detailed analyses of resource limits, but are instead presented in order to provide a range of concentration and forcing pathways for use in climate model experiments. In contrast to the simple stabilization of concentrations after 2100 used for CMIP3, the current ECPs provide a wider range of forcing pathways in which to test long-term model responses.
The historical, 21st century and extended GHG concentration and harmonized emission data presented here are a result of a wide collaboration across scientific communities. In order to obtain a single set of best-estimate projections for future GHG concentrations for the four RCP scenarios, we used an emulation of the median response of both climate and carbon cycle models that took part in the previous climate model inter-comparison exercises CMIP3 (Meehl et al. 2005) and C4MIP (Friedlingstein et al. 2006). The derived concentration results are generated as the starting point for the CMIP5 inter-comparison exercise (Taylor et al. 2009), which will be evaluated in the forthcoming IPCC Fifth Assessment Report. While the inverse emission results here can also provide a yardstick for comparison, it can be expected that the forthcoming CMIP5 generation of ESMs will diagnose ‘allowable’/inverse emissions that differ from the harmonized emissions presented here. This is because of limitations in the extrapolation of previous model's emulation results, and partly because of new process parameterizations within the new generation of climate and carbon cycle models.
While the provision of concentration pathways for use in model inter-comparison exercises is the end point for the RCP scenario production activity, this is still just the beginning of the overall scientific effort to investigate climate change, its impacts and mitigation options under different scenarios (Moss et al. 2010). With respect to the IPCC WG1 community, the harmonized concentrations and emissions data provided here are a starting point for model experiments that will enable a deeper understanding of the earth systems’ response to the anthropogenic perturbations that are driving climate changes.
A note on the naming of the lower RCP pathway: In the literature, this lower pathway is both called RCP3-PD and RCP2.6. “PD” reflects the unique characteristic of this pathway, i.e., its “Peak & Decline” shape—in contrast to other mere stabilization scenarios. Historically, two candidates were discussed for this lower RCP, RCP2.6 and RCP2.9 with RCP2.6 being finally chosen. Hence, both names, RCP3-PD and RCP2.6, can be used interchangeably.
A research version of MAGICC6 with RCP default settings used in this study will be available from www.magicc.org for the wider scientific community.
RCP6 was harmonized as well, but its values were not used to determine the growth rates (or other averages for harmonization) due to the later finalization date of this data set. Taking into account RCP6 does not substantially change these results relative to other uncertainties.
1GtC/yr = 44/12 GtCO2/yr
An optional extra extension is provided online as addition to the RCPs and extensions described in this paper, i.e., an extension that brings concentrations back to RCP3-PD levels after 21st century emissions followed RCP4.5. See http://www.pik-potsdam.de/~mmalte/rcps/.
available at http://www.pik-potsdam.de/~mmalte/rcps/.
We are deeply thankful to all those in the scientific community, that contributed invaluable assistance, datasets, model code and review comments. Without those contributions, creating the harmonized and consolidated GHG concentrations for the RCP scenarios would not have been possible. We are especially indebted to Tom M. L. Wigley and Karl E. Taylor for helpful in-depth comments on an earlier manuscript version. Furthermore, we thank those, who contributed critical data and assistance, namely Toshihiko Masui, Peter Kolp, Volker Krey, A. Mendoza Beltrán, E. Stehfest, Robert Andres, Greg Marland, Richard Houghton, Judith Lean, David Worton, Makiko Sato, Edward Dlugokencky, Patricia Lang, Kenneth A. Masarie, D.M. Etheridge, J.A. Culbertson, G.S. Dutton, T.M. Thompson, J.W. Elkins, B.D. Hall, J. Flückiger, J. van Aardenne, J. Nabel, K. Markmann, J. Rogelj, and Chris Jones and the contributors to data.giss.nasa.gov.
This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
- Canadell JG, Le Quere C, Raupach MR, Field CB, Buitenhuis ET, Ciais P, Conway TJ, Gillett NP, Houghton RA, Marland G (2007) Contributions to accelerating atmospheric CO2 growth from economic activity, carbon intensity, and efficiency of natural sinks. Proc Natl Acad Sci USA 104(47):18866–18870CrossRefGoogle Scholar
- Clarke L, Edmonds J, Jacoby H, Pitcher H, Reilly J, Richels R (2007) Scenarios of the greenhouse gas emission 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. Washington, USA, Department of Energy, Office of Biological & Environmental Research, p 154Google Scholar
- Clerbaux C, Cunnold D, Anderson J, Bernath P, Engel A, Fraser PJ, Mahieu E, Manning AC, Miller J, Montzka SA, Prinn R, Reimann S, Rinsland CP, Simmonds P, Verdonik D, Wuebbles D, Yokouchi Y (2007) Long-lived compounds, Chapter 2. Scientific Assessment of Ozone Depletion: 2006, Global Ozone Research and Monitoring Project - Report No. 50. World Meteorological Organization. GenevaGoogle Scholar
- Conway TJ, Tans PP, Waterman LS, Thoning KW (1994) Evidence for interannual variability of the carbon-cycle from the national-oceanic-and-atmospheric-administration climate-monitoring-and-diagnostics-laboratory global-air-sampling-network. J Geophys Res Atmos 99(D11):22831–22855CrossRefGoogle Scholar
- Daniel JS, Velders GJM, Douglass AR, Forster PMD, Hauglustaine DA, Isaksen ISA, Kuijpers LJM, McCulloch A, Wallington TJ (2007) Halocarbon scenarios, ozone depletion potentials, and global warming potentials, Chapter 8. Scientific Assessment of Ozone Depletion: 2006, Global Ozone Research and Monitoring Project - Report No. 50. World Meteorological Organization, GenevaGoogle Scholar
- Deeds DA, Muhle J, Weiss RF (2008) Tetrafluoromethane in the deep North Pacific Ocean. Geophys Res Lett 35(14)Google Scholar
- EC-JRC and PBL (2009) European Commission, Joint Research Centre (JRC)/Netherlands Environmental Assessment Agency (PBL)—Emission Database for Global Atmospheric Research (EDGAR), release version 4.0. from http://edgar.jrc.ec.europa.eu
- Ehhalt D, Prather MJ, Dentener F, Derwent RG, Dlugokencky E, Holland E, Isaksen ISA, Katima J, Kirchhoff V, Matson P, Midgley P, Wang M (2001) Atmospheric chemistry and greenhouse gases. In: Houghton JT, Ding Y, Griggs DJ et al (eds) Climate change 2001: The scientific basis. Cambridge University Press, Cambridge, p 892Google Scholar
- Etheridge DM, Steele LP, Langenfelds RL, Francey RJ, Barnola JM, Morgan VI (1998b) Historical CO2 record from the Law Dome DE08, DE08-2, and DSS ice cores. Retrieved May, 2007, from ftp://ftp.ncdc.noaa.gov/pub/data/paleo/icecore/antarctica/law/law_co2.txt
- Fluckiger J, Monnin E, Stauffer B, Schwander J, Stocker TF, Chappellaz J, Raynaud D, Barnola JM (2002) High-resolution Holocene N2O ice core record and its relationship with CH4 and CO2. Global Biogeochem Cy 16(1)Google Scholar
- Forster P, Ramaswamy V, Artaxo P, Berntsen T, Betts R, Fahey DW, Haywood J, Lean J, Lowe DC, Myhre G, Nganga J, Prinn R, Raga G, Schulz M, Van Dorland R (2007). Chapter 2: Changes in Atmospheric Constituents and in Radiative Forcing. IPCC Fourth Assessment Report WG 1. IPCC. Cambridge, Cambridge University PressGoogle Scholar
- Friedlingstein P, Cox P, Betts R, Bopp L, von Bloh W, Brovkin V, Cadule P, Doney S, Eby M, Fung I, Bala G, John J, Jones C, Joos F, Kato T, Kawamiya M, Knorr W, Lindsay K, Matthews HD, Raddatz T, Rayner P, Reick C, Roeckner E, Schnitzler K-G, Schnur R, Strassmann K, Weaver K, Yoshikawa C, Zeng N (2006) Climate–carbon cycle feedback analysis: results from the C4MIP model intercomparison. J Clim 19(14):3337–3353CrossRefGoogle Scholar
- Fujino J, Nair R, Kainuma M, Masui T, Matsuoka Y (2006) Multi-gas mitigation analysis on stabilization scenarios using aim global model. Energ J 343–353Google Scholar
- Granier C, Bessagnet B, Bond T, D’Angiola A, van der Gon HG, Frost G, Heil A, Kainuma M, Kaiser J, Kinne S, Klimont Z, Kloster S, Lamarque JF, Liousse C, Matsui T, Meleux F, Mieville A, Ohara T, Riahi K, Schultz M, Smith S, Thomson AM, van Aardenne J, van der Werf G (2011). Evolution of anthropogenic and biomass burning emissions at global and regional scales during the 1980–2010 period. Climatic Change (this issue). doi:10.1007/s10584-011-0154-1
- Hijioka Y, Matsuoka Y, Nishimoto H, Masui M, Kainuma M (2008) Global GHG emissions scenarios under GHG concentration stabilization targets. J Global Environ Eng 13:97–108Google Scholar
- Houghton RA (2008) Carbon flux to the atmosphere from land-use changes: 1850–2005. In TRENDS: A compendium of data on global change. Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tenn., U.S.A. from http://cdiac.ornl.gov/trends/landuse/houghton/houghton.html
- Houghton J, Ding Y, Griggs DJ, Noguer M, van der Linden PJ, Xiaosu D (eds) (2001) Climate change 2001: The scientific basis; contribution of working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change (IPCC)ge. Cambridge University Press, CambridgeGoogle Scholar
- Hurtt G, Chini L, Frolking S, Betts R, Edmonds J, Feddema J, Fisher G, Goldewijk K, Hibbard KA, Houghton R, Janetos A, Jones C, Kinderman G, Konoshita T, Riahi K, Shevliakova E, Smith S, Stehfest E, Thomson A, Thornton P, van Vuuren DP, Wang Y (2011). Land use Change and earth system dynamics. Climatic Change (this issue). doi:10.1007/s10584-011-0153-2
- IPCC (1996) Climate change 1995: The science of climate change. Contribution of WGI to the Second Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, CambridgeGoogle Scholar
- Keeling CD, Whorf TP (2004) Atmospheric CO2 records from sites in the SIO air sampling network. Retrieved May, 2007, from http://cdiac.esd.ornl.gov/trends/co2/sio-keel.htm
- Lamarque JF, Bond TC, Eyring V, Granier C, Heil A, Klimont Z, Lee D, Liousse C, Mieville A, Owen B, Schultz MG, Shindell D, Smith SJ, Stehfest E, Van Aardenne J, Cooper OR, Kainuma M, Mahowald N, McConnell JR, Naik V, Riahi K, van Vuuren DP (2010) Historical (1850–2000) gridded anthropogenic and biomass burning emissions of reactive gases and aerosols: methodology and application. Atmos Chem Phys 10(15):7017CrossRefGoogle Scholar
- Lamarque JF, Riahi K, Smith S, van Vuuren DP, Vitt F, Meinshausen M (2011) Simulated evolution of the distribution of short-lived greenhouse gases and aerosols using the emissions from the Representative Concentration Pathways. Climatic Change (this issue). doi:10.1007/s10584-011-0155-0
- Laube JC, Martinerie P, Witrant E, Blunier T, Schwander J, Brenninkmeijer CAM, Schuck TJ, Bolder M, Rockmann T, van der Veen C, Bonisch H, Engel A, Mills GP, Newland MJ, Oram DE, Reeves CE, Sturges WT (2010) Accelerating growth of HFC-227ea (1,1,1,2,3,3,3-heptafluoropropane) in the atmosphere. Atmos Chem Phys 10(13):5903–5910CrossRefGoogle Scholar
- Lean JL, Rind DH (2009) How will Earth’s surface temperature change in future decades? Geophys Res Lett 36Google Scholar
- Lowe JA, Huntingford C, Raper SCB, Jones CD, Liddicoat SK, Gohar LK (2009) How difficult is it to recover from dangerous levels of global warming? Environ Res Lett 4(1)Google Scholar
- Marland G, Boden TA, Andres RJ (2008) Global, regional, and national fossil fuel CO2 emissions. In Trends: A Compendium of Data on Global Change. O. R. N. L. Carbon Dioxide Information Analysis Center, U.S. Department of Energy. Oak Ridge, Tenn., USAGoogle Scholar
- Masui T, Matsumoto K, Hijioka Y, Kinoshita T, Nozawa T, Ishiwatari S, Kato E, Shukla PR, Yamagata Y, Kainuma M (2011). An Emission Pathway for Stabilization at 6 W/m2 Radiative Forcing. Climatic Change doi:10.1007/s10584-011-0150-5
- Meehl GA, Covey C, McAvaney B, Latif M, Stouffer RJ (2005) Overview of coupled model intercomparison project. Bull Am Meteorol Soc (BAMS) 86(89)Google Scholar
- Meehl GA, Stocker TF, Collins W, Friedlingstein P, Gaye A, Gregory JM, Kitoh A, Knutti R, Murphy J, Noda A, Raper SCB, Watterson I, Weaver A, Zhao Z-C (2007). Chapter 10: Global climate projections. IPCC Fourth Assessment Report. IPCC. Cambridge, Cambridge University PressGoogle Scholar
- Metz B, Kuijpers L, Solomon S, Anderson SO, Davidson O, Pons J, de Jager D, Kestin T, Manning M, Meyer L (eds) (2005) IPCC/TEAP special report on safeguarding the ozone layer and the global climate system: Issues related to hydrofluorocarbons and perfluorocarbons. Cambridge University Press, New YorkGoogle Scholar
- Moss R, Babiker M, Brinkman S., Calvo E, Carter TR, Edmonds J, Elgizouli I, Emori S, Erda L, Hibbard K, Jones R, Kainuma M, Kelleher J, Lamarque J-F, Manning MR, Matthews B, Meehl J, Meyer L, Mitchell JFB, Nakicenovic N, O’Neill B, Pichs R, Riahi K, Rose SK, Runci P, Stouffer RJ, van Vuuren DP, Weyant JP, Wilbanks TJ, van Ypersele JP, Zurek M (2008) Towards new scenarios for analysis of emissions, climate change, impacts, and response strategies: IPCC Expert Meeting Report, 19–21 September 2007. Noordwijkerhout, The Netherlands, pp 155Google Scholar
- Moss RH, Edmonds JA, Hibbard KA, Manning MR, Rose SK, van Vuuren DP, Carter TR, Emori S, Kainuma M, Kram T, Meehl GA, Mitchell JFB, Nakicenovic N, Riahi K, Smith SJ, Stouffer RJ, Thomson AM, Weyant JP, Wilbanks TJ (2010) The next generation of scenarios for climate change research and assessment. Nature 463(7282):747–756CrossRefGoogle Scholar
- Nakicenovic N, Swart R (eds) (2000) IPCC special report on emissions scenarios. Cambridge University Press, CambridgeGoogle Scholar
- Olivier JGJ, Peters JAHW (2010) No growth in total global CO2 emissions in 2009. Bilthoven, Netherlands, Netherlands Environmental Assessment Agency (PBL) 16Google Scholar
- PCMDI (2009) CMIP5 Coupled Model Intercomparison Project—Overview. from http://cmip-pcmdi.llnl.gov/cmip5/
- Peters W, Krol MC, Dlugokencky EJ, Dentener FJ, Bergamaschi P, Dutton G, von Velthoven P, Miller JB, Bruhwiler L, Tans PP (2004) Toward regional-scale modeling using the two-way nested global model TM5: Characterization of transport using SF6. Journal of Geophysical Research-Atmospheres 109(D19)Google Scholar
- Prather MJ, Hsu J (2008) NF3, the greenhouse gas missing from Kyoto. Geophys Res Lett 35(12)Google Scholar
- Prather MJ, Hsu J (2010) NF3, the greenhouse gas missing from Kyoto (vol 37, L11807, 2010). Geophys Res Lett 37Google Scholar
- Prinn RG, Weiss RF, Fraser PJ, Simmonds PG, Cunnold DM, Alyea FN, O’Doherty S, Salameh P, Miller BR, Huang J, Wang RHJ, Hartley DE, Harth C, Steele LP, Sturrock G, Midgley PM, McCulloch A (2000) A history of chemically and radiatively important gases in air deduced from ALE/GAGE/AGAGE. J Geophys Res Atmos 105(D14):17751–17792CrossRefGoogle Scholar
- RCP Database (2009) RCP Database version 1.0 hosted at IIASA. Retrieved 23 Nov, 2009, from http://www.iiasa.ac.at/web-apps/tnt/RcpDb
- Riahi K, Krey V, Rao S, Chirkov V, Fischer G, Kolp P, Kindermann G, Nakicenovic N, Rafai P (2011). RCP-8.5: Exploring the consequence of high emission trajectories. Climatic Change (this issue). doi:10.1007/s10584-011-0149-y
- Smith SJ, Wigley TML (2006) Multi-gas Forcing stabilisation with the MiniCAM. Energ J (Special Issue 3): 373–391Google Scholar
- Taylor K, Stouffer RJ, Meehl GA (2009) A summary of the CMIP5 Experiment Design. from http://cmip-pcmdi.llnl.gov/cmip5/docs/Taylor_CMIP5_design.pdf
- Thomson AM, Calvin KV, Smith SJ, Kyle GP, Volke A, Patel P, Delgado-Arias S, Bond-Lamberty B, Wise MA, Clarke LE, Edmonds JA (2011) RCP4.5: A pathway for stabilization of radiative forcing by 2100. Climatic Change (this issue). doi:10.1007/s10584-011-0151-4
- Thornton PE, Lamarque JF, Rosenbloom NA, Mahowald NM (2007) Influence of carbon-nitrogen cycle coupling on land model response to CO2 fertilization and climate variability. Global Biogeochem Cycles 21(4)Google Scholar
- van Vuuren DP, Meinshausen M, Plattner GK, Joos F, Strassmann KM, Smith SJ, Wigley TML, Raper SCB, Riahi K, de la Chesnaye F, den Elzen MGJ, Fujino J, Jiang K, Nakicenovic N, Paltsev S, Reilly JM (2008) Temperature increase of 21st century mitigation scenarios. Proc Natl Acad Sci 105(40):15258–15262CrossRefGoogle Scholar
- van Vuuren DP, Edmonds J, Kainuma MLT, Riahi K, Thomson A, Matsui T, Hurtt G, Lamarque J-F, Meinshausen M, Smith S, Grainer C, Rose S, Hibbard KA, Nakicenovic N, Krey V, Kram T (2011a). Representative concentration pathways: An overview. Climatic Change (This Issue). doi:10.1007/s10584-011-0148-z
- van Vuuren DP, Stehfest E, Den Elzen MGJ, Deetman S, Hof A, Isaac M, Klein Goldewijk K, Kram T, Mendoza Beltran A, Oostenrijk R, Van Vliet J, Van Ruijven B (2011b) RCP2.6: Exploring the possibility to keep global mean temperature change below 2 degree C. Climatic Change (This Issue). doi:10.1007/s10584-011-0152-3
- Vollmer MK, Reimann S, Folini D, Porter LW, Steele LP (2006) First appearance and rapid growth of anthropogenic HFC-245fa (CHF2CH2CF3) in the atmosphere. Geophys Res Lett 33(20)Google Scholar
- WMO (2006) Scientific assessment of ozone depletion: 2006. Global ozone research and monitoring project—Report No. 50. Geneva, Switzerland, World Meteorological Organization: 572Google Scholar
- WMO (2007) Scientific assessment of ozone depletion: 2006. Global ozone research and monitoring project—Report No. 50. Geneva, Switzerland, World Meteorological Organization: 572Google Scholar