An overview of research needs and the availability of climate change scenario data and their socio-economic background
Ole B. Christensen
Danish Climate Centre, Danish Meteorological Institute
Ian Harris and Clare Goodess
Climatic Research Unit, University of East Anglia
Alistair Hunt
University of Bath
Robert Nicholls
University of Southampton
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Research area: / 212774
ClimateCost
Full Costs of Climate Change
ENV.2007.1.1.6.1.
Deliverable Number: 1.1
Actual submission date: May, 2009
Title: / Climate and Socio-economic Scenarios: An overview of research needs and the availability of climate change scenario data and their socio-economic background
Purpose: / Report reviewing research needs and existing available climate and socio-economic data and set-up of web-portal for information, metadata and data links.
Filename: / Deliverable 1_1 vs 2.doc
Date: / May 2009
Authors: / Ole B. Christensen, Ian Harris, Clare Goodess, Alistair Hunt, Robert Nicholls
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Project Coordinator: Thomas E Downing
Stockholm Environment Institute, Oxford
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Technical Coordinator: Paul Watkiss
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Executive Summary
The choice of emissions scenarios in this work package has ramifications for every corner of the ClimateCost project. The scenario selection must take account of the completeness of the scenario description, as well as the availability of climate model data at the appropriate resolutions from as many simulations as possible.
While new initiatives, specifically those in support of IPCC AR5, are ideally suited to the task in terms of scoping, the timescales for the production of the related data sets are not within this project’s time line. Existing IPCC SRES scenarios are therefore proposed as the main focus, specifically A1B. The ENSEMBLES E1 scenario (A1B with long-term stabilisation at 450ppm) is also proposed, as some supportive climate scenario data already exists or is timetabled to arrive within this project’s timescales.
User needs identified thus far focus on bottom-up WP2 impacts modelling. They point to requirements for high-resolution gridded series over Europe, with lower-resolution (GCM) series needed globally and to assist in construction of regional means. These needs will principally be met with data from the ENSEMBLES project, available from the data portals at CERA and PCMDI (global model output) and DMI (regional model output).
Table of Contents
1. Introduction 1
2. Current State of Play: Socio-economic Projections 1
3. Current State of Play: Climate Scenarios 7
4. Sea Level Rise 15
5. User Needs for Climate Model Outputs 17
6. Recommendations for Emissions Scenarios 21
7. Other Project-wide Issues 23
8 Outlook 25
References 25
Appendix 1. Summary of Partner Requirements 28
1. Introduction
In recent years, the amount of simulation data from numerical climate models available to the public has increased enormously. The purpose of this report is mainly to give an overview of the background of the major simulation archives and of the kind of data that are available. Finally, a number of decisions are identified which need to be taken by the ClimateCost community to ensure the consistent and robust use of appropriate climate scenario information.
Work package 1 in the ClimateCost project will take care of the organization of climate change scenarios, which later work packages of the project will use in order to estimate effects of climate change and of mitigation on various sectors. In this report, an overview is provided of existing output data from coupled General Circulation Models (GCMs) and downscaling of these, either with the use of Regional Climate Models (RCMs) or Statistical Downscaling (SD). Within the project, there are very limited resources allocated to complementary simulations, corresponding to roughly 100 simulation years, i.e. 100 years in total for a choice of area, emission scenario and GCM. This means that the models of the project depend almost entirely on external data from other projects. Thus the focus here is on the identification of appropriate modelling outputs from other projects, and on how these can be processed and ‘re-packaged’ for the purposes of ClimateCost.
Section 2 of this document covers the current situation for socio-economic projections. It looks principally at the SRES scenarios, examining their definition, use and flaws.
Section 3 looks at climate scenarios, giving a broad overview of existing GCM/RCM/SD output archives and web portals, and those planned, which could support the emissions scenarios in section 2.
Section 4 examines sea level rise.
Section 5 documents user needs for climate information, as communicated by project partners (these needs are also summarised in Appendix 1). Ways of meeting these needs are also postulated. The consolidation of these needs into a coherent set of requirements is then discussed.
Section 6 discusses realistic options for emissions scenario selection.
Section 7 includes information on maintaining consistency across the project in terms of spatial definitions and temporal ranges, and addresses issues of uncertainty.
Section 8 provides a brief outlook for WP1.
The appendix includes a summary of user needs.
Note that the overview in Section 3 concerns data existing today. New and very ambitious initiatives are on their way, in particular the new CMIP-5 simulation plan, which will provide numerical data for the use of the next IPCC report AR5. CMIP-5 data will be available in the second half of 2010, i.e., around month 20 of the ClimateCost project. A next-generation international RCM programme, CORDEX, covering most world regions (and initially focusing on Africa) is also being defined under WCRP auspices (see http://wcrp.ipsl.jussieu.fr/Workshops/Downscaling/), but data from this initiative will not be available in time for ClimateCost.
2. Current State of Play: Socio-economic Projections
The future effects of climate change are strongly influenced by socio-economic change. This firstly relates to the emission scenarios that drive the climate change outlined above, which themselves are driven by assumptions regarding population, technological change and economic growth. However, these non-climate scenarios also determine the vulnerability of social and economic systems to climate change in the future ( i.e. when climate change occurs). They describe the changes in the “stock at risk”, with respect to size, and subsequent sensitivity to climate change. Implicitly, they also determine adaptation options available, adaptive capacity and vulnerability.
Future socio-economic scenarios will result in a change in vulnerability or exposure, even in the absence of future climate change. As an example, the changing age distribution of a population will alter the vulnerability of the population to the current level of health impacts, irrespective of any changes in climate. Following from this, future socio-economic change also affects the vulnerability or exposure to any future climate signal. To illustrate, the future impact of extreme events such as floods or storms will be determined by the increased wealth of individuals and assets (driven by socio-economic growth) but also changes in exposure from land-use changes, e.g. from building (or not) in areas that are more susceptible to flood risk. In some cases, socio-economic changes may even affect the sign of changes in damages.
For assessment of climate change impacts, it is important to separate out the socio-economic component to identify the ‘net’ impacts attributable to climate change, rather than the ‘gross’ impacts due to the combination of ‘climate + socio-economic change’. However, it is also important to recognise that adaptation responses need to address the combined ‘gross’ effect of climate and socio-economic change together. It should be noted, moreover, that – as with climate change scenarios – there are major uncertainties in future socio-economic trends, which affect the magnitude and probability of any potential impact.
There is limited experience of using socio-economic scenarios in vulnerability, impact or adaptation assessments. However, absence of their use implies that projected future climate change will take place in a world similar to today. In order to progress the study, therefore, we develop and present socio-economic data that can be used in concert with climate change data in order to derive impact estimates and inform adaptation assessment.
2.1 IPCC SRES
2.1.1 Overview
The starting point for specification of socio-economic scenarios is the existing IPCC Special Report on Emission Scenario (SRES) projections (Nakicenovic et al. 2000), from which this overview is taken. This set superseded previous sets and was designed to ensure a degree of consistency in the modelling of climate change, and its impacts, as well as mitigation and adaptation responses. These scenarios (Box 1) were created by modelling a wide range of the main driving forces of future emissions, including demographic, technological and economic developments. The scenarios include different future socio-economic developments that might influence greenhouse gas (GHG) sources and sinks, such as alternative structures of energy systems and land-use changes. The scenarios do not include any future policies that explicitly address additional climate change initiatives, although GHG emissions are directly affected by non-climate change policies designed for a wide range of other purposes, and in practice this distinction is difficult to make. The scenarios are therefore known as baseline, or reference, scenarios. However, the major driving forces of future emissions also provide the basis for the assessment of possible mitigation strategies and policies designed to avoid climate change.
The uncertainty in the evolution of the underlying driving forces of GHG emissions is reflected in the wide range of future emissions paths in the literature captured by the SRES scenarios. It seems likely that the driving forces considered in the SRES are the dominant ones in determining GHG emissions, though, clearly, other factors – either known or unknown – are difficult to capture in quantitative scenarios.
The SRES scenarios involve both qualitative and quantitative components; they have a narrative part called "storylines" and a number of corresponding quantitative scenarios for each storyline. The SRES scenarios are descriptive and are designed to be value-free. They have been built as descriptions of plausible alternative futures, rather than preferred developments.
Box 1. Structure and features of SRES Scenarios
The four scenario families each have a narrative storyline and consist of 40 scenarios developed by six modelling groups.
The 40 scenarios cover the full range of GHGs and SO2 emissions consistent with the underlying range of driving forces from scenario literature.
The 40 SRES scenarios fall into various groups - the three scenario families A2, B1, and B2, plus different groups within the A1 scenario family. The A1 groups are distinguished by their technological emphasis - on coal (A1C), oil and gas (A1G), non-fossil energy sources (A1T), or a balance across all sources (A1B). The A1C and A1G scenario groups are sometimes combined into one fossil intensive group A1FI.
The scenarios are also grouped into four categories of cumulative CO2 emissions, which indicate that scenarios with different driving forces can lead to similar cumulative emissions and those with similar driving forces can branch out into different categories of cumulative emissions.
Four from 40 scenarios are designated as marker scenarios that are characteristic of the four scenarios families. Together with the two additional illustrative scenarios selected from the scenario groups in the A1 family, they capture most of the emissions and driving forces spanned by the full set of the scenarios.
There is no single central or "best guess" scenario, and probabilities or likelihood are not assigned to individual scenarios.
All scenarios describe futures that are generally more affluent than today and a convergence in per capita income ratios in the world.
Alternative combinations of main scenario driving forces can lead to similar levels of GHG emissions by the end of the 21st century. Scenarios with different underlying assumptions can result in very similar climate changes.
Technology is at least as important a driving force of GHG emissions as population and economic development across the set of 40 SRES scenarios.
Source: Based on Box TS-4 Technical Summary. (Nakicenovic et al. 2000)
The narrative storylines of the four scenario families are outlined in Table 1. They are shaped by patterns of global socio-economic development thought to be plausible. Each storyline assumes a distinctly different direction for future developments, such that the four storylines differ in increasingly irreversible ways. They cover a wide range of key "future" characteristics such as population growth, economic development, and technological change. For this reason, IPCC argue that their plausibility or feasibility should not be considered solely on the basis of an extrapolation of current economic, technological, and social trends (although recent critiques have focused on comparing projected trends with current trends, see Tol et al., (2005)).
Table 1. SRES Scenario storylines
IPCC SRES Storyline / SRES DescriptionA1 / Very rapid economic growth; population peaks mid-century; social, cultural and economic convergence among regions; market mechanisms dominate.
Subdivisions: A1F1 – reliance on fossil fuels; A1T – reliance on non-fossil fuels; A1B - a balance across all fuel sources
A2 / Self reliance; preservation of local identities; continuously increasing population; economic growth on regional scales
B1 / Clean and efficient technologies; reduction in material use; global solutions to economic, social and environmental sustainability; improved equity; population peaks mid-century
B2 / Local solutions to sustainability; continuously increasing population at a lower rate than in A2; less rapid technological change than in B1 and A1
Source: Derived from (Nakicenovic et al. 2000)
The IPCC SRES presents global estimates of the GHG emissions resulting from the socio-economic scenarios developed. The SRES scenarios are characterised by quantitative data on:
· Population: total
· GDP: US Dollars (1990 prices)
· Land Use: Croplands, grasslands, energy biomass, forest, other.
· Energy Use: Final and primary energy use by fuel; cumulative resource use.
These data are presented on a decadal basis to 2100. The data can be found at http://sres.ciesin.columbia.edu/final_data.html
In constructing these estimates, the evolution of these socio-economic drivers is considered for large scale regions. Datasets for the four categories of quantitative data are therefore available at this scale. By way of illustration, the scenarios for economic growth are reproduced in Table 2.