Sea level response and impacts of a 1°C to
7°C prescribed temperature rise by 2100
Sally Brown1*, Robert Nicholls1, Jason Lowe2, Jochen Hinkel3
1. School of Civil Engineering and the Environment, University of Southampton, UK.
2. Met Office, Hadley Centre (Reading Unit), Reading, UK.
*sb20@soton.ac.uk.
3. Potsdam Institute of Climate Impact Research, Potsdam, Germany.
Introduction
Rising temperatures create a rise in sea levels, threatening low-lying land and increasing the probability of flood events. Some of the largest impacts are
mostt likely
lik l to
t be
b felt
f lt in
i places
l
off high
hi h population
l ti density.
d
it Using
U i DIVA,
DIVA an integrated
i t
t d modelling
d lli tool
t l (DINAS-COAST
(DINAS COAST Consortium,
C
ti
2006;
6 McFadden
M F dd ett al.
l
2007; Vafeidis et al. 2008), the number of additional people flooded per year due to sea level rise and storm surges has been estimated.
From the ensemble mean MAGICC A1B sea level scenario
(projecting a 3°C rise in temperature and a 0.40m rise in sea
level by 2100 with respect to 1961
1961-1990),
1990), prescribed scenarios
based on a temperature increase of 0.5°C to 4.0°C in 2050 in
increments of 0.5°C were generated (Figure 1). This resulted in
a 1°C and 7°C rise in temperature and a 0.13m to 1.09m rise in
sea-levels by 2100 (Figure 2).
1.2
4.0ºC at 2050
1.0
3.5ºC at 2050
3.0ºC at 2050
0.8
2.5ºC at 2050
0.6
2.0ºC at 2050
1.5ºC at 2050
0.4
MAGICC mean
1.0ºC at 2050
0.2
0.5ºC at 2050
0.0
1990
2000
2010
2020
2030 2040
2050 2060
2070
2080 2090
Sea level rise relative to 196
61-1990 (m)
Sea level rise relative to 196
61-1990 (m)
Methodology
2100
1.2
1.0
4.0°C at 2050
3.5°C
°C at 2050
0.8
3.0°C at 2050
2.5°C at 2050
0.6
2.0°C at 2050
1.5°C at 2050
0.4
MAGICC mean
1.0°C at 2050
0.2
0.5°C at 2050
0.0
0.0
Year
2.0
3.0
4.0
5.0
6.0
7.0
8.0
Temperature rise relative to 1961-1990 (°C)
Downscaling the sea level scenarios and combining with vertical
land movements, DIVA estimates the number of people subject
to flooding due to storms events. Adaptation strategies of no
upgrade and a cost-benefit approach were assessed.
Figure 1. Prescribed sea level rise scenarios
based on the A1B ensemble MAGICC mean
dataset against time.
1.0
Figure 2. Prescribed sea level rise scenarios
based on the A1B ensemble MAGICC mean
dataset against temperature.
If defences are not upgraded as time progresses, and
temperatures and sea levels rise, the number of additional
people flooded by surges increases as shown in Figures 3 and 4
(note that population declines after 2050 in the A1B scenario,
p
g the decrease in number flooded at high
g
explaining
temperatures). The faster the rate of sea level rise the greater
the risk. For the MAGICC ensemble mean, a 3ºC and 0.40m
rise in temperature and sea-level in 2100 would put 89 million
people at risk from flooding globally. For a 7ºC temperature rise
by 2100, 204 million additional people per year would be
expected to be flooded. Using a cost-benefit approach to
adaptation, these figures could be reduced to less than 0.2
million per year at costs of US$17 and US$41 billion dollars per
year respectively (1995 values, not discounted).
250
200
4.0ºC at 2050
3.5ºC at 2050
150
3.0ºC at 2050
2.5ºC at 2050
2.0ºC at 2050
100
1.5ºC at 2050
MAGICC mean
50
1.0ºC at 2050
0.5ºC at 2050
0
1990
2000
2010
2020
2030 2040 2050 2060
2070 2080 2090
2100
Year
Figure 3. Additional number of people flooded
due to surges using the A1B socio-economic
scenario and prescribed sea-level changes
against time.
Additional number of people flooded due to
s relative (millions / year)
extreme water levels
Additional number of people flooded due to
s relative (millions / year)
extreme water levels
Results and regions at risk
250
200
4.0°C at 2050
3.5°C at 2050
3.0°C at 2050
150
2.5°C at 2050
2.0°C
2.0
C at 2050
100
1.5°C at 2050
MAGICC mean
1.0°C at 2050
50
0.5°C at 2050
0
0.0
1.0
2.0
3.0
4.0
5.0
6.0
7.0
8.0
Temperature rise relative to 1961-1990 (°C)
Figure 4. Additional number of people flooded
due to surges using the A1B socio-economic
scenario and prescribed sea-level changes
against temperature.
Looking at the highest rise considered (7ºC in 2100), three quarters of the global number of people at risk without adaptation throughout the 21st century
are, due to high population densities, located in Asia (Figure 5). North and West Europe and the Baltic Sea coast are greatly threatened, but adaptation
seems likely. Small islands will be especially vulnerable as they have the reduced ability to adapt, potentially prompting forced migration.
a) 2025 (2ºC and 0.23m rise)
b) 2050 (4ºC and 0.48m rise)
Additional number people flooded per year due to extreme water levels (millions)
c) 2075 (6ºC and 0.78m rise)
Additional number people flooded per year due to extreme water levels (millions)
d) 2100 (7ºC and 1.09m rise)
Additional number people flooded per year due to extreme water levels (millions)
Additional number people flooded per year due to extreme water levels (millions)
0-0.1
0.1-0.5
0.5-1
1- 5
0-0.1
0.1-0.5
0.5-1
1- 5
0-0.1
0.1-0.5
0.5-1
1- 5
0-0.1
0.1-0.5
0.5-1
1- 5
5-20
20-30
30-50
50-80
5-20
20-30
30-50
50-80
5-20
20-30
30-50
50-80
5-20
20-30
30-50
50-80
Figure 5. Additional people flooded per year (millions) based on GVA regions throughout the 21st century using the highest prescribed sea level scenario (a 4°C rise by 2050)..
Implications and conclusions
Using the DIVA model with the A1B prescribed sea level scenarios,
scenarios potentially many millions of people could be flooded as temperatures and sea levels
increase. However, technically sound adaptation measures are available for coastal areas: the DIVA analysis indicates protection will be widespread and the
main consequences of sea level rise will be investment in defences. Through the increased risks associated with rising temperatures and sea levels, effective
management at global, regional and country scales is essential to balance coastal development with environmental values.
ACKNOWLEDGEMENTS AND REFERENCES:
This research has been undertaken as part of the Quantifying and Understanding the Earth System - Global Scale Impacts
programme (QUEST-GSI) funded by the UK Natural Environment Research Council (NERC).
DINAS-COAST Consortium, 2006. DIVA 1.5.5. Potsdam Institute for Climate Impact Research, Potsdam, Germany, CD-ROM. Available at
http://www.pik-potsdam.de/diva
McFadden, L. et al. (2007) A methodology for modelling coastal space for global assessment. Journal of Coastal Research, 23, 911-920.
Vafeidis, A.T. et al. (2008) A new global coastal database for impact and vulnerability analysis to sea-level rise. Journal of Coastal
Research, 24, 917-924.