Transcript Climate Impact Research in the BSR: State of the Art

Dr. Jürgen Kropp
Potsdam Institute for Climate Impact Research
Climate Impact Research in the
BSR: State of the Art
Structure
1.
2.
3.
4.
5.
6.
Climate research and modelling: what do we know?
What have we learned?
Regional climate effects & consequences: can we estimate them?
What are preconditions for good policies?
The necessary connection of mitigation and adaptation
Conclusion – transition to talk II
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1
Scope of decision makers: Extremes and
their Frequency
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1
2
Climate in the Past and the Future
We are here!
*
Eem
Holocene
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3
Mechanisms are clear more than 100 years
(some physics….)
e.g. Clausius-Clapeyron Law (1834)
Stefan-Boltzmann Law: (1879)
Example: Zero-dimensional climate model
We need:
S
=
π R2
=
4πR2
=
α
=
εσT4
=
solar constant (1340 W/m2)
eliminated area of solar insolation (R radius of earth)
total earth surface
earth Albedo
Stefan-Boltzmann-Law (SB constant: σ = 5.669*10-8 W/m2 K4)
ε: counts for thermal absorption
of atmospheric gases
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2
4
2
4

R

T

S
(
1


)

R
4
T4=S(1
-
)
T = - 18.6 °C (=1)
TT=14,9 °C (=0.6)
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4
Natural Disasters
Increase of big large natural disasters (Source MunichRe):
Decade
1950-69 1960-69 1970-79 1980-89 1990-99
number
20
27
47
63
91
Mrd.US$ (2004)
45
81
148
228
704
Extreme weather related loss: ~10% of GNP in industrial nations
1. There is no direct cause effect relation
for single events and climate change, but:
2. Since ~1970 and accelerated in the 90ths significant changes are
observed for several extreme weather indicators:
• More days with intense precipitation
• Increasing numbers of floods in many regions
• Increasing wind peak velocities in various regions
• Increasing starting conditions for thunderstorms in some regions
• Increasing damage potential for tropical storms (!) and winter storms
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Basic Foundations of Climate Modelling
Climate = Statistics of Weather
(30yr averages)
Structure:
Multilayer Grid-Sized Coupled
Ocean Atmosphere General
Circulation Models (~ 300 km2)
(Origin early 80ties)
Preconditions
Forcing Scenarios:
IPCC Storylines (A1, A2, B1, B2)
Consistency & Validation:
CMIP: Coupled Model Intercomparison Project
Validation by observation/reconstruction
http://www-pcmdi.llnl.gov/projects/cmip/index.php
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Global Climate  Regional Climate
Global Scenario
precipitation
GCM
T
~300 km
>| |<
~10-50 km
Regionalisation
global
?
local
precipitation
2050
climate
hydrology
Regional
Simulator
Land use
soils/
Geology
Infrastructure
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Uncertainties in Global Climate Change
Temperature Increase [°C]
a) Emission Storylines
b) Model Uncertainties
IPCC-Report 2001
http://www.ipcc.ch
climate
scenario
YEAR
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Local Models: why it is so difficult?
Downscaling: from global model scale (~ 300 km2) to a
regional scale (~10-50 km2)
Two strategies: statistical models/dynamical models
• Physical representation of processes must be more explicit
• Need more computational power and time
• Orography must be represented adequately
• Boundary constraints (which model?)
• Statistical transfer functions do not change in time
• “Migration” of boundary inputs, etc.
LCM Errors: Statistical (local) models: 10-20%
Dynamical (local) models 30-40%
Model intercomparisons are ongoing research (e.g. at PIK)!
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First Project: PRUDENCE
(Special Issue: Climatic Change 2006)
Only a few sources of uncertainties were analysed:
Radiative uncertainty: A2 which is only one IPCC hypothesis
Model uncertainty: subgrid, discretization effects
Sampling uncertainty: averages 30yrs
Boundary conditions: running under constraints of one GCM
Main results: A2, Dmeans 1961/1990 – 2071/2100
Northwards migration of ecosystems
Increase of precipitation in the north, decrease in the south, more torrential
rain
Increase of extreme wind speeds between 45° - 55°N, more north-westerly
Faster increase of more hot, days than the increase of moderate days
Increase of heatwaves over central Europe
Large differences between certain models!
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Gaussian distributions of mean
summer maximum temperatures as
Basle (Switzerland), (measured: 19611990, A); A': HIRHAM4 model), 20712100 A2 scenario simulation (B) and
2003 summer heatwave (C).
economic
global
DJF and JJA precipitation changes,
simulated by Rossby Centre LCM
under Hadley Centre (left) and
MPI HH (right) constraints
(A2 storyline)
A1 A2 regional
B1 B2
ecological
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PRUDENCE Comparison
1961/90 – 2075/2100, A2 Hadley Boundary
DT (°C)
BSR Countries
Ta
DP (%)
T (DJF)
T(JJA)
Pa
P(DJF)
P(JJA)
Denmark
1.1
1.0
1.1
2.4
9.8
-6.4
Estonia
1.4
1.6
1.2
4.2
10.2
4.5
Finland
1.4
1.7
1.0
5.8
10.9
4.6
Germany North
1.2
1.1
1.3
0.1
6.0
-7.3
Latvia
1.4
1.6
1.2
3.2
9.7
1.8
Lithuania
1.4
1.5
1.2
2.0
8.8
-1.1
Sweden North
1.3
1.5
1.0
5.3
9.0
2.7
Sweden South
1.2
1.3
1.1
3.5
11.4
-2.1
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Recent Statements on Regional Climate
Modelling
Model outputs commonly have to be manipulated and combined with observed
climate data to be usable, for example, as inputs to impact models (IPCC 2001,
WGI, p. 743, Ch. 13)
We are not yet at promised level where regional climate models can really
influence regional policy making (Amanatidis, 2004, scientific officer EC)
We cannot calculate robust regional climate scenarios (R. Betts, Hadley Centre,
2006)
Regional temperature prognosis for Europe has the largest uncertainty of all
continents (P. Stott, 2006)
We just understand what we are doing, but our knowledge will remain uncertain
(certain climate modellers 2006)
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Yes!
It is not a question whether, where and how large a change
may be, it is only relevant that climate change comes true!
On the local scale this needs an analysis of potential impacts
and their associated exposure units and its vulnerability!
Good policies needs a systematic analysis of decision lines,
Institutional settings, in particular, inhibiting and forcing
factors!
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Even modern societies as, US, Germany, or
France are sensitive against weather extremes,
therefore also to long-term climate change!
This implies that they are mal-adapted
to current weather situations
It is very likely that CC will increase this
problem (cf. 2cd transparency)!
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Download at:
http://www.defra.gov.uk/environment/climatechange/internat/sciencesassess.htm
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Initial Impacts
Effects
Expected
Adaptations
Residual or
Net Impacts
VULNERABILITIES
MITIGATION
of Climate Change
via GHG sources
and sinks
CLIMATE CHANGE
incl. variability
IMPACTS
Human
Interference
dangerous? vulnerable?
Planned
ADAPTATION
to the
Impacts and
Vulnerabilities
Policy
Responses
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Combating and Coping with Climate Change
(Post-) Kyoto-Process:
Mitigation, definition of stabilization
levels; technical solutions, e.g. carbon
capturing and sequestration (will be
not discussed here in detail!)
Improving Preparedness:
Adaptation, avoid unmanageable
situations, develop strategies to
manage the unavoidable
ASTRA‘s main issue!
Consequences of maladaptations?
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Hurricane Katrina,
Gulf of Mexico
2005
(SS5; SS4 - landfall)
1000km
Example of maladaptation!
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New Orleans Terrain model
Lake Pontchartrain
Gulf-Coast
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They have had the possibility to know it, but
- may be – that the awareness was too low….
Drowning New Orleans
by Mark Fischetti
Scientific American (October 1, 2001)
The boxes are stacked eight feet high and line the walls of the large, windowless room. Inside them
are new body bags, 10,000 in all. If a big, slow-moving hurricane crossed the Gulf of Mexico on the
right track, it would drive a sea surge that would drown New Orleans under twenty feet of water. "As
the water recedes", says Walter Maestri, a local emergency management director, "we expect to find
a lot of dead bodies".
New Orleans is a disaster waiting to happen. The city lies below sea level, in a bowl bordered by
levees that fend off Lake Pontchartrain to the north and the Mississippi River to the south and west.
And because of a damning confluence of factors, the city is sinking further, putting it at increasing
flood risk after even minor storms. The low-lying Mississippi Delta, which buffers the city from the
gulf, is also rapidly disappearing. A year from now another 25 to 30 square miles of delta marsh - an
area the size of Manhattan - will have vanished. An acre disappears every 24 minutes. Each loss
gives a storm surge a clearer path to wash over the delta and pour into the bowl, trapping one
million people inside and another million in surrounding communities. Extensive evacuation would
be impossible because the surging water would cut off the few escape routes. Scientists at
Louisiana State University (LSU), who have modeled hundreds of possible storm tracks on
advanced computers, predict that more than 100,000 people could die. The body bags wouldn't go
very far...................
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Methodological Developments for improved
Flood Risk - Prognosis
Ilz/Kalteneck Change of river run-off
Return levels for 100yr floods:
Interval of prognosis
for fitting used Data
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extrapolated Trend
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− stationary GEV
− instationary GEV
− instationary GEV
extrapolated trend,
prognostic interval 5 yrs
Conclusion
Problem of adaptation ist not new, but the view on adaptation
changes: humanity now can anticipate disastrous developments!
Results from climate models provide valuable hints that
adaptation/mitigation is necessary task!
They cannot provide information for concrete regional actions,
since this lies outside the scope of models!
Actions must be developed in close cooperation of decision
makers, and scientists
....
Closer look and
preconditions....
Knowledge improvement
Awareness rising
Talk: K. Eisenack &
J. Kropp
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Implementation of
best practices
Talk: J.Kropp &
M. Stock
Dr. Jürgen Kropp and Dr. Manfred Stock
Potsdam Institute for Climate Impact Research
AMICA - Adaptation and Mitigation
- an Integrated Climate Policy Approach:
European Cities Striving for Best Practice Examples
Interregional Thematic Working Groups on
Key Themes Related to Climate Impacts:
1. Flooding
2. Coastal erosion
3. Drought
4. Overheating
Approach to combine long-term climate protection
and short- and midterm adaptation measures
on the local level (transfer of best practice examples)
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AMICA Project Partners
(http://www.klimabuendnis.org)
Coordinator: European Secretariat
Galvanistr. 28, D-60486 Frankfurt am Main
Cooperation with PIK for Scientific Support
KLIMABÜNDNIS
ÖSTERREICH
ALLEANZA PER
IL CLIMA ITALIA
Provincia di Ferrara
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Scope of the Scientific Analysis
 Reasons of Concern - Dealing with Risks under Uncertainty
 Dimensions of
Scale, Time Delay, Multiple Causes, Feedback and Side Effects
 Concept of Vulnerability and Adaptation with some
Best Practice Examples:
1. River Flood Events
2. Water Management: Droughts and Flash Floods
3. Urban Planning: Heat Waves and Overheating
4. Storms, Thunderstorms and Related Events
5. Sea Level Rise and Coastal Erosion
 Adaptation - Main Findings and Evaluation
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Definition:
Adaptation to Climate Change
Adjustments in ecological, social or economic
systems in response to actual or expected
climate change stimuli, their effects or impacts
• to reduce vulnerability
• to moderate damages
• to realize opportunities
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Climate Impact, Systems Response and Vulnerability
Climate Change
IMPACT
vulnerable
System
disastrous
impact
significant
impact
minor impact
adapted
critical limit
temperature change
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Types of Adaptation
Anticipatory
• changes in ecosystem
composition, location
• wetland migration
Private
• crop diversification
• purchase insurance
• house designs
• crop development
• borrow, change activity
• reconstruction,
relocation
Public
Natural
Systems
Human
Systems
Reactive
• early-warning
• building codes
• infrastructure
• disaster relief
• relocation incentives
Best Practice Examples
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AMICA: Best Practice Examples
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Vulnerabiliy and Adaptation I - Water Management
Global Change
Socio-economic
Climate Change
change
Sensitivity
Regional Exposure
•High water demand
•High population density
•Lack of Precipitation
•Extreme rainfall events
greenhousesgasemissions
Adaptability
•Land use management
•Risik management
Potential Impacts
•Loss due to extreme droughts
•Loss due to extreme floods
Society
Interaction
Environment
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Vulnerability
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Awareness &
Preparedness
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Thematic working group
„flooding/rivers/water-balance in urban areas“
First catalogue for adaptation measures (City of Dresden preliminary survey):
1. Retention measurements in urban areas (using for flood and draughts)
2. Protection of retention areas for flood events near rivers
3. Seasonal stabilisation of water-balance (management of groundwater,
deceleration in the run-off of precipitation, seasonal water-storage)
4. Adaptations in landscape planning
5. Modification of forest structure and new forest areas
6. Water conservating techniques in the cultivation of soil
7. Adaptations in the waste and drain water systems as an example for necessary
measures in infrastructure
8. Adaptations in parks and to road-side trees
9. Adequate treatment of rainfalls in plans for the development of new building
areas and new streets
10. Change from flood protection to flood risk management
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Christmas flood
Cologne 1993
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www
0373
Flood Cologne
1995
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Financial damage of the
1993 and 1995 floods in Cologne
•
Almost the same
water level
1993: 10,63 m
1995: 10,69 m
•
Same sentivity
•
But reduction of financial damage
by more than 50% !
•
Explained to a great extent by
higher preparedness of
affected households and business
companies
Mio. DM
160
140
120
150
Mio.
DM
100
80
65
Mio.
DM
60
40
20
0
Schäden 1993
1993
Schäden 1995
1995
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Adaptation - Main Findings
1. Adaptation can reduce adverse impacts
2. Communities will adapt autonomously, but not without costs
3. The key features of climate change are variabilities and extremes
4. Planned adaptation measures usually have immediate benefits
5. Adaptations are likely to be implemented only if they are
integrated with existing management and development processes
6. Adaptive capacity varies considerably among countries, regions
and socio-economic groups
7. Development activities modify adaptive capacity, yet they tend to
omit climate change risks
8. Enhancement of adaptive capacity is necessary to reduce
vulnerability, especially for the most vulnerable (people, regions…)
9. Current knowledge of adaptation & adaptive capacity is insufficient
10. Significant enhancements will result from joint projects with
decision making authorities
and scientific experts
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37
Thank you
for your attention!
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