Download Future Climate Extremes

Future Climate Extremes:
Physical and Human Dimensions
Claudia Tebaldi
Climate Central & NCAR
Brian O’Neill
NCAR
November 13, 2012
CONFIDENTIAL AND PROPRIETARY
Any use of this material without specific permission of UCAR-NCAR is strictly prohibited
From IPCC SREX (2012) SUMMARY FOR POLICY MAKERS
Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX)
1
The physical dimension of changing risks:
• Climate Extremes
• Coastal Flooding
The human dimension of changing risks:
• Exposure: Spatial Population Distribution
• Vulnerability: Indexes and Economic Interactions
2
The physical dimension of changing risks:
• Climate Extremes
• Coastal Flooding
The human dimension of changing risks:
• Exposure: Spatial Population Distribution
• Vulnerability: Indexes and Economic Interactions
3
Mechanisms responsible for changes in climate extremes
1)
4
Mechanisms responsible for changes in climate extremes
2)
5
Mechanisms responsible for changes in climate extremes
3)
6
When the shift in mean explains the most:
Heat extremes : Ratio of record high vs. record low
US average, observed
Annual values of the
ratio of record high vs.
record low
Meehl et al., 2009: Relative increase of record high maximum temperatures compared to record low minimum temperatures in the U.S. GRL
7
When the shift in mean explains the most:
Heat extremes : Ratio of record high vs. record low
US average, observed
Annual values of the
ratio of record high vs.
record low
Long term trend
Meehl et al., 2009: Relative increase of record high maximum temperatures compared to record low minimum temperatures in the U.S. GRL
8
When the shift in mean explains the most:
Heat extremes : Ratio of record high vs. record low
US average, observed
Annual values of the
ratio of record high vs.
record low
Long term trend
Confidence interval
under the assumption
of no long term trend
Meehl et al., 2009: Relative increase of record high maximum temperatures compared to record low minimum temperatures in the U.S. GRL
9
When the shift in mean explains the most:
Heat extremes : Ratio of record high vs. record low
US average, observed
US average, CCSM
US average, CCSM, Future
Meehl et al., 2009: Relative increase of record high maximum temperatures compared to record low minimum temperatures in the U.S. GRL
10
And just in case you are curious about the past year:
US as a
whole:
7.6
http://www.climatecentral.org/news/2012-record-temperatures-which-states-led-the-nation-14951
11
When the shift in variance is more relevant:
Precipitation extremes
Future Changes in Mean Precipitation
Future Changes in Precipitation Intensity
Green-Blue: Increase in precipitation amounts
Pink-Brown: Decrease in precipitation amounts
Stippling: Model consensus
Meehl et al., 2005: Understanding future patterns of increased precipitation intensity in climate model simulations. GRL
Tebaldi et al., 2007: Going to the extremes. Climatic Change
Tebaldi et al., 2012: Mapping model agreement on future climate projections. GRL
12
Most recent simulation results:
NCAR’s CCSM4 under different scenarios
Changes in average temperature during the warmest
three nights of the year (degrees C)
by the end of the century
Low Forcing – High Mitigation
High Forcing – No Mitigation
Meehl et al., 2012: Climate System Response to External Forcings and Climate Change Projections in CCSM4. J. of Climate
13
Most recent simulation results:
CCSM4 under different scenarios
Change in Precipitation Intensity (mm/day)
by the end of the century
Low Forcing – High Mitigation
High Forcing – No Mitigation
Meehl et al., 2012: Climate System Response to External Forcings and Climate Change Projections in CCSM4. J. of Climate
14
The physical dimension of changing risks:
• Climate Extremes
• Coastal Flooding
The human dimension of changing risks:
• Exposure: Spatial Population Distribution
• Vulnerability: Indexes and Economic Interactions
15
Changes in risk of coastal floods from storm surges
as an effect of mean sea level rise
Current 100-year events
(meters above Mean High Water)
0-1
1-2
2-3
3-4
4-5
Tebaldi et al. 2012: Modelling sea level rise impacts on storm surges along US coasts. Envir. Res. Letters
16
Changes in risk of coastal floods from storm surges
as an effect of mean sea level rise
Current Sea Level Rise (1959-2008)
(mm/year)
-2 – 0
0–2
2–4
4–6
6 – 6.5
17
Future (2008-2050)
Sea Level Rise
(meters)
0.1-0.2
0.2-0.3
0.3-0.4
0.4-0.5
18
The Battery, NY: Storm Surges
(meters above Mean High Water)
Sandy’s
surge
19
The Battery, NY: Storm Surges
(meters above Mean High Water)
The 100-yr event
becomes
the 15-yr event by
2050
20
Future extremes’ changed frequencies
Every how many years will today’s
100-year event recur, by 2050?
1
2
5
10
20
30
50
75
100
21
By at most the end of the century 6 ft surges will be
happening on average every other year, or more
frequently.
Terrain
inundated
by 6ft
surges
http://sealevel.climatecentral.org
Strauss et al., 2012: Tidally adjusted estimates of topographic vulnerability to sea level rise and flooding for the contiguous United States. Envir. Res. Letters
22
From IPCC SREX (2012) SUMMARY FOR POLICY MAKERS
Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX)
23
The physical dimension of changing risks:
• Climate Extremes
• Coastal Flooding
The human dimension of changing risks:
• Exposure: Spatial Population Distribution
• Vulnerability: Indexes and Economic Interactions
24
Spatial Population Projection: Florida
Physical Impact
Population Exposure
Terrain
inundated
by 6 ft
surges
2000
2100
Jones & O’Neill, in prep.
25
Spatial Population Projection: Florida
Population (Millions)
12
High Growth, 2100
10
8
Medium Growth, 2100
6
4
Current
2
0
0-10 10-20 20-30 30-40 40-50 50-60 60-70 70-80 80-90 90-100 100+
Distance from coast (km)
26
Spatial Population Projection:
Hurricane Sandy Landfall Area
The
Battery
2100
2000
27
Spatial Population Projection: National
State of the art, 2007
Existing Projection, 2100
Shortcomings:




Topography
Protected areas
Borders
Calibration
Gruebler et al., 2007.
28
Spatial Population Projection: National
NCAR Projection, 2100
Existing Projection, 2100
Jones & O’Neill, in prep.
29
Spatial Population Projection: Global
Projected Heat Extremes
Projected Population Distribution
Gruebler et al., 2007.
30
The physical dimension of changing risks:
• Climate Extremes
• Coastal Flooding
The human dimension of changing risks:
• Exposure: Spatial Population Distribution
• Vulnerability: Indexes and Economic Interactions
31
Vulnerability Index
Modeled
Outcomes
Income
Measuring vulnerability
Fertility,
Population
Growth, Age
Structure
Separate
Projections
Education
Human
Development
Index
Vulnerability
Life
Expectancy
32
Human Development Index
Very High
0.9
0.8
OIC
Other Indust. Ctries
LAC
Lat. Am. & Carrib.
CHN
China
High
ODC
Other Dev. Ctries
0.7
IND
India
Medium
SSA
Sub-Saharan Africa
0.6
0.5
0.4
2010
Low
Human Development Index (HDI)
1
2020
2030
2040
2050
O’Neill et al., in prep.
33
Integrated PopulationEconomy-Technology-Science
(iPETS) Model
EU-27+
Transition
Countries
USA
China
India
Sub-Sah.
Africa
Latin
America
Other Devel.
Countries
Other Indust.
Countries
34
Economic interactions
CESM
iPETS
Climate
Risks
e.g., Extreme Heat, Drought
e.g., Crop Production
35
Economic Interactions: Agricultural impacts
iPETS Results, Latin America region:
Effect of reduced productivity on land use and food prices
Cropland
80%
Reduced
Productivity
70%
800
600
Price change (%)
Million Hectares
1000
Change in Food Price
Baseline
Scenario
400
60%
50%
Increase in Food
Price due to
Reduced Productivity
40%
30%
20%
200
10%
0
2000
2020
2040
2060
2080
2100
0%
2000
2020
2040
2060
2080
2100
36
Summary
Projecting changes in both physical and human
systems is necessary for anticipating future risks
from climate change
Progress requires closer integration of research
on climate science and human systems
37
Acknowledgments
NCAR Integrated Science Program
DOE Cooperative Agreement DE-FC02-97ER62402
DOE Integrated Assessment Research Program
G. Meehl, G. Strand (NCAR); J. Arblaster (NCAR and CSIRO);
B. Strauss, D. Adams-Smith, R. Ziemelinski (Climate Central);
Chris Zervas (NOAA);
Bryan Jones, Xiaolin Ren, Leiwen Jiang (NCAR); Shonali
Pachauri, Regina Fuchs, Samir KC (IIASA); Michael Dalton
(NOAA); Ed Balistreri (Colorado School of Mines).
38