Changes of storm surge and typhoon intensities under the ... · Changes of storm surge and typhoon intensities under the future global warming ... New Orleans, 2005. 8. 30 Typhoon

Changes of storm surge and typhoon intensities under the future global warming

conditions

Il-Ju Moon & S. M. OhJeju (Cheju) National University, Korea

Storm Surge Congress 2010

Hurricanes KatrinaNew Orleans, 2005. 8. 30

Typhoon ShanShanKyushu, Japan, 2006. 9

Tropical Cyclone (TC) and Climate Change

After recent catastrophic attacks of strong hurricanes and typhoons over the world, whether the characteristics of tropical cyclones have changed or will change in a warming climate became a very interesting research subject

Knutson et al. Knutson et al. (1998, Science)(1998, Science)

Knutson et al.Knutson et al.(2010, Nature)(2010, Nature)

Bender et al.Bender et al.(2010, Science)(2010, Science)

No.

of T

C O

ccur

renc

e Category 5

Future

Agreement

Hurricane Intensity

Category 4 Category 3

Central pressure (hPa)

Although there are still a lot of arguments in this issue, now some agreements are made. One of the agreements is that future greenhouse warming will cause the globally averaged intensity of tropical cyclones to shift towards stronger storms.In the future, we will experience more frequent strong TC than present.

Present

Knutson et al. (1998)Knutson et al. (1998)

Lowe and Gregory (2005)

Change in the surge height of 50 year return period extreme water level event

Change of simulated extreme water levels at Immingham

present

future

Impacts on Storm Surge

Some results based on statistical and dynamical climate projection experiments suggested that future warm conditions will increase extreme wind speeds and this will cause an increase in surge height extreme of the same proportion (Lowe and Gregory, 2005; Woth et al., 2006; Sterl et al., 2009)

presentfuture-

[m]

Motivation and Purpose

Curiosity...

If the historical worst storm surge events happen again in the future global warming conditions

Questions...

1. How much will the storm intensity increase?

2. How much will the extreme storm surge height increase?

This allows us to estimate a possible extreme of storm surge height in the future in a certain region

Procedure of the present study

2. Constructing future climate conditions- Using results of IPCC global climate models- Extracting global warming mode using Cyclostationary EOF

1. Selecting the historical worst typhoons- Based on the highest storm surge events- Targeted region: the Korean peninsula

3. Simulating selected typhoons- under both the present and future conditions- Using WRF model

4. Simulating storm surges - Using storm surge model based on POM - Compare surge heights between present and future- Analyzing causes of the changed storm surge

Selected Two Typhoons

1. Typhoon Maemi (2003)

Records during typhoon’s landfall- Central pressure= 950hPa- Maximum wind speed = 60 m/s- Surge height = 2.16 m at Masan(the highest record in Korean history

Korea

Typhoon Maemi (2003)Typhoon Maemi (2003)▶ Strong winds and storm surge brought considerable damage to Korea

(Total property damage : about 5 billions)

Collapse of Cargo Crane (900ton) in Busan

Busan

▶ Typhoon Maemi became one of the deadliest typhoons to hit South Korea.

▶ Serious storm surge killed 117 people

Storm Surge

Typhoon Maemi (2003)Typhoon Maemi (2003)

Masan

Selected Typhoons

2. Typhoon Rusa (2002)

Record during typhoon’s landfall- Central pressure= 960hPa- Maximum wind speed = 55 m/s- Surge height = 81 cm at Seoguypo

▶ 870mm precipitation during a day : serious flooding

KimhaeKimhaeNakdong River

Typhoon Typhoon RusaRusa (2002)(2002)

▶ The most expensive typhoon in Korean history ( Total property damage : about 6 billions)

Storm surge + Flooding

▶ All the highest storm surges along the Korean coasts are recorded by Typhoon Maemi and Rusa

CSEOF Analysis of IPCC climate model results

Global warming mode Target variable: skin temp.

Predictor variables regressed on skin temp.

Selecting typhoons

Constructing future climate conditions

Flow Charts

Construction of future environments

-. Using six IPCC global climate model results based on global warming scenario (A1B)

• Mpi_echam5 : MPI: Max Planck Institute for Meteorology • Bccr_bcm2_0 : Bjerknes Centre for Climate Research • Cccma_cgcm3_1 : Canadian Centre for Climate Modeling and Analysis• Ncar_pcm1_run2 : National Center for Atmospheric Research • Mri_cgcm2_3_2a_run1 : MRI: Meteorological Research Institute, Japan • Ukmo_hadgem1 : United Kingdom Met Office

-. Extracting global warming components from climate projection results: Cyclostationaly EOF (CSEOF) analysis

• Targeted variable : Surface (skin) temperature• Predictor variables : Air pressure, Air temperature, Relative humidity,

Geopotential height, Wind at 16 levels

EOF vs. CSEOF

In EOF analysis, physical response is uniform (stationary) in time, while in CSEOF analysis, physical response characteristics is periodically time independent with a given nested period

EOF Analysis

CSEOF Analysis

=

=

ⅹ

ⅹ

1-Dimensional

Bn(t): physical process (e.g. El Niňo, seasonal cycle)Pn(t): Principal Component (PC) time series (amplitude);

same length as T(t)B(t)=B(t+d); physics is periodic, d: nested period

∑= )()()( tPtBtT nn

2-Dimensional

Bn (r,t)=Bn (r,t+d); covariance statistics (Eigen vector) is periodic

∑= )(),(),( tPtrBtrT nn

CSEOF analysis[Kim and North, 1997]

Under the assumption of cyclostationarity, extracting temporally evolving spatial patterns by modal decomposition

Skin Temperature(Surface land air temp.+SST)

Results of CSEOF Analysis

Seasonal Mode

1 2 3

4 5 6

7 8 9

10 11 12

First modeVariance (Eigen value) = 89%

• Northern and southern hemisphere shows opposite sign • PC-time series shows always positive signs. This represents a seasonal mode• Seasonal amplitude is decreasing• Temperature differences between winter and summer become smaller

Temporally evolving spatial patterns of skin temp. 1st mode

Nested period =12 months

PC time series

(100yr)

0123

-1-2-3

1

4

7

10

2

5

8

11

3

6

9

12

Global Warming Mode

Skin Temperature

Second modeVariance = 6.5%

Results of CSEOF Analysis

• Globally all are positive signs. • PC-time series is changing from negative to positive signs• Arctic and land areas show the largest increase. • In winter time, the increase is dominant

0123

-1-2-3

0

1

2

3

-1

-3

-2

((℃℃))

Skin Temp. variations due to global warming for 100 years(Based on the CSEOF second mode)

~7oC increase

()

~4oC increase

All predictor variables are regressed on the 2nd mode PC time series of the skin temperature. This allows us to produce the variation of all atmospheric variables in the future conditions, which is consistent with the variation of future skin temperature

Sea level pressure variations due to global warming for 100 years

1000 hPa Geopotential Height Variations for 100 years

(GPM(GPM))

1000 hPa Air Temperature Variations for 100 years

1000 hPa Relative Humidity Variations for 100 years

(%(%))

1000 hPa Wind Variations for 100 years

Producing future background conditions under global warming scenario (A1B) for

typhoon simulations

-. Target variable: Skin Temperature

-. Predictor variables: Air Pressure

Air Temperature

Relative Humidity

Geopotential Height

Wind

Atmosphere

16 levels (hPa)

Surface

10

30

50

70

100

150

200

250

300

400

500

600

700

850

925

1000

Future variations for all variables at 16 levels

Past conditions (NCEP/NCAR reanalysis data)+

Future background conditions




Simulating typhoons under the past conditions

Simulating typhoon under the global warming conditionsComparison

Selecting typhoons


Flow Charts

Model for typhoon simulation

WRF (Weather Research and Forecasting model)

WRF 3.1 model configuration

Horizontal Spacing 10 Km

Dimension 100 x 100 x 17

Time Step 30s

Initial Data NCEP/NCAR reanalysis FNL 1〬 x 1〬 data

Bogussing WRF 3.1 Bogussing scheme

PBL scheme YSU

Microphysics WSM 3 class

Run time1. 2003. 09. 12. 00UTC ~ 09. 13. 00UTC (24hours)

2. 2002. 08. 30. 12UTC ~ 08. 31. 18UTC (30hours)

VariablesVariables ControlControl Exp. 1Exp. 1 Exp. 2Exp. 2 Exp. 3Exp. 3 Exp. 4Exp. 4 Exp. 5Exp. 5

SST P GW GW GW GW GW

SLP P P GW P P GW

T P P GW GW P P

RH P P GW P GW P

GH P P GW P P GW

W P P GW P P GW

Experimental Designs

SST : Sea Surface Temperature

SLP : Sea Level Pressure

T : Air Temperature

RH : Relative Humidity

GH : Geopotential Height

W : Wind

P : Present Condition

GW : Global Warming Condition

-. Control Exp is conducted under present conditionsfor all variables

-. In Exp 1, future conditions are applied only for SST-. In Exp 2., future conditions are applied for all variables-. In other Exp., future conditions are applied for some variables

Typhoon Maemi (2003)Control Exp. 1

(hPa) (hPa)

Results of Typhoon simulations

Under the future SST conditions. Typhoon is more intensified

Surface wind and pressure simulation results for typhoon Maemi under 2003 real conditions

Comparison of typhoon intensity between present and future simulation for typhoon Meami (2003)

Central Pressure

Exp. 1

Control

If we use a future SST condition, the central pressure is decreased about 18 hPaduring the landfall period. This is a huge increase of typhoon intensity considering that this future SST forcing is applied only for 12 hours in this experiment

Landfallperiod

18hPa



SLP P P GW P P GW

T P P GW GW P P

RH P P GW P GW P

GH P P GW P P GW

W P P GW P P GW

Experimental Designs

SST : Sea Surface Temperature

SLP : Sea Level Pressure

T : Air Temperature

RH : Relative Humidity

GH : Geopotential Height

W : Wind

P : Present Condition

GW : Global Warming Condition-. Control Exp is conducted under present real condition

for all variables-. In Exp 1, only for SST, future conditions are applied-. In Exp 2., future conditions are applied for all variables

(hPa) (hPa)

Typhoon Maemi (2003)Control Exp. 2

Results of Typhoon simulations

Under the future conditions applied for all variables. TC intensity is not much changed

Under 2003 real conditions

Comparison of typhoon intensity between present and future simulation for typhoon Meami (2003)

Central Pressure

Exp. 1

ControlExp. 2Landfall

period

18hPa

4hPa

If we use future conditions for all variables, the central pressure is decreased only 4 hPaduring the landfall period. This is a small increase of typhoon intensity compared to the Exp. 1. The reason why this happens?

Comparison of typhoon intensity between present and future simulation for typhoon Rusa (2002)

Central Pressure

Exp. 1

Control

Exp. 2

LandfallPeriod

13hPa

5hPa

Conducting same experiments for typhoon Rusa in 2002, in Exp. 1, the central pressure is decreased about 13 hPa during the landfall period, while in Exp. 2, the pressure is decreased about 5 hPa.


Simulating typhoon under the global warming conditions

Remaking wind fields based on real track and intensity under the past conditions

Remaking wind fields only considering the intensity change

under the GW conditions

Comparison




FutureTC intensityprojection

Selecting typhoons


Flow Charts

Results of Typhoon Maemi (2003) simulationsfor control experiment

• We cannot simulate exact track and intensity for a specific typhoon due to limitation of present typhoon model although our simulations for typhoon Maemi and Rusa are very consistent with observations.

• To verify the performance of our storm surge model in the control experiment, we also need to reproduce real exact typhoon track and intensity

• So, in the control. wind and pressure fields are reproduced using best track data and Holland (1981) model. In the experiments for future conditions, we reproduced them only considering intensity change based on Exp. 1 & 2 results

Typhoon intensities adjusted to the real best track data

Maemi (2003) Rusa (2002)

Central Pressure Central Pressure

Max. Wind Speed Max. Wind Speed

Control Exp. 1

Wind and pressure fields of Typhoon Maemi (2003) adjusted to the real best track

(hPa)

Control Exp. 1 Exp. 2

(hPa)

Typhoon Rusa (2002)

Control Exp. 1

Exp. 2

(hPa)

(hPa)


Simulating typhoon under the global warming conditions

Remaking wind fields based on real track and intensity under the past conditions

Remaking wind fields only considering the intensity change

under the GW conditions

Comparison




Simulating storm surge under the past conditions

Simulating storm surge under the global warming

conditionsComparison

Futureintensity

projection

Selecting typhoons


Flow Charts

• Based on Princeton Ocean Model (POM)

• Grid resolution: 1/12º by 1/12ºfor both longitude and latitude

• Extending from 23ºN to 42ºN and from 117ºE to 132ºE

• Real-time tides are expressed by using 8 tidal constituents (M2, S2, K1, O1, K2 , N2, P1 and Q1).

Storm Surge Model

Real-time tide and storm surge prediction model

118 120 122 124 126 128 130 132Longitude [ o E]

24

26

28

30

32

34

36

38

40

42

Latit

ude

[ o N

] Yellow Sea

East China Sea

Korea

China

Japan

Taiwan

Yangtz River

Taiwan Strait

Tokara Strait

Pohai

T/K Strait

M2

S2

K1

O1

Amplitude Amplitude

Amplitude Amplitude

Phase

Phase

Phase

Phase

Verification of Tides

Observation Points

Model-predicted amplitudes and phases for major tidal components are in a good agreement with observations

Verifications of Sea Level Height (Tides + Storm Surges) during Typhoon Maemi (2003) event

TongYoung

Busan

Masan

Yeosu

Model results and observations are generally in good agreements

Control Exp. 1 Exp. 2

Sea Level Height (Storm surge + Tides) Simulations for Typhoon Maemi (2003)

(m) (m)

Comparison of storm surge between present and future conditions for typhoon Maemi (2003)

YeosuTongyoung

Busan Masan

Exp. 1: 45 cmExp. 2: 10 cm

Exp. 1: 67 cmExp. 2: 16 cm

Exp. 1: 58 cmExp. 2: 14 cm

Exp. 1: 41 cmExp. 2: 2 cm

Exp. 2

(m) (m)

(m)

Control Exp. 1

Exp. 2

Typhoon Rusa (2002)

Exp. 1: 58 cmExp. 2: 23 cm

Exp. 1: 39 cmExp. 2: 20 cm

JejuTongyoung

Mokpo Yeosu

Exp. 1: 17 cmExp. 2: 9 cm

Exp. 1: 24 cmExp. 2: 16 cm

Comparison of storm surge between present and future conditions for typhoon Rusa (2002)

Maximum increase of storm surge extreme under future climate conditions based on two typhoon’s results

67

455841

2432

5

58

17 27

16 1016

2911

3

23

9 10

EXP. 1Ave=37cm

EXP. 2Ave=11cm

Unit=[cm] Unit=[cm]

What caused the difference between EXP 1 and EXP 2?



SLP P P GW P P GW

T P P GW GW P P

RH P P GW P GW P

GH P P GW P P GW

W P P GW P P GW

Additional Experiments

P : Present Condition GW : Global Warming Condition

ResultsVariablesVariables ControlControl Exp. 1Exp. 1 Exp. 2Exp. 2 Exp. 3Exp. 3 Exp. 4Exp. 4 Exp. 5Exp. 5


SLP P P GW P P GW

T P P GW GW P P

RH P P GW P GW P

GH P P GW P P GW

W P P GW P P GW

• However, when we include future temperature conditions, the typhoon’s intensity is not much increased

EXP 3EXP 2

• Future air temperature distributions seem to provide an unfavorable condition to typhoon’s development

• SST and air temperature are major factors to affect typhoon intensity.

• For all cases, SST increase contributes to a great increase of typhoon intensity

-. Here, temperature difference between upper and lower level is important

-. Large temperature increase at top troposphere leads to reduction of vertical temp. . gradient and reduction of maximum typhoon intensity

Tem

pera

ture

Ano

mal

y (℃

)

Change of air temperature during 100 yr according to altitude

~4oC

SST increase during 100 yr

~4oC

~7oC

-. SST is increased about 4℃/100yr near the Korean peninsula (E122º - 132º, N28º - 36º)

-. Air temperature at top troposphere is more increased than surface temperature

(~ 7oC increase)

-. Based on Emanual (2005), maximum typhoon intensity can be expressed by

Vmax : Maximum wind speed Thot : Temperature of bottom troposphereTcold : Temperature of top troposphereE : Evaporative potential of the sea surface

(℃)

Temperature anomaly between present and future for other IPCC climate models

Air temperature at top troposphere is more increased than surface temperature, which is definitely unfavorable condition for TC

development

Tem

pera

ture

Ano

mal

y (℃

)

Tem

pera

ture

Ano

mal

y (℃

)

-. This study investigates the intensity change of typhoon and storm surge under the global warming conditions, which are projected by IPCC climate models based on A1B scenario.

ConclusionsConclusions

-. The CSEOF is used to produce future warming conditions based on 21st

century prediction results. For all variables, the 2nd mode shows global warming signals. Using skin temperature as a target variable, future atmospheric conditions are reproduced for all layers

-. From the numerical experiments for typhoon Maemi (0314) and Rusa(0215), we found that, when the future warmed SST is considered, the intensities are greatly increased. The central pressures were dropped about 18hPa for Maemi and 13hPa for Rusa. This results in a increase of storm surge, maximum 67cm in Masan and 58cm in Mokpo, respectively.

-. However, considering future changes for all atmospheric variables, the magnitude of typhoon intensification is much reduced.

-. This is mainly because air temperature near the top of troposphere is more increased than the surface temperature

Thank you!

Empirical Orthogonal Functions (EOF) vs. CycloStationary EOF (CSEOF)

When a independent physical system (or process) fluctuates due to an external stochastic forcing, the responses of two physical variables might be different from each other because of the different physical response characteristics of the variables. Then, the resulting evolution histories will be different between two

CSEOF Analysis Flow chart

-. Holland model made wind and pressure fields using RSMC typhoon best track

P(r) : the pressure at radius r

W(r) : the gradient wind at radius r

Holland (1981) Model

Documents

Changes of storm surge and typhoon intensities under the ... · Changes of storm surge and typhoon intensities under the future global warming ... New Orleans, 2005. 8. 30 Typhoon