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표제지=0,1,1

제출문=i,2,2

요약문=iii,4,3

SUMMARY=vi,7,3

List of Contents=ix,10,3

목차=xii,13,3

List of Figures=xv,16,4

List of Tables=xix,20,4

제1장 서론=1,24,2

제2장 국내외 기술 개발 현황=3,26,3

제3장 연구 개발 수행 내용 및 결과=6,29,1

제1절 장기 강수량 예보 현황 파악 및 성능 분석=6,29,1

1. 장기 강수량 예보 현황 분석=6,29,1

가. 국내 장기 예보 현황 분석=6,29,3

나. 기상청 장기 예보 발표의 정량적 기준=8,31,2

다. 국외 장기 예보 현황 분석=10,33,2

라. 미국 장기 예보 발표의 정량적 기준=12,35,1

2. 국내 강수량 예보 정확도 평가=13,36,3

제2절 전구모델을 이용한 강수 예측성 검증=16,39,1

1. 국내외 모델 자료의 확보=16,39,1

가. AMIP 자료=16,39,2

나. METRI AGCM 장기 적분 자료=17,40,2

2. 전구 강수량의 특성=18,41,1

가. 공간 분포 특성=18,41,4

나. 시간 분포 특성=21,44,2

다. 시.공 자료의 일치도=22,45,3

3. 동아시아 강수량의 특성=24,47,1

가. 공간 특성=24,47,3

나. 계절 변동성=26,49,3

4. 한반도 강수량의 특성=28,51,2

가. 시간 특성=29,52,2

나. 예측성 검증=30,53,3

5. 요약 및 결론=32,55,3

제3절 한반도 유역별 강수량의 장기 변동=35,58,1

1. 개요=35,58,1

2. 장기 강수량 자료의 재구성=35,58,1

가. 강수량 관측자료의 현황=35,58,3

나. 지역-평균 강수량 시계열으 구성=37,60,8

3. 분석=44,67,1

가. 장기 강수량의 공간 분포 특징=44,67,23

나. 변동 특성=66,89,6

4. 예측=71,94,1

가. 배경=71,94,3

나. 조화 분석=73,96,3

다. 조화 분석을 이용한 외삽법=75,98,3

라. 조화 분석과 외삽을 이용한 장기 강수량 예측=77,100,9

마. 결과 및 결론=86,109,3

5. 요약=88,111,2

제4절 유역별 단기 국지 강수량 예보 성능 분석=90,113,1

1. 유역별 강수량 관측 현황분석=90,113,1

가. 사용대상 관측데이터 선정=90,113,1

나. AWS 관측지점의 분류=90,113,10

다. AWS 자료를 이용한 유역 강수량 산출=99,122,2

2. 유역별 모델(GDAPS) 예측 자료 생산=101,124,4

3. GDAPS 10일 예측 강수의 검증=105,128,1

가. 검증 방법=105,128,2

나. 강수 검증 결과=106,129,6

제5절 하천유역의 인공강우 타당성조사=112,135,1

1. 인공강우 실험을 위한 기반자료조사=112,135,1

가. 낙동강 유역 구름의 운형 및 운저 조사=112,135,3

나. 영산강 유역의 인공증우를 위한 지형적 조사=114,137,3

다. 합천댐 유역의 인공증우 실시 조건 조사=117,140,4

라. 인공강우 구름물리 기초연구=120,143,3

마. 계절별 구름의 분포도 조사=122,145,3

바. 인공강우 실시지침서 작성=124,147,3

사. 한반도 위성이미지 구름온도 조사=126,149,3

2. 인공강우를 위한 국내외 과측체계조사=129,152,8

3. 항공기를 이용한 인공강우 실험실시=136,159,1

가. 인공강우 실험으로 구름 발달 과정 분석=136,159,4

나. 인공강우 실험 후 위성관측 분석=139,162,4

제6절 인공강우 실시 모의를 위한 수치모형 조사=143,166,1

1. 수치 해석 모형 입력자료 검토=143,166,2

2. 운형별 강수 모형 검토=145,168,4

제4장 목표달성도 및 관련분야의 기여도=149,172,2

제5장 연구개발결과 활용계획=151,174,1

제6장 연구개발과정에서 수집한 해외과학기술정보=152,175,2

제7장 참고 문헌=154,177,5

영문목차

[title page etc.]=0,1,6

Summary=vi,7,3

List of Contents=ix,10,6

List of Figures=xv,16,4

List of Tables=xix,20,4

Chapter 1. Introduction=1,24,2

Chapter 2. Review of Current Status=3,26,3

Chapter 3. Contents and Results=6,29,1

Session 1. Understanding and Analysis of Long-Term Precipitation Prediction Status=6,29,1

1. Long-Term Precipitation Prediction Status=6,29,1

a. Status of National Prediction=6,29,3

b. Categories for Long-Term Prediction of KMA=8,31,2

c. Status of Foreign Prediction=10,33,2

d. Categories for Long-Term Prediction of CPC=12,35,1

2. Assessment of Predictability for KMA=13,36,3

Session 2. Verification of Precipitation Predictability using AGCM=16,39,1

1. AGCM Data=16,39,1

a. AMIP Data=16,39,2

b. METRI AGCM Data=17,40,2

2. Characteristics of Global Precipitation=18,41,1

a. Spatial Distribution=18,41,4

b. Temporal Distribution=21,44,2

c. Coincidence of Spatial and Temporal Data=22,45,3

3. Characterstics of East Asia Precipitation=24,47,1

a. Spatial Charcteristics=24,47,3

b. Seasonal Change=26,49,3

4. Characteristics of Korean Precipitation=28,51,2

a. Temporal Characteristics=29,52,2

b. Assessment of Predictability=30,53,3

5. Summary and Conclusion=32,55,3

Session 3. Long-Term Variation of Precipitation in Korean Major Basins=35,58,1

1. Introduction=35,58,1

2. Construction of Longest Precipitation Series Using Modern Instrumental Records=35,58,1

a. Description of available modern instrumental precipitation data=35,58,3

b. Preparation of representative area-averaged precipitation series=37,60,8

3. Analysis=44,67,1

a. Statistical characteristics of the longest precipitation series=44,67,23

b. Fluctuation characteristics=66,89,6

4. Prediction=71,94,1

a. Background=71,94,3

b. The harmonic analysis=73,96,3

c. Extrapolation through the harmonic analysis=75,98,3

d. Long range rainfall prediction through harmonic analysis and extrapolation=77,100,9

e. Results and conclusion=86,109,3

5. Summary=88,111,2

Session 4. Performance of the short-range basin QPF=90,113,1

1. Analysis for the basin observed precipitation=90,113,1

a. Data=90,113,1

b. AWS Observation Point=90,113,10

c. Basin Precipitation using AWS Data=99,122,2

2. Basin QPF of GDAPS 10-day forecast=101,124,4

3. Vrification of GDAPS 10-day precipitation forecast=105,128,1

a. Methodology=105,128,2

b. Results=106,129,6

Session 5. Assessment of Cloud Seeding in River Basin=112,135,1

1. Examination of Basic Data for Experiment in Cloud Seeding=112,135,1

a. Type and Height of cloud in the Nakdong River Basin=112,135,3

b. Geographic Information of Youngsan River Basin=114,137,3

c. Condition of Cloud Seeding in the habchon Dam Basin=117,140,4

d. Study of Cloud Physics for Cloud Seeding=120,143,3

e. Distribution of Seasonal Cloud=122,145,3

f. Manual for Cloud Seeding=124,147,3

g. Satellite Image and Cloud Temperature=126,149,3

2. Examination of Observation System for Cloud Seeding=129,152,8

3. Aviation Experiment of Cloud Seeding=136,159,1

a. Analysis of Cloud Field Evolution in Cloud Seeding=136,159,4

b. Analysis of Satellite Observation after Cloud Seeding=139,162,4

Session 6. Examination of Numerical Model for Cloud Seeding=143,166,1

1. Examination of Input Data of Numerical Model=143,166,2

2. Examination of Explicit Predictive Cloud and Precipitation Process=145,168,4

Chapter 4. Achievements and External Contributions=149,172,2

Chapter 5. Application Plan for Research Outputs=151,174,1

Chapter 6. Useful Informations from Foreign Countries=152,175,2

Chapter 7. Reference=154,177,5

그림목차

Fig. 3.1.1. An example of long range forecasting by Korea Meteorological Administration=6,29,1

Fig. 3.1.2. An example of long range forecastiong by NCEP／CPC=11,34,1

Fig. 3.1.3. Categories for long range forecasting by NCEP／CPC=12,35,1

Fig. 3.1.4. Climatologies of precipitation and temperature used in long range forecasting=13,36,1

Fig. 3.1.5. An example of the comparison between forecast and observation in 1999=14,37,1

Fig. 3.1.6. Definition of Heidks Skill Score=15,38,1

Fig. 3.2.1. Seasonal ensemble prediction system=18,41,1

Fig. 3.2.2. Global distributions of mean precipitation from CMAP observation and AMIP 2 models. (a) JJA mean (B) DJF mean=19,42,1

Fig. 3.2.3. Global distributions of RMSE of model precipitation=20,43,1

Fig. 3.2.4. Zonal mean precipitation. The upper and lover panels are respectively for DJF,JJA and annual mean=21,44,1

Fig. 3.2.5. Seasonal Variations of precipitation in (a) global (b) 30N-30S (c) Northern Hemisphere (d) Southern Hemisphere=22,45,1

Fig. 3.2.6. Horizontal distribution of DJF precipitation in East Asia region=25,48,1

Fig. 3.2.7. Horizontal distribution of JJA precipitation in East Asia region=26,49,1

Fig. 3.2.8. Normalized amplitude and phase of the annual cycle in precipitation=27,50,2

Fig. 3.2.9. Region of Korean penisular=28,51,1

Fig. 3.2.10. Seasonal variation of climatological monthly mean precipitation in Models and Observation=29,52,1

Fig. 3.2.11. Percent Correct(upper panel) and Heidke Skill Score (lower level) of models=32,55,1

Fig. 3.3.1. Location of the 61 raingauge stations that are considered in the present study and approximate boundary of five major river catchments of the South Korea=36,59,1

Fig. 3.3.2. Increase in the density of raingauge network over South Korea=36,59,1

Fig. 3.3.3. Instrumental period annual precipitation series (in mm) for different regions of South Korea. Linear trend is shown by the thick straight line=68,91,1

Fig. 3.3.4. Instrumental period monsoon precipitation series (in mm) for different regions of South Korea. Linear rend is shown by the thick straight line=69,92,1

Fig. 3.3.5. Instrumental period annual precipitation series (in mm) for 8 selected stations from different parts of the country. The linear is shown by the thick straight line=70,93,1

Fig. 3.3.6. Seasonal precipitation series (in mm) of the whole South Korea for the period 1905-2001. The series in the lower panel is in continuation with the series in the upper panel=73,96,1

Fig. 3.3.7. Comparison of actual and predicted winter precipitation over different regions of South Korea for the period 1992-2001=82,105,1

Fig. 3.3.8. Comparison of actual and predicted spring precipitation over different regions of South Korea for the period 1992-2001=83,106,1

Fig. 3.3.9. Comparison of actual and predicted summer precipitation over different regions of South Korea for the period 1992-2001=84,107,1

Fig. 3.3.10. Comparison of actual and predicted autumn precipitation over different regions of South Korea for the period 1992-2001=85,108,1

Fig. 3.4.1. The distribution of AWS and observation points operated by KMA=91,114,1

Fig. 3.4.2. The distribution of AWS and observation points in 5-river basin=92,115,1

Fig. 3.4.3. Thiessen's polygon for AWS points in 5-river basin=100,123,1

Fig. 3.4.4. The grid-points of (a) 3.5-day and (b) 10-day forecast near Korea Peninsula=102,125,1

Fig. 3.4.5. Weight values for 4-river basins in South Korea=103,126,1

Fig. 3.4.6. The (a) first and (b) next 12-hr accumulated precipitation of GDAPS 10-day forecast started from 00 UTC 1 April 2002=104,127,1

Fig. 3.4.7.／3.6.7 An example of the time series of the AWS and GDAPS basin precipitation for May 2002=107,130,1

Fig. 3.4.8. The BLAS and RMSE(mm／12 hr) versus forecast time (hr) for the GDAPS forecasts in April 2002=108,131,1

Fig. 3.4.9. The BLAS and RMSE(mm／12 hr) versus forecast time (hr) for the GDAPS forecasts in May 2002=109,132,1

Fig. 3.4.10. The temporal correlation between the GDAPS basin QPF and the AWS basin rainfall in April 2002. This correlation represents the predictability of trends=110,133,1

Fig. 3.4.11. The temporal correlation between the GDAPS basin QPF and the AWS basin rainfall in May 2002. This correlation represents the predictability of trends=111,134,1

Fig. 3.5.1. The distribution map of an altostratus cloud occurrence in Nakdong river basin=114,137,1

Fig. 3.5.2. Monthly Average of Cloud Occurances=116,139,1

Fig. 3.5.3. Youngsan river basin's topographical map=116,139,1

Fig. 3.5.4. Yearly and seasonal rainfall in Youngsan river basin=116,139,1

Fig. 3.5.5. The GIS of Hapchen Dam surroundings=118,141,1

Fig. 3.5.6. The flight paths according as a cloud seeding experment=118,141,1

Fig. 3.5.7. The cloud-base level on March in Hapchen(1991~2000)=120,143,1

Fig. 3.5.8. Monthly the FL in Pohang=121,144,1

Fig. 3.5.9. The distribuction map of 30 years rainfall in Korea(1970~2000)=123,146,1

Fig. 3.5.10. Cloud Types of Hapchean(1990~2000)=123,146,1

Fig. 3.5.11. Cloud Types of Andong(1990~2000)=124,147,1

Fig. 3.5.12. Cloud Types of Mokpo(1990~2000)=124,147,1

Fig. 3.5.13. The marine observation network and the upper-air observation systems=130,153,1

Fig. 3.5.14. The cloud particle sonde=131,154,1

Fig. 3.5.15. Schematic diagram of cloud particle and rain particle's distribution in snow clouds=131,154,1

Fig. 3.5.16. The observation system for cloud seeding experiments with an aircraft=135,158,1

Fig. 3.5.17. The observation and analysis of aircraft-experiments=136,159,1

Fig. 3.5.18. The target area of an aircraft experiment=137,160,1

Fig. 3.5.19. The PPI composite image (09:00)=138,161,1

Fig. 3.5.20. The CAPPI 3km image and RHI=138,161,1

Fig. 3.5.21. The CAPPI 3km image and RHI (10:10)=139,162,1

Fig. 3.5.22. The CAPPI 3km image and RHI (10:20)=139,162,1

Fig. 3.5.23. GMS-5 visible images observed from 1001UTC to 1002UTC on December 10,2001=141,164,1

Fig. 3.5.24. GMS-5 IR images of cloud top temperature observed from 0900LST to 1200LST on December 10,2001=142,165,1

Fig. 3.6.1. The Flowchart of the MM5 model system=144,167,1

Fig. 3.6.2. Schematic Diagram of microphysical interactions among hydrometers=148,171,1

표목차

Table 3.1.1. Categories for temperature departure in ℃ and relative precipitation difference in %=9,32,1

Table 3.1.2. New categories for long-term temperature and precipitation predictions by KMA=9,32,1

Table 3.2.1. Available AMIP2 Model Data for AMIP2 period(1979-95)=17,40,1

Table 3.2.2. MRBP results comparing the obsered seasonal cycle of precipitation over the Eastern Asia to the model simulation=24,47,1

Table 3.2.3. Template of the 3×3 contingency tables in verification=31,54,1

Table 3.3.1. Brief description of stations and their data used in the present study=39,62,1

Table 3.3.2. Correlation between station with available data and station with non-available data based on the period 1973-2000=41,64,1

Table 3.3.3. Mean and stanard deviation (S.D.) of the CC between representative area-averaged precipitation series (1973-2000) and the individual raingauges for different regions of South Korea=41,64,1

Table 3.3.4. Available number of raingauges for period prior to 1973 and the CC between mean series of the available raingauges and the representative series (1973-2000) for the whole South Korea=43,66,1

Table 3.3.5. The instrumental period constructed (1904-1972) and representative(1973-2001) area-averaged precipitation data (in mm) of the whole South Korea. Some important statistics of the full series (1904-2001) are given in the last rows=45,68,2

Table 3.3.6. Available number of raingauges for period prior to 1973 and the CC between mean series of the aailable raingauges and the repersentative series (1973-2000) for the Contiguous South Korea=47,70,1

Table 3.3.7. The instrumental period constructed (1904-1972) and representative (1973-2001) area-averaged precipitation data (in mm) of the contiguous South Korea. Some important statistics of the full series (1904-2001) are given in the last rows=48,71,2

Table 3.3.8. Available number of raingauges for period prior to 1973 and the CC between mean series of the available raingauges and the representative series (1973-2000) for the Hangang catchment (South Korea)=50,73,1

Table 3.3.9. The instrumental period constructed (1904-1972) and representative (1973-2001) area-averaged precipitation data (in mm) of the Han catchment,South Korea. Some important statistics of the full series (1904-2001) are given in the last rows=51,74,2

Table 3.3.10. Available number of raingauges for period prior to 1973 and the CC between mean series of the avilale raingauges and the representative series (1973-2000) for the Nak-Dong catchment (South Korea)=53,76,1

Table 3.3.11. The instrumental period constructed (1904-1972) and representative (1973-2001) area-averaged precipitation data (in mm) of the Nak-Dong catchment,South Korea. Some inportant statistics of the full series (1904-2001) are given in the last ro=54,77,2

Table 3.3.12. Available number of raingauges for period prior to 1973 and the CC between mean series of the available raingauges and the representative series (1973-2000) for the Gum catchment (South Korea)=56,79,1

Table 3.3.13. The instrumental period constructed (1919-1972) and representative (1973-2001) area-averaged precipitation data (in mm) of the Gum catchment,South Korea. Some important statistics of the full series (1919-2001) are given in the last rows=57,80,2

Table 3.3.14. Available number of raingauges for period prior to 1973 and the CC between mean series of the available raingauges nd the representative series (1973-2000) for the Young-San catchment (South Korea)=58,81,1

Table 3.3.15. The instrumental period constructed(10904-1972) and representative (1973-2001) area-averaged precipitation data (in mm) of the Young-San catchment,South Korea. Important statistics of the full series (1904-2001) are given in the last rows=59,82,2

Table 3.3.16. Available number of raingauges for period prior to 1973 and the CC between mean series of the available raingauges and the representative series (1973-2000) for the Sum-Jin catchment (South Korea)=61,84,1

Table 3.3.17. The instrumental period constructed (1942-1972) and representative (1973-2001) area-averaged precipitation data (in mm) of the Sum-Jin catchment,South Korea. Some inportant statistics of the full series (1942-2001) are given in the last row=61,84,2

Table 3.3.18. Available number of raingauges for period prior to 1973 and the CC between mean series of the available raingauges and the representative series (1973-2000) for the Jeju Island (South Korea)=62,85,1

Table 3.3.19. The instrumental period constructed (1923-1972) and representative (1973-2001) area-averaged precipitation data (in mm) of the Jeju island,South Korea. Some important statistics of the full series (1923-2001) are given in the last rows=63,86,2

Table 3.3.20. Linear trend (tr,mm／100-yr) in the monthly,monsoonal and annual precipitation fluctuations over the whole South Korea,the contiguous South Korea,the five major catchments and the Jeju island. % shows the linear trend value as percentage=65,88,2

Table 3.3.21. Values of the important parameters of the prediction method for different regions of the South Korea. hlimit is the standardized variance contribution above which all harmonics are selected; CC the corresponding actual precipitation amounts=87,110,1

Table 3.4.1. The list of AWS points in Han river basin=93,116,2

Table 3.4.2. The list of AWS points in Nak-dong river basin=95,118,2

Table 3.4.3. The list of AWS points in Keum river basin=97,120,1

Table 3.4.4. The list of AWS points in Sum-jin river basin=98,121,1

Table 3.4.5. The list of AWS points in Young-san river basin=99,122,1

Table 3.5.1. Seasonal cloud types in Nakdong river basin(1990-2000)=113,136,2

Table 3.5.2. FL,LCL and CCL in Pohang=121,144,1

Table 3.5.3. The CDC(Convective Day Category)=125,148,1

Table 3.5.4. The cloud frequency and the destribution of cloud top temperature on July,2001=127,150,1

Table 3.5.5. The rate of distributed cloud top temperature on July,2001=128,151,1

Table 3.5.6. The classification of cloud types from satellite images=140,163,1

Table 3.6.1. Cloud Types along with the level=145,168,1

Table 3.6.2. The charcteristics of clouds=145,168,1

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