The effect of tropical cyclone on the The effect of tropical cyclone on the primary production enhancementprimary production enhancement-- Some results from the WSome results from the W--PASS PASS

(Western Pacific Air(Western Pacific Air--Sea interaction Sea interaction Study) projectStudy) project

PICES MONITOR/BIO Workshop 5October 27, 2007

Eko Siswanto, Joji Ishizaka, Mitsuhiro Toratani, Toru Hirawake and Sei-Ichi Saitoh

WW--PASS (Western Pacific AirPASS (Western Pacific Air--Sea interaction Study) projectSea interaction Study) project

Solas-Japan Chair: Mitsuo Uematsu

Linkages in Biogeochemical Cycles Between Surface Ocean and Lower Atmosphere

Background

The facts have been known:• Typhoon passage can enhance ocean phytoplankton

chlorophyll-a and primary production,• The northwest Pacific typhoon activities have been

known to be related to El Nino/La Nina events, but

Some information have not been documented yet, such as:

• How El Nino/La Nina events influence ocean primary production in the East China Sea through typhoon activity,

• Complete interannual and interdecadal variations in typhoon-enhanced ocean primary production,

• Estimation of typhoon contribution to summer-fall new production in the East China Sea.

Number of Typhoon per yearNumber of Typhoon per year

台風経路データ（気象業務支援センター）より

mean26.6

LiLife Time of Typhoonfe Time of Typhoon

（日

）

台風経路データ（気象業務支援センター）より

mean4.8 days

Spatial Pattern of Frequency Spatial Pattern of Frequency of Typhoon Passageof Typhoon Passage

(1951(1951--20052005））

Number of Typhoon

Study AreaStudy Area

East-China Sea

Western North Pacific

Interannual and Interdecadal Variations of Typhoon-Induced Primary Production:

A Case Study for The Outer Shelf of The East China Sea

Siswanto, E., J. Ishizaka, K. Yokouchi, K. Tanaka, C.K.Tan

Geophysical Research Letter, 34 (2007)

Study Area:• Area delineated with blue polygonal• The west border of the area (green contour)

is 0.37 mg m-3 chlorophyll-a (Chl-a) isoplethderived from summer mean SeaWiFS Chl-a

Satellite Data (1998 ~ 2004):• SeaWiFS Chl-a• SeawiFS photosynthetically available

radiation (PAR)• TRMM/TMI sea surface temperature (SST)

Typhoon Data:• 13 typhoons (red curves and circles) before

and after which clear SeaWiFS Chl-a data are available (from Japan Meteorological Agency)

• Typhoon variables: typhoon transit speed (TS) and maximum sustained wind (MSW)

Primary Production Model:• VGPM (Behrenfeld and Falkowski, 1997)

( ) irr0euBopt DChlZ

4.1PARPARP0.66125PP ×××⎥

⎦

⎤⎢⎣

⎡+

××=SST08.0e06.9=B

optP

Combined with specific PBopt model for the

ECS (Siswanto et al., 2006)

121 122 123 124 125 126 127 128 129 130

121 122 123 124 125 126 127 128 129 130

25

26

27

28

29

30

31

32

33

25

26

27

28

29

30

31

32

33

Lat

itude

(o N)

Longitude (oE)

200 m

100 m

100 m

Trajectories of 13 typhoons crossed the study area

Study Period:• Summer-fall period (June – October)

Materials and Methods

Pre- and post-typhoonSeaWiFS Chl-a images

Pre- and post-typhoonprimary productionimages

0

20

40

60

80

100

0 200 400 600 800 1000 1200

PP e

nhan

cem

ent (

Gg

C d

-1)

Mean BD (m)

0

20

40

60

80

100

0 2 4 6 8 10 12

Chl

-a (M

g) a

nd P

P (G

g C

d-1

) en

hanc

emen

ts

Mean TS (m s-1)

Sa00

Sa00

Td98 0

20

40

60

80

100

20 25 30 35 40 45 50

Chl

-a (M

g) a

nd P

P (G

g C

d-1

) e

nhan

cem

ents

Mean MSW (m s-1)

Sa00

Sa00

Td98

Chl-a, PP Enhancements Vs. Typhoon Variables, Bottom Depth (BD)

Intense typhoon (> 40 m/s)Weak typhoon (< 40 m/s)

PP enhancementChl-a enhancement

PP enhancement = -28.14 + 2.57 Mean MSW – 0.98 Mean TS – 0.04 Mean BD

0

20

40

60

80

100

0 20 40 60 80 100

Sate

llite

PP

enha

ncem

ent (

Gg

C d

-1)

Predicted PP enhancement (Gg C d-1)

Empirical relationship

R2 = 0.65, p < 0.001TS: Transit SpeedMSW: Maximum

Sustained WindBD: Bottom Depth

-7-6-5-4-3-2-101234567

Jan-

80M

ay-8

0Se

p-80

Jan-

81M

ay-8

1Se

p-81

Jan-

82M

ay-8

2Se

p-82

Jan-

83M

ay-8

3Se

p-83

Jan-

84M

ay-8

4Se

p-84

Jan-

85M

ay-8

5A

ug-8

5Se

p-85

Jan-

86M

ay-8

6Se

p-86

Jan-

87M

ay-8

7Se

p-87

Jan-

88M

ay-8

8Se

p-88

Jan-

89M

ay-8

9Se

p-89

Dec

-89

Apr

-90

Aug

-90

Dec

-90

Apr

-91

Aug

-91

Sep-

91Ja

n-92

May

-92

Sep-

92Ja

n-93

May

-93

Sep-

93Ja

n-94

May

-94

Aug

-94

Dec

-94

Apr

-95

Aug

-95

Dec

-95

Apr

-96

Aug

-96

Dec

-96

Apr

-97

Aug

-97

Nov

-97

Mar

-98

Jul-9

8O

ct-9

8Fe

b-99

Jun-

99Se

p-99

Dec

-99

Apr

-00

Aug

-00

Nov

-00

Mar

-01

Jul-0

1O

ct-0

1Fe

b-02

Jun-

02A

ug-0

2D

ec-0

2A

pr-0

3A

ug-0

3D

ec-0

3A

pr-0

4A

ug-0

4Se

p-04

Dec

-04

-70-60-50-40-30-20-10010203040506070

La Niña eventEl Niño eventPP enhancement deviation

Sout

hern

Osc

illat

ion

Inde

xPP enhancem

ent deviation (Gg

C d

-1)

In general, PP enhancements inversely oscillated with SOI

0

10

20

30

40

50

60

70

20 25 30 35 40 45Ave

rage

PP

enha

ncem

ent (

Gg

C d

-1)

Average mean MSW (m s-1)

El NinoLa Nina

PP enhancements were higher during El Nino years associated with higher MSW

0

50

100

150

200

250

300

350

400

0 1 2 3 4 5 6 7 8 9

Tota

l PP

enha

ncem

ent (

Gg

C d

-1)

Number of typhoons

El NinoLa Nina

Total PP enhancements were not related to number of typhoons

Relation to El Nino/La Nina events

Trend During the Past 25 Years

0123456789

1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

050100150200250300350400450

Number of typhoonsTotal PP enhancement

Num

ber

of ty

phoo

ns

Year

Total PP enhancem

ent (Gg

C d

-1)

Trend Observed:• During the past 25 years, the number of typhoons

has tended to increase (R = 0.48, p < 0.05),• The mean number of typhoons (red lines) during

1991-2004 period (mean ~3.9 typhoon yr-1) > during 1980-1990 period (mean ~ 2.5 typhoons yr-1),

• As a consequence, mean total PP enhancement (black lines) during 1991-2004 period (133 Gg C d-1) > during 1980-1990 period (82 Gg C d-1).

Estimates of typhoon contribution on the summer-fall new production in the study region

Mean summer-fall primary production(1998 – 2004)

Mean summer-fall new production(1998 – 2004)

f-ratio = 0.15 (Chen et al., 2003)f-ratio = 0.1 (Eppley, 1989)

Estimates of summer-fall new production

Estimates of typhoon-induced new production

Typhoon-enhanced primary production

Pre-typhoon Post-typhoon

f-ratio = 0.6

Typhoon-induced new production

Typhoon contribution to summer-fall new production was lowest in 1988 (0.4%) and highest in 2004 (39.7%) (mean 13.7%),

Typhoon contribution to summer-fall new production was also higher during El Nino years (16.7%) than during La Nina years (7.2%).

NP/PP ratio

Study AreaStudy Area

East-China Sea

Western North Pacific

Number of Typhoon in 2003 = Number of Typhoon in 2003 = 2121

Trajectory of Typhoon in 2003

Typhoon No.0317 (2003)Typhoon No.0317 (2003)

デジタル台風 北本 朝展 @ 国立情報学研究所 (NII)http://agora.ex.nii.ac.jp/digital-typhoon/summary/wnp/s/200317.html.ja

2003-10-19 ～2003-10-26Minimum Pressure 940hPaMaximum Wind Speed 46.3m/sMean Speed 4.67m/s

SeaWiFS 8days Mean Chl-aOctober 24-31, 2003

Before and After Before and After ChlChl--aa iamgesiamges

October 8-15, 2003 October 24-31, 2003

Using typhoon variables and bottom depth, PP enhancements due to typhoon passage are possible to be estimated even without satellite ocean color data,In general, because typhoons tended to be more (less) intense during El Nino (La Nina) years, typhoon-enhanced PP was also higher (lower) during El Nino (La Nina) years,Typhoon-enhanced PP has also shown a tendency to be higher during 1991-2004 period than that during 1980-1990 period,Typhoon crossing the ECS might contribute within 0.4% - 39.7% of the summer-fall new production in the study region of ECS.

Summary

Thank you