rcps and ssps - joint global change research institute · 10/2/2013 · i.3 explanation of rcp...

RCPs and SSPs: What are they and where are they going?

Stephanie Waldhoff and Jae Edmonds Joint Global Change Research Institute

GTSP Annual Meeting 2 October 2013

College Park, MD

This work has been done with support from the U.S. Environmental Protection Agency’s Climate Change Division and the U.S. Department of Energy’s Office of

Science, Integrated Assessment Research Program.

Outline

!   Why do we need scenarios?

!   The “Parallel Process” !   Representative Concentration Pathways !   Shared Socioeconomic Pathways !   Shared Policy Assumptions

!   SSPs: Current Status !   Example: Forest cover

!   Future SSP development

Scenarios !   Need for common scenarios

!   Earth System Model (ESM) !   Integrated Assessment Models (IAM) !   Impacts, Adaptation, and Vulnerability (IAV) models

!   IPCC Scenario history !   IS92 (1992) !   SRES (2000)

!   Community-based, not IPCC-led scenario design (2007-present): RCPs and “parallel process”

The Parallel Process: Community-based scenario development

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Radiative forcing

Climate projections(CMs)

Impacts, adaptation & vulnerability

(IAV)

IPCC Expert Meeting Report: Towards New Scenarios - Technical Summary

Figure 1. Approaches to the development of global scenarios: (a) previous sequential approach; (b) proposed parallel approach. Numbers indicate analytical steps (2a and 2b proceed concurrently). Arrows indicate transfers of information (solid), selection of RCPs (dashed), and integration of information and feedbacks (dotted).

The parallel process is an advance from the prior sequential approach for a number of reasons. The approach will allow better use of the expensive and time-consuming simulations carried out by the CM community, as these no longer need to be rerun each time the emissions scenarios are changed. A parallel approach using RCPs partially decouples climate science from the issues of socioeconomic projections because a given concentration trajectory can result from different socioeconomic

the model simulations had to be run again, even though the changes seldom resulted in meaningful (i.e., detectable) alterations to the modeled future climates. In the future, updated CMs can be run using the same RCPs, allowing modelers to isolate the effects of changes in the CMs themselves. New forcing scenarios can be used to scale the existing CM simulations using simpler models that have been calibrated to give comparable results to the full three-dimensional climate models. There would be no need to rerun models for each new scenario. The saving in computing time could be used to generate

extreme events, and a more robust representation of uncertainties and/or probabilities. Of course, the use of pattern scaling always yields an approximation to the output that would have been produced by a state-of-the-art climate model had it been run, and the resulting approximation is better for some variables than for others. The savings in cost and time for climate model set up and runs is therefore purchased at the price of approximation.

I.3 Explanation of RCP terminology, and the role of RCPs in the “parallel process”

The name “representative concentration pathways” was chosen to emphasize the rationale behind their use. RCPs are referred to as pathways in order to emphasize that their primary purpose is to provide time-dependent projections of atmospheric greenhouse gas (GHG) concentrations. In addition, the term

outcome, such as a stabilization level, that is of interest, but also the trajectory that is taken over time to

a) Sequential approach b) Parallel approach

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Emissions & socioeconomic scenarios

(IAMs)1

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Representative concentration pathways (RCPs) and levels

of radiative forcing

Radiative forcing

Climate projections (CMs)

Impacts, adaptation & vulnerability

(IAV)

Climate, atmospheric & C-cycle projections

(CMs)

Emissions & socioeconomic scenarios

(IAMs)

Impacts, adaptation vulnerability (IAV) & mitigation analysis

2

4Moss et al (2008)

!   Goals of the parallel scenario process !   Shorten the time required to develop and apply new scenarios !   Improve integration between socio-economic drivers, climate system, and natural and human systems !   Develop consistent reference and policy scenarios

!   The Representative Concentration Pathways (RCPs) are alternative future global greenhouse gas and aerosol concentrations, developed to be used in parallel by: !   Earth System Models (ESMs) : CMIP5 (climate model intercomparison, experiments using emissions,

concentration, and land use outputs from RCPs, ½ x ½ degree resolution for LULUC and short-lived species) !   Integrated Assessment Models (IAMs): Shared Socioeconomic Pathways (exploration of alternative socio-

economic conditions consistent with future atmospheric composition changes) !   Climate projections from CMIP5 and socioeconomic drivers from RCPs used in Impacts, Adaptation, and

Vulnerability (IAV) and IAM studies

Scenario Elements

!   Representative Concentration Pathways (RCPs) !   Four climate pathways defined by radiative forcing at the end of the century

!   CMIP5 database, ½ x ½ degree gridded climate projections

!   Shared Socioeconomic Pathways (SSPs)

!   Shared Policy Assumptions (SPAs)

Representative Concentration Pathways

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The selected set of models are those capable of satisfying the data requirements and the modeling teams have substantial experience relevant to developing the required data sets;

updated IPCC AR4 parameterization;Among the modeling teams represented in Table 2 who are willing to participate, the MESSAGE and IMAGE models can produce scenarios on the high and low end (RCP3-PD and RCP8.5). The IMAGE model was selected for the low pathway, due to the larger number of low stabilization scenarios available from the model. The MESSAGE model was selected for the high scenario, since it can provide an updated and revised A2-like scenario, which would allow comparisons with earlier climate assessments and thus continuity from the perspective of the CM community. This scenario includes features requested by the IAV community, namely a high magnitude of climate change and factors related to higher vulnerability (e.g., higher population growth and lower levels of economic development);Both the AIM and the MiniCAM models could provide the required data for the intermediate levels. The MiniCAM model was chosen for RCP4.5, while AIM was chosen for RCP6.

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Figure 5. Radiative forcing compared to pre-industrial (left panel) and energy and industry CO2 emissions (right panel) for the RCP candidates (colored lines), and for the maximum and minimum (dashed lines) and 10th to 90th percentile

and should not be considered probabilities. Blue shaded area indicates mitigation scenarios; gray shaded area indicates baseline scenarios.14

14 Note that it was not possible to clearly distinguish between energy/industry and land-use emissions for all scenarios in the literature. Therefore, the CO2 emissions ranges in Figure 5 (denoted by the blue and gray shaded areas in the left panel) include scenarios with both energy/industry and land-use CO2 emissions.


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The scenario literature was reviewed with respect to the desirable characteristics of range, number,

characteristics given the available literature (Table 1).

The set of pathways in Table 1 are representative of the range of baseline and stabilization radiative forcing, concentration, and emissions pathways in the literature, with the full range of available radiative forcing and concentration pathways covered and from the 90th percentile down to below the 10th percentile of GHG emissions covered.10

Table 1. Types of representative concentration pathways.

Name Radiative Forcing1 Concentration2 Pathway shapeRCP8.5 >8.5 W/m2 in 2100 > ~1370 CO2-eq in 2100 Rising

RCP6 ~6 W/m2 at stabilization after 2100

~850 CO2-eq (at stabilization after 2100)

Stabilization without overshoot

RCP4.5 ~4.5 W/m2 at stabilization after 2100

~650 CO2-eq (at stabilization after 2100)

Stabilization without overshoot

RCP3-PD3 peak at ~3W/m2 before 2100 and then decline

peak at ~490 CO2-eq before 2100 and then decline Peak and decline

Notes:1 2. Radiative forcing values include the net effect of all anthropogenic GHGs and other forcing agents.2 Approximate CO2 equivalent (CO2-eq) concentrations. The CO2-eq concentrations were calculated with the simple formula Conc = 278 * exp(forcing/5.325). Note that the best estimate of CO2-eq concentration in 2005 for long-lived GHGs only is about 455 ppm, while the corresponding value including the net effect of all anthropogenic forcing agents (consistent with the table) would be 375 ppm CO2-eq.3 PD = peak and decline.

III.4 Climate modeling community prioritization

some CM teams may only be able to run a subset of the proposed RCPs. Therefore, the CM community has assigned a preferred order to RCP runs. The priority order for CM RCP simulations is:

1. Both the high and low RCPs at a minimum (RCP8.5 and RCP3-PD);2. The intermediate-range RCP with near-term resolution (RCP4.5); and3. RCP6.

10 continuity with earlier experiments, so it should not be considered a frequency distribution of independent analyses from which relative robustness, likelihood, or feasibility can be deduced.


Moss et al (2008)

Each RCP is an independent pathway

RCP 8.5 is not a reference scenario for the other, lower RF scenarios

Scenario Elements

!   Representative Concentration Pathways (RCPs) !   Four climate pathways defined by radiative forcing at the end of the century

!   CMIP5 database, ½ x ½ degree gridded climate projections

!   Shared Socioeconomic Pathways (SSPs) !   Five socioeconomic development trajectories defined in terms of challenges to

adaptation and mitigation

!   Not “matched” to reference RCPs

!   Shared Policy Assumptions (SPAs)

Shared Socioeconomic Pathways (SSPs) ! SSPs are the basis of the new scenarios

! Narrative storylines ! Quantitative scenarios (demographics, economics, technology) ! Other socieoeconomic indicators

! Represent a range of future development pathways, defined around ! Challenges to adaptation ! Challenges to mitigation

Shared Socioeconomic Pathways (SSPs) ! SSPs are the basis of the new scenarios

! Narrative storylines ! Quantitative scenarios (demographics, economics, technology) ! Other socieoeconomic indicators

! Represent a range of future development pathways, defined around ! Challenges to adaptation ! Challenges to mitigation

SSP1: Sustainability

SSP3: Fragmenta5on

SSP4: Inequality

SSP5: Conven5onal Development

SSP2: Middle of the Road

SSP Narratives

SSP2: Middle of the Road •  Current trends conAnue •  Moderate populaAon growth •  Slowly converging incomes

between industrialized and developing countries

•  Delayed MDG achievement •  ReducAons in resource and energy

intensity at historic rates •  Environmental degradaAon

SSP3: Fragmenta5on •  Rapid populaAon growth •  Slow economic growth •  Failing to achieve MDG •  High resource intensity and fossil

fuel dependency •  Low investments in technology

development and educaAon •  Unplanned seMlements •  Weak int’l governance and local

insAtuAons

SSP5: Conven5onal Development

•  Rapid economic development •  Stabilizing populaAon •  Consumerism •  High fossil fuel dependency •  EradicaAon of extreme poverty

and universal access to educaAon and basic services

•  Highly engineered infrastructure and ecosystems

SSP1: Sustainability •  Good progress towards

sustainable development •  Stabilizing populaAon •  Decreasing income inequality •  Early MDG achievement •  Low resource intensity and fossil

fuel dependency •  Strong int’l governance and local

insAtuAons •  Well managed urbanizaAon •  Environmentalism

SSP4: Inequality •  Increasing inequality within and

across countries •  EffecAve governance controlled by

a small number of rich global elites

•  Most of populaAons with limited access to higher educaAon and basic services

•  Energy tech R&D made by global energy corporaAons

•  Low social cohesion Adapted from the meeAng report of the Workshop on The Nature and Use of New Socioeconomic Pathways for Climate Change Research hMps://

www.isp.ucar.edu/sites/default/files/Boulder%20Workshop%20Report_0_0.pdf

Shared Socioeconomic Pathways

! SSPs are designed to provide a link between the RCPs and the CMIP5 climate ensembles.

SPAs

SSP 1 SSP 2 SSP 3 SSP4 SSP5

Reference X X X X X

RCP ReplicaAon

8.5 Wm-‐2 X

6.0 Wm-‐2 X X X X X

4.5 Wm-‐2 X X X X X

2.6 Wm-‐2 X X X

SSP Reference and RCP Radiative Forcings

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AIM/CGE GCAM IMAGE MESSAGE-GLOBIOM REMIND-MAGPIE SSP1 SSP2 SSP3 SSP4 SSP5

SSP5: 8.9 -‐ ... W/m2

SSP2: 6.4 -‐ 7.9 W/m2

SSP3: 6.3 -‐ 7.7 W/m2 SSP4: SSP1: 5.3 -‐ 7.1 W/m2

K. Riahi

# models repor+ng forcing in first round

Reference forcings, current results:

Scenario Elements

!   Representative Concentration Pathways (RCPs) !   Four climate pathways defined by radiative forcing at the end of the century !   CMIP5 database, ½ x ½ degree gridded climate projections

!   Shared Socioeconomic Pathways (SSPs) !   Five socioeconomic development trajectories defined in terms of challenges to

adaptation and mitigation !   Not “matched” to reference RCPs

!   Shared Policy Assumptions (SPAs) !   Five (?) policy regimes used to meet policy targets !   Not yet finalized !   Potential attributes include:

!   Accession: immediate vs. delay !   Carbon tax: universal vs. fossil fuel and industry

Current Status: SSP development

!   First round: five IAMs ran multiple RCP-SSP combinations—no SPAs !   Currently analyzing results

!   Are the models’ implementations of SSPs consistent with the underlying land use storylines?

!   Challenges in comparing LU results across models and SSPs? !   SSP harmonization !   Definitions: regions, variables !   Data reporting !   Many scenarios… Models x RCPs x SSPs x SPAs

!   5 x 4 x 5 x 5(?) = 500* scenarios! (*Not all combinations may be appropriate or feasible)

!   How will IAV and ESMs deal with so many runs?

!   Example: Forest cover

!   Focus areas !   Core set of scenarios? !   Analytical topics?

6,000 8,000 10,000 12,000 14,000

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(There are a LOT of scenarios!)

REFERENCE

RCP 4.5 – SPA0

Preliminary Results: Forest Cover

Global Forest Area

!   Definition of forest varies by model !   Harmonization in base year? !   Particularly a problem for managed forest

!   Patterns across SSPs vary by model !   Is there a need for more guidance/harmonization in SSP storylines?

!   Forest protection levels !   SSP1 = Strong !   SSP2 = Medium !   SSP3 = Weak

Strong -‐ strong forest protecAon, limited non-‐agricultural land for conversion Weak -‐ weak forest protecAon, high availability of non-‐agricultural land for conversion

Challenges: Base Year Data Total Forest in 2005

!   Differences across models in calibration year data

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Challenges: Variable Definition (& Data Reporting) Managed Forest in 2005

!   Various definitions of “managed forest”

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Global Managed Forest

SSP Forest Protection Narratives

!   Forest protection levels !   Strong - strong forest protection, limited non-agricultural land for conversion !   Weak - weak forest protection, high availability of non-agricultural land for conversion

!   SSP1 !   Low Income - Strong !   Medium Income - Strong !   High Income - Strong

!   SSP2 !   Low Income - Medium !   Medium Income - Medium !   High Income - Medium

!   SSP3 !   Low Income - Weak !   Medium Income - Weak !   High Income - Weak

!   SSP4 !  Low Income - Weak !  Medium Income - Medium !  High Income - Strong

!   SSP5 !  Low Income - Medium !  Medium Income - Medium !  High Income - Medium

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SSP1: Low Income -‐ Strong

SSP2: Low Income -‐ Medium

SSP3: Low Income -‐ Weak

SSP Future

!   SSP near-term development !   Specific analytical focus areas, of particular importance to ESM community

!   Non-Kyoto forcing !   Overshoots !   Land use change

!   Proposed time line !   October 2013: Revise land use figures to include 5th model (data reporting issue) !   November 2013

!  Five SSP teams update first round results !  Improve data reporting, particularly for land use; additional reported variables; variable definition harmonization

!   March-April 2014 !   Final runs !   Revisions to land use inputs and reporting outputs

!   Special Issue of Global Environmental Change on SSPs

!   Lessons learned !   Things always take longer than planned… publications had been planned for Spring 2013 !   Too many scenarios?

!   Need to focus on specific SSP-Policy combinations !   Marker scenarios?

!   Continued coordination and collaboration across modeling communities !   Some topics highly relevant to all communities (e.g. LUC)

Back-up Slides

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Drivers

SSP Storylines: Land Productivity

!   SSP1 - faster catch-up of low-income countries; sustainability focus !   Low Income - Rapid !   Medium Income - Rapid !   High Income - Medium

!   SSP2 - declining rates for high-income countries, converging rates for low-income countries !   Low Income - Medium !   Medium Income - Medium !   High Income - Medium

!   SSP3 - lower rates everywhere !   Low Income - Slow !   Medium Income - Slow !   High Income - Slow

!   SSP4 - no convergence between low-income and high-income regions !   Low Income - Slow !   Medium Income - Medium !   High Income - Rapid

!   SSP5 - high yield growth !   Low Income - Rapid !   Medium Income - Rapid !   High Income - Rapid

Cereal Yield Growth Rates

!   SSP1 - faster catch-up of low-income countries; sustainability focus !   Low Income - Rapid !   Medium Income - Rapid !   High Income - Medium

!   SSP2 – declining rates for high-income countries, converging rates for low-income countries !   Low Income - Medium !   Medium Income - Medium !   High Income - Medium

!   SSP3 - lower rates everywhere !   Low Income - Slow !   Medium Income - Slow !   High Income - Slow

SSP1−45−SPA0−V1 SSP1−Ref−SPA0−V1



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Yield|cereal ReporAng is sparse

PaMerns vary by model, but not by SSPs

Is there a need for more guidance/harmonizaAon in SSP storylines?

Yield growth in the SSPs SSP1 = Rapid SSP2 = Medium SSP3 = Slow

rcps and ssps - joint global change research institute · 10/2/2013 · i.3 explanation of rcp...

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