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연구보고서 : 기후변화협약대응 지역기후시나리오 활용기술 개발(III)
목차
CONTENTS 6
요약문 17
SUMMARY 20
제1장 서론 23
제2장 온실가스+에어러솔 복사강제력에 대한 전지구 기후변화 시나리오 산출 25
제1절 개요 25
제2절 20C3M과 시나리오별(A1B, B1, A2) 앙상블 결과 비교 분석 27
1. 서론 27
2. 모델 및 자료 28
3. 결과 32
4. 요약 및 결론 50
제3절 COSMOS-0.9.0의 신버전 도입 및 시험 운영 51
1. 서론 51
2. 모델 및 실험방법 52
3. 결과 55
4. 요약 및 결론 64
제4절 ECHAM4 T106을 이용한 A1B 온실가스 증가 시나리오에 따른 장기 기후변화 자료 생산 및 분석 65
1. 개요 65
2. 모델 및 실험 방법 67
3. 20세기후반 동아시아 여름몬순 69
4. 미래 동아시아 여름몬순 전망 79
5. 요약 및 결론 83
제5절 소결론 85
제3장 중위도지역 대기순환 변화의 미래 전망 분석 86
제1절 개요 86
제2절 A1B 시나리오에 근거한 중위도 및 적도지역 순환장의 변화 87
1. 서론 87
2. 20세기 상층 발산장 분포 88
3. 상층발산장의 미래 변화 92
4. 요약 및 결론 99
제3절 A1B 시나리오에 근거한 겨울철 스톰트랙의 변화 99
1. 서론 99
2. 자료 및 방법 101
3. 분석결과 101
4. 요약 및 결론 112
제4절 미래 열대 저기압 관련 연구 동향 113
1. 연구 배경 113
2. 국내 동향 114
3. 해외 동향 115
제5절 소결론 115
제4장 관측 자료 및 시나리오를 활용한 기후요소의 변화 특성 분석 118
제1절 개요 118
제2절 A1B 시나리오에 근거한 우리나라 아열대 기후구 전망 120
1. 서론 120
2. 연구 자료 및 방법 122
3. 결과 및 토의 125
4. 결론 130
제3절 A1B 시나리오에 근거한 우리나라 자연 계절 시작일 및 지속기간 변화 전망 132
1. 서론 132
2. 연구 자료 및 방법 134
3. 결과 및 토의 136
4. 결론 148
제4절 A1B 시나리오에 근거한 우리나라 기온변화 150
1. 서론 150
2. 결과 150
3. 요약 153
제5절 IPCC WGI 평가보고서 주요내용 비교를 통한 기후변화에 관한 과학적 진보 154
1. 서론 154
2. 기후시스템 내의 지구온난화를 포함한 여러 가지 변화들 155
3. 인간활동에 의한 온실가스와 에어러솔 배출 158
4. 기후변화 탐지 및 원인규명 160
5. 기후 시나리오 161
6. 모델 162
7. 미래 기후변화 전망 164
8. 인위적 기후변화의 지속 여부 167
9. 불확실성(Uncertainty) 및 향후계획 167
10. 결론과 토의 168
제6절 소결론 169
제5장 지구시스템 모델 개발 방안에 관한 연구 172
제1절 지구시스템모델 개발안 마련 172
제2절 국내외 현황 조사 173
1. IPCC AR4에 참가한 지구시스템 모델 현황 173
2. 선진국 지구시스템 모델 개발 방향 176
3. 국내 기술현황 178
제3절 모델 개발 방안 180
제4절 소결론 183
제6장 결론 185
참고문헌 187
부록 201
부록 1. COSMOS-1.0의 시험적분 201
부록 2. 제5차 기후변화학술대회 223
부록 3. 기후자료 활용기술 조사 229
SRES 시나리오에 의한 동아시아 상세 기후변화 시나리오 생산(III) 247
연구보고서 248
목차 249
CONTENTS 250
요약문 256
SUMMARY 257
제1장 서론 258
제1절 연구개발 배경 258
제2절 국내·외 연구 동향 258
제3절 연구개발의 필요성 259
제2장 동아시아 지역 고해상도 지역기후변화자료 생산 261
제1절 서론 261
제2절 지역기후 모델 및 자료 262
1. 모델 262
2. 자료 264
제3절 물리모수화 설정을 위한 실험 265
1. 실험 방법 266
2. 분석 결과 267
제4절 시나리오 자료 생산 272
제5절 현재기후 모의 결과의 분석 275
1. 강수량 275
2. 지표 평균 기온 282
3. 500 hPa 지위고도 290
4. 상층 동서 바람 297
제6절 미래기후변화 모의 결과의 분석 304
1. 강수량 304
2. 지표 평균 기온 312
3. 500 hPa 지위고도 321
4. 상층 동서 바람 328
제3장 요약 및 결론 336
참고문헌 339
기후변화 영향평가 및 적응방안을 위한 파일로트 연구(II) 341
연구보고서 342
목차 343
CONTENTS 345
요약문 355
SUMMARY 357
제1장 서론 359
제1절 연구개발의 필요성 359
1. 연구개발 배경 359
2. 연구개발 필요성 360
제2절 국내·외 연구 동향 361
1. 기후변화의 취약성 및 영향평가 361
2. 평야지역의 농업과 농업 생태 363
3. 평야지역의 자연재해 364
제2장 연구 방법 및 연구지역 개관 368
제1절 추진전략 368
제2절 연구자료 및 방법 369
1. 연구 자료 및 현장 답사 369
2. 연구방법 374
제3절 연구지역의 사회·경제적 배경 376
제3장 농업 380
제1절 작물의 생산량 변화 380
1. 주곡류 380
2. 과수류 389
3. 채소류 394
제2절 작물의 재배면적 변화 403
1. 주곡류 403
2. 과수류 410
3. 채소류 416
제4장 농업생태 426
제1절 기후변화와 나주시 작물의 생육시기 426
1. 생육시기의 변화 426
2. 생육시기와 기후변화 사이의 관계 435
제2절 기후변화와 나주시 작물의 생육 444
1. 생육 특성의 변화 444
2. 생육 특성과 기후변화 사이의 관계 460
제3절 기후변화와 나주시 작물의 병해충 476
1. 병해충 발생의 변화 476
2. 병해충 발생과 기후변화 사이의 관계 483
제4절 농사일기 사례 분석 487
1. 생육시기의 변화 487
2. 생육시기와 기후변화 사이의 관계 492
제5장 자연재해 495
제1절 기후변화와 자연재해 495
제2절 나주평야에서 기후변화와 자연재해 497
1. 나주평야의 지형과 자연재해 497
2. 나주평야의 과거 자연재해 502
3. 자연재해 극복을 위한 나주평야의 근대적 수리시설 508
4. 2004년 태풍 메기로 인한 나주평야의 자연재해 514
제6장 기후변화에 대한 취약성 평가 519
제1절 농업 및 농업 생태 519
제2절 자연재해 521
제7장 요약 및 결론 524
제1절 농업 및 농업 생태 524
제2절 자연재해 525
참고문헌 528
부록 I - 주민면담 내용 요약 533
부록 II 기후변화 영향 관련 기사 모음 564
부록 III 기후변화 영향 관련 기사 검색 576
Table. 2.2.1. The detailed description of AR4 models. 29
Table. 2.3.1. Description of experiments performed in this study. 54
Table. 2.3.2. Mean seasonal 2 m temperature and precipitation averaged over East Asia and globe from COSMOS with T31 and T63 and observation where ECMWF 2 m temperature (1971~2000) and CMAP precipitation (1979~999) were used. Right two columns mean differences between model and observation and model... 60
Table. 2.4.1. Description on experiment design and data. 67
Table. 2.4.2. Description of IPCC SRES AR4 models and ECHAM4 T106. 73
Table. 4.3.1. The change of onset date of natural seasons at weather stations (1921~2000). 137
Table. 4.5.1. The major abbreviation for working group I contribution to the Inter-governmental Panel on climate Change used in this paper. 155
Table. 5.2.1. Earth system model for IPCC AR4 (2007). 173
Table. 5.3.1. Main topics for the development of the earth system model. 181
SRES 시나리오에 의한 동아시아 상세 기후변화 시나리오 생산(III) 255
Table 2.2.1. Summary of MM5 configuration used in this study. 263
Table 3.1.1. MM5 configuration used in experiments for physical parameterization. 266
Table 4.1.1. Saved variables in this study. 273
Table 4.1.2. Saved data sizes in this study. 274
기후변화 영향평가 및 적응방안을 위한 파일로트 연구(II) 354
Table 1.2.1. The principal field of study about natural disasters. 365
Table 1.2.2. Research institute and program related to deluge and floodwaters. 366
Table 2.2.1. Document data for crops. 369
Table 2.2.2. Field investigation region and crops. 370
Table 2.2.3. Classification of crops. 371
Table 2.2.4. Area ratio(%) of land category in Naju. 373
Table 3.1.1. Need cumulated hours of 7.2℃ below in winter for fruits. 389
Table 3.1.2. Change of persimmon cultivation area and yield. 391
Table 3.1.3. Frost damage of February 1977. 392
Table 3.1.4. Yield change of hot pepper in Korea. 395
Table 3.1.5. Soil moisture (pF) and chinese cabbage weight. 400
Table 3.2.1. Change of rice paddy areas in Korea. 403
Table 3.2.2. Change of utilization coefficient on cultivated land in Korea. 406
Table 3.2.3. Change of barley cultivation areas in Korea. 407
Table 3.2.4. Change of pear cultivation area in Korea. 411
Table 3.2.5. Cultivation area of hot pepper in Korea. 416
Table 5.2.1. The terrace soils in study area. 499
Table 5.2.2. The scale of main dam in study area. 508
Table 5.2.3. The flooding damage of main flooding event. 516
Fig. 2.1.1. Producing system of global and regional climate change projection based on IPCC SRES. 26
Fig. 2.2.1. Land-sea mask over East Asia for (a)OCN and (b)LND experiments using ECHO-G/S(land: 1, sea: 0). The solid square boxes display around Korean peninsula(120˚~130˚E, 32˚~42˚N). 31
Fig. 2.2.2. Mean biases of monthly mean surface air temperature (SAT) and precipitation (PCP) over East Asia for AR4 models and ECHO-G/S results during the period of 1980 ~ 1999. The thin and thick lines display the ranges of AR4 models and ECHO-G/S 5 ensemble members, respectively. The bright bars are multi-model ensemble means (MME) and the dark bars... 33
Fig. 2.2.3. Change of monthly mean surface air temperature (SAT), precipitation (PCP) and land precipitation(PCP_land) over East Asia for AR4 models and ECHO-G/S results during the period of 2080~2099 relative to 1980~1999. The thin and thick lines display the likely ranges of AR4 models and ECHO-G 5 ensemble members, respectively. The bright bars... 34
Fig. 2.2.4. (a) The annual cycle (the first cyclo-stationary loading vector) of monthly surface air temperature during the period of 1971~2000 and (b) the difference with the annual cycle of the 30-year (2071~2100) monthly surface air temperature based on A2 scenarios. Shade indicates positive values. 36
Fig. 2.2.5. Same as Fig. 2.2.4, but for precipitation. 37
Fig. 2.2.6. East Asian averaged annual cycle of (a)monthly surface air temperature and (b)precipitation during the period of 1971~2000(20C3M) and 2071~2100 based on A2 scenarios. 38
Fig. 2.2.7. The time-series of monthly mean precipitation (mm/day) averaged over (a) East Asia and (b) around Korean peninsula from CMAP (closed circle), each AR4 model (none), their multi-model ensemble mean (cross) and ECHO-G/S (open circle) for the period of 1980~1999. 40
Fig. 2.2.8. Climatological distribution of JJA-mean precipitation (mm/day) from (a, b, c) group-L and (d, e) group-S of AR4 models for the period of 1980~1999. 41
Fig. 2.2.9. Climatological distribution of JJA-mean precipitation (mm/day) from (a) ECHO-G/S and (b) CMAP data, and differences between observed and simulated precipitation from (c) ECHO-G/S and (d) 22 AR4 models. 41
Fig. 2.2.10. Latitude-time cross section of monthly precipitation (shaded; mm/day) and 850 hPa meridional wind (contour; m/s) from (a) CMAP data and (b) ECHO-G/S and (c) their differences for the period 1980~1999. 42
Fig. 2.2.11. Climatological distribution of JJA-mean (a) total precipitation (PCP) over 5 mm/day from CMAP data, (b) large-scale precipitation (LSP) over 3 mm/day and (c) convective precipitation (CP) over 1 mm/day from ECHO-G/S (shaded). Four contours indicate month-to-month evolution from May to August with thin solid, thick solid, dashed and... 43
Fig. 2.2.12. Climatological distribution of JJA-mean surface air temperatures (SAT); ℃),sea level pressure (SLP; hPa), 850 hPa wind (V; m/s) and 850 hPa specific humidity (q; g/kg) from (a, c, e) observation and (b, d, f) ECHO-G/S. 44
Fig. 2.2.13. The time-serious of monthly mean precipitation (mm/day) over (a) East Asia and (b) around Korean peninsula from CMAP (solid line), OCN (dashed line) and LND (dotted line) experiments using ECHO-G/S for the period of 1980~1999. 45
Fig. 2.2.14. Latitude-time cross map of monthly precipitation (shaded; mm/day) and 850 hPa meridional wind (contour, m/s) from (a) LND experiment using ECHO-G/S and (b) difference between LND and OCN experiments for the period of 1980~1999. 46
Fig. 2.2.15. Climatological distribution of JJA-mean (a) large-scale precipitation (LSP) over 3mm/day and (b) convective precipitation (CP) over 1 mm/day from LND experiment using ECHO-G/S (shaded) and difference between (c) LND and (d) OCN experiments. Four contours on (a) and (b) indicate month-to-month evolution from May to August... 47
Fig. 2.2.16. Climatological distribution of JJA-mean precipitation (mm/day) from (a) LND experiment using ECHO-G/S and (b) difference between LND and OCN experiments. 48
Fig. 2.2.17. Climatological distribution of JJA-mean surface air temperatures (TAS; ℃), sea level pressure (SLP; hPa), 850 hPa wind vector (V; m/s) and 850 hPa specific humidity (q; g/kg) from (a, c, e) LND experiment and (b, d, f) difference between LND and OCN experiment using ECHO-G/S. 49
Fig. 2.3.1. Schematic structure of COSMOS-2.0. However, COSMOS-1.0 includes only atmospheric (ECHAM5) and oceanic (MPI0M) components. 52
Fig. 2.3.2. Land sea mask of COSMOS with 731 and T63, respectively. 53
Fig. 2.3.3. Horizontal distribution of climatological annual mean of 2m temperature for (a) observation (b) ECHAM5 AMIP type simulation (c) COSMOS with T31 and (d) with T63 resolution. 56
Fig. 2.3.4. Same as Fig. 2.3.3, but for precipitation. 57
Fig. 2.3.5. Time series of annual (black), JJA (red) and DJF (green) mean of globally averaged 2m temperature for COSMOS (T31) and COSMOS (T63), respectively. 58
Fig. 2.3.6. Same as Fig. 2.3.5, but for precipitation. 59
Fig. 2.3.7. Same as Table 2.3.2 but for seasonal mean and model bias diagram. Upper panels show seasonal mean of 2m temperature and precipitation for annual, JJA and DJF averaged over east Asia and globe and lower panels are model bias in percentage, respectively. 60
Fig. 2.3.8. Horizontal distribution of seasonal mean 2 m temperature from COSMOS (T31), COSMOS (T63) and observation (left three panels) and model bias (right two panels). 61
Fig. 2.3.9. Same as Fig. 2.3.8, but for precipitation. 62
Fig. 2.3.10. Same as Fig. 2.3.8, but for mean sea level. 63
Fig. 2.4.1. Land sea mask (left) and topography (right) used in (a, c) T30 ECHO-G/S and (b, d) T106 ECHAM4 AGCM, respectively. 68
Fig. 2.4.2. Summer mean precipitation over East Asia from OBS (1979~2000), 21 IPCC SRES participating models (1971~2000), and ECHAM4_T106. Values greater (lower) than 1.5 are shaded. 70
Fig. 2.4.3. Taylor diagrams of precipitation over the regions of (a) 100˚~150˚E, 25˚~50˚N, (b) 110˚~145˚E, 30˚~45˚N, (c) 120˚~145˚E, 32˚~42˚N using 22models. 73
Fig. 2.4.4. Summer (June~September) mean precipitation of (a) observation, (b) T30, and (c) T106. The evolution of precipitation above 5 mm/day from June to September using (d) observation, (e) T30, and (f) T106 (solid: June, long short dash: July, shor dash: August, dot: September). 74
Fig. 2.4.5. (a) Latitude-time (20˚~50˚N)-time cross section and (b) time-longitude (100˚~150˚E) cross section of mean annual precipitation for the observation, T30, and T106. 75
Fig. 2.4.6. Area-averaged mean annual precipitation over the Globe, Land, Ocean, Northern Hemisphere (NH), Southern Hemisphere (SH), Eurasia, East Asia (100˚-150˚E, 25˚-50˚N), eastern part of East Asia (110˚~145˚E, 30˚~45˚N), and Korea & Japan (120˚~145˚E, 32˚~42˚N). Bottom figure: Area-averaged... 76
Fig. 2.4.7. Summer mean (JJAS) precipitation for the (a) present (_P) and (b) future (_F) climate and the (c) difference in percentage (shading) between (a) and (b). The contour in (c) depicts the regions of statistically significant at 95% confidence level. 78
Fig. 2.4.8. Same as Fig. 2.4.7 but for the latitude-time cross-section averaged over 100˚~150 ˚E. 80
Fig. 2.4.9. Summer mean (JJAS) distributions of precipitation (shading), mean sea level pressure (contour), and 850 hPa wind (vector) in the (a) present, (b) future climate, and (c) the difference between (a) and (b). In (c), precipitation (shading) is depicted in %. 81
Fig. 2.4.10. Precipitation change (%) during summer (JJAS) over the regions of globe, northern hemisphere (NH), southern hemisphere (SH), East Asia (EA, 100˚-150˚E, 25˚-50˚N), and eastern part of East Asia (E-EA, 120˚~145˚E, 32˚~42˚N). 83
Fig. 3.2.1. Monthly mean velocity potential and divergent wind at 200 hPa for the climate (1971~2000) in (a) January (b) April (c) July (d) October. The units are 106(이미지참조)㎡/s. 89
Fig. 3.2.2. Deviation from the zonal mean of the velocity potential for the climate in (a) January (b) April (c) July (d) October. The units are 106(이미지참조)㎡/s. 90
Fig. 3.2.3. Deviation from the annual mean of the velocity potential for the climate in (a) January (b) April (c) July (d) October. The units are 106(이미지참조)㎡/s. 91
Fig. 3.2.4. Annual mean of the velocity potential for the present, future climate, and the difference. The units are 106(이미지참조)㎡/s. 93
Fig. 3.2.5. Time series of Walker circulation index for the present (1971 ~ 2000) and future (2071~2100) climate for 30 years. 94
Fig. 3.2.6. Zonal mean of the velocity potential for the present (open circle) and future (closed circle) climate in January, April, July, and October. The units are 106(이미지참조)㎡/s. 95
Fig. 3.2.7. Difference of zonal mean of the velocity potential in January, April, July, and October. The units are 106(이미지참조)㎡/s. 96
Fig. 3.2.8. Time series of the Hadley circulation index in the present and future climate during DJF and JJA. 97
Fig. 3.2.9. Time series of the Monsoon circulation index in the present and future climate during DJF and JJA. 98
Fig. 3.3.1. Climatology of storm track activity calculated by standard deviation of high-frequency (period with 2~8 day) streamfunction at 300 hPa (a) for NCEP (1970~2000), (b) for 20C (1970~2000), and (c) for A1B (2070~2100), and (d) difference between A1B and 20C. The units are 105(이미지참조)㎡/s-¹. 102
Fig. 3.3.2. 98th percentile of maximum daily 10 m wind speed (a) for present, and (b) difference between future and present. The units are ms-¹. 103
Fig. 3.3.3. Cyclone track density... 103
Fig. 3.3.4. Horizonal structure of 2 m temperature. The line denote present climatology, and the shading areas denote difference between future and present climatology. The units are K. 105
Fig. 3.3.5. Zonal mean temperature over Pacific (90˚~200 ˚E)... 106
Fig. 3.3.6. Climatology of zonal wind at 300 hPa... 107
Fig. 3.3.7. Climatology of zonal-mean zonal wind over Pacific (90˚~200˚E)... 109
Fig. 3.3.8. Climatology of thickness between 300 hPa and 800 hPa... 110
Fig. 3.3.9. Zonal-mean lapse rate.... 110
Fig. 3.3.10. Boroclinicity index at 700 hPa... 111
Fig. 4.2.1. Subtropical climate region by Koppen's(이미지참조) climate classification (1971 ~ 2000) 121
Fig. 4.2.2. The projection of CO₂ concentration increase by IPCC SRES 123
Fig. 4.2.3. Subtropical climate region by Trewartha's cliamte classification (1971 ~ 2000) 125
Fig. 4.2.4. Subtropical climate region by Trewartha's climate classification using observational data (1975 ~ 1990) 126
Fig. 4.2.5. Subtropical climate region by Trewartha's climate classification using observational data (1991 ~ 2005) 126
Fig. 4.2.6. SST and anomalies (℃) (contour: mean SST for 1998~2005, shaded: anomalies of mean SST for 1996~2005 relative to the 1971 ~2000 mean) 126
Fig. 4.2.7. Subtropical climate region by Trewartha's climate classification using MM5 (A1B scenario) 128
Fig. 4.2.8. Subtropical climate region by Trewartha's climate classification using MM5 (A1B scenario) 129
Fig. 4.2.9. The projection of subtropical climate region change by the end of the 21st century. The red line indicates the future (2071~2100) projected northern limit derived from current (1971~2000) observed data (purple line)... 130
Fig. 4.3.1. The change of onset date and duration of natural seasons in Seoul 138
Fig. 4.3.2. Same as in Fig. 4.3.1, but for Incheon 139
Fig. 4.3.3. Same as in Fig. 4.3.1, but for Gangneung 140
Fig. 4.3.4. Same as in Fig. 4.3.1, but for Jeonju 140
Fig. 4.3.5. Same as in Fig. 4.3.1, but for Daegu 141
Fig. 4.3.6. Same as in Fig. 4.3.1, but for Mokpo 141
Fig. 4.3.7. Same as in Fig. 4.3.1, but for Busan 141
Fig. 4.3.8. Annual mean temperature anomalies (℃) from 1971~2000 mean over Korea (125 ˚E~ 130 ˚E, 34.5 ˚N~42 ˚N) based on KMA observations (solid line with filled circle) and MM5 (A1B... 142
Fig. 4.3.9. The change of summer and winter durations in Seoul 144
Fig. 4.3.10. Same as in Fig. 4.3.9, but for Incheon 144
Fig. 4.3.11. Same as in Fig. 4.3.9, but for Gangneung 144
Fig. 4.3.12. Same as in Fig. 4.3.9, but for Jeonju 145
Fig. 4.3.13. Same as in Fig. 4.3.9, but for Daegu 146
Fig. 4.3.14. Same as in Fig. 4.3.9, but for Mokpo 146
Fig. 4.3.15. Same as in Fig. 4.3.9, but for Busan 146
Fig. 4.3.16. The changes of Heating degree days averaged across seven wether stations(Incheon, Seoul, Gangneung, Jeonju, Daegu, Mokpo, Busan) 147
Fig. 4.4.1. Annual and seasonal near surface temperature changes [℃] for the period of 2021~2050 and 2071~2100 relative to 1971~2000 mean from MM5 simulations based on SRES A1B. Area-averaged value is depicted at the top of each panel. 151
Fig. 4.4.2. Time series of annual and seasonal mean temperature change with respect to the 30-year period of 1971~2000 over Korean peninsula. 152
Fig. 4.4.3. Annual and seasonal mean temperature change in different latitude for the period of 2071~2100 with respect to the 30-year period of 1971~2000. 152
Fig. 5.2.1. Introduction and coupling strategy of the earth system model including the atmosphere-ocean-sea ice-land process. 174
Fig. 5.2.2. Introduction and coupling strategy of the unit climate processes such as biogeochemistry and atmospheric chemistry from the earth system model. 175
Fig. 5.3.1. First phase plan for the development of the earth system model. 182
Fig. 5.3.2. Second phase plan for the development of the earth system model. 183
SRES 시나리오에 의한 동아시아 상세 기후변화 시나리오 생산(III) 252
Fig. 2.1.1. The MM5 model domain and terrain height. 263
Fig. 2.2.1. Various emission scenarios in Special Report on Emission Scenarios.... 264
Fig. 3.2.1. Surface air temperature difference between MM5 and MM5_CO2 (MM5_CO2 minus MM5).Shading interval is 0.1˚C. 267
Fig. 3.2.2. Monthly mean surface air temperature over the South korea region. 268
Fig. 3.2.3. Precipitation difference between MM5 and MM5_CO2 (MM5_CO2 minus MM5).Shading interval is 0.05 mm/day. 269
Fig. 3.2.4. Monthly mean precipitation over the South korea region. 270
Fig. 3.2.5. Monthly mean precipitation over the South korea region for ECHAM4 T106. 271
Fig. 4.1.1. Flow chart of dynamic downscaling using MM5 from ECHAM4. 274
Fig. 5.1.1. Averaged precipitation in spring over the East Asia for current climate state. Contour interval is 2 mm/day. 277
Fig. 5.1.2. Same as Fig. 5.1.1 except for summer. 278
Fig. 5.1.3. Same as Fig. 5.1.1 except for autumn. 279
Fig. 5.1.4. Same as Fig. 5.1.1 except for winter. 280
Fig. 5.1.5. Monthly mean precipitation over the South korea region for current climate state. 282
Fig. 5.2.1. Averaged surface air temperature in spring over the East Asia for current climate state. Contour interval is 3˚C. 284
Fig. 5.2.2. Same as Fig. 5.2.1 except for summer. 285
Fig. 5.2.3. Same as Fig. 5.2.1 except for autumn. 286
Fig. 5.2.4. Same as Fig. 5.2.1 except for winter. 287
Fig. 5.2.5. Monthly mean surface air temperature over the South Korea region for current climate state. 289
Fig. 5.3.1. Averaged 500 hPa geopotential height in spring over the East Asia for current climate state. Contour interval is 60 gpm. 291
Fig. 5.3.2. Same as Fig. 5.3.1 except for summer. Contour interval is 30 gpm. 292
Fig. 5.3.3. Same as Fig. 5.3.1 except for autumn. 294
Fig. 5.3.4. Same as Fig. 5.3.1 except for winter. 295
Fig. 5.3.5. Monthly mean 500 hPa geopotential height over the South Korea region for current climate state. 296
Fig. 5.4.1. Averaged 300 hPa zonal wind in spring over the East Asia for current climate state. Contour interval is 5 m/s. 298
Fig. 5.4.2. Averaged 200 hPa zonal wind in summer over the East Asia for current climate state. Contour interval is 5 m/s. 299
Fig. 5.4.3. Same as Fig. 5.4.1 except for autumn. 300
Fig. 5.4.4. Same as Fig. 5.4.1 except for winter. Contour interval is 10 m/s. 302
Fig. 5.4.5. Monthly mean upper level zonal wind over the South Korea region for current climate state. 303
Fig. 6.1.1. Averaged precipitation in spring over the East Asia for years 2079 ~ 2100 and it's difference to that of years 1979~2000. Dashed lines represent the negative value and positive regions are shaded. Contour interval is 2 mm/day for (a), (c), (e) and 0.5 mm/day for (b), (d), (f). 305
Fig. 6.1.2. Same as Fig. 6.1.11 except for summer. Contour interval is 1 mm/day for (b), (d), (f). 306
Fig. 6.1.3. Same as Fig. 6.1.1 except for autumn. 308
Fig. 6.1.4. Same as Fig. 6.1.1 except for winter. 309
Fig. 6.1.5. Annual mean precipitation in the current (1979~2000) and future (2079~2100) periods over the South Korea region. 311
Fig. 6.1.6. Change of monthly mean precipitation over the South Korea region (2079~2100 minus 1979~2000) 311
Fig. 6.2.1. Averaged surface air temperature in spring over the East Asia for years 2079~2100 and it's difference to that of years 1979~2000. Contour interval is 3˚C for (a), (c), (e) and 0.5˚C for (b), (d), (f). 313
Fig. 6.2.2. Same as Fig. 6.2.1 except for summer. 314
Fig. 6.2.3. Same as Fig. 6.2.1 except for autumn. 315
Fig. 6.2.4. Same as Fig, 6.2.1 except for winter. Dashed lines represent the negative value and positive regions are shaded. 316
Fig. 6.2.5. Annual mean surface air temperature in the current (1979-200) and future (2079-2100) periods over the South Korea region. 318
Fig. 6.2.6. Change of monthly mean surface air temperature over the South Korea region (2079~2100 minus 1979~2000). 318
Fig. 6.3.1. Averaged precipitation in spring over the East Asia for years 2079~2100 and it's difference to that of years 1979 ~2000. Contour interval is 60 gpm for (a),(c),(e) and 5 gpm for (c), (d), (f). 322
Fig. 6.3.2. Same as Fig. 6.3.1 except for summer. Contour interval is 30 gpm for (a),(c),(e) and 5 gpm for (c), (d), (f). 323
Fig. 6.3.3. Same as Fig. 6.3.1 except for autumn. 324
Fig. 6.3.4. Same as Fig. 6.3.1 except for winter. Contour interval is 60 gpm for (a),(c),(e) and 10 gpm for (c), (d), (f). 325
Fig. 6.3.5. Annual mean 500 hPa geopotential height in the current (1979~2000) and future (2079~2100) periods over the South Korea region. 327
Fig. 6.3.6. Change of monthly mean 500 hPa geopotential height over the South Korea region (2079~ 2100 minus 1979~2000). 327
Fig. 6.4.1. Averaged 300 hPa Zonal wind in spring over the East Asia for years 2079~2100 and it's difference to that of years 1979~2000. Dashed lines represent the negative bale and positive regions are shaded. Contour interval is 5 m/s for (a),(c),(e) and 1 m/s for (c), (d), (f). 329
Fig. 6.4.2. Averaged 200 hPa Zonal wind in spring over the East Asia for years 2079~2100 and it's difference to that of years 1979~2000. Contour interval is 5 m/s for (a),(c),(e) and 1 m/s for (c), (d), (f). 330
Fig. 6.4.3. Same as Fig. 6.4.1 except for autumn. 331
Fig. 6.4.4/6.4.3. Same as Fig. 6.4.1 except for winter. 332
Fig. 6.4.5. Annual mean upper level zonal wind in the current (1979~2000) and future (2079~2100) periods over the South Korea region. 335
Fig. 6.4.6. Change of monthly mean upper level zonal wind over the South Korea region (2079~2100 minus 1979~ 2000). 335
기후변화 영향평가 및 적응방안을 위한 파일로트 연구(II) 347
Fig. 2.1.1. Assessment of vulnerability and impact of climate change in Naju plain. 368
Fig. 2.2.1. Field investigation region for staple crops. 371
Fig. 2.2.2. Field investigation region for fruits. 372
Fig. 2.2.3. Field investigation region for vegetables. 373
Fig. 2.3.1. The changing trend of population in Naju (1985~2005). 377
Fig. 2.3.2. The changing trend of agricultural population in Naju. 378
Fig. 2.3.3. The changing trend of farmhouse number in Naju. 379
Fig. 3.1.1. Changes of rice paddy area and rice production. 381
Fig. 3.1.2. Change of rice yield (ton/ha) in Naju. 382
Fig. 3.1.3. Relationship of rice yield (ton/ha) and cloud. 383
Fig. 3.1.4. Change of barley safe cultivation zones (left: 1974-1986, right: 1987-2000, Sim et al.(2004)). 384
Fig. 3.1.5. Change of naked barley yield in Naju. 385
Fig. 3.1.6. Change of malting barley yield in Naju. 385
Fig. 3.1.7. Change of naked barley yield (ton/ha) in Naju. 386
Fig. 3.1.8. Change of malting barley yield (ton/ha) in Naju. 387
Fig. 3.1.9. Relationship of naked barley yield (ton/ha) and January mean temperature (Tmin1). 387
Fig. 3.1.10. Relationship of malting barley yield (ton/ha) and January mean temperature (Tmean1). 388
Fig. 3.1.11. Change of cumulated hours of 7.2℃ below in winter. 390
Fig. 3.1.12. Change of pear yield (ton/ha) in Naju. 390
Fig. 3.1.13. Change of persimmon yield (ton/ha) in Naju. 393
Fig. 3.1.14. Last occurrence day of spring frost. 394
Fig. 3.1.15. Change of hot pepper yield (ton/ha) in Naju. 396
Fig. 3.1.16. Change of 15℃ below days and 30℃ above days of daily mean temperature. 397
Fig. 3.1.17. Change of cumulated temperature after blooming. 397
Fig. 3.1.18. Change of chinese cabbage yield (ton/ha) in Naju. 398
Fig. 3.1.19. Change of radish yield (ton/ha) in Naju. 399
Fig. 3.1.20. Relationship of chinese cabbage yield (ton/ha) and rainfall days. 400
Fig. 3.1.21. Change of dropwort yield (ton/ha) in Naju. 402
Fig. 3.2.1. Change of rice paddy area in Naju. 404
Fig. 3.2.2. Regional change of rice paddy area in Naju.... 405
Fig. 3.2.3. Change of barley cultivation area in Naju (up: naked barley down: malting barley). 408
Fig. 3.2.4. Regional change of barley cultivation area in Naju.... 409
Fig. 3.2.5. Change of pear cultivation area in Naju. 411
Fig. 3.2.6. Regional change of pear cultivation area in Naju.... 412
Fig. 3.2.7. Change of persimmon cultivation area in Naju. 414
Fig. 3.2.8. Regional change of persimmon cultivation area in Naju.... 415
Fig. 3.2.9. Change of hot pepper cultivation area in Naju. 417
Fig. 3.2.10. Regional change of hot pepper cultivation area in Naju.... 418
Fig. 3.2.11. Change of chinese cabbage and radish cultivation area in Naju(up: chinese cabbage, down: radish). 420
Fig. 3.2.12. Regional change of chinese cabbage cultivation area in Naju.... 421
Fig. 3.2.13. Regional change of radish cultivation area in Naju.... 422
Fig. 3.2.14. Change of dropwort cultivation area in Naju. 423
Fig. 3.2.15. Regional change of dropwort cultivation area in Naju.... 424
Fig. 4.1.1. Trends of rice heading date. 427
Fig. 4.1.2. Trends of barley heading date. 429
Fig. 4.1.3. Trends of barley maturity date. 430
Fig. 4.1.4. Trends of pear sprouting date. 432
Fig. 4.1.5. Trends of pear flowering date. 433
Fig. 4.1.6. Trends of pear full flowering date. 433
Fig. 4.1.7. Trends of pear maturity date. 434
Fig. 4.1.8. Correlation between rice heading date and maximum temperature (Tmax). 435
Fig. 4.1.9. Correlation between barley heading date and maximum temperature (Tmax). 437
Fig. 4.1.10. Correlation between barley heading date and maturity date. 437
Fig. 4.1.11. Correlation between barley maturity date and May minimum temperature (Tmin5). 438
Fig. 4.1.12. Correlation between pear sprouting date and mean February-March maximum temperature (Tmax23). 439
Fig. 4.1.13. Correlation between pear flowering date and mean February-April maximum temperature (Tmax24). 440
Fig. 4.1.14. Correlation between pear full flowering date and February-April average temperature (Tave24). 441
Fig. 4.1.15. Correlation between maturity date and full flowering date. 441
Fig. 4.1.16. Correlation between maturity date and February-April average temperature (Tave24). 442
Fig. 4.1.17. Trends of late frost date. 443
Fig. 4.2.1. Trends of rice plant length. 445
Fig. 4.2.2. Trends of rice stem length. 446
Fig. 4.2.3. Trends of rice spike length. 446
Fig. 4.2.4. Trends of rice grain numbers per ㎡. 447
Fig. 4.2.5. Trends of rice grain numbers per spike. 448
Fig. 4.2.6. Trends of percent ripened grain. 448
Fig. 4.2.7. Trends of barley stem length. 449
Fig. 4.2.8. Trends of barley spike length. 450
Fig. 4.2.9. Trends of barley grain numbers per ㎡. 450
Fig. 4.2.10. Trends of barley grain numbers per spike. 451
Fig. 4.2.11. Trends of pear brix. 452
Fig. 4.2.12. Trends of pear fruit weight. 453
Fig. 4.2.13. Trends of radish plant length. 454
Fig. 4.2.14. Trends of radish leaf number. 455
Fig. 4.2.15. Trends of Chinese cabbage plant length. 456
Fig. 4.2.16. Trends of Chinese cabbage leaf number. 457
Fig. 4.2.17. Trends of hot pepper plant length(6/16, 7/1, 7/16). 458
Fig. 4.2.18. Trends of hot pepper plant length(8/1, 8/16, 9/1, 9/16). 458
Fig. 4.2.19. Trends of hot pepper fruit set numbers. 459
Fig. 4.2.20. Correlation between rice plant length and July maximum temperature (Tmax7). 461
Fig. 4.2.21. Correlation between rice stem length and July average temperature (Tave7). 461
Fig. 4.2.22. Correlation between rice spike length and August average temperature (Tmin8). 462
Fig. 4.2.23. Correlation between rice grain numbers per m² and May sunshine duration. 463
Fig. 4.2.24. Correlation between rice grain numbers per spike and August minimum temperature (Tmin8). 464
Fig. 4.2.25. Correlation between rice percent ripened grain and accumulated temperature. 465
Fig. 4.2.26. Correlation between barley stem length and May maximum temperature (Tmax5). 466
Fig. 4.2.27. Correlation between barley spike length and average temperature (left: March, right: May). 466
Fig. 4.2.28. Correlation between barley grain numbers per m² and May average temperature (Tave5). 467
Fig. 4.2.29. Correlation between barley grain numbers per ear and April precipitation. 467
Fig. 4.2.30. Correlation between Pear brix and August maximum temperature (Tmax8). 468
Fig. 4.2.31. Correlation between pear brix and August sunshine duration. 469
Fig. 4.2.32. Correlation between pear brix and August radiation. 469
Fig. 4.2.33. Correlation between pear weight and September average temperature (Tave9). 470
Fig. 4.2.34. Correlation between radish plant length and September maximum temperature (Tmax9). 471
Fig. 4.2.35. Correlation between radish leaf numbers and September average temperature (Tave9). 472
Fig. 4.2.36. Correlation between chinese cabbage plant length and September average temperature (Tave9). 473
Fig. 4.2.37. Correlation between chinese cabbage leaf numbers and September mafmum temperature (Tmax9). 473
Fig. 4.2.38. Correlation between hot pepper plant length and May minimum temperature (Tmin5). 474
Fig. 4.2.39. Correlation between hot pepper fruit numbers and August average temperature (Tave8). 475
Fig. 4.3.1. Monthly trends of rice sheath blight. 478
Fig. 4.3.2. Annual trends of rice sheath blight. 478
Fig. 4.3.3. Monthly trends of rice leaf folder. 479
Fig. 4.3.4. Annual trends of rice leaf folder. 479
Fig. 4.3.5. Annual trends of Xanthomonas oryzae pv. oryzae, Burkholderia glumae and brown planthopper. 480
Fig. 4.3.6. Trends of phytophthora bligh. 482
Fig. 4.3.7. Trends of Colletotrichum gloeosporioides. 483
Fig. 4.3.8. Correlation between rice sheath blight and precipitation. 484
Fig. 4.3.9. Correlation between rice sheath blight and relative humidity. 484
Fig. 4.3.10. Correlation between rice leaf folder and precipitation. 485
Fig. 4.3.11. Correlation between precipitation and Xanthomonas oryzae pv. oryzae, Burkholderia glumae and brown planthopper. 485
Fig. 4.3.12. Correlation between phytophthora blight and rainfall days. 486
Fig. 4.3.13. Correlation between Colletotrichum gloeosporioides and rainfall days. 487
Fig. 4.4.1. Trend of rice seeding date. 488
Fig. 4.4.2. Trend of radish seeding date. 488
Fig. 4.4.3. Trend of Chinese cabbage planting date. 489
Fig. 4.4.4. Trend of hot pepper seeding date. 490
Fig. 4.4.5. Trend of hot pepper planting date. 491
Fig. 4.4.6. Trend of hot pepper harvesting date. 492
Fig. 4.4.7. Correlation between Chinese cabbage planting date and August minimum temperature (Tmin8). 493
Fig. 4.4.8. Correlation between hot pepper planting date and April average temperature (Tave4). 494
Fig. 5.2.1. The elevation of study area. 499
Fig. 5.2.2. The inundated area of 1934 and 1964 years. 501
Fig. 5.2.3. The geological map in study area. 501
Fig. 5.2.4. The track of 2004 typhoon megi. 515
Fig. 5.2.5. The infrared image of 2004 typhoon megi. 515
Fig. 5.2.6. Distribution of precipitation by 2004 typhoon megi. 517
Fig. 6.2.1. The change of inundated area in study area. 521
Fig. 6.2.2. The variation of precipitation in study area(1961~1990 mean deviation). 522
Photo 4.1.1. Rice after heading (August 24, 2007). 426
Photo 4.1.2. Barley ahead of heading stage (April 7, 2007). 428
Photo 4.1.3. Barley ahead of harvest (May 26, 2007). 428
Photo 4.1.4. Pear during full flowering period (April 14, 2007). 431
Photo 4.1.5. Pear after mean maturity date (October 6, 2007). 431
Photo 4.1.6. Damage of pear by late frost (May 5, 2007). 443
Photo 4.1.7. Facilities for prevention from late frost damage (May 5, 2007). 444
Photo 4.2.1. Growing radish (October 6, 2007). 454
Photo 4.2.2. Growing of chinese cabbage (October 19, 2007). 455
Photo 4.2.3. Growing hot pepper (May 26, 2007). 459
Photo 4.3.1. Rice sheath blight (October 6, 2007). 476
Photo 4.3.2. Brown planthopper. 477
Photo 4.3.3. Phytophthora blight. 481
Photo 4.3.4. Colletotrichum gloeosporioides. 481
Photo 4.4.1. Planting of hot pepper (May 5, 2007). 491
Photo 5.2.1. Study area.... 497
Photo 5.2.2. Fluvial terrace.... 498
Photo 5.2.3. Rivetment.... 500
Photo 5.2.4. The flooding area by means of 2004 typhoon megi. 518