PrimaryPrimary productivity productivity of the Yellow Seaof the Yellow Sea

SinjaeSinjae YooYoo, , JisooJisoo ParkParkKORDIKORDI

AnsanAnsan, South Korea, South Korea

OutlineOutline

BackgroundsBackgrounds• Uncertainty in PP estimation in the YS• Env. characteristics

Results of our previous studyResults of our previous studyThings to consider furtherThings to consider furtherCurrent efforts & future directionsCurrent efforts & future directions

(PICES NPESR, 2004)

The Yellow Sea is the most productive sea in NP, or is it?

Primary productivity of YS Primary productivity of YS (limitation of current knowledge)(limitation of current knowledge)

Point measurements vary Point measurements vary in the range of 11.78 in the range of 11.78 ∼∼ 3,175 3,175 ㎎㎎ C mC m--22 dd--11 depending on time and depending on time and space. space. Some of Some of inin--situ estimates situ estimates on annual production on annual production are ~150 are ~150 gCgC mm--22 yy--11, which is small compared , which is small compared to fish landings.to fish landings.Uncertainty is Uncertainty is significantsignificant

~600 gC m-2 yr-1

Annual Global Primary Production(IMCS, Rutgers)

Comparison of CHL by OC4 (standard) algorithm and in-situ CHL

Some Some envenv. characteristics of the YS . characteristics of the YS Major forcing of hydrographic condition Major forcing of hydrographic condition ((GuoGuo, 1993), 1993)• Wind stress (monsoon) and heat exchange with

atmosphere• Strong tides (max. ~11 m excursion)• Fresh water input

Extreme temperature range (seasonally and Extreme temperature range (seasonally and vertically)vertically)Extreme turbidity range (Extreme turbidity range (SecchiSecchi transparency: transparency: >12 m ~ <0.2m) >12 m ~ <0.2m)

Bathymetry and vertical temp. structureBathymetry and vertical temp. structure

Xia et al. (2006)

FEB

FEB APR

APR

JUL

JUL OCT

OCT

Better algorithm is needed for:Better algorithm is needed for:

Better retrieval of CHL and KPARBetter retrieval of CHL and KPAREstimation of photosynthesis rate in extreme Estimation of photosynthesis rate in extreme turbidity range.turbidity range.Vertical structure of chlorophyllVertical structure of chlorophyll• Error of PP estimation when ignoring subsurface

chlorophyll maximum = 17.7%~30.1% (Park, 2000)

Dep

th (m

)

Chlorophyll-a (mg m-3)

Our previous approach Our previous approach (Son et al., 2005)(Son et al., 2005)

We divided the YS into three areas We divided the YS into three areas and got averages from each. and got averages from each. • P-I parameters (141 sets)• Vertical CHL profiles were parameterized

(86 profiles).Smith model (1936) was used for Smith model (1936) was used for photosynthesis.photosynthesis.KPAR was derived from nLw555KPAR was derived from nLw555Empirical local algorithm (Empirical local algorithm (AhnAhn, 2004) , 2004) was used to retrieve chlorophyllwas used to retrieve chlorophyll

y = 0.267x0.7472

R2 = 0. 5964

(this study )

y = 0.2249 x0.7269

(Son et al ., 20 05)

0 .01

0.1

1

10

0.1 1 10

SeaWi FS l evel2 nLw5 55

KP

AR

(m

-1)

Primary production in the 3 regions of the Yellow SeaPrimary production in the 3 regions of the Yellow Sea

Sub-regionArea×103

km2

Mean Primary Production Rate

mgC m-2 d-1 ×104 tonC d-1

May Sep May Sep

CCW 58.9 590.3 589.3 3.5 3.5

MYW 147.4 946.5 722.6 13.9 10.6

KCW 28.9 734.2 553.7 2.1 1.6

mean 835.6 672.4

total 235.2 19.7 15.8

Limitations of the previous studyLimitations of the previous studyEstimation was possible only for two seasons Estimation was possible only for two seasons (spring and autumn).(spring and autumn).Regions were fixed geographically but not Regions were fixed geographically but not optically.optically.• Averages of P-I parameters were used.• Averages of CHL profile parameters were used.

PP in the turbid region was not modeled PP in the turbid region was not modeled accurately.accurately.CHL algorithm needs improvements.CHL algorithm needs improvements.

Seasonal changes of KPAR (m-1)

Seasonal changes of depth-integrated PAR (mE m-2 s-1)

Two types of production systems Two types of production systems in YSin YS

TidallyTidally--mixed zonemixed zoneLight-limitedDark-adaptedTyco-pelagic species

Seasonally stratified Seasonally stratified regionregion

Nutrient-limited in the upper layerSCM production is significant

Zone-1

Zone-2

Zone-3

Zone-4

Optical characteristicsOptical characteristics

May, 1998(Yoo & Park, 1998)

PP--I curves in the turbid zone I curves in the turbid zone

Yoo & Shin (1995)

Current effortsCurrent efforts

Better parameterization of physiological Better parameterization of physiological parametersparameters• In turbid environment

More inMore in--situ measurements are planned.situ measurements are planned.• Turbid waters• Winter

Better estimation of CHL vertical structureBetter estimation of CHL vertical structureChlorophyll algorithmChlorophyll algorithm• YOC workshop (YS Ocean Color Database)

Can we retrieve/estimate CHL structure parameters Can we retrieve/estimate CHL structure parameters from surface properties (CHL, KPAR, SST)?from surface properties (CHL, KPAR, SST)?

y = 53.97x0.889

R² = 0.9081

10

100

0.01 0.1 1 10

B_t

ot (m

g m

-3)

B_pd (mg m-3)

y = 1.140x1.070

R² = 0.9170.01

0.1

1

10

0.01 0.1 1 10

B_p

d (m

g m

-3)

B0 (mg m-3)

y = 1.076x + 0.005R² = 0.764

0

0.3

0.6

0.9

1.2

1.5

0 0.5 1

B_p

d (m

g m

-3)

B0 (mg m-3)

y = 0.573x + 4.456R² = 0.664

0

10

20

30

40

50

0 20 40 60 80

Zm (m

)

Z_eu (m)

y = 1.005x + 8.365R² = 0.596

010203040506070

0 50

Z_eu

(m)

MLD (m)

y = 3.659x-0.92

R² = 0.725

05

101520253035404550

0 0.1 0.2 0.3 0.4 0.5

Zm (m

)

KPAR (m-1)

Yellow Sea Ocean Color DatabaseYellow Sea Ocean Color Database(Bio(Bio--optical measurements)optical measurements)

ChinaChina• TANG Junwu

National Satellite Ocean Application Service, SOA, Beijing

JapanJapan• KAWAMURA Hiroshi

Tohoku University• ISHIZAKA Joji

Nagasaki University

KoreaKorea• AHN Yu-Hwan, YOO Sinjae

KORDI• KIM Sang-Woo

NFRDI

Thank You!Thank You!