Extreme value analysis in typhoon
prone areas
Case study for the Pearl River Estuary
IAHR 2015
Emiel Moerman, Reimer de Graaff, Deepak Vatvani, Joao de Lima Rego
Deltares, [email protected]
8 July, 2015
Introduction
• Extreme events such as tropical storms and typhoons often are the
determining factor in the extreme values of wind, wave and water
level conditions
• Strong stochastic behavior leading to uncertainty in standard EVA
• Comparison of classic scenario based modeling versus typhoon
modeling (historic and artificial)
• Approach to better quantify the uncertainty in the extreme values
analysis in typhoon prone areas
• Case study Pearl River estuary China
8 July, 2015
Content
• Introduction
• Pearl River estuary
• Scenario based modeling (standard EVA)
• Typhoon modeling (historic + artificial)
• Comparison
• Conclusions
8 July, 2015
Pearl River estuary
• 5 to 10 tropical storms or typhoons observed every year
• Once every few years and extreme typhoon
Wanda, 1962
Ida, 1964
Ruby, 1964
Rose, 1971
Elsie, 1975
Hope, 1979
Ellen, 1983
York, 1999
Dujuan, 2003
Hagupit, 2008
Vicente, 2012
8 July, 2015
Pearl River estuary
• 5 to 10 tropical storms or typhoons observed every year
• Once every few years and extreme typhoon
Wanda, 1962
Ida, 1964
Ruby, 1964
Rose, 1971
Elsie, 1975
Hope, 1979
Ellen, 1983
York, 1999
Dujuan, 2003
Hagupit, 2008
Vicente, 2012
8 July, 2015
Extreme wave modeling
• extreme wave climate governed by local wind (limited swell)
• scenario based wave modeling (Delft3D)
• stationary modeling
• uniform extreme wind conditions + assoc. water levels
• extreme wind + waves boundary conditions from offshore
ERA-Interim hind cast data (ECMWF)
• waves associated to wind
• extreme water levels derived from long-term measurements
10-yr wind speed
with 100-yr water level
12 directional sectors with 30 degree interval
50-yr wind speed
with 50-yr water level
12 directional sectors with 30 degree interval
100-yr wind speed
with 10-yr water level
12 directional sectors with 30 degree interval
100-yr wind speed
with MLLW
12 directional sectors with 30 degree interval
conservative
8 July, 2015
Extreme wave modeling
• extreme wave climate governed by local wind (limited swell)
• scenario based wave modeling (Delft3D)
• stationary modeling
• uniform extreme wind conditions + assoc. water levels
• extreme wind + waves boundary conditions from offshore
ERA-Interim hind cast data (ECMWF)
• waves associated to wind
• extreme water levels derived from long-term measurements
10-yr wind speed
with 100-yr water level
12 directional sectors with 30 degree interval
50-yr wind speed
with 50-yr water level
12 directional sectors with 30 degree interval
100-yr wind speed
with 10-yr water level
12 directional sectors with 30 degree interval
100-yr wind speed
with MLLW
12 directional sectors with 30 degree interval
conservative
8 July, 2015
Extreme wave modeling
Classic Extreme Value Analysis:
• sample the extremes by a Peak Over Threshold method
• fit an trend line (distribution) to these extreme values (exponential)
• determine the 10, 50 and 100 year return values, including the 95%
confidence intervals (total: 4x12x3 scenarios)
8 July, 2015
Extreme water levels + currents
Extreme water levels are derived from local measurements
Extreme currents in the area are related to:
• extreme hydrodynamic processes (e.g. extreme tidal water level
variations and/or extreme river discharges) or
• extreme wind conditions (e.g. storms and typhoons)
No coincidence: wind effect relatively short (few hours) and direct: →
allows for separation in the analysis
3 scenarios applied to determine the extreme currents
Delft3D-FLOW
8 July, 2015
Extreme water levels + currents
Extreme water levels are derived from local measurements
Extreme currents in the area are related to:
• extreme hydrodynamic processes (e.g. extreme tidal water level
variations and/or extreme river discharges) or
• extreme wind conditions (e.g. storms and typhoons)
No coincidence: wind effect relatively short (few hours) and direct: →
allows for separation in the analysis
3 scenarios applied to determine the extreme currents
Delft3D-FLOW
8 July, 2015
Extreme currents
Scenario 1: Highest or Lowest Astronomical Tide (HAT or LAT)
conditions
tide related gradient between high and low water is at its maximum.
Scenario 2: Extreme river discharge conditions
dry season average: 4,100 m3/s, wet season average: 19,400 m3/s
extreme river discharge estimated at 3 or 4 times the wet season
discharge
strong relation between water level
differences and current magnitude
8 July, 2015
Extreme currents
Scenario 3: Extreme wind conditions
a combination of the tide and wind drive currents determines the total
current in the area.
wind-only simulations to determine the ‘surge current’
surge current is combined with a representative tidal current
(average wet season tidal current)
since extreme wind conditions are related to typhoons in the area,
they are not limited to a specific wind direction
omni-directional extreme wind speeds applied for each wind direction
(1, 10, 50 and 100 year extreme winds)
extreme currents from maximum of the 3 scenarios
8 July, 2015
Extreme currents
Scenario 3: Extreme wind conditions
a combination of the tide and wind drive currents determines the total
current in the area.
wind-only simulations to determine the ‘surge current’
surge current is combined with a representative tidal current
(average wet season tidal current)
since extreme wind conditions are related to typhoons in the area,
they are not limited to a specific wind direction
omni-directional extreme wind speeds applied for each wind direction
(1, 10, 50 and 100 year extreme winds)
extreme currents from maximum of the 3 scenarios
8 July, 2015
Typhoon modeling
• Extreme events such as tropical storms and typhoons often are the
determining factor in the extreme values of wind, wave and water level
conditions
• No typhoon events in ERA-interim data: need for typhoon modeling
• Stochastic behavior of typhoons: a slight variation of the typhoon track,
propagation speed or wind speed intensity can have a significant impact
on the local extreme values: need for (artificial) typhoon modeling
• Extreme values that follow from the typhoon modeling assessment are
compared against the scenario based modeling results to better
quantify the uncertainty in the extreme values analysis in typhoon prone
areas when using a scenario-based approach
8 July, 2015
Typhoon modeling
• Coupled Delft3D FLOW + WAVE model (domain decomposition)
• Offshore boundaries: astronomical components
• Time and space varying (spiderweb) wind and pressure fields
(making use of Deltares’ Wind Enhancement Scheme: WES)
• Input WES: typhoon track data:
• location of the typhoon center, maximum wind speed, distance of
the typhoon center to the maximum wind speed and the minimum
central pressure
• typhoon track data from The Hong Kong Observatory
www.hko.gov.hk/
• Hindcast of historic typhoons validated against measured wind and
water level data
• Spiderweb wind fields (WES)
8 July, 2015
Typhoon modeling
• Coupled Delft3D FLOW + WAVE model (domain decomposition)
• Offshore boundaries: astronomical components
• Time and space varying (spiderweb) wind and pressure fields
(making use of Deltares’ Wind Enhancement Scheme: WES)
• Input WES: typhoon track data:
• location of the typhoon center, maximum wind speed, distance of
the typhoon center to the maximum wind speed and the minimum
central pressure
• typhoon track data from The Hong Kong Observatory
www.hko.gov.hk/
• Hindcast of historic typhoons validated against measured wind and
water level data
• Spiderweb wind fields (WES)
8 July, 2015
Typhoon modeling
• Coupled Delft3D FLOW + WAVE model (domain decomposition)
• Offshore boundaries: astronomical components
• Time and space varying (spiderweb) wind and pressure fields
(making use of Deltares’ Wind Enhancement Scheme: WES)
• Input WES: typhoon track data:
• location of the typhoon center, maximum wind speed, distance of
the typhoon center to the maximum wind speed and the minimum
central pressure
• typhoon track data from The Hong Kong Observatory
www.hko.gov.hk/
• Hindcast of historic typhoons validated against measured wind and
water level data
• Spiderweb wind fields (WES)
8 July, 2015
Typhoon modeling- wind
wind speed wind direction
YORK, 1999
HAGUPIT, 2008
VICENTE, 2012
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Typhoon modeling – water level
water level surge
YORK, 1999
HAGUPIT, 2008
VICENTE, 2012
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Typhoon modeling - waves
Reasonable at KYC station
Overestimation at (more offshore) WLC station (coarse track data)
YORK, 1999
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Typhoon modeling - waves
DUJUAN, 2003
Reasonable at (more offshore) WLC station (coarse track data)
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Typhoon modeling - waves
HAGUPIT, 2008
Overestimation at (more offshore) WLC station (coarse track data)
Overall it is concluded that the historical typhoon model simulations are
in reasonable agreement with the (limited amount of) measurements.
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Typhoon modeling - artificial
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wave height - historic typhoons
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wave height - artificial typhoons
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water level
HA Shift track north by 0.25
HB Reduce propagation speed by 80 %
HC Increase of radius to max wind speed: 40 km
+10%
+10%
8 July, 2015
Typhoon modeling - historic
8 July, 2015
Typhoon modeling - historic
8 July, 2015
Conclusions and recommendations
• Historic typhoon simulations are generally in line with the scenario
based modeling: waves, water levels and currents
• Artificial typhoon simulations however can lead to higher extreme
values: for wave, water levels and currents
• 95% confidence intervals in the scenario-based modeling approach
generally ‘save’ the scenario-based approach
• With extreme events becoming more and more dominant in the
changing climate, the modeling of artificial typhoons is however
considered to be a valuable addition
• Model improvements and more data for validation is needed to further
assess and quantify the uncertainties in the extreme values in typhoon
prone areas