목차
[표제지 등]=0,1,2
연구보고서=0,3,1
목차=i,4,2
Contents=iii,6,2
List Of Figures=v,8,4
List Of Tables=ix,12,2
요약문=xi,14,3
Summary=xiv,17,3
제1장 서론=1,20,3
제2장 기상연구소 3개월 예측 시스템 운영 및 개선=4,23,1
제1절 기상연구소 3개월 예측 시스템 시험 운영=4,23,1
1. 기상연구소 3개월 예측 시스템 개요=4,23,4
2. 기상연구소 3개월 예측시스템의 시험 운영 결과=8,27,13
3. 기상청 현업 계절예보 지원=21,40,13
제2절 기상연구소 3개월 예측시스템 개선=34,53,1
1. 계절 예측의 표준 검증 시스템 구축=34,53,20
2. 기후모델의 새로운 격자체계에 대한 기초 연구=54,73,9
제3장 해수온도의 변동이 동아시아 계절 예측에 미치는 영향=63,82,1
제1절 해수온도의 계절안 변동이 동아시아 국지 기후에 미치는 영향=63,82,1
1. 서론=63,82,2
2. 중위도 대기 순환에 영향을 미치는 열대 SST 강제력=64,83,3
3. 사용된 수치모델과 Rossby Wave 전파의 형태 분류=67,86,5
4. 모델 결과 및 토의=71,90,10
5. 종합 정리 및 결론=80,99,2
제2절 북서태평양 지역의 계절안 변동성=82,101,3
제3절 동아시아 기후의 장주기변동의 특징과 해양의 영향=85,104,1
1. 우리나라장주기변동에 영향을 주는 아시아대륙 대기장주기변동의 특징=85,104,15
2. 해수면온도의장주기 변동에 따른 METRl AGCM의 예측성 변동=100,119,12
제4장 기상연구소 기후 모델의 물리과정 개선=112,131,1
제1절 METRI AGCM의 지면 물리과정 개선=112,131,1
제2절 METRl AGCM의 복사 물리과정 개선=113,132,2
제3절 물리과정 개선 결과 및 향후 계획=115,134,1
제5장 결론=116,135,6
참고문헌=122,141,8
부록 1. 학술용역: 기상연구소 기후모델의 물리과정 개선 (I)=130,149,1
연구보고서=131,150,1
차례=132,151,1
요약문=133,152,1
제1장 연구개발 개요=134,153,1
제2장 연구개발 결과=135,154,1
2.1. 지면과정의 개선=135,154,1
2.1.1. 접합된 지면과정의 소개=135,154,2
2.1.2. 지면모형의 접합과정=137,156,5
2.1.3. CLM3 접합에 따른 METRl-AGCM의 평균 기후 모의, 계절 예측성의 변화=142,161,4
2.2. 복사과정의 개선=146,165,1
2.2.1. 복사과정 개선작업의 소개=146,165,2
2.2.2. METRI AGCM의 기존 복사 모수화 방안=148,167,18
2.2.3. 새로 접합된 NASA/GSFC 복사 모수화 방안=166,185,57
2.2.4. NASA/GSFC 복사 모수화 방안이장착된 METRI AGCM의 계절 예측성 평가=223,242,43
제3장 요약 및 결론=266,285,1
참고문헌=267,286,6
부록 2. Final Report : Intraseasonal Oscillations In The Western North Pacific During Summer In A Regional Model=273,292,1
1. Intrnduction=274,293,5
2. Data And AnalysIs Procedure=278,297,2
3. Model description=279,298,2
4. Climatological Seasonal Evolution=281,300,1
5. Model Results And Comparison With Obsetvations=281,300,5
6. Summary=285,304,1
References=286,305,5
Captions=291,310,52
Fig. 2.1.1. The Schematic Diagram Of METRI EPS Using The METRI AGCM=6,25,1
Fig. 2.1.2. Results Of Prediction Of Monthly Precipitation For Boreal Summer Season=10,29,1
Fig. 2.1.3. Same As In Fig. 2.1.2, Except For 850 hPa Air Temperature=11,30,1
Fig. 2.1.4. Pattern Correlation Of Monthly 500 hPa Geopotential Height Anomalies Between Prediction And Observation=13,32,1
Fig. 2.1.5. Same As In Fig. 2.1.4, But For Precipitation=14,33,1
Fig. 2.1.6. Same As In Fig. 2.1.4, But For 850 hPa Air Temperature=15,34,1
Fig. 2.1.7. Pattern Correlation Of 500 hPa Geopotential Height, 850 hPa Air Temperature, And Precipitation Anomalies Between Prediction And Observation=16,35,1
Fig. 2.1.8. Anomaly Pattern Correlation Coefficient And Root Mean Square Error Of Prediction For 500 hPa Geopotential Height During February~October 2005=18,37,1
Fig. 2.1.9. Same As In Fig. 2.1.8, But For 850 hPa Air Temperature=19,38,1
Fig. 2.1.10. Same As In Fig. 2.1.8, But For Precipitatiion=20,39,1
Fig. 2.1.11. Key Contents Of Presentation Of The Seasonal Prediction For Spring 2005=23,42,2
Fig. 2.1.12. Same As In Fig. 2.1.7, But For Summer 2005=25,44,2
Fig. 2.1.13. Same As In Fig. 2.1.7, But For Fall 2005=27,46,2
Fig. 2.1.14. Same As In Fig. 2.1.7, But For Winter 2005/2006=29,48,2
Fig. 2.2.1. Formulation Of The Standardized Verification System(SVS)=35,54,1
Fig. 2.2.2. Perfect Advanced Forecasting System Including The Standardization Verification System=43,62,1
Fig. 2.2.3. The Standardized Verification Of 850hPa Temperature (Left) And Precipitation (Right) Between METRI AGCM And Observation In Spring=45,64,1
Fig. 2.2.4. Same As Fig. 2.2.3, But In Summer=46,65,1
Fig. 2.2.5. Same As Fig. 2.2.3, But In Autumn=47,66,1
Fig. 2.2.6. Same As Fig. 2.2.3, But In Winter=48,67,1
Fig. 2.2.7. The Standardized Verification Of 850hPa Temperature (Left) And Precipitation (Right) In Korea(32.5N~37.5N, 125E~130E)=50,69,1
Fig. 2.2.8. Same As Fig. 2.2.7, But In Tropics (20N~20S)=51,70,1
Fig. 2.2.9. Same As Fig. 2.2.7, But In North Extratropics (20N~90N)=52,71,1
Fig. 2.2.10 Same As Fig. 2.2.7, But In South Extratropics (20S~90S)=53,72,1
Fig. 2.2.11. The Unfolded Structure Of Sphere On The Cubic=55,74,1
Fig. 2.2.12. The Unfolded Structure Of Cubic=56,75,1
Fig. 2.2.13. Example Of C80 Conformal-Cubic=61,80,1
Fig. 2.2.14. Same As In Fig 2.2.13, Except For Different Schmidt Number (0.03)=61,80,1
Fig. 2.2.15. The Example Of Domain Decomposition For Parallelizing Code On The Cubic Grid=62,81,1
Fig. 3.1.1. Weekly Averaged Wind Vector Of NCEP Reanalysis Data=65,84,1
Fig. 3.1.2. Spatial Distributions Of Weeldy NCEP-OISST=66,85,1
Fig. 3.1.3. Weekly Averaged Deviation Of Geopotential Height (NCEP Reanalysis Data)=66,85,1
Fig. 3.1.4. Propagation Types Of Rossby Wave For Typical Case=69,88,1
Fig. 1.5. Ten-Day Averaged Precipitation Of CMAP (a) And MM5 (b) During 16~25 July Of 1996=72,91,1
Fig. 3.1.6. Five-Day Averaged Deviation Of Geopotential Height In Meter (GPM) For Different SST Forcing=73,92,1
Fig. 3.1.7. Five-Day Averaged Deviation=76,95,1
Fig. 3.1.8. Time Tendencies Of Horizontally Averaged RMSE=77,96,1
Fig. 3.1.9. Ten-Day Averaged Precipitation=78,97,1
Fig. 3.1.10. Same As Fig. 6, Except For Negative SST Forcing=79,98,1
Fig. 3.1.11. Same As Fig. 9, Except For Negative SST Forcing=79,98,1
Fig. 3.1.12. Schematic Diagram Of Rossby Wave Propagation=81,100,1
Fig. 3.2.1. Schematic Diagram Of Research=84,103,1
Fig. 3.3.1. Differences Between Mean Temperature For 1958~1976 And For 1977~2000 (The Latter Minus The Former)=87,106,1
Fig. 3.3.2. Hovmoeller Diagram Of Sea Surface Anomaly In Tropics (20N~20S) And 850hPa Geopotential Height Anomaly In Subtropics (15N~30N) And Mid-Latitude (35N~65N) Regions For 1958~2004=89,108,1
Fig. 3.3.3. Composites Of 850hPa Geopotential Height Anomalies (a), 850hPa Horizontal Wind Anomahes (b) And 1000hPa Temperature Anomalies (c) Of NCEP Reanalysis Dataset For 1977~2004=90,109,1
Fig. 3.3.4. Power Analysis Of CRU Temperature Anomaly Time Series Averaged In 65N~35N, 60E~120E, For 195 8~2000=91,110,1
Fig. 3.3.5. Meridional And Vertical Structure Of Wind Anomalies Field And Temperature Anomalies (Shading) In The Asian Section (80E~120E), For 1977~2004=92,111,1
Fig. 3.3.6. Composites Of Meridional V Wind And 500hPa Velocity Potential Anornalies, The Left Denotes Meridional Cross-Section Of The Asian Region (80E~120E) And The Right Denotes That Of The Non-Asian Section (120E~60E)=94,113,1
Fig. 3.3.7. Composite Of 200hPa Zonal Wind Anomaly For 1977~2004=94,113,1
Fig. 3.3.8. Vertical Profile Of U Wind Anomaly And Meridional W Wind Anomaly At Each Level In The North Area Of Interdecadal Asian High (43N~55N, 80E~120E)=96,115,1
Fig. 3.3.9. Same As Fig. 3.3.8, But In The South Area Of Interdecadal Asian High (35N~43N, 80E~120E)=96,115,1
Fig. 3.3.10. EOF Analysis Of Geopotential Height Anomaly At Each Level=97,116,1
Fig. 3.3.11. The Summation Of 850hPa Geopotential Height EOF Modes For 1977~2004=98,117,1
Fig. 3.3.12. The Summation Of All Modes Except First Mode (a) And Except Second Mode (b) For 1977~2004=98,117,1
Fig. 3.3.13. Schematic Diagram Of The Interdecadal Asian High=99,118,1
Fig. 3.3.14. Time Series Of Global Mean Surface Temperature Anomaly For 1956-2001=102,121,1
Fig. 3.3.15. Wavelet Analysis Of Global Mean SST Anomaly For 43 Years=102,121,1
Fig. 3.3.16. Correlation Maps Between Time Series Of Latitude-Weighted Global Mean SST And Global SST (The Upper) And 1000hPa Temperature (The Lower)=103,122,1
Fig. 3.3.17. Time Series Of The Warm Or Cold Area Change Rates=103,122,1
Fig. 3.3.18. Wavelet Analysis Of The Warm (Right) And Cold (Left) Area Change Rates=104,123,1
Fig. 3.3.19. Correlation Between Global SST And The Cold (The Upper) Or Warm (The Lower) Area Change Rates=104,123,1
Fig. 3.3.20. Prescribed The Warm (a) And Cold (b) SST Anomaly Patterns=106,125,1
Fig. 3.3.21. Difference Between Exp.1 And Control Run In Spring=108,127,1
Fig. 3.3.22. Same As Fig. 3.3.21, But In Summer=108,127,1
Fig. 3.3.23. Same As Fig. 3.3.21, But In Autumn=108,127,1
Fig. 3.3.24. Same As Fig. 3.3.21, But In Winter=108,127,1
Fig. 3.3.25. Difference Between Exp.2 And Control Run In Spring=109,128,1
Fig. 3.3.26. Same As Fig. 3.3.25, But In Summer=109,128,1
Fig. 3.3.27. Same As Fig. 3.3.25, But In Autumn=109,128,1
Fig. 3.3.28. Same As Fig. 3.3.25, But In Winter=109,128,1
Fig. 3.3.29. Monthly Mean Temperature (a) And Precipitation (b) Of Ensemble Experiments Based On Prescribed Warm SST Anomaly Pattern=111,130,1
Fig. 3.3.30. Same As Fig. 3.3.29, But Using Cold SST Anomaly Pattern=111,130,1
Table 2.1.1. Description Of The METRI AGCM=7,26,1
Table 2.1.2. The List Of Results Of METRI 3-Month Prediction System During 2005=8,27,1
Table 2.1.3. List Of Prediction And Observation Over The Korean Peninsula During 2005=31,50,1
Table 2.1.4. Various Skill Scores Of Prediction For Temperature And Precipitation Over The Korean Peninsula During 2005=31,50,1
Table 2.1.5. The Three-By-Three Contingency Table For Calculation Of Heidke Skill Score=32,51,1
Table 2.1.6. The Three-By-Three Contingency Table Of Temperature=32,51,1
Table 2.1.7. The Three-By-Three Contingency Table Of Precipitation=32,51,1
Table 2.1.8. The Two-By-Two Contingency Table To Calculate General Relative Operating Characteristics=33,52,1
Table 2.1.9. The Two-By-Two Contingency Table Of Temperature=33,52,1
Table 2.1.10. The Two-By-Two Contingency Table Of Precipitation=33,52,1
Table 2.2.1. Summary Of The Core SVS(Standardized Verification System) For Long-Range Forecasting=36,55,1
Table 3.1.1. List Of Numerical Experiment Cases=70,89,1
Table 3.1.2. List Of Ensemble Members For CTL Case=71,90,1
Table 3.1.3. List Of Ensemble Members For E15 Case=71,90,1