The Challenge Imposed by Climate Change...4 1880-1884 average Global mean temperature relative to...
Transcript of The Challenge Imposed by Climate Change...4 1880-1884 average Global mean temperature relative to...
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TheChallengeImposedbyClimateChange
Francis Zwiers Pacific Climate Impacts Consortium
University of Victoria, Victoria, Canada Action Canada Vancouver, 2 April 2016
Phot
o: F
. Zw
iers
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Outline • Observed changes • Interpretation • Projections • Limiting future warming • Key messages • Impacts (if time permits) • Questions
Photo: F. Zwiers
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Observed Changes
Photo: F. Zwiers
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1880-1884 average
Global mean temperature relative to 1951-1980 1.0
0.5
0.0
-0.5
°C
1880 1900 1920 1940 1960 1980 2000 2020
2011-2015 average
2
0
-2
°C
Courtesy NASA GISS (accessed 28 March 2016)
Warming is unequivocal Multiple lines of evidence including
• Temperature • Snow cover extent • Arctic sea ice • Ocean heat content • Sea level rise
Associated changes in • Precipitation • Ocean surface
salinity • Temperature and
precipitation extremes
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Interpretation of the Evidence
Photo: F. Zwiers
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Global mean temperature anomaly
Jonesetal,2013
Krakatoa Santa Maria
Agung El Chichon
Pinatubo °C
See also Figure 10.1, IPCC WG1 AR5
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Jonesetal,2013
Jonesetal,2013
All forcings Greenhouse gas forcing
Global mean temperature anomaly
Solar and volcanic forcing
See also Figure 10.1, IPCC WG1 AR5
It is extremely likely that human influence has been the dominant cause of the observed warming since the mid-20th century.
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Impacts in BC • Warming clearly evident • Glaciers in retreat across the province • Winter snowpack reductions • Summer stream flow declining • Large reduction in number of frost days each year • Pine bark beetle infestation linked to less intense
winter cold extremes
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Annual frost days
Frost day change relative to 1986-2005
Historical 1900-2011 trend: 24 days (statistically significant)
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Projected climate change
Photo: F. Zwiers
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Summary for Policymakers
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Figure SPM.7 | CMIP5 multi-model simulated time series from 1950 to 2100 for (a) change in global annual mean surface temperature relative to 1986–2005, (b) Northern Hemisphere September sea ice extent (5-year running mean), and (c) global mean ocean surface pH. Time series of projections and a measure of uncertainty (shading) are shown for scenarios RCP2.6 (blue) and RCP8.5 (red). Black (grey shading) is the modelled historical evolution using historical reconstructed forcings. The mean and associated uncertainties averaged over 2081−2100 are given for all RCP scenarios as colored verti-cal bars. The numbers of CMIP5 models used to calculate the multi-model mean is indicated. For sea ice extent (b), the projected mean and uncertainty (minimum-maximum range) of the subset of models that most closely reproduce the climatological mean state and 1979 to 2012 trend of the Arctic sea ice is given (number of models given in brackets). For completeness, the CMIP5 multi-model mean is also indicated with dotted lines. The dashed line represents nearly ice-free conditions (i.e., when sea ice extent is less than 106 km2 for at least five consecutive years). For further technical details see the Technical Summary Supplementary Material {Figures 6.28, 12.5, and 12.28–12.31; Figures TS.15, TS.17, and TS.20}
6.0
4.0
2.0
−2.0
0.0
(o C)
4232
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historicalRCP2.6RCP8.5
Global average surface temperature change(a)
RC
P2.6
R
CP4
.5
RC
P6.0
RC
P8.5
Mean over2081–2100
1950 2000 2050 2100
Northern Hemisphere September sea ice extent(b)R
CP2
.6
RC
P4.5
R
CP6
.0
RC
P8.5
1950 2000 2050 2100
10.0
8.0
6.0
4.0
2.0
0.0
(106 k
m2 )
29 (3)
37 (5)
39 (5)
1950 2000 2050 2100
8.2
8.0
7.8
7.6
(pH
uni
t)
12
9
10
Global ocean surface pH(c)
RC
P2.6
R
CP4
.5
RC
P6.0
R
CP8
.5
Year
SPM
We have a choice …
Figure SPM.7, IPCC WG1 AR5
Carbon emissions CO2 concentration
Van Vuuren et al. 2011
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Projected warming (mean climate)
RCP2.6
RCP8.5
Difference between 1986-2005 and 2081-2100
Figure SPM.8, IPCC WG1 AR5
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Projected mean precip change
RCP2.6
RCP8.5
Difference between 1986-2005 and 2081-2100
Figure SPM.8, IPCC WG1 AR5
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Limiting future warming
Photo: F. Zwiers
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Keeping warming below 2°C … • Warming is essentially permanent (even if
emissions are completely curtailed) • Global temperature change is proportional to the
total amount of carbon emissions accumulated over time.
• To have decent odds of keeping global warming below 2°C (likely, i.e., ≥ 2 chances in 3), the total amount of carbon dioxide emissions (since the pre-industrial era) needs to be limited to less than 1000 GtC.
• More than half of this amount has already been emitted.
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Cumulative emissions and warming Fi
gure
SP
M.1
0, IP
CC
WG
1 A
R5
RCP2.6 RCP4.5 RCP6.0 RCP8.5
Cumulative total anthropogenic CO2 emissions from 1870 (GtC)
Tem
pera
ture
ano
mal
y re
lativ
e to
186
1-18
80 (°
C)
~66%
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Some key messages
Photo: F. Zwiers
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• Warming of the climate system is unequivocal • Warming is essentially permanent • Impacts are occurring • Continued emissions will cause further warming and
exacerbate some types of extremes • Adaptation will be required to reduce impacts and risks • The magnitude of impacts, risks and adaptation costs
depends upon the level of warming • Limiting warming will require deep emissions reductions • Cumulative emissions largely determine the amount of
long-term warming • Selecting a warming limit implies a fixed, global,
emissions budget
Some messages
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Impacts experienced via extremes
Photo: F. Zwiers (Gravelbourg Sunset)
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China’s Summer of 2013
Photo: F. Zwiers (Yangtze River)
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Eastern China is densely observed
• 1749 stations (1955 onwards) • JJA mean temperature increased
0.82°C over 1955-2013 • records were broken at more
than 45% of stations in JJA 2013
JJA mean temperature in Eastern China
-1
-0.5
0
0.5
1
1.5
1955
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57
1959
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61
1963
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65
1967
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69
1971
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73
1975
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77
1979
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81
1983
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1987
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89
1991
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93
1995
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1999
20
01
2003
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2007
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09
2011
20
13
The 5 hottest summers have all occurred since 2000
(2013, 2007, 2000, 2010 and 2011)
1.1°C
Ano
mal
y re
lativ
e to
195
5-19
84 °C
Sun et al, Nature Climate Change, 2014
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The multi-model ensemble mean (ALL forcing) well simulates the observed temperature record.
Observed and simulated JJA mean temperature in Eastern China (1955-2012)
125 (26) 49 (12)
Anomalies relative to 1955-1984
Sun et al, Nature Climate Change, 2014
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JJA mean temperature in Eastern China
-1
-0.5
0
0.5
1
1.5
1955
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57
1959
19
61
1963
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65
1967
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1971
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1975
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77
1979
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81
1983
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1987
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89
1991
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93
1995
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97
1999
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01
2003
20
05
2007
20
09
2011
20
13
The 5 hottest summers have all occurred since 2000
(2013, 2007, 2000, 2010 and 2011)
1.1°C
Ano
mal
y re
lativ
e to
195
5-19
84 °C
Sun et al, Nature Climate Change, 2014
• How rare was this event? • once in 270-years in control simulations • once in 29-years in “reconstructed” observations • once in 4.3 years relative to the climate of 2013
• Fraction of Attributable Risk in 2013: (p1 – p0)/p1≈ 0.984
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Calgary flood, 2013
Looking towards downtown Calgary from Riverfront Avenue (June 21, 2013), courtesy Ryan L.C. Quan
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Calgary floods (Teufel et al, submitted)
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Figure 13. Return times of (a) average May-June evapotranspiration over the northern
Great Plains, (b) maximum 1-day and (c) 3-day May-June precipitation over southern
Alberta, in present-day (red) and pre-industrial ensembles (blue). Gray horizontal
lines show (a) average evapotranspiration during the 14-21 June period, (b) average
precipitation on 20 June and (c) average precipitation during the 19-21 June period,
for the members of the CRCM5_Ref ensemble. Black dashed lines show (b) average
precipitation across the region on 20 June and (c) average precipitation during the 19-
21 June period, as estimated from CaPA.
100 101 102 1030
10
20
30
40
50
60
70
1−da
y m
axim
um (m
m)
Return period (years)
IRPIRaPIRbPIRc
100 101 102 1030
20
40
60
80
100
120
3−da
y m
axim
um (m
m)
Return period (years)
IRPIRaPIRbPIRc
(a)
(b) (c) Distribution of annual May-June maximum 1-day southern-Alberta precipitation in CRCM5 under factual and counter-factual conditions (conditional on prevailing global pattern of SST anomalies)
Frequency doubles (~25-yr à ~12 yr)
Magnitude increases ~10%
Southern Alberta MJ max 1-day precip
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Calgary floods (Teufel et al, submitted)
Distribution of annual May-June maximum 1-day Bow River Basin precipitation in CRCM5 under factual and counter-factual conditions (conditional on prevailing global pattern of SST anomalies)
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Figure 14. Return times of maximum 1-day (left) and 3-day (right) May-June
precipitation (top) and surface runoff (bottom) in present-day (red) and pre-industrial
ensembles (blue), over the western BRB. Gray horizontal lines show the average
precipitation (top) and average surface runoff (bottom) over this region on 20 June
(left) and during the 19-21 June period (right) for the members of the CRCM5_Ref
ensemble. Black dashed lines show the average precipitation over this region on 20
June (top left) and during the 19-21 June period (top right), as estimated from CaPA.
100 101 102 1030
20
40
60
80
100
120
1−da
y m
axim
um (m
m)
Return period (years)
IRPIRaPIRbPIRc
100 101 102 1030
50
100
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200
3−da
y m
axim
um (m
m)
Return period (years)
IRPIRaPIRbPIRc
100 101 102 1030
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20
30
40
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1−da
y m
axim
um ru
noff
Return period (years)
IRPIRaPIRbPIRc
100 101 102 1030
20
40
60
80
100
3−da
y m
axim
um ru
noff
(mm
)
Return period (years)
IRPIRaPIRbPIRc
(a) (b)
(c) (d)
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www.PacificClimate.org
Thank You!
Photo: F. Zwiers