Simulated future changes in extreme water levels

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Simulated future changes in extreme water levels
Simulated Future Changes in Extreme
Water Levels
Jason Lowe1, Katja Woth2, Kathy McInnes3
June 2006
1 The
2
Hadley Centre, Met Office, UK.
GKSS, Geesthacht, Germany.
3 CSIRO,
Aspendale, Australia.
© Crown copyright 2004
Page 1
 The problem and the tools
 Surge case studies:
 1 – Europe
 2 – Australia
 Conclusions and key recommendations
 Don’t forget about waves
© Crown copyright 2004
Page 2
We require credible predictions of future
changes in extreme water levels caused by
storm surges.
1. Are we able to simulate real surge events with
existing surge models driven by numerical
weather predictions or climate model
simulations of the present day?
2. Can we estimate the future (century scale) time
average local sea level?
3. Can we estimate future (century scale)
Meteorology?
© Crown copyright 2004
Page 3
Two main approaches for surges and waves
Statistical approach
1. Relationships between large-scale
driving meteorology and extreme
water levels are developed for
present day.
2. Projection made of future largescale meteorology using a climate
model.
3. Future extreme water levels
estimated from 1 and 2.


Don’t need to run dynamic storm
surge or wave model for future.
Assumes that the relationship
between the large-scale variables
and the extreme sea level remain
unchanged in a future perturbed
climate.
© Crown copyright 2004
Dynamic approach
 Physically-based models used to
simulate storm surge levels and waves in
past/present day and future periods.
Driven by tidal and meteorological (wind
stress and air pressure) forcings across
the model domain.
 Driving winds and pressure are taken
directly from atmospheric climate models
for both past/present and future periods
or large-scale climate model predictions
used to perturb reanalysis winds and
pressure.
 Do not rely on the past or present
relationship between Meteorological
drivers and surges being the same in the
future.
 May be bias even in present day.
Page 4
Surge Model
Barotropic shelf seas models: e.g. CSX/CS3, TRIMGEO, barotropic
version of POM, GCOM2D
 h
  (H q)  0
 t
q
1
1
 q q  f k  q   gh  Pa 
( s   b )  A2 q
t

H

s

sb
 C D  air u u
  q q
•h: Surface elevation
•q: Depth mean current
•tb: Stress on the sea bottom
•: Water density
•air: Air density
© Crown copyright 2004
H: The total depth
Ts: Wind stress on sea-surface
A: Coefficient of horizontal diffusion
Cd: Drag coefficients
: Friction coefficient
Page 5
Are surge models adequate?
Comparison of 40+ years hindcast
with observations from Woth et al.
studies at Cuxhaven.
RMS errors on storm surge forecasts
from 5 operational European surge
models along North sea coasts.
RMS on surge forecast: all stations
- no threshold -
rms on surge [m]
0.25
0.2
0.15
0.1
0.05
0
0-6h
bsh_oper
+simulations of Bernier and Thompson
for Canadian region (see poster)
© Crown copyright 2004
6-12 h
dmi_oper
12-24 h
dnmi_oper
knmi_noos
24 -48 h
ukmo_oper
Results courtesy of Martin Verlann RIKZ and
Martin Holt, NCOF
Page 6
 The problem and the tools
 Surge case studies:
 1 – Europe
 2 – Australia
 Conclusions and key recommendations
 Don’t forget about waves
© Crown copyright 2004
Page 7
Surge results are region specific
European
Von Storch and Reichardt (1997)
Langenberg et al. (1999)
Flather and Smith (1998)
WASA and STOWASUS
Lowe et al. (2001)
Debernard et al. (2002)
Lowe and Gregory (2005)
Woth et al. (2005) and Woth (2005)
Note: surges do occur in
other regions. The regions
highlighted in the position
paper are only a sample.
They do include NH and
SH plus tropical and midlatitude regimes.
Australia (North and South)
McInnes et al. (2003)
McInnes and Hubbert (2003)
McInnes et al. (2005)
Bay of Bengal
Flather and Khandker (1993)
Flather (1994)
As-Selek and Yasuda (1995)
Unnikrishnan et al. (2006)
Mitchell, Lowe, Wood and Vellinga (2006) + CLASIC (ongoing)
© Crown copyright 2004
Page 8
Overview of modelling system
Global coupled
model
Historic
scenario
SRES
future
scenario
Higher resolution
atmospheric model
Regional climate
model
Estimate of
mean SLR
Tide only
Generate 2x30 year
regional time slices
Barotropic storm
surge model
Surge plus tide
Results &
Statistics
© Crown copyright 2004
Page 9
Changes in 50-year storm surge height (m) due to
changes in storminess.
2080s minus present day.
A2 Scenario
© Crown copyright 2004
B2 Scenario
Page 10
Changes in 50-year water level (m) due to changes in
storminess, mean sea-level rise and vertical land movement.
2080s minus present day.
A2 Scenario
© Crown copyright 2004
B2 Scenario
Page 11
Simulated extreme water levels (m) for Immingham. 2080s
and present day. SRES A2 scenario for 2080s
2080s includes
changes in
storminess, mean
sea-level rise and
vertical land
movements.
© Crown copyright 2004
Page 12
IPCC TAR range of global sea-level rise
Include uncertainty
in ice parameters
All models
all SRES
© Crown copyright 2004
Page 13
Sea level rise regional variations
due to thermal expansion and ocean circulation changes only
Source:IPCC
© Crown copyright 2004
0
0.1
0.2
0.3
0.4
0.5
0.6
m
Page 14
Comparison of storm surge predictions (50-year surge height [m]).
Changes are due to future changes in storminess.
Lowe, Gregory and Flather, 2001
HadCM2/HadRM2
IS92a
Gumbel
© Crown copyright 2004
STOWASUS
(from R Flather, POL)
Lowe and Gregory, 2005
ECHAM4
2*CO2
GEV
HadCM3/HadAM3H/HadRM3
SRES A2
GEV
Page 15
An alternative examination of uncertainty by Woth et al.
Domain
Spread due to driving GCM and scenario
99.5th
See poster by Katja Woth
© Crown copyright 2004
Spread due to choice of
downscaling RCM was
less important
Page 16
 The problem and the tools
 Surge case studies:
 1 – Europe
 2 – Australia
 Conclusions and key recommendations
 Don’t forget about waves
© Crown copyright 2004
Page 17
Methodology + see poster by Kathy McInnes
 Historic
 Identify population of sea level events in historical record
 Model under current conditions using reanalysis plus surge model
 Future 2070
 Since storm surges are driven by mid latitude westerlies, analyse
changes in surface winds in climate models
 Range of change in wind speed determined from analysis of 13
climate models using pattern scaling technique which regresses
wind against model’s global warming signal, then scales to
temperature uncertainty range
 Changes applied as a perturbation to current climate winds and
surge model was rerun
ason
Mean Wind Speed
95th Percentile Wind Speed
nual
ter
2070
Mid
3
5
2070
Mid
3
7
Low
-5
© Crown copyright 2004
-4
High
10
14
Low
-6
-6
High
11
19
Page 18
1.2
Future (2070) extreme levels (m)
Present Climate Residuals
Low Scenario Residuals
Mid Scenario Residuals
High Scenario Residuals
High JJA Scenario Residuals
0.8
0.6
0.4
Return level (m)
1.0
Fit to
Fit to
Fit to
Fit to
Fit to
1
10
100
Return period (years)
© Crown copyright 2004
Page 19
Combining storm surge and tide using Monte-Carlo
sampling. 100 yr event.
storm surge + astronomical tide = storm tide
Further downscaled with nested higher resolution model
100 year events
At
Surge level (m)
Storm tide level
(m)
Storm tide level
(m) with wind
speed (High)
increase
Storm tide level
(m) with wind
speed increase
and SLR (49cm)
Lakes Entrance
0.71
0.98
1.07 (adds 0.09)
1.56 (adds 0.49)
Land subsidence could add a further 1 m
© Crown copyright 2004
Page 20
Modelling conclusions and recommendations
 European examples show importance of both mean sea level
change and changes in storminess for projections of future
extreme water levels. In present studies both uncertainties are
probably underestimated.
 Australian example shows dominance of mean sea level
uncertainty in projections of future extreme water levels. This
is probably underestimated – e.g. no MSL pattern information.
 The current studies do not provide information on the shape of
the uncertainty distribution. This would be useful for risk
calculations.
 The results need to be linked to credible inundation models
with knowledge of defences (where appropriate) at more sites.
© Crown copyright 2004
Page 21
Waves
 Damage coastal defences plus lead to
additional overtopping
 WASA and STOWASUS → future
increases in high waves were found in the
north eastern part of the North Atlantic but
decreases occurred further southwest.
 Correlation with the NAO (e.g. Woolf et
al., 2002). Wang et al. (2004) assumed
the relationship will continue to hold for
predictive purposes.
 Caires et al. (2006); Wang and Swail
(2006) → significant changes. Most
significant changes under the more
severe emission scenarios.
Wolf and Woolf (2006) used a dynamic wave model approach to show how
different climate change effects (e.g. increase in wind speed or change in wind
direction) are likely to alter wave conditions around the United Kingdom.
© Crown copyright 2004
Page 22

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