Fig.3.1.1.1. 드레이크 해협 주변을 통과하는 TOPEX/Poseidon의 궤도(185Cycle을 표시), 검은 점(ㆍ)은 Track을 0.1° 간격으로 정리한 것이고, 십자표시(+)는 해당 Cycle 궤도(185 Cycle)가 겹쳐지는 부분(Crossover Point), 원형표시(O)는 전체 Cycle에 대한 Crossover Poi=18,56,1

Fig.3.1.1.2. CLS/CNES에서 합성한 해수면 고도 편차자료의 격자점(1995년 4월). 10일주기, 1/4° 수평 격자로 재편집 하였다(Grid Points Of 1/4 Degree For The Data Of Sea Surface Height Anomaly Provided By CLS/CNES)=18,56,1

Fig.3.1.1.3. CLS/CNES에서 제공하는 T/P 해수면고도편차 자료의 격자점(1995년 4월). 7일 주기, 경도 1/3° 수평격자 자료이다(Grid Points Of 1/3 Degree For The Data Of Sea Surface Height Anomaly Provided By CLS/CNES)=18,56,1

Fig.3.1.1.4. 합성된(T/P+ERS) 해수면 고도 편차(Sea Level Anomalies)를 이용하여 계산한 5.7년 동안(1995년 4월-2000년 11월)의 평균 표층해류(0.5°×0.5° 수평격자). 화살표는 해류 벡터, 회색 실선은 수심(ETOPO5, 1000m 간격)을 나타낸다(Vectors Of Mean Sea Surface=19,57,1

Fig.3.1.1.5. 합성된(T/P+ERS) 해수면 고도 편차(Sea Level Anomalies)를 이용하여 계산한 5.7년 동안(1995년 4월-2000년 11월)의 해수면 높이의 시간 변동 성분(η')(0.25°×0.25° 수평격자, 단위는 ㎝)(The Variability Of Sea Surface Height For 5.7 Years(April(Aprol=19,57,1

Fig.3.1.1.6. T/P 위성의 해수면 고도 편차(Sea Level Anomalies)를 이용하여 계산한 5.7년 동안(1995년 4월-2000년 11월)의 평균 표층해류(0.5°×0.5° 수평격자). 화살표는 해류 벡터, 회색 실선은 수심(ETOPO5, 1000m 간격)을 나타낸다(Vectors Of Mean Sea Surface Flow=20,58,1

Fig.3.1.1.7. T/P 위성의 해수면 고도 편차(Sea Level Anomalies)를 이용하여 계산한 5.7년 동안(1995년 4월-2000년 11월)의 해수면 시간 변동(η')(0.25°×0.25° 수평격자, 단위는 ㎝)(The Variability Of Sea Surface Height For 5.7 Years(April(Aprol) 1995-November 2=20,58,1

Fig.3.1.1.8. 합성된(T/P+ERS) 해수면 고도 편차(Sea Level Anomalies)를 이용하여 계산한 연평균 표층해류[(A) 1995년, (B) 1996년, (C) 1997년 (D) 1998년 (E) 1999년]. 화살표는 해류 벡터(그림 3.1.1.4.와 3.1.1.6의 스케일과 같음), 회색 실선은 수심(ETOPO5, 1000m 간=21,59,1

Fig.3.1.1.9. T/P & Jason 고도계 위성 이동궤적. 동그라미로 표시한 점은 프랑스와 공동으로 각 위치마다 500, 1000, 2000m 수심에 해류계를 2년간(2006년 1월-2008년 1월) 계류할 곳이다(The Plan Of Current Meter Mooring In Drake Passage)=21,59,1

Fig.3.1.2.1. Location Of The Bransfield Strait. Solid Line Indicates Study Region. Bottom Bathymetry Contours Are Given In Meters=23,61,1

Fig.3.1.2.2. Station Map Of The Current Moorings=23,61,1

Fig.3.1.2.3. Time Series Of Observed Current And Residual Current Vectors In The Central Basin=27,65,1

Fig.3.1.2.4. Progressive Vector Diagram And The Wavelet Analysis In The Central Basin=28,66,1

Fig.3.1.2.5. Time Series Of Observed Current And Residual Current Vectors In The Eastern Basin=29,67,1

Fig.3.1.2.6. Progressive Vector Diagram And The Wavelet Analysis In The Eastern Basin=30,68,1

Fig.3.1.2.7. The Temperature And Salinity Variations And The Wavelet Analysis In The Central Basin=32,70,1

Fig.3.1.2.8. The Temperature And Salinity Variations And The Wavelet Analysis In The Eastern Basin=33,71,1

Fig.3.1.3.1. Station Map Of 15th KORDI Antarctic Survey=43,81,1

Fig.3.1.3.2. Station Map Of 16th KORDI Antarctic Survey=43,81,1

Fig.3.1.3.3. Station Map Of 17th KORDI Antarctic Survey=43,81,1

Fig.3.1.3.4. Station Map Of 18th KORDI Antarctic Survey=44,82,1

Fig.3.1.3.5. A Radial Photosynthetron=44,82,1

Fig.3.1.3.6. Deployment Of An Ocean Color Profiler=44,82,1

Fig.3.1.3.7. 8-Day Composite SeaWiFS Chlorophyll α Image During 17, Mov.~24, Nov. In 2003=45,83,1

Fig.3.1.3.8. 8-Day Composite SeaWiFS Chlorophyll α Image During 25, Nov.~2, Dec. In 2003=45,83,1

Fig.3.1.3.9. Distribution Of Measured(In Situ) Chlorophyll α From 2003 Cruise=46,84,1

Fig.3.1.3.10. Distribution Of Nano-Sized(<20 ㎛) Fraction(%) Of Chlorophyll α In The 2003 Cruise=46,84,1

Fig.3.1.3.11. Four Types Of Vertical Profiles Of Chlorophyll α Converted From Fluorescence In The Study Area, In 2001~2004. Each Panel Represents 1) The Type With Surface Chlorophyll Maximum(Upper Left), 2) The Type With DCM's Shallower Than 50m(Upper Ri=47,85,1

Fig.3.1.3.12. The Spatial Distribution Of The Four Types Of Chlorophyll Profiles, The Details Of Types Were Mentioned In Fig. 3.1.3.11.=47,85,1

Fig.3.1.3.13. Relationship Between Temperature Minimum Depth And Chlorophyll Maximum Depth In 2001 And 2004 Cruises=48,86,1

Fig.3.1.3.14. Relationship Between Chlorophyll Maximum Depth And Surface Chlorophyll α In 2001 And 2004 Cruises=48,86,1

Fig.3.1.3.15. Relationships Between Surface Chlorophyll α(㎎ m-3) And Euphotic Depth(m) [left Panel], And Integrated Chlorophyll α(㎎ m-2 By The 1% Light Depth) [Right Panel]. At Each Panel, Gray Line Represents The Result Of Previous Study(이미지참조)=48,86,1

Fig.3.1.3.16. The Mean And Standard Deviation Of Water Column Primary Production In Each Year(㎎C m-2)(이미지참조)=49,87,1

Fig.3.1.3.17. The Mean And Standard Deviation Of Surface Chlorophyll α(㎎ m-3) And Assimilation Number(㎎C(㎎ Chl-α)-1 h-1) In Each Year(이미지참조)=49,87,1

Fig.3.1.3.18. Estimated Daily Primary Production And Yearly Primary Production Of The Southern Ocean(South To 50°S) By Using 8-Days Composites=49,87,1

Fig.3.1.3.19. Relationship Between SeaWiFS Level 3 Daily Data(Spatial Resolution Is About 9㎞) And Shipboard Measurements Of Chlorophyll α=50,88,1

Fig.3.1.3.20. Relationship Between SeaWiFS Level 2 Daily Data(Spatial Resolution Is About 1㎞) And Shipboard Measurements Of Chlorophyll α=50,88,1

Fig.3.1.3.21. Same Figure As Fig.3.1.3.20, But The Regression Was Drawn Separately For The Three Latitudinal Zones=50,88,1

Fig.3.1.3.22. Relationship Between In Situ And Retrieved Chlorophyll α In This Study(2001~2003)=51,89,1

Fig.3.1.3.23. Band Ratio(490/555) Versus In Situ Chlorophyll α In The Study Area. It Shows Underestimation Of Chlorophyll α By Standard Chlorophyll Algorithm=51,89,1

Fig.3.1.3.24. The Variations Of The Absorption Coefficients Of Phytoplankton As A Function Of The Chl-a Concentration At Five Bands. In Each Panel, Gray Line Represents Bricaud et al.'s(1995) Equation=51,89,1

Fig.3.1.3.25. Adjusted Chlorophyll Algorithm In This Study. Blue Line Represents The Best Fit Of Our Data=52,90,1

Fig.3.1.3.26. An Example Of Diagram For Estimation Of Primary Production=52,90,1

Fig.3.1.3.27. Relationship Between Directly Estimated Primary Production By Using Depth Integrated Model And Estimated Primary Production By Using Behrenfeld And Falkowski(1997)'s VGPM(Vertically Generated Production Model)(Left Panel), And Surface Temper=52,90,1

Fig.3.1.4.1. Three Maps Of The Study Area Showing The Sampling Stations Of 2001(Upper Left), 2002(Upper Right), And 2003 Cruise(Lower Left), Respectively=64,102,1

Fig.3.1.4.2. The Mean And Standard Deviation Of Water Column Primary Productivity At Each Year(㎎C m-2)(이미지참조)=64,102,1

Fig.3.1.4.3. Spatial Distributions Of PmB(㎎C(㎎ Chl a)-1 h-1), Surface Chlorophyll α(㎎ m-3), Surface Primary Production(㎎C m-3), And Water Column Primary Production(㎎C m-2) In The Study Area(이미지참조)=65,103,1

Fig.3.1.4.4. Spatial Distributions Of Surface Temperature(℃), Euphotic Depth(m), Nano(<20㎛) Size Fraction(%), And Mixed Layer Depth(m) In The Study Area=65,103,1

Fig.3.1.4.5. Profiles Whose Maximum Chlorophyll α Are Less Than 1㎎ m-3 Are Shown In The Left Panel, Which The Ones Whose Maximum Chlorophyll α Are Greater Than 1㎎ m-3 Are Shown In The Right. The Black Heavy Lines Represent The Mean Profile, Respective=66,104,1

Fig.3.1.4.6. Three Types Of Vertical Profiles Of Chlorophyll α In The Study Area, In 2001~2003. Each Panel Represents 1) There Are No SCM Peak And Mostly Chl-a Decrease To Depth(SCM Peaks Are Lower Than 105% Of Surface Chl-a)(Left), 2) The Profiles Are G=66,104,1

Fig.3.1.4.7. The Spatial Distribution Of The Three Types Of Chlorophyll Profiles, The Details Of Types Were Mentioned In Fig.3.1.4.6. Green Circles Represent The Profiles Of None SCM Peak(Type 1), Blue Circles Represent The Profiles Are Generally Uniform(=67,105,1

Fig.3.1.4.8. Relationship Between Remote And Shipboard Estimate Of Chlorophyll α. Data Were Used SeaWiFS Level 3 Daily Data(Left Panel) And SeaWiFS Level 2 Daily Data(Right Panel)=67,105,1

Fig.3.1.4.9. Same Figure As Right Panel Of Fig.3.1.4.8, But The Regression Was Drawn Separately For The Three Latitudinal Zones=68,106,1

Fig.3.1.4.10. Relationships Between Surface Chlorophyll α(㎎ m-3) And Euphotic Depth(m) [Left Panel], And Integrated Chlorophyll α(㎎ m-2 By The 1% Light Depth) [Right Panel]. At Each Panel, Gray Line Represents The Result Of Previous Study(이미지참조)=68,106,1

Fig.3.1.4.11. In Situ Primary Production(C-14 Method) Versus Primary Production By Vertically Generalized Production Model(Behrenfield And Falkowski, 1997)=68,106,1

Fig.3.1.4.12. The Relationship Of Directly Measured PoptB And Temperature. The Line Represents The Value Of Behrenfield And Falkowski's VGPM(1997)=69,107,1

Fig.3.1.4.13. Relationship Between Surface Chlorophyll α(㎎ m-3) And Water Column Primary Production(㎎C m-2 d-1). Gray Line Represents Dierssen et al.'s(2000) Equation(이미지참조)=69,107,1

Fig.3.1.4.14. Time-Series Of 8-days Composite SeaWiFS Chlorophyll α In The ROI(Region Of Interest). Left Panel Shows The Study Area And ROI. Right Panel Is The Time-Series Of 8-Days Composite Chlorophyll Concentration In The ROI Over Seven Years=69,107,1

Fig.3.1.5.1. Map Showing The Study Area. The Solid Line Shows The Surface Water Observations And The Hydrographic Transect Along 52°W. The Sites For Vertical Observations Are Indicated By Crosses(X). The Gray Line Shows The 1000m Depth Contour And The Bl=90,128,1

Fig.3.1.5.2. Vertical Sections Of Temperature(℃), (a), Salinity (b) And Potential Density(σt) (c) Along 52°W In December 2001. The Arrows Indicate The Location Of Fronts:PF(Polar Front) And SF(Scotia Front)=90,128,1

Fig.3.1.5.3. Meridional Distributions Of Salinity And Temperature(℃), (a), pCO2(μatm) (b), Total Alkalinity And Total Inorganic Carbon(μ㏖ ㎏-1) Normalized To S＝34 (c) And Nitrate+Nitrite, Phosphate And Silicate(μ㏖ ㎏-1) Normalized To S＝34 (d) In S=91,129,1

Fig.3.1.5.4. Vertical Profiles Of Temperature(℃), (a), Salinity (b), Potential Density(σt) (c), AOU(μ㏖ ㎏-1) (d), Total Inorganic Carbon(μ㏖ ㎏-1) Normalized To S＝34 (e), Nitrate+Nitrite(μ㏖ ㎏-1) Normalized To S＝34 (f), Phosphate(μ㏖ ㎏-1) Norma=91,129,1

Fig.3.1.5.5. Composite Plots Of The Deficit Of Total Inorganic Carbon Against The Deficit Of Nitrate+Nitrite (a), The Deficit Of Total Inorganiccarbon Against The Deficit Of Phosphate (b), The Deficit Of Silicate Against The Deficit Of Total Inorganic Car=92,130,1

Fig.3.1.5.6. The pCO2 Variation Due To Each Process In The Mass Balance Model(Eq.(3.1.25)) During The Winter To Observation Time, Plotted Versus The Hydrographic Stations Along 52°W=92,130,1

Fig.3.1.6.1. The Cruise Survey Areas And Survey Lines. The Polar Front Was Crossed And Surveyed 4 Times During The Study Cruise Period(December 1998). The Marked Lines, Line-01 & 02 And Line-03 Are The Lines Crossing The Front. Line-01 & 02 Was Traversed=99,137,1

Fig.3.1.6.2. The Flowing pCO2 System And TA Titration System. a) The Flowing System Is Similar To That Of Wanninkof And Thoning(1993). The Equilibrator Was Designed Based On Weiss(1981). The Fraction Of CO2 In The Equilibrated Air Sample Is Measured By LI=99,137,1

Fig.3.1.6.3. Sea Surface Temperature(T), Salinity(S), And pCO2 Variations Along The Cruise Survey Lines. a) Line-01, b) Line-02, And c) Line-03. Sea Surface T And S Fluctuated Greatly When Traversing The Polar Front. Fluctuating Pattern Of T And S Coincid=100,138,1

Fig.3.1.6.4. The Vertical Profiles Of Temperature, Salinity, And Dissolved Oxygen(DO) At The 3 Selected Stations Along The Line-03. PF-01 Was A Station North Of The Polar Front, And PF-03 Was South Of The Front, And PF-02 Was Located Between PF-01 And PF-=100,138,1

Fig.3.1.6.5. TA, TCO2, And pH Changes Along The Cruise Survey Lines In Dec. 1998. TA Values Were Almost Constant Along The Lines But, At The Southern Tip Of Line-03, A Little Bit Higher Values Were Observed. TCO2 Values Were Increasing Along The Lines To=101,139,1

Fig.3.1.6.6. Strong Variations Were Observed In Nutrient Concentrations Across The Polar Front. Silicate Concentrations Significantly Increased Toward The South As Well As Increasing Nitrate And Phosphate. Nutrients Showed Similar Fluctuating Patterns Alo=101,139,1

Fig.3.1.6.7. Surface Nitrate vs Phosphate Plots(N/P Ratio). N/P Ratios In The Surface Seawater Decreased Slightly From The North(Low Concentrations) To The South(High Concentrations). Higher Nutrient Concentrations Were Observed Along The Line-03. Lower N=101,139,1

Fig.3.1.6.8. The Relationships Between Carbonate Parameters And Nutrients In The Surface Waters Of The Cruise Survey Lines. a) Surface pCO2 vs Nutrients, b) Normalized Total CO2(NTCO2) vs Nutrients. Strong Relationships Were Found Between pCO2 And The Nut=102,140,1

Fig.3.1.6.9. The Difference Of Carbonate System Between In The Carbonate Ocean(North Of The Polar Front) And In The Silica Ocean(South Of The Polar Front), Organic Carbon Production Occurs In Both Ocean. Calcium Carbonate Formation, However, Occurs In The=103,141,1

Fig.3.2.1.1. (a) Heat Flux Pattern Diagnosed From A Run With A Restoring Boundary Condition, And (b) Its Zonal Average. The Units Are W/㎡ In Both Cases. The Pattern Shown In (a) Is Used In FLUX As The Surface Boundary Condition And That In (b) In All Oth=117,155,1

Fig.3.2.1.2. The Temporal Variation Of Total Kinetic Energy Density Obtained Through Averaged Over The Entire Basin For Each Case=117,155,1

Fig.3.2.1.3. Mean Surface Circulation And Sea Surface Temperature Distribution Patterns From FLAT=118,156,1

Fig.3.2.1.4. Evolutions Of Surface Temperature(Grey Scale Shading In 0.4℃ Interval) And Velocity Anomalies(Arrows) From FLAT Case Over The Northern Half Of The Basin. Darker Shading Means Cooler Water=119,157,1

Fig.3.2.1.5. Schematic Diagrams For The Dynamics Of The Variability. 'W' Is For A Warm Anomaly And 'C' For A Cold One. Arrows Indicates Velocity Anomalies Due To Temperature Anomalies. Here, Ty is Mean Meridional Temperature Gradient Over The Northern Par=120,158,1

Fig.3.2.1.6. Time Series Of The Vertical Distribution Of (a) Vertical Temperature Gradient(∂T/∂z) In ℃/m, (b) The Vertical Velocity Anomaly(w') In 10-5 m/s, (c) The Vertical Shear Of The Velocity Anomaly(∂w'/∂z) In 10-7/s, (d) And The Zonal(u', Shadi=120,158,1

Fig.3.2.1.7. Phase Relation Between The Maximum Of The Meridional Overturning Circulation Anomaly(Dashed Line) And The Mean North-south Temperature Difference Anomaly(Solid Line) In Arbitrary Scales=121,159,1

Fig.3.2.1.8. Evolutions Of The Meridional Overturning Streamfunction During An Oscillation Cycle=121,159,1

Fig.3.2.1.9. Mean Surface Temperature(Grey Scale Shading) And Velocity(Arrows) Distributions From Each Case Over The Northern Half Of The Basin. Darker Shading Means Cooler Water=122,160,1

Fig.3.2.1.10. Evolutions Of Surface Temperature(Grey Scale Shading In 0.4℃ Interval) And Velocity Anomalies(Arrows) From FLUX In Which The Heat Flux Shown In Fig.3.2.1.2a Is Used As The Heat Flux Boundary Condition At The Surface. Darker Shading Means Co=122,160,1

Fig.3.2.2.1. Temperature(shading) And Velocity(arrows) Distributions At The Surface Over The Northern Half Of The Basin From (a) TWO, (b) ONE, (c) HALF, And (d) QUARTER=135,173,1

Fig.3.2.2.2. Meridional Velocities At The Surface Near The Eastern Wall In Each Case=136,174,1

Fig.3.2.2.3. Sections Of Meridional Velocity(Shading) And Temperature(Contours) Along The Eastern Most Grid Point From (a) TWO, (b) ONE, (c) HALF, And (d) QUARTER(QUARETR)=137,175,1

Fig.3.2.2.4. Sections Of Zonal Velocity(Shading) And Temperature(Contours) (a) Along The Northern Most Grid Point From TWO, (b) Average Over Two, (c) Four, And (d) Eights Northern Most Grid Points From ONE, HALF, And QUARTER, Respectively=138,176,1

Fig.3.2.2.5. Distributions Of (a) Meridional And (b) Zonal Velocities Along The Eastern Most Grid Points At The Surface, And The Profiles Of (c) Vertical Velocity w And (d) w/z In The Eastern Most Grid Points At 48°N In Each Case=139,177,1

Fig.3.2.2.6. Zonal Integral Of Meridional Flow Over The Three Eastern Most Grid Points(3Dχ). The Unit Is 10³㎡/s=140,178,1

Fig.3.2.2.7. Zonal Profiles Of The Surface Meridional Velocity Near The Eastern Wall (a) Mean Over 48-51°N And (b) At 54°N=141,179,1

Fig.3.2.2.8. Comparison Of (a) Meridional Velocity At The Surface Near The Eastern Wall And (b) Vertical Velocity From HALF, ONE, And HALF-HF At 48°N=141,179,1

Fig.3.2.2.9. Meridional Velocity At The Surface Near The Eastern Boundary From HIM Results Used In PB I. The Model Is Configured Comparable To TWO=141,179,1

Fig.3.2.2.10. Meridional Overturning Streamfunction Estimated Along Depth Level Surfaces Y(y,z) From (a) TWO, (b) ONE, (c) HALF, And (d) QUARTER=142,180,1

Fig.3.2.2.11. Meridional Heat Transports From Each Case. The Dash-Dotted Line Is For TWO, Dotted For ONE, Dashed For HALF And Solid For QUARTER=142,180,1

Fig.3.2.3.1. (a) 전해양이 수심 4,000m의 평탄한 해저면을 갖는 경우, (b) Drake Passage 해역에 수심 2,500m의 해저지형이 있는 경우(Model Ocean For The Cases Of The Plat Bottom (a) With 4,000m Depth In The Whole Ocean And (b) With 4,000m Depth In The Whole Oce=143,181,1

Fig.3.2.3.2. 바람이 없는 경우, (a) 해저지형이 없는 경우와 (b) Drake 해협에 수심 2500m 해저지형이 있는 경우의 대양별 수직 Stream Function, (c) 두 경우의 차이(위:전대양, 가운데:태평양, 아래:대서양)(Distributions Of Vertical Stream Function Obtained From The=144,182,1

Fig.3.2.3.3. 바람이 없는 경우, (a) 해저지형이 없는 경우와 (b) Drake 해협에 수심 2500m 해저지형이 있는 경우의 수평 수온분포, (c) 두 경우의 차이(위:수심 200m, 아래:수심 4000m)(Horizontal Distributions Temperature Obtained From The Model Without Wind (a) For=145,183,1

Fig.3.2.3.4. 동 - 서 방향의 바람이 있는 경우, (a) 해저지형이 없는 경우와 (b) Drake 해협에 수심 2500m 해저지형이 있는 경우의 대양별 수직 Stream Function, (c) 두 경우의 차이(위:전대양, 가운데:태평양, 아래:대서양)(Distributions Of Vertical Stream Function Ob=146,184,1

Fig.3.2.3.5. 동 - 서 방향의 바람 있는 경우, (a) 해저지형이 없는 경우와 (b) Drake 해협에 수심 2500m 해저지형이 있는 경우의 수평 수온분포, (c) 두 경우의 차이(위:수심 200m, 아래:수심4000m)(Horizontal Distributions Temperature Obtained From The Model With Zon=146,184,1

Fig.3.2.3.6. (a) 바람이 없는 조건에서의 전해양 및 대양별 열수송량(바닥지형이 평평한 경우, Flat Bottom와 Drake 해협의 바닥 수심이 2,500m인 경우, Drake Passage Bottom 및 두 경우의 차이), (c) 위도에 따른 수평적인 바람 조건에서의 전해양 및 대양별 열수송량(Hea=147,185,1

Fig.3.2.4.1. 여러 가지 기후모델에 의한 지구평균 온도 변화 예측(IPCC 2001)(Global Mean Temperature Predicted By Various Climate Models(IPCC 2001))=148,186,1

Fig.3.2.4.2. 모델의 해저지형(Bathymetry In The Model)=151,189,1

Fig.3.2.4.3. 대기이산화탄소농도변화(Variation Of Atmospheric CO₂)=160,198,1

Fig.3.2.4.4. CIS9에 따른 대기이산화탄소농도증가 시나리오(Increase Of Atmospheric CO₂ Concentration Based On IPCC Scenario CIS9)=160,198,1

Fig.3.2.4.5. 2월과 8월 해수면 인산염 농도 분포(Distributions Of PO₄ In The Sea Surface In February And August)=161,199,1

Fig.3.2.4.6. 모델결과 검증에 사용된 2003년 관측선(Ship Track For CO₂ Observation In 2003)=162,200,1

Fig.3.2.4.7. 모델결과 검증에 사용된 2004년 6월(좌)과 8-9월(우) 관측선(Ship Tracks For CO₂ Observation In June 2004(Left) And August-September 2004(Right))=162,200,1

Fig.3.2.4.8. 위, 경도 1°×1°의 픽셀로 변환된 2003년도 표층 fCO₂ 관측값(위)과 모델결과(아래)의 분포(Distributions Of Sea Surface fCO₂ Based On Observation In 2003(Top) And Model Results(Bottom))=163,201,1

Fig.3.2.4.9. 2004년 6월 표층 fCO₂ 관측값의 분포(Distribution Of Sea Surface fCO₂ Observed In June 2004)=164,202,1

Fig.3.2.4.10. 2004년 8-9월 표층 fCO₂ 관측값의 분포(Distribution Of Sea Surface fCO₂ Observed In August-September 2004)=164,202,1

Fig.3.2.4.11. 표층해수 fCO₂에 대한 모델결과와 관측자료 비교(Comparisons Of Sea Surface fCO₂ Between Model Results And Observed Data)=164,202,1

Fig.3.2.4.12. 위도에 따른 모델결과와 관측자료의 fCO₂ 값의 차이(Latitudinal Difference Between Observed fCO₂ And Model Results)=165,203,1

Fig.3.2.4.13. 경도에 따른 모델결과와 관측자료의 fCO₂ 값의 차이(Longitudinal Difference Between Observed fCO₂ And Model Results)=165,203,1

Fig.3.2.4.14. 수온에 대한 모델결과와 관측자료 비교(Comparison Of Temperature Between Model Results And Observed Data)=166,204,1

Fig.3.2.4.15. 염분에 대한 모델결과와 관측자료 비교(Comparison Of Salinity Between Model Results And Observed Data)=166,204,1

Fig.3.2.4.16. fCO₂에 대한 관측과 모델결과의 차이와의 관계(Relation Between Observed fCO₂ And Model Results)=167,205,1

Fig.3.2.4.17. 대기 fCO₂에 대한 관측과 모델결과의 차이와의 관계(Relation Between Observed Atmospheric fCO₂ And Model Results)=167,205,1

Fig.3.2.4.18. 각 파라메터에 대한 관측 결과와 모델결과의 차이의 상관관계(Relation Between Observed Parameters And The Difference Between Observed fCO₂ And Model Results)=168,206,1

Fig.3.2.4.19. 인산염 관측값과 fCO₂ 모델 결과와의 상관관계(Correlation Between Observed PO₄ And Simulated fCO₂)=169,207,1

Fig.3.2.4.20. 관측된 인산염과 엽록소와의 상관관계(Correlation Between Observed PO₄ And Chlorophyll)=169,207,1

Fig.3.2.4.21. 모델과 관측값의 PO₄ 비교(Comparison Of PO₄ Between Observation And Modeling Result)=170,208,1

Fig.3.2.4.22. 위도에 따른 관측값과 모델의 PO₄ 차이(The Latitudinal Difference Of PO₄ Between Observation And Modeling Result)=170,208,1

Fig.3.2.4.23. 해양 - 대기 이산화탄소 교환량(㏖C m-2yr-1) 및 표층 수온, BIOTIC 모델 결과와 관측 결과(Air-Sea CO₂ Flux And Sea Surface Temperature Based On The Estimation From BIOTIC Model And Observation)(이미지참조)=172,210,1

Fig.3.2.4.24. 해양 - 대기 이산화탄소 교환량(㏖C m-2yr-1) BIOTIC모델 결과와 ABIOTIC 모델 결과의 연도별 비교(Air-Sea CO₂ Flux Estimated From BIOTIC And ABIOTIC Models In 1995 And 2045)(이미지참조)=172,210,1

Fig.3.2.4.25. 해양 - 대기 이산화탄소 교환량(㏖C m-2yr-1) 2045-1995(The Difference Of Air-Sea CO₂ Flux Between 2045 And 1995)(이미지참조)=173,211,1

Fig.3.2.5.1. 10m 수심에서 연평균 수온분포 (a) 1도격자모형 (b) 0.5도격자모형 (c) 관측치(Distributions Of Annual Mean Temperature At 10m Depth Based On (a) 1 Degree Grid Model, (b) 0.5 Degree Grid Model, And (c) Observation)=180,218,1

Fig.3.2.5.2. 10m 수심에서 모사된 연평균수온과 관측치의 차이 : (a) 1도격자모형-관측치, (b) 0.5도격자모형-관측치 (c) 0.5도격자모형-1도격자모형(The Difference Of Annual Mean Temperature At 10m Depth Between Model Simulation And Observation : (a) 1 Degree Gri=180,218,1

Fig.3.2.5.3. 500m 수심에서 연평균 수온분포 (a) 1도격자모형, (b) 0.5도격자모형, (c) 관측치(Distributions Of Annual Mean Temperature At 500m Depth Based On (a) 1 Degree Grid Model, (b) 0.5 Degree Grid Model, And (c) Observation)=181,219,1

Fig.3.2.5.4. 500m 수심에서 모사된 연평균수온과 관측치의 차이 : (a) 1도격자모형-관측치, (b) 0.5도격자모형-관측치 (c) 0.5도격자모형-1도격자모형(The Difference Of Annual Mean Temperature At 500m Depth Between Model Simulation And Observation : (a) 1 Degree G=181,219,1

Fig.3.2.5.5. 10m 수심에서 연평균 염분분포 (a) 1도격자모형 (b) 0.5도격자모형 (c) 관측치(Distributions Of Annual Mean Salinity At 10m Depth Based On (a) 1 Degree Grid Model, (b) 0.5 Degree Grid Model, And (c) Observation)=182,220,1

Fig.3.2.5.6. 10m 수심에서 모사된 연평균염분과 관측치의 차이 : (a) 1도격자모형-관측치, (b) 0.5도격자모형-관측치 (c) 0.5도격자모형-1도격자모형(The Difference Of Annual Mean Salinity At 10m Depth Between Model Simulation And Observation : (a) 1 Degree Grid M=182,220,1

Fig.3.2.5.7. 500m 수심에서 연평균 염분분포 (a) 1도격자모형 (b) 0.5도격자모형 (c) 관측치(Distributions Of Annual Mean Salinity At 500m Depth Based On (a) 1 Degree Grid Model, (b) 0.5 Degree Grid Model, And (c) Observation)=183,221,1

Fig.3.2.5.8. 500m 수심에서 모사된 연평균염분과 관측치의 차이 : (a) 1도격자모형-관측치, (b) 0.5도격자모형-관측치 (c) 0.5도격자모형-1도격자모형(The Difference Of Annual Mean Salinity At 500m Depth Between Model Simulation And Observation : (a) 1 Degree Grid=183,221,1

Fig.3.2.5.9. 120°E-175°E 구간 동서 평균된 태평양의 연평균 수온의 남북단면 : (a) 1도격자모형 (b) 0.5도격자모형 (c) 관측치(South-North Vertical Section Of Annual Zonal(120°-175°E) Mean Temperature In The Pacific Ocean Based On (a) 1 Degree Grid Model, (=184,222,1

Fig.3.2.5.10. 모형에서 모사된 120°E-175°E 구간 동서 평균된 태평양의 연평균수온과 관측치의 차이의 남북 단면 : (a) 1도격자모형-관측치, (b) 0.5도격자모형-관측치 (c) 0.5도격자모형-1도격자모형(South-North Section Of The Difference Between Annual Zonal(120°-=184,222,1

Fig.3.2.5.11. 75°W-20°W 구간 동서 평균된 대서양의 연평균 수온의 남북단면 : (a) 1도격자모형 (b) 0.5도격자모형 (c) 관측치(South-North Vertical Section Of Annual Zonal(75°-20°W) Mean Temperature In The Atlantic Ocean Based On (a) 1 Degree Grid Model, (b)=185,223,1

Fig.3.2.5.12. 모형에서 모사된 75°W-20°W 구간 동서 평균된 대서양의 연평균수온과 관측치의 차이의 남북 단면: (a) 1도격자모형-관측치, (b) 0.5도격자모형-관측치 (c) 0.5도격자모형-1도격자모형(South-North Section Of The Difference Between Annual Zonal(75°-20°=185,223,1

Fig.3.2.5.13. 120°E-175°E 구간 동서 평균된 태평양의 연평균 염분의 남북단면 : (a) 1도격자모형 (b) 0.5도격자모형 (c) 관측치(South-North Vertical Section Of Annual Zonal(120°-175°E) Mean Salinity In The Pacific Ocean Based On (a) 1 Degree Grid Model, (b)=186,224,1

Fig.3.2.5.14. 75°W-20°W 구간 동서 평균된 대서양의 연평균 염분의 남북 단면 : (a) 1도격자모형 (b) 0.5도격자모형 (c) 관측치(South-North Vertical Section Of Annual Zonal(75°-20°W) Mean Salinity In The Atlantic Ocean Based On (a) 1 Degree Grid Model, (b) 0=186,224,1

Fig.3.2.5.15. 연평균 수온의 연직구조: (a) 태평양(120°E-175°E, 60°S-60°N) (b) 대서양(75°W-20°W, 60°S-60°N)(Vertical Structure Of Annual Mean Temperature : (a) Pacific Ocean(120°-175°E, 60°S-60°N) And (b) Atlantic Ocean(75°-20°W, 60°S-60°N))=187,225,1

Fig.3.2.5.16. 연평균 염분의 연직구조: (a) 태평양(120°E-175°E, 60°S-60°N) (b) 대서양(75°W-20°W, 60°S-60°N)(Vertical Structure Of Annual Mean Salinity : (a) Pacific Ocean(120°-175°E, 60°S-60°N) And (b) Atlantic Ocean(75°-20°W, 60°S-60°N))=187,225,1

Fig.3.2.6.1. Schematic Diagram For Heat Fluxes In The Energy Balance Model=189,227,1

Fig.3.2.6.2. Horizontal Distributions Of Surface Air Temperature(Left) And Sea Surface Temperature(Right) From Observational Climatology(Upper) And The Model(Lower). For Observational Climatology COADS Air Temperature And Levitus94 Sea Temperature Are Use=190,228,1

Fig.3.2.6.3. Domain-Mean Annually Averaged Potential Temperature And Salinity. The Climatological Potential Temperature Are From Levitus And Boyer(1994)=191,229,1

Fig.3.2.6.4. Vertical Profiles Of Annual-And Horizontal-Mean Potential Temperature(Upper) And Salinity(Lower)=192,230,1

Fig.3.2.6.5. Latitude-Depth Sections Of Zonally Averaged Annual-Mean Potential Temperature From The OGCM Coupled Into Energy Balance Model, The OGCM With The Restoring Boundary Condition, And The Difference=193,231,1

Fig.3.2.6.6. Annual-Mean Meridional Overturning Steam-Functions(Sv) From(Upper) The OGCM Coupled Into Energy Balance Model,(Middle) The OGCM With The Restoring Boundary Condition, And(Lower) The Difference=193,231,1

Fig.3.2.7.1. POP 해양모델의 3, 6, 9, 12월 해면수온(Sea Surface Temperature In March, June, September And December From POP Ocean Model)=207,245,1

Fig.3.2.7.2. 계산 5년째 3, 6, 9, 12월의 북반구 해빙 두께 분포(m)(Sea Ice Thickness Distribution Of The Northern Hemisphere In March, June, September And December At The 5th Year Of Integration In The Sea Ice Model(m))=208,246,1

Fig.3.2.7.3. 계산 20년째 3, 6, 9, 12월의 북반구 해빙 두께 분포(m)(Sea Ice Thickness Distribution Of The Northern Hemisphere In March, June, September And December At The 20th Year Integration In The Sea Ice Model(m))=209,247,1

Fig.3.2.7.4. 계산 20년째 3, 6, 9, 12월의 남반구 해빙 두께 분포(m)(Sea Ice Thickness Distribution Of The Southern Hemisphere In March, June, September And December At The 20th Year Of Integration In The Sea Ice Model)=210,248,1

Fig.3.2.7.5. 계산 20년째 3, 6, 9, 12월의 북반구 해빙 면적 분포(백분율)(Sea Ice Area Of The Northern Hemisphere In March, June, September And December At The 20th Year Of Integration In The Sea Ice Model(%))=211,249,1

Fig.3.2.7.6. 계산 20년째 3, 6, 9, 12월의 남반구 해빙 면적 분포(백박지수 1, 2, 분율)(Sea Ice Area Of The Southern Hemisphere In March, June, September And December At The 20th Year Of Integration In The Sea Ice Model(%))=212,250,1

Fig.3.3.1.1. Comparison Between Sea Level Anomalies At T/P Crossovers(X1, X2, X3) And Thermosteric Sea Level(TSL) At Nearby Locations(P1, P2, P3). These Are Located At Southwestern End Of EJS, Ulleung Basin, And Yamato Basin, Respectively(See Fig. 1). Sho=215,253,1

Fig.3.3.1.2. Sea Level Anomaly At Stage Of The Large Phase Difference Between Northeastern Pacific And Eastern Equator Where PDO Signal Appears To Be Dominant=215,253,1

Fig.3.3.2.1. Model Domain And The Bottom Topography In The East Sea=220,258,1

Fig.3.3.2.2. Annual Mean Sea Surface Height(Unit:㎝, Left) And Current Vectors(Right) In The Surface Layer Calculated From The Climatological Run(Annual Mean Transport In The Korea Strait＝2.61 Sv)=223,261,1

Fig.3.3.2.3. Annual Mean Horizontal Transport Stream Function(Unit:Sv, Left) And The Upper 200m Heat Content(Unit:J/㎡, Right) In The Climatological Run(Annual Mean Transport In The Korea Strait＝2.61 Sv)=224,262,1

Fig.3.3.2.4. Meridional Overturning Circulation(Unit:Sv) In The East Sea From The Climatological Run(Annual Mean Transport In The Korea Strait＝2.61 Sv)=225,263,1

Fig.3.3.2.5. Zonally Averaged Annual Mean Temperature(Unit:℃, Left) And Salinity(Unit:psu, Right) Distribution From The Climatological Run(Annual Mean Transport In The Korea Strait＝2.61 Sv)=225,263,1

Fig.3.3.2.6. Mixed Layer Depth(Unit:Meter) In The February From The Climatological Run(Annual Mean Transport In The Korea Strait＝2.61 Sv)=226,264,1

Fig.3.3.2.7. Annual Mean Sea Surface Height Difference From The Climatological Run(Unit:㎝, Left) And The Current Vector(Right) At The Surface Layer In Case That The Annual Mean Transport In The Korea Strait Is Increased To 3.9 Sv=227,265,1

Fig.3.3.2.8. Horizontal Transport Stream Function(Unit:Sv. Left) And The Upper 200m Heat Content(Unit:J/㎡, Right) In Case That The Annual Mean Transport In The Korea Strait Is Increased To 3.9 Sv=228,266,1

Fig.3.3.2.9. Meridional Overturning Transport Stream Function(Unit:Sv) In Case That The Annual Mean Transport In The Korea Strait Is Increased To 3.9 Sv=229,267,1

Fig.3.3.2.10. Zonally Averaged Annual Mean Temperature(Unit:℃, Left) And Salinity(Unit:psu, Right) Difference From The Climatological Run(2.61 Sv Case) In Case That The Annual Mean Transport In The Korea Strait Is Increased To 3.9 Sv=229,267,1

Fig.3.3.2.11. Mixed Layer Depth(Unit:Meters) In February In Case That The Annual Mean Transport In The Korea Strait Is Increased To 3.9 Sv=230,268,1

Fig.3.3.2.12. Annual Mean Sea Surface Height Difference From The Climatological Run(Unit:㎝, Left) And The Current Vector(Right) At The Surface Layer In Case That The Annual Mean Transport In The Korea Strait Is Decrease To 1.3 Sv=231,269,1

Fig.3.3.2.13. Horizontal Transport Stream Function(Unit:Sv. Left) And The Upper 200m Heat Content(Unit:J/㎡, Right) In Case That The Annual Mean Transport In The Korea Strait Is Decreased To 1.3 Sv=231,269,1

Fig.3.3.2.14. Meridional Overturning Transport Stream Function(Unit:Sv) In Case That The Annual Mean Transport In The Korea Strait Is Decreased To 1.3 Sv=232,270,1

Fig.3.3.2.15. Zonally Averaged Annual Mean Temperature(Unit:℃, Left) And Salinity(Unit:psu, Right) Difference From The Climatological Run(2.61 Sv Case) In Case That The Annual Mean Transport In The Korea Strait Is Decreased To 1.3 Sv=233,271,1

Fig.3.3.2.16. Mixed Layer Depth(Unit:Meters) In February In Case That The Annual Mean Transport In The Korea Strait Is Decreased To 1.3 Sv=234,272,1

Fig.3.3.2.17. Depth-Latitude Distributions Of The Temperature Along 134°E From(Upper) EXP A0 And EXP A1(Lower) In February(Left) And August(Right)=244,282,1

Fig.3.3.2.18. Depth-Latitude Distributions Of The Temperature Along 134°E From(Upper) EXP B1 And(Lower) EXP C1 In February(Left) And August(Right)=245,283,1

Fig.3.3.2.19. Seasonal Variations Of The Sea Surface Temperature Averaged Over (a) The Northern And (b) Southern Regions=246,284,1

Fig.3.3.2.20. Seasonal Variations Of The Sea Surface Temperature Anomaly Averaged Over (a) The Northern And (b) Southern Regions=247,285,1

Fig.3.3.2.21. Mixed Layer Depths(m) From Levitus Climatology In February. White Means The Mixed Layer Depths Reaches To The Bottom=248,286,1

Fig.3.3.2.22. Mixed Layer Depths(m) From(Left) EXP B1 And(Right) EXP C1 In February. White Means The Mixed Layer Depths Reaches To The Bottom=248,286,1

Fig.3.3.3.1. Total Points That Level Survey For Land Topography Has Been Carried Out Around Cheju Island. About 1-2 Week Further Survey Seems To Be Necessary For Whole Survey Around Cheju Island To Be Completed. Red Marks Denote The Points Leveling Was Ca=249,287,1

Fig.3.3.3.2. Example For Surveying Points For Level Height Around Pyosun At Cheju. Level Measurement Was Carried Out During Ebb Tide, Which Is Clearly Seen At The Central Region Flooded=250,288,1

Fig.3.3.3.3. An Example Of The Inundation Area For 50㎝ And 100㎝ Mean Sea Level Rise At Hamdeok Beach Of Chejudo. Area Which Is 1.5m Less Than The Local Mean Sea Level(MSL) Amounts To 11,866㎡ And Level Marked By Yellow Colour. Three Green Lines Denotes=251,289,1

Fig.3.4.1.1. (a) SPDEEY와 (b) ERA 재분석 자료에서 계산된 925hPa의 평균대상 바람장. (c) SPEEDY와 ERA의 차이를 보인 것이며 음의 값은 점선으로 표시되었다(Mean Zonal Wind Fields Of 925 hPa Calculated Based On (a) SPDEEY And (b) ERA Reanalysis Data. (c) Differ=256,294,1

Fig.3.4.1.2. (a) SPEEDY에 의해 모의된 전지구 겨울철 강수량 분포 (b) CMAP 자료에서 계산된 겨울철 강수량 분포. (c) SPEEDY 대기모형의 강수량 모의결과(검은선)와 CMAP(녹색) 그리고 ERA 강수자료(빨간색)의 대상평균을 보인 것이다(Distributions Of Global Precipitat=257,295,1

Fig.3.4.1.3. (a) SPEEDY 대기모형에서 모의된 겨울 북반구 500hPa 평균 지오포텐셜 고도장(a) 및 (b) ERA 기후 평균값과 (c) 차이를 보인 것이다. (d)-(e)는 (a)-(c)와 다르게 전체 평균 고도장에서 대상 평균을 뺀 에디(eddy) 장을 보인 것이다((a) The Mean Geopotential=258,296,1

Fig.3.4.1.4. (a) 해양 - 대기 접합모델에서 모의된 적도 태평양 해수면 온도의 계절주기를 그리고 (b)는 관측결과를 보인 것이다((a) Seasonal Cycle Of Sea Surface Temperature In The Tropical Pacific Simulated In The A-OCGCM And (b) The Results Of Observation.)=262,300,1

Fig.3.4.1.5. 왼쪽 그림은 해양 - 대기 결합모델에서 모의된 적도 태평양(120°E-90°W) 지방에서의 해수면 온도 편차의 시간 - 경도분포도. (b) 최근 50년간(1953-2002) 관측된 적도 해수면 온도편차의 변동성. 모델결과와 관측 값 모두 해수면 온도편차는 2°N-2°S에서 평=263,301,1

Fig.3.4.1.6. 해양 - 대기 접합모델의 초기 구동결과를 보여주는 것으로서 모델 내에서 모의된 전 지구(78°N-75°S, 0-360°E) 해수면 온도의 시계열을 보인 것이다(Time Series Of Global(78°N-75°S, 0-360°E) Sea Surface Temperature Obtained From A Primary A-OCGCM=264,302,1

Fig.3.4.3.1. Maps Of The Standard Deviation Of SSTA Variability Simulated In The Control Run (a), Exp1 (b) And Exp2 (c) For The Analyzed Period Of Each Run. Contour Interval Is 0.1C=278,316,1

Fig.3.4.3.2. Power Spectra Of The Observed NINO3 SST Index (a) And Simulated NINO3 SST Index In The Control Run (b), Exp1 (c) And Exp2 (d). The Solid Curve Shows The Power Spectra And The Long-Dashed Curve Shows The Power Spectra For Red Noise=278,316,1

Fig.3.4.3.3. Probability Density Function For The Monthly NINO3 SST Index Simulated In The Control Run(Thick Solid), Exp1(Thin Solid) And Exp2(Dashed). STD Indicates Standard Deviation=279,317,1

Fig.3.4.3.4. Ratio Of Standard Deviations(Control/Exp2) For Rainfall Variability During JJAS. Shading Is Above 1.0=279,317,1

Fig.3.4.3.5. The Regression Coefficients Between The Indian Ocean SSTAs And NINO3 SST Index In Observations During Periods Of 1950-2000 (a), (b), (c) As In (a) Except For Exp1 And Exp2 For The Entire Analyzed Period. Contour Interval Is 0.02 And Shading I=280,318,1

Fig.3.4.3.6. Power Spectra Of The Simulated Monthly Indian Monsoon Rainfall Anomaly In The Control Run (a) And Exp2 (b). The Solid Curve Shows The Power Spectra And The Long-Dashed Curve Shows The Power Spectra For Red Noise=280,318,1

Fig.3.4.3.7. The Linear Regression Coefficients Between The Indian Monsoon Rainfall Index And Zonal Wind Stress Anomalies Simulated In The Control Run (a) And Exp2 (b) For The Entire Analyzed Period. Contour Interval Is 0.02(dy/㎠*day/㎜)), Dashed Indicat=281,319,1

Fig.3.4.3.8. Precipitation(Shading) And Lower Tropospheric Zonal Wind(Contour) Response To The Imposed North Indian Ocean SST Anomalies(Inserted Plot) Derived From The Simple Atmosphere Model. The Contour Interval Is 0.1m/s For Zonal Wind And 0.2℃ For SS=281,319,1

jpg

Fig.3.1.3.7. 8-Day Composite SeaWiFS Chlorophyll α Image During 17, Mov.~24, Nov. In 2003=45,83,1

Fig.3.1.3.8. 8-Day Composite SeaWiFS Chlorophyll α Image During 25, Nov.~2, Dec. In 2003=45,83,1

Fig.3.1.3.9. Distribution Of Measured(In Situ) Chlorophyll α From 2003 Cruise=46,84,1

Fig.3.1.3.10. Distribution Of Nano-Sized(<20 ㎛) Fraction(%) Of Chlorophyll α In The 2003 Cruise=46,84,1

Fig.3.1.3.11. Four Types Of Vertical Profiles Of Chlorophyll α Converted From Fluorescence In The Study Area, In 2001~2004. Each Panel Represents 1) The Type With Surface Chlorophyll Maximum(Upper Left), 2) The Type With DCM's Shallower Than 50m(Upper Ri=47,85,1

Fig.3.1.3.12. The Spatial Distribution Of The Four Types Of Chlorophyll Profiles, The Details Of Types Were Mentioned In Fig. 3.1.3.11.=47,85,1

Fig.3.1.4.3. Spatial Distributions Of PmB(㎎C(㎎ Chl a)-1 h-1), Surface Chlorophyll α(㎎ m-3), Surface Primary Production(㎎C m-3), And Water Column Primary Production(㎎C m-2) In The Study Area(이미지참조)=65,103,1

Fig.3.1.4.4. Spatial Distributions Of Surface Temperature(℃), Euphotic Depth(m), Nano(<20㎛) Size Fraction(%), And Mixed Layer Depth(m) In The Study Area=65,103,1

Fig.3.1.5.2. Vertical Sections Of Temperature(℃), (a), Salinity (b) And Potential Density(σt) (c) Along 52°W In December 2001. The Arrows Indicate The Location Of Fronts:PF(Polar Front) And SF(Scotia Front)=90,128,1

Fig.3.1.5.6. The pCO2 Variation Due To Each Process In The Mass Balance Model(Eq.(3.1.25)) During The Winter To Observation Time, Plotted Versus The Hydrographic Stations Along 52°W=92,130,1

Fig.3.2.1.3. Mean Surface Circulation And Sea Surface Temperature Distribution Patterns From FLAT=118,156,1

Fig.3.2.1.4. Evolutions Of Surface Temperature(Grey Scale Shading In 0.4℃ Interval) And Velocity Anomalies(Arrows) From FLAT Case Over The Northern Half Of The Basin. Darker Shading Means Cooler Water=119,157,1

Fig.3.2.1.5. Schematic Diagrams For The Dynamics Of The Variability. 'W' Is For A Warm Anomaly And 'C' For A Cold One. Arrows Indicates Velocity Anomalies Due To Temperature Anomalies. Here, Ty is Mean Meridional Temperature Gradient Over The Northern Par=120,158,1

Fig.3.2.1.6. Time Series Of The Vertical Distribution Of (a) Vertical Temperature Gradient(∂T/∂z) In ℃/m, (b) The Vertical Velocity Anomaly(w') In 10-5 m/s, (c) The Vertical Shear Of The Velocity Anomaly(∂w'/∂z) In 10-7/s, (d) And The Zonal(u', Shadi=120,158,1

Fig.3.2.1.9. Mean Surface Temperature(Grey Scale Shading) And Velocity(Arrows) Distributions From Each Case Over The Northern Half Of The Basin. Darker Shading Means Cooler Water=122,160,1

Fig.3.2.1.10. Evolutions Of Surface Temperature(Grey Scale Shading In 0.4℃ Interval) And Velocity Anomalies(Arrows) From FLUX In Which The Heat Flux Shown In Fig.3.2.1.2a Is Used As The Heat Flux Boundary Condition At The Surface. Darker Shading Means Co=122,160,1

Fig.3.2.2.1. Temperature(shading) And Velocity(arrows) Distributions At The Surface Over The Northern Half Of The Basin From (a) TWO, (b) ONE, (c) HALF, And (d) QUARTER=135,173,1

Fig.3.2.2.3. Sections Of Meridional Velocity(Shading) And Temperature(Contours) Along The Eastern Most Grid Point From (a) TWO, (b) ONE, (c) HALF, And (d) QUARTER(QUARETR)=137,175,1

Fig.3.2.2.4. Sections Of Zonal Velocity(Shading) And Temperature(Contours) (a) Along The Northern Most Grid Point From TWO, (b) Average Over Two, (c) Four, And (d) Eights Northern Most Grid Points From ONE, HALF, And QUARTER, Respectively=138,176,1

Fig.3.2.3.2. 바람이 없는 경우, (a) 해저지형이 없는 경우와 (b) Drake 해협에 수심 2500m 해저지형이 있는 경우의 대양별 수직 Stream Function, (c) 두 경우의 차이(위:전대양, 가운데:태평양, 아래:대서양)(Distributions Of Vertical Stream Function Obtained From The=144,182,1

Fig.3.2.3.3. 바람이 없는 경우, (a) 해저지형이 없는 경우와 (b) Drake 해협에 수심 2500m 해저지형이 있는 경우의 수평 수온분포, (c) 두 경우의 차이(위:수심 200m, 아래:수심 4000m)(Horizontal Distributions Temperature Obtained From The Model Without Wind (a) For=145,183,1

Fig.3.2.3.4. 동 - 서 방향의 바람이 있는 경우, (a) 해저지형이 없는 경우와 (b) Drake 해협에 수심 2500m 해저지형이 있는 경우의 대양별 수직 Stream Function, (c) 두 경우의 차이(위:전대양, 가운데:태평양, 아래:대서양)(Distributions Of Vertical Stream Function Ob=146,184,1

Fig.3.2.3.5. 동 - 서 방향의 바람 있는 경우, (a) 해저지형이 없는 경우와 (b) Drake 해협에 수심 2500m 해저지형이 있는 경우의 수평 수온분포, (c) 두 경우의 차이(위:수심 200m, 아래:수심4000m)(Horizontal Distributions Temperature Obtained From The Model With Zon=146,184,1

Fig.3.2.4.1. 여러 가지 기후모델에 의한 지구평균 온도 변화 예측(IPCC 2001)(Global Mean Temperature Predicted By Various Climate Models(IPCC 2001))=148,186,1

Fig.3.2.4.2. 모델의 해저지형(Bathymetry In The Model)=151,189,1

Fig.3.2.4.5. 2월과 8월 해수면 인산염 농도 분포(Distributions Of PO₄ In The Sea Surface In February And August)=161,199,1

Fig.3.2.4.6. 모델결과 검증에 사용된 2003년 관측선(Ship Track For CO₂ Observation In 2003)=162,200,1

Fig.3.2.4.7. 모델결과 검증에 사용된 2004년 6월(좌)과 8-9월(우) 관측선(Ship Tracks For CO₂ Observation In June 2004(Left) And August-September 2004(Right))=162,200,1

Fig.3.2.4.8. 위, 경도 1°×1°의 픽셀로 변환된 2003년도 표층 fCO₂ 관측값(위)과 모델결과(아래)의 분포(Distributions Of Sea Surface fCO₂ Based On Observation In 2003(Top) And Model Results(Bottom))=163,201,1

Fig.3.2.4.9. 2004년 6월 표층 fCO₂ 관측값의 분포(Distribution Of Sea Surface fCO₂ Observed In June 2004)=164,202,1

Fig.3.2.4.10. 2004년 8-9월 표층 fCO₂ 관측값의 분포(Distribution Of Sea Surface fCO₂ Observed In August-September 2004)=164,202,1

Fig.3.2.4.11. 표층해수 fCO₂에 대한 모델결과와 관측자료 비교(Comparisons Of Sea Surface fCO₂ Between Model Results And Observed Data)=164,202,1

Fig.3.2.4.23. 해양 - 대기 이산화탄소 교환량(㏖C m-2yr-1) 및 표층 수온, BIOTIC 모델 결과와 관측 결과(Air-Sea CO₂ Flux And Sea Surface Temperature Based On The Estimation From BIOTIC Model And Observation)(이미지참조)=172,210,1

Fig.3.2.4.24. 해양 - 대기 이산화탄소 교환량(㏖C m-2yr-1) BIOTIC모델 결과와 ABIOTIC 모델 결과의 연도별 비교(Air-Sea CO₂ Flux Estimated From BIOTIC And ABIOTIC Models In 1995 And 2045)(이미지참조)=172,210,1

Fig.3.2.4.25. 해양 - 대기 이산화탄소 교환량(㏖C m-2yr-1) 2045-1995(The Difference Of Air-Sea CO₂ Flux Between 2045 And 1995)(이미지참조)=173,211,1

Fig.3.2.5.1. 10m 수심에서 연평균 수온분포 (a) 1도격자모형 (b) 0.5도격자모형 (c) 관측치(Distributions Of Annual Mean Temperature At 10m Depth Based On (a) 1 Degree Grid Model, (b) 0.5 Degree Grid Model, And (c) Observation)=180,218,1

Fig.3.2.5.2. 10m 수심에서 모사된 연평균수온과 관측치의 차이 : (a) 1도격자모형-관측치, (b) 0.5도격자모형-관측치 (c) 0.5도격자모형-1도격자모형(The Difference Of Annual Mean Temperature At 10m Depth Between Model Simulation And Observation : (a) 1 Degree Gri=180,218,1

Fig.3.2.5.3. 500m 수심에서 연평균 수온분포 (a) 1도격자모형, (b) 0.5도격자모형, (c) 관측치(Distributions Of Annual Mean Temperature At 500m Depth Based On (a) 1 Degree Grid Model, (b) 0.5 Degree Grid Model, And (c) Observation)=181,219,1

Fig.3.2.5.4. 500m 수심에서 모사된 연평균수온과 관측치의 차이 : (a) 1도격자모형-관측치, (b) 0.5도격자모형-관측치 (c) 0.5도격자모형-1도격자모형(The Difference Of Annual Mean Temperature At 500m Depth Between Model Simulation And Observation : (a) 1 Degree G=181,219,1

Fig.3.2.5.5. 10m 수심에서 연평균 염분분포 (a) 1도격자모형 (b) 0.5도격자모형 (c) 관측치(Distributions Of Annual Mean Salinity At 10m Depth Based On (a) 1 Degree Grid Model, (b) 0.5 Degree Grid Model, And (c) Observation)=182,220,1

Fig.3.2.5.6. 10m 수심에서 모사된 연평균염분과 관측치의 차이 : (a) 1도격자모형-관측치, (b) 0.5도격자모형-관측치 (c) 0.5도격자모형-1도격자모형(The Difference Of Annual Mean Salinity At 10m Depth Between Model Simulation And Observation : (a) 1 Degree Grid M=182,220,1

Fig.3.2.5.7. 500m 수심에서 연평균 염분분포 (a) 1도격자모형 (b) 0.5도격자모형 (c) 관측치(Distributions Of Annual Mean Salinity At 500m Depth Based On (a) 1 Degree Grid Model, (b) 0.5 Degree Grid Model, And (c) Observation)=183,221,1

Fig.3.2.5.8. 500m 수심에서 모사된 연평균염분과 관측치의 차이 : (a) 1도격자모형-관측치, (b) 0.5도격자모형-관측치 (c) 0.5도격자모형-1도격자모형(The Difference Of Annual Mean Salinity At 500m Depth Between Model Simulation And Observation : (a) 1 Degree Grid=183,221,1

Fig.3.2.5.9. 120°E-175°E 구간 동서 평균된 태평양의 연평균 수온의 남북단면 : (a) 1도격자모형 (b) 0.5도격자모형 (c) 관측치(South-North Vertical Section Of Annual Zonal(120°-175°E) Mean Temperature In The Pacific Ocean Based On (a) 1 Degree Grid Model, (=184,222,1

Fig.3.2.5.10. 모형에서 모사된 120°E-175°E 구간 동서 평균된 태평양의 연평균수온과 관측치의 차이의 남북 단면 : (a) 1도격자모형-관측치, (b) 0.5도격자모형-관측치 (c) 0.5도격자모형-1도격자모형(South-North Section Of The Difference Between Annual Zonal(120°-=184,222,1

Fig.3.2.5.11. 75°W-20°W 구간 동서 평균된 대서양의 연평균 수온의 남북단면 : (a) 1도격자모형 (b) 0.5도격자모형 (c) 관측치(South-North Vertical Section Of Annual Zonal(75°-20°W) Mean Temperature In The Atlantic Ocean Based On (a) 1 Degree Grid Model, (b)=185,223,1

Fig.3.2.5.12. 모형에서 모사된 75°W-20°W 구간 동서 평균된 대서양의 연평균수온과 관측치의 차이의 남북 단면: (a) 1도격자모형-관측치, (b) 0.5도격자모형-관측치 (c) 0.5도격자모형-1도격자모형(South-North Section Of The Difference Between Annual Zonal(75°-20°=185,223,1

Fig.3.2.6.2. Horizontal Distributions Of Surface Air Temperature(Left) And Sea Surface Temperature(Right) From Observational Climatology(Upper) And The Model(Lower). For Observational Climatology COADS Air Temperature And Levitus94 Sea Temperature Are Use=190,228,1

Fig.3.2.6.5. Latitude-Depth Sections Of Zonally Averaged Annual-Mean Potential Temperature From The OGCM Coupled Into Energy Balance Model, The OGCM With The Restoring Boundary Condition, And The Difference=193,231,1

Fig.3.2.6.6. Annual-Mean Meridional Overturning Steam-Functions(Sv) From(Upper) The OGCM Coupled Into Energy Balance Model,(Middle) The OGCM With The Restoring Boundary Condition, And(Lower) The Difference=193,231,1

Fig.3.2.7.1. POP 해양모델의 3, 6, 9, 12월 해면수온(Sea Surface Temperature In March, June, September And December From POP Ocean Model)=207,245,1

Fig.3.2.7.2. 계산 5년째 3, 6, 9, 12월의 북반구 해빙 두께 분포(m)(Sea Ice Thickness Distribution Of The Northern Hemisphere In March, June, September And December At The 5th Year Of Integration In The Sea Ice Model(m))=208,246,1

Fig.3.2.7.3. 계산 20년째 3, 6, 9, 12월의 북반구 해빙 두께 분포(m)(Sea Ice Thickness Distribution Of The Northern Hemisphere In March, June, September And December At The 20th Year Integration In The Sea Ice Model(m))=209,247,1

Fig.3.2.7.4. 계산 20년째 3, 6, 9, 12월의 남반구 해빙 두께 분포(m)(Sea Ice Thickness Distribution Of The Southern Hemisphere In March, June, September And December At The 20th Year Of Integration In The Sea Ice Model)=210,248,1

Fig.3.2.7.5. 계산 20년째 3, 6, 9, 12월의 북반구 해빙 면적 분포(백분율)(Sea Ice Area Of The Northern Hemisphere In March, June, September And December At The 20th Year Of Integration In The Sea Ice Model(%))=211,249,1

Fig.3.2.7.6. 계산 20년째 3, 6, 9, 12월의 남반구 해빙 면적 분포(백박지수 1, 2, 분율)(Sea Ice Area Of The Southern Hemisphere In March, June, September And December At The 20th Year Of Integration In The Sea Ice Model(%))=212,250,1

Fig.3.3.1.2. Sea Level Anomaly At Stage Of The Large Phase Difference Between Northeastern Pacific And Eastern Equator Where PDO Signal Appears To Be Dominant=215,253,1

Fig.3.3.2.1. Model Domain And The Bottom Topography In The East Sea=220,258,1

Fig.3.3.2.2. Annual Mean Sea Surface Height(Unit:㎝, Left) And Current Vectors(Right) In The Surface Layer Calculated From The Climatological Run(Annual Mean Transport In The Korea Strait＝2.61 Sv)=223,261,1

Fig.3.3.2.3. Annual Mean Horizontal Transport Stream Function(Unit:Sv, Left) And The Upper 200m Heat Content(Unit:J/㎡, Right) In The Climatological Run(Annual Mean Transport In The Korea Strait＝2.61 Sv)=224,262,1

Fig.3.3.2.4. Meridional Overturning Circulation(Unit:Sv) In The East Sea From The Climatological Run(Annual Mean Transport In The Korea Strait＝2.61 Sv)=225,263,1

Fig.3.3.2.5. Zonally Averaged Annual Mean Temperature(Unit:℃, Left) And Salinity(Unit:psu, Right) Distribution From The Climatological Run(Annual Mean Transport In The Korea Strait＝2.61 Sv)=225,263,1

Fig.3.3.2.6. Mixed Layer Depth(Unit:Meter) In The February From The Climatological Run(Annual Mean Transport In The Korea Strait＝2.61 Sv)=226,264,1

Fig.3.3.2.7. Annual Mean Sea Surface Height Difference From The Climatological Run(Unit:㎝, Left) And The Current Vector(Right) At The Surface Layer In Case That The Annual Mean Transport In The Korea Strait Is Increased To 3.9 Sv=227,265,1

Fig.3.3.2.8. Horizontal Transport Stream Function(Unit:Sv. Left) And The Upper 200m Heat Content(Unit:J/㎡, Right) In Case That The Annual Mean Transport In The Korea Strait Is Increased To 3.9 Sv=228,266,1

Fig.3.3.2.9. Meridional Overturning Transport Stream Function(Unit:Sv) In Case That The Annual Mean Transport In The Korea Strait Is Increased To 3.9 Sv=229,267,1

Fig.3.3.2.10. Zonally Averaged Annual Mean Temperature(Unit:℃, Left) And Salinity(Unit:psu, Right) Difference From The Climatological Run(2.61 Sv Case) In Case That The Annual Mean Transport In The Korea Strait Is Increased To 3.9 Sv=229,267,1

Fig.3.3.2.11. Mixed Layer Depth(Unit:Meters) In February In Case That The Annual Mean Transport In The Korea Strait Is Increased To 3.9 Sv=230,268,1

Fig.3.3.2.12. Annual Mean Sea Surface Height Difference From The Climatological Run(Unit:㎝, Left) And The Current Vector(Right) At The Surface Layer In Case That The Annual Mean Transport In The Korea Strait Is Decrease To 1.3 Sv=231,269,1

Fig.3.3.2.13. Horizontal Transport Stream Function(Unit:Sv. Left) And The Upper 200m Heat Content(Unit:J/㎡, Right) In Case That The Annual Mean Transport In The Korea Strait Is Decreased To 1.3 Sv=231,269,1

Fig.3.3.2.14. Meridional Overturning Transport Stream Function(Unit:Sv) In Case That The Annual Mean Transport In The Korea Strait Is Decreased To 1.3 Sv=232,270,1

Fig.3.3.2.15. Zonally Averaged Annual Mean Temperature(Unit:℃, Left) And Salinity(Unit:psu, Right) Difference From The Climatological Run(2.61 Sv Case) In Case That The Annual Mean Transport In The Korea Strait Is Decreased To 1.3 Sv=233,271,1

Fig.3.3.2.16. Mixed Layer Depth(Unit:Meters) In February In Case That The Annual Mean Transport In The Korea Strait Is Decreased To 1.3 Sv=234,272,1

Fig.3.3.2.21. Mixed Layer Depths(m) From Levitus Climatology In February. White Means The Mixed Layer Depths Reaches To The Bottom=248,286,1

Fig.3.3.2.22. Mixed Layer Depths(m) From(Left) EXP B1 And(Right) EXP C1 In February. White Means The Mixed Layer Depths Reaches To The Bottom=248,286,1

Fig.3.4.1.1. (a) SPDEEY와 (b) ERA 재분석 자료에서 계산된 925hPa의 평균대상 바람장. (c) SPEEDY와 ERA의 차이를 보인 것이며 음의 값은 점선으로 표시되었다(Mean Zonal Wind Fields Of 925 hPa Calculated Based On (a) SPDEEY And (b) ERA Reanalysis Data. (c) Differ=256,294,1

Fig.3.4.1.2. (a) SPEEDY에 의해 모의된 전지구 겨울철 강수량 분포 (b) CMAP 자료에서 계산된 겨울철 강수량 분포. (c) SPEEDY 대기모형의 강수량 모의결과(검은선)와 CMAP(녹색) 그리고 ERA 강수자료(빨간색)의 대상평균을 보인 것이다(Distributions Of Global Precipitat=257,295,1

Fig.3.4.1.3. (a) SPEEDY 대기모형에서 모의된 겨울 북반구 500hPa 평균 지오포텐셜 고도장(a) 및 (b) ERA 기후 평균값과 (c) 차이를 보인 것이다. (d)-(e)는 (a)-(c)와 다르게 전체 평균 고도장에서 대상 평균을 뺀 에디(eddy) 장을 보인 것이다((a) The Mean Geopotential=258,296,1

Fig.3.4.1.4. (a) 해양 - 대기 접합모델에서 모의된 적도 태평양 해수면 온도의 계절주기를 그리고 (b)는 관측결과를 보인 것이다((a) Seasonal Cycle Of Sea Surface Temperature In The Tropical Pacific Simulated In The A-OCGCM And (b) The Results Of Observation.)=262,300,1

Fig.3.4.1.5. 왼쪽 그림은 해양 - 대기 결합모델에서 모의된 적도 태평양(120°E-90°W) 지방에서의 해수면 온도 편차의 시간 - 경도분포도. (b) 최근 50년간(1953-2002) 관측된 적도 해수면 온도편차의 변동성. 모델결과와 관측 값 모두 해수면 온도편차는 2°N-2°S에서 평=263,301,1

Fig.3.4.3.4. Ratio Of Standard Deviations(Control/Exp2) For Rainfall Variability During JJAS. Shading Is Above 1.0=279,317,1

Fig.3.4.3.5. The Regression Coefficients Between The Indian Ocean SSTAs And NINO3 SST Index In Observations During Periods Of 1950-2000 (a), (b), (c) As In (a) Except For Exp1 And Exp2 For The Entire Analyzed Period. Contour Interval Is 0.02 And Shading I=280,318,1

Fig.3.4.3.7. The Linear Regression Coefficients Between The Indian Monsoon Rainfall Index And Zonal Wind Stress Anomalies Simulated In The Control Run (a) And Exp2 (b) For The Entire Analyzed Period. Contour Interval Is 0.02(dy/㎠*day/㎜)), Dashed Indicat=281,319,1

Fig.3.4.3.8. Precipitation(Shading) And Lower Tropospheric Zonal Wind(Contour) Response To The Imposed North Indian Ocean SST Anomalies(Inserted Plot) Derived From The Simple Atmosphere Model. The Contour Interval Is 0.1m/s For Zonal Wind And 0.2℃ For SS=281,319,1

Figure3. Nine Year Trend Of Sea Level In The Southern East/Japan Sea From TOPEX/Poseidon Altimeter Data=316,354,1

Figure7. Vertical Temperature Profiles At All Stations Inside The 1˚×1˚ UB Box(Figure 1) During June And August For The 3 Years 1996, 1998, And 2000=319,357,1