Transcript Presentation for UNEP-GRID Arendal Jun 2007

Presentation at GRID/GVU Arendal 11 Jun 2007
CONNECTING GLOBAL CLIMATE SCIENCE, POLICY,
TEACHING AND OUTREACH
WITH AN INTERACTIVE JAVA MODEL
IN CONTEXT OF
RECENT DEVELOPMENTS IN IPCC AND FCCC
Ben Matthews
with Jean-Pascal van Ypersele
Insititut d'Astronomie et de Géophysique,
Université catholique de Louvain,
Louvain-la-Neuve, Belgium
[email protected]
www.climate.be/jcm
Recalling vision of 2001:
(during early development of JCM in Copenhagen and Arendal)
Personal transition:
measuring air-sea CO2 fluxes in laboratory (group of Peter Liss, UEA)
also attending UNFCCC COPs (Geneva, Kyoto, Den Haag, Marrakech...)
=> perceive lack of connection between climate science and policy
=> Develop simple interactive climate model as tool for global dialogue
policymakers need to know sensitivity to options, not 'fatalistic' predictions
=> initial focus on flexible stabilisation scenarios (contrast to IPCC-SRES)
core science based (then) on IPCC-TAR
useful to science-policy advisors (Denmark, Switzerland, Belgium...)
“the ultimate integrated assesment model is the global network of human heads”
Ben Matthews
[email protected]
interactive model: www.climate.be/jcm
Recent Development of JCM 5 in UCL-ASTR
(see www.climate.be/jcm)
New adaptable structure/interface using Java 5
Update of core science from IPCC TAR => AR4 in progress
More complex modules developed for specific research projects
Has been applied to research applications e.g.:
Stabilisationunder Uncertainty (remaining within EU 2C limit)
Probabilistic Economic Risk Analysis (Climneg project)
Attribution of Contributions to Climate Change
Past & future Land-Use Change emissions
Aviation emissions of CO2, NOx, contrails and cirrus (ABCI project)
But still interactive / good for teaching
explore the sensitivity to policy options, scientific uncertainties, risk / value assumptions,
just by adjusting parameters with a mouse
instant cause-effect response on linked plots from emissions to impacts
easy to save model setups, plots, tables etc.
available online, open source, documented
(earlier versions were translated... update in progress)
used for university courses in several countries
Speed and flexibility useful for both interactivity and probabilistic / scenario analysis
Ben Matthews
[email protected]
interactive model: www.climate.be/jcm
Java Climate Model:
Year=>
Version
2000
2001
Chooseclimate website
History of Development
JCM1
2002
JCM2
2003
JCM3
2004
JCM4
Core ScienceImprovised
...=>TAR
WG1
UDEB & Bern models Radiative forcing, ice-melt
(Heat & Carbon)
33 gases CC Feedbacks
WG2
Regional Climate Maps
WG3
SRES Emissons
Socioeconomic
Costs
Paradigm
Contract
Stabilise
Emissions Concentration
Convergence
Stabilise
Temperature (Iteration)
Other sharing...
Java
1
1.1
Structure
Applet within web page
Doc
Translations...Documentation
For unep.net
Where
With
Project
UEA & GCI DEA-CCAT UNEP-GRID
Norwich Copenhagen Arendal
UK
Denmark
Norway
Jesper
B.Lucas,
Gundermann L. Hislop,
...
ACCC/MATCH
Presentation
2006
JCM5
2007
JCM6
...=> AR4
UDEB updated
Aviation NOx & Cirrus, Efficacy
Regional / Sectoral Impacts
Regional => National data
Land Use Change Model
Optimisation
Risk Analysis
1.4
1.5=5
1.6=6
Standalone Application, flexible structure for research
Interactive Documentation Scripts/Demos
Update in progress
Teaching & role play
KUP
UCL-ASTR
...=>
Bern
Louvain la Neuve
Switz
Belgium
Fortunat
Jean-Pascal Van Ypersele ....=>
Joos
Climneg II
ACCC Intercomparison
ESSP
COP7
Amsterdam Marrackech
Ben Matthews
Stabilisation
Under Uncertainty
Attribution of Responsibility
2005
[email protected]
WCCC
Moscow
Christiano Pires de Campos
Philippe Marbaix
ABCI (Aviation)
MATCH –Paper #1
COP9
EEE-ICM
Milano
Trieste
MATCH – national / uncertainty
SB
Bonn
interactive model: www.climate.be/jcm
We still need a range of model complexities...
Simpler models are still important, GCMs ( or even ESMs) can't do everything
JCM defies the trend towards using only high-resolution GCMs, supercomputer networks
but... “a chain is only as strong as it's weakest link”
e.g .scenarios, impacts, communication
+ computing power didn't yet resolve uncertainty
=> still need probabilistic risk analysis
whilst making more transparent the sensitivity to risk/value assumptions
Research applications made JCM more complex,
(GRID might say too complex for effective communication).
Others say such models are too simple.
But policymakers can't use GCMs, and want to create diverse scenarios
If scientists don't give policymakers simple, flexible relevant tools,
policymakers will create their own even simpler models (e.g. Brazilian proposal...)
or “back-of-the-envelope” interpolations missing all feedbacks and nonlinearities
Need to ensure quality of simpler models used for policy -relevant analysis...?
(e.g. ACCC/MATCH process on attribution of contributions to climate change
=> recent meeting in Cicero)
Ben Matthews
[email protected]
interactive model: www.climate.be/jcm
A range of model complexities....
Reports
Models
Intermediate
Simple
Complex
Good for:
Clarity / Consensus
Understanding,
Visualisation,
Transparency
Role in
integrated
assessment
Consensus
Synthesis?
Exploring options and
risk/value parameters
Probabilistic / Risk
Analysis
Parameterising simpler
models
Lack:
Flexibility
Physical basis
Neither intuitive nor
realistic =>
misunderstandings?
Speed, flexibility
Not good for:
Coupling / Interface
Detailed /final
conclusions
Ben Matthews
[email protected]
Exploring feedbacks,
couplings
Realism, Resolution,
Nonlinearities,
Variability, Extremes
Exploring scenarios
interactive model: www.climate.be/jcm
Synthesis by connecting reports?
Examples from IPCC AR4:
below: AR4 WG2 Table SPM-1:
above: AR4 WG2 TS4:
temperature as function of CO2 stabilisation scenario and time
below: AR4 WG3 Fig 3.25
mitigation costs as a function of CO2eq stabilisation level
Ben Matthews
[email protected]
interactive model: www.climate.be/jcm
BUT making such synthesis based on single indicators can be misleading, for example:
Mitigation costs
Climate Change Impacts
not just a function of
CO2 concentration
Global Average Temperature level,
but also depend strongly on:
socioeconomic baseline
value assumptions in aggregation over space, time, sector & risk
timing of investments,
timing of warming,
learning by doing
mixture of gases, flexible
regional effect of short-lived gases & aerosols
mechanisms, etc.
Ben Matthews
[email protected]
interactive model: www.climate.be/jcm
IPCC Scenarios - AR4
WG1 concept that GCMs should do everything
was inefficient way to compare scenarios
=> too few scenarios were run – 3 SRES are not enough!
(simple model still used for others)
Policymakers need mitigation scenarios
and to see the sensitivity to options (marginal effects)
=> GCMs should parameterise simpler flexible models
New IPCC Scenario Process towards AR5
(meetings in Laxenburg, Sevilla, Noordwijkerhout)
agreed that using special reports as a data interface between models too inefficient!
=> “new” parallel process concept to save time:
define simple stabilisation scenarios in the middle of cause effect chain (CO2eq concentration / forcing)
(at least three to cover full plausible (>likely) range and so GCMs identify nonlinearities in climate response and
impacts)
GCMs => forward to climate, impacts, adaptation
Socioeconomic (& Biogeochemical?) models => inverse calculation to emissions and mitigation
Challenges of this approach:
how to take account of cross-cutting feedbacks...?
climate change => soil respiration, plant growth, methane release...
climate change impacts => population, economic growth
(when these are between separate models/processes)
Integrated models might do it better...
.
Ben Matthews
[email protected]
interactive model: www.climate.be/jcm
JCM already demonstrated this approach: Example below from presention of Matthews & VanYpersele at
WCCC 2003 Moscow, also to European strategy meeting Firenze
Stabilisation under uncertainty: fixing a concentration or temperature (EU 2C) target:
Defining the scenario by concentration or forcing spreads the cascade of uncertainty more evenly:
Ben Matthews
[email protected]
interactive model: www.climate.be/jcm
JCM can also be used to explore economic optimisation
(Risk Analysis integrating over uncertainty)
- Belgian project Climneg II
Make transparent the sensitivity to different ways of aggregating over...
space (regions, intra-generational equity),
time (discounting: intergenerational equity),
risk (risk-aversion)
sector (comparing different types of impacts)
Similar approach to Stern report
But need better mitgation and impact cost functions
(chain is only as strong as the weakest link)
=> will return to this in new AR4-version
Ben Matthews
[email protected]
interactive model: www.climate.be/jcm
Java Climate Model, Live demonstration of the model:
Note: the slides that follow were not shown at the side-event,
they are just example snapshots for the online copy.
Demonstrate webstart
1. 9 plots, show everything connected to concentration
2. stabilise temperature, change GCM => effect on emissions
3. core science – ocean layers, RF etc., cc feedback, AR4 GCMs
4. land use change, past and future
5. responsibility – brazilian
6. aviation emissions
7. regional emissions => regional impacts
8. interactions map and tree, also doc on click
Ben Matthews
[email protected]
interactive model: www.climate.be/jcm
Ben Matthews
[email protected]
interactive model: www.climate.be/jcm
Ben Matthews
[email protected]
interactive model: www.climate.be/jcm
Ben Matthews
[email protected]
interactive model: www.climate.be/jcm
Ben Matthews
[email protected]
interactive model: www.climate.be/jcm
Java Climate Model 2001-2007: Reflections
Making interactive model tougher than making papers!
Classic process model => papers : (One task at a time)
Modeller sets assumptions, fixes model, runs once (can be slow), selects best data, explains
results in sequence
Interactive model: (Multiple applications)
User changes assumptions, model adapts quickly, user selects any data,
should be self-explanatory, in any order
Also slower to expand...
100s of adjustable parameters => infinite combinations, impossible to check all
Add new items => interactions grow expontentially => logarithmic pace of development...
Funding for specialist research projects not overview / outreach
(although “the chain is only as strong as the weakest link”)
=> tools become more convenient for experts rather than for public / stakeholders
Nevertheless...
Good feedback, users appreciate JCM
Fast & Flexible => can also iterate 1000s of combinations
(e.g. to make probabilistic risk analysis more transparently)
Structure robust, modular, open-source, scope for expansion
JCM was a “proof of concept” in 2001, now more complex...
but no great breakthrough in Science-Policy interaction.
Should we continue?
Coming soon:
Anticipate AR4-based synthesis version (JCM6) by autumn 2007
Joint project with IVIG (Rio de Janerio) – global => regional policy.
Apply to IPCC new scenarios processes (connecting, interpolating)
Java-6 => scripting languages (demonstrations, automated analyses)
Structured open-source project ? ( “parallel processing...”)
“The ultimate integrated assessment model is the global network of human heads”
Experiment and adapt JCM – for both research and outreach
www.climate.be/jcm
let's work together to improve the science <=> policy interface