[보고서]고해상도 전구모델을 활용한 RCP 시나리오 기반 한반도 상세 기후전망 자료 생산

고해상도 전구모델을 활용한 RCP 시나리오 기반 한반도 상세 기후전망 자료 생산
Production of detailed climate projection over korean peninsula using high-resolution global model based on RCP scenario 원문보기

보고서 정보
주관연구기관	부경대학교 Pukyong National University
보고서유형	1단계보고서
발행국가	대한민국
언어	한국어
발행년월	2015-02
과제시작연도	2014
주관부처	기상청 Korea Meteorological Administration(KMA)
등록번호	TRKO201500013496
과제고유번호	1365001935
사업명	기후변화 감시ㆍ예측 및 국가 정책 지원 강화
DB 구축일자	2015-08-15
키워드	기후변화.RCP 시나리오.고해상도 전구 모델.전지구 상세 기후전망.Climate change.RCP scenario.High-resolution global model.Future climate projection.
DOI	https://doi.org/10.23000/TRKO201500013496

초록 ▼

• 고해상도 전구모델을 활용한 현재기후(1979-2010년) 자료 생산 및 검증
- 전구모델 GME(40-km)를 활용한 AMIP-type 현재기후 자료 생산
- 관측자료, 타 기후모델 결과와의 기온, 강수, 몬순 시스템 등 비교를 통한 전구모델의 모의성능 검증
• RCP 4.5, 8.5 기반 전구모델을 활용한 미래기후(2011~2100년) 상세 전망 자료 생산 및 기후변동성 분석
- RCP 4.5, 8.5 기반 4개의 CMIP5 모델 결과 수집을 통한 전구모델의 경계자료 생성
- RCP 4.5, 8.5에

Abstract ▼

Ⅳ. Results
∘ Producing present climate(1979-2010) data and verifying performance of simulation using global high resolution model
- Model capture the global seasonal mean and zonal mean of temperature, precip itation and zonal wind in present climate(1979-2010)
- In Taylor analysis on geopotential height, precipitation, wind, OLR etc. most of variables show high skill score and model precipitation is coincident with APHRODITE data.
- In case of global monsoon, the performance of GME model is the lowest among 4 CMIP5 model but, GME model capture well distribution and monthly variation of Asia summer monsoon
∘ Producing future climate(2010-2100) data using global high resolution model GME based on RCP8.5, 4.5
- The results of future climate projection based on RCP8.5, 4.5 scenario shows in creasing trend of global mean time series and RCP8.5 is especially higher increase of temperature than RCP4.5, which is coincident with the results of IPCC AR5.
- Through categorizing 3 periods (Near-future, Mid-future, Far-future) based on RCP8.5, 4.5 scenario about future climate, temperature increase linearly and it in autumn and winter is higher than other season.
- Future climate variation in Korea is similar to characteristic in Asia region based on RCP8.5, 4.5 scenario. temperature, and precipitation
- Based on RCP8.5, 4.5 scenario in analyzing the number of days with frost, heat wave days and tropical night days in Korea, frost days increase in east region of Korea and the trend of heat wave days and tropical night increase in capital area, south central and southwest region, which is significant at the 95% level.
- Based on RCP4.5 scenario in analyzing the number of raining days, heavy rainf all and no rainfall the variation of precipitation is insignificant due to variability.But the number of precipitation in the Tae Baek Mountains shows decrease, the number of no rainfall in south region increase markedly, but small increasing distrib ution around capital region and there's no trend of increase on the number of heavy rainfall.

목차 Contents

표지 ... 1
제출문 ... 3
보고서 요약서 ... 5
요약문 ... 7
SUMMARY ... 11
CONTENTS ... 15
목차 ... 18
표목차 ... 21
그림목차 ... 23
제1장 연구개발과제의 개요 ... 31
제1절 연구개발의 최종 목표 ... 31
제2절 연구개발의 필요성 및 범위 ... 31
제3절 단계별 연구개발 목표 및 범위 ... 36
1. 1차년도 연구개발 목표 및 범위 ... 36
2. 2차년도 연구개발 목표 및 범위 ... 37
3. 3차년도 연구개발 목표 및 범위 ... 37
제2장 국내외 기술개발 현황 ... 38
제3장 연구개발수행 내용 및 결과 ... 51
제1절 이론적, 실험적 접근방법 ... 51
1. 고해상도 전구모델(GME)을 이용한 AMIP-type 현재기후(1979-2010년) 모의 실험 ... 51
2. RCP8.5, 4.5 기반 GME를 이용한 상세 미래기후(2011~2100년) 전망 자료실험 ... 63
3. 현재기후의 모의 성능 평가를 위한 관측 및 모델 자료 ... 67
4. KISTI 전산자원 및 부경대 슈퍼컴퓨터센터의 전산자원 기반 미래 기후전망 실험 기반 구축 ... 69
제2절 연구내용 및 결과 ... 72
1. 고해상도 전지구 모델(GME)의 AMIP-type 현재기후(1979-2010년) 모의평가 ... 72
2. RCP8.5, 4.5 기반 GME를 이용한 상세 미래기후 전망 결과 분석 ... 95
3. RCP 시나리오에 따른 ENSO와 IOD가 한반도 여름철 기온 및 강수량에 미치는 영향 ... 105
4. RCP 시나리오에 따른 열대저기압(TCs) 발생에 관한 연구 ... 112
5. RCP 시나리오에 따른 북반구 해빙면적의 변동성에 따른 항로의 변화분석 ... 117
6. RCP 시나리오에 따른 남반구 해빙 면적의 변동성 및 지역별 추세 분석 ... 120
제3절 연구개발 성과 ... 123
1. 1차년도 연구개발 성과 ... 123
2. 2차년도 연구개발 성과 ... 153
3. 3차년도 연구개발 성과 ... 191
제4장 목표달성도 및 관련분야에의 기여도 ... 193
제1절 연구 추진 목표 ... 193
제2절 세부 연구목표별 달성도 ... 193
1. 1차년도 세부 연구목표별 달성도 ... 193
2. 2차년도 세부 연구목표별 달성도 ... 194
3. 3차년도 세부 연구목표별 달성도 ... 195
제3절 관련분야에의 기여도 ... 195
제5장 연구개발결과의 활용계획 ... 198
제6장 연구개발과정에서 수집한 해외과학기술정보 ... 204
1. 전지구 상세 장기 기후 전망 실험에 관한 자문회의 ... 204
2. 전지구 상세 미래기후 전망 결과 활용을 위한 해외 유사 연구와의 연계 ... 204
제7장 연구시설 · 장비 현황 ... 206
1. 자료 분석용 컴퓨터 서버 구입 ... 206
2. 기후실험 결과 분석용 스토리지 구입 ... 207
3. 기후실험 결과 분석용 스토리지 구입 ... 208
제8장 참고문헌 ... 209
제9장 연구개발과제 수행에 따른 연구실 등의 안전조치 이행실적 ... 213
끝페이지 ... 215

표/그림 (78)

표 Global mean surface temperature anomaly and 2005 surface temperature anomaly
표 New RCP scenarios
표 Radiative forcing and Emissions of four RCP scenarios
표 Model evaluation of CMIP3
표 Experiment results on dependence of domain size and location of RCMs
표 CMIP5 multi-model simulated time series from 1950 to 2100 for (a) change in global annual mean surface temperature relative to 1986–2005, (b) Northern Hemisphere September sea ice extent (5-year running mean), and (c) global mean ocean surface pH
표 Maps of CMIP5 multi-model mean results for the scenarios RCP2.6 and RCP8.5 in 2081–2100 of (a) annual mean surface temperature change, (b) average percent change in annual mean precipitation, (c) Northern Hemisphere September sea ice extent, and (d) change in ocean surface pH. Changes in panels (a), (b) and (d) are shown relative to 1986–2005
표 Model list and resolution information of CMIP3 and CMIP5
표 CORDEX Experiment design
표 CORDEX Data portal service
표 CORDEX East Asia region
표 Climate simulation in MRI
표 Grid Generation by successive halving the triangles edges to form new triangles.
표 Icosahedral-hexagonal grid at different resolutions. ni means resolution (i.e. number of intervals on main triangle side) and Δmin, Δav and Δmax means minimum, average and maximum mesh size. nGP is total number of grid points on sphere (nGP = 10ni2 + 2).
표 Logical data structure of the icosahedral-hexagonal GME grid.
표 Structure of the GME grid which consists of 10 diamonds.
표 Domain decomposition for 6 processors: Each diamond is divided into six sub-domains. One processor handles one sub-domain per diamond.
표 2-D domain decomposition of a diamond at ni = 192 for 18x20 PEs.
표 Schematic representation of the processes included in GME
표 PKNU Experiment design for model evaluation
표 Radiative forcing of RCP scenario
표 PKNU Experiment design for model projection
표 Various observation dataset of mean precipitation
표 Computing Resources for long-term climate simulation using high-resolution AGCM
표 Computing resources for climate projection data storage and analysis
표 Data processing system of Climate projection
표 Spatial distribution of seasonal mean precipitation in Summer [June-August (JJA)] for (a) the GME model (40-km, 1979-2009, 31 years), (b) observation of CMAP (2.5o, 1979-2009, 31 years), (c) observation of GPCP (2.5o, 1979-2009, 31 years) and (e), (f) difference between the GME model and observations (CMAP and GPCP). (d) Seasonal zonal-mean precipitation in JJA and for the GME model (solid line), observation of CMAP (dot-dash line) and observation of GPCP (dot line). Units are mm day-1..
표 same as Fig 3.14, but in Winter [January-February (DJF)]
표 Horizontal distribution of climatological seasonal mean air 2m temperature in (a), (b) Summer [June-August (JJA)] and (c), (d) Winter [December-February (DJF)]. Shading indicates difference from the climatology of NCEP2 and ERA Interm. Units are degree C.
표 Zonal-averaged Air 2m temperature in (a) Winter [December-February (DJF)] and (b) Summer [June-August (JJA)] GME model (solid line), observation of NCEP2 (dot-dash line) and observation of ERA-Interim (dash line). Units are degree C.
표 Zonal-averaged Mean Sea Level Pressure in (a) Winter [December-February (DJF)] and (b) Summer [June-August (JJA)] GME model (solid line), observation of NCEP2 (dot-dash line) and observation of ERA-Interim (dash line). Units are hPa.
표 Zonal-averaged zonal wind at 850hPa in (a) Winter [December-February (DJF)] and (b) Summer [June-August (JJA)] GME model (solid line), observation of NCEP2 (dot-dash line) and observation of ERA-Interim (dash line). Units are degree m/s.
표 Zonal-averaged zonal wind at 200hPa in (a) Winter [December-February (DJF)] and (b) Summer [June-August (JJA)] GME model (solid line), observation of NCEP2 (dot-dash line) and observation of ERA-Interim (dash line). Units are degree m/s.
표 Seasonal averages of zonal-mean temperatures in (a), (b), (c) Winter [December-February (DJF)] and (d), (e), (f) Summer [June-August (JJA)] for GME model, observation of NCEP2 and ERA-Interim. Units are degree C.
표 Seasonal averages of zonal wind velocities in (a), (b), (c) Winter [December-February (DJF)] and (d), (e), (f) Summer [June-August (JJA)] for GME model, observation of NCEP2 and ERA-Interim. Units are m/s.
표 Taylor diagram for the global and Asia region. The terms "PRCP", "Z500", "SLP", "T850", "U850", "W850", "W200" and "OLR" indicate precipitation, geopotential height at 500hPa, sea level pressure, temperature at 850hPa, zonal velocity at 850hPa, wind speed at 850hPa and 200hPa, and longwave radiation. The skill for precipitation is compared with GPCP and APHRODITE (over Asia) and skill of GPCP data relative to CMAP and APHRODITE is plotted by mark asterisk for reference. Other variables are compared with ERA Interm and OLR is validated with EBAF data. And in case of precipitation, CMIP5 models are also compared with GPCP (open circles) and APHRODITE (open circles & point) used for comparison.
표 Global monsoon precipitation domain referred by Wand et al., (2012)
표 Global monsoon area (GMA) for GME model, observation (CMAP, GPCP, GPCP1DD and TRMM) and 4 CMIP5 model. GMA is defined as the regions where the annual range (i.e., the difference between local summer and winter) of precipitation exceeds 1.5 mm day-1, and the local summer precipitation exceeds 55% of annual rainfall.
표 Global monsoon precipitation (GMP) for GME model, observation (CMAP, GPCP, GPCP1DD and TRMM) and 4 CMIP5 model. GMP is defined as total summer monsoon rainfall falling in the monsoon domain (GMA).
표 Mean of Global monsoon area (GMA), Global monsoon precipitation (GMP) and Global monsoon intensity (GMI) over Global and 6 monsoon regions (Asian, Australian, North America, South America, North Africa and South Africa) for GME model, observations (CMAP, GPCP) and 4 CMIP5 model with minimum/maximum bar. Units are ×107 km2 (GMA), × 1011 m3 d-1 (GMP) and mm d-1 (GMI), respectively.
표 Simulation biases of global monsoon activities [GMA (global monsoon area), GMP (global monsoon precipitation), and GMI (global monsoon intensity) relative to GPCP observation [i.e., (Xmodel - Xobs.)/X obs.]. For the comparison, CMIP5 best models (referred by Lee and Wang, 2014) and their average are also used.
표 Performance using NRMSD (Normalized Root Mean Square Difference) and PCC (Pattern Correlation Coefficient) on Global Monsoon Activity: AMP (Annual Mean Precipitation), GMA (Global Monsoon Area), GMP (Global Monsoon Precipitation) relative to observation (GPCP). For comparison, other observations (CMAP, GPCP1DD) are also used.
표 Monthly rainfall variations within the northern hemispheric and southern hemispheric monsoon regions. GME model (soild line with big circle) are compared with CMAP, GPCP, GPCP1DD observation data (all dot line with small circle). The four CMIP5 models are also used (shaded).
표 Spatial distribution of mean precipitation in JJA [June-August] over Asia summer monsoon region for (a) GME model, (b-f) observations (CMAP, GPCP, GPCP1DD, TRMM and APHRODITE) and (g-j) 4 CMIP5 models (CanESM2, CNRM-CM5, HadGEM2-ES and MIROC5). Units are mm day-1.
표 Zonal-averaged precipitation in Asian summer monsoon region (65-145oE) for (a) GME model, (b-e) observations (CMAP, GPCP, GPCP1DD and TRMM) and (g-j) 4 CMIP5 models (CanESM2, CNRM-CM5, HadGEM2-ES and MIROC5). Units are mm day-1.
표 Annual cycle of precipitation in main countries over Asia monsoon regions. (a) India, (b) Mongolia, (c) China. (d) Korea and (e) Japan. Units are mm day-1.
표 Climatological Seasonal cycle of Asian monsoon indices. (a) Webster-Yang monsoon index (WYI, Webster and Yang, 1992), (b) Indian monsoon index (IMI, Wang and Fan,1999), (c) Western North Pacific monsoon index (WNPI, Wang et al., 2001), and (d) South Asia monsoon index (SAMI, Gos
표 Global Annual mean of future climate projection in air 2m temperature (unit: degree C) and mean precipitation (unit: mm/day) during 2006-2100 relative to current climate (1979-2005) based on RCP scenarios (RCP8.5 and RCP4.5).
표 Future seasonal change of Air 2m temperature in near-future (2010-2039), mid-future (2040-2069) and far-future (2070-2099) relative to current (1979-2005). Units are degree C.
표 same as Fig 3.36, but precipitation. Units are %.
표 Future seasonal change of precipitation and 850hPa wind in near-future (2010-2039), mid-future (2040-2069) and far-future (2070-2099) relative to current (1979-2005). Units are % for precipitation and m/s for wind.
표 Future change of time-latitude cross section of monthly precipitation in near-future (2010-2039), mid-future (2040-2069) and far-future (2070-2099) relative to current (1979-2005). Units are %.
표 Future seasonal change of interannual variability in near-future (2010-2039), mid-future (2040-2069) and far-future (2070-2099) relative to current (1979-2005). Units are %.
표 Future seasonal change of Air 2m temperature over korean peninsula in near-future (2010-2039), mid-future (2040-2069) and far-future (2070-2099) relative to current (1979-2005). Units are degree C.
표 Same as Fig. 3.41, but mean precipitation. Units are %.
표 Future change of extreme temperature indices (frost days, heat wave days and tropical nights) in Far-future (2070-2099) relative to current (1979-2005) and time series during 2010-2100 relative to current (1979-2005) over Korean peninsula based on RCP scenarios (RCP8.5 and RCP4.5). '*' indicates the statistical significance of 95% and '**' indicates the statistical significance of 99%.
표 Future change of extreme precipitation indices (wet days, heavy rainfall days and consecutive dry days) in near-future (2010-2039), mid-future (2040-2069) and far-future (2070-2099) relative to current (1979-2005) over Korean peninsula based on two RCP scenarios (RCP8.5 and RCP4.5).
표 Time series of future change in extreme precipitation indices (wet days, heavy rainfall days and Rainfall intensity) during 2010s-2090s relative to current (1979-2005) over Korean peninsula based on two RCP scenarios. There is no statistical significance of trend.
표 Indian Dipole Model
표 Normal case and El Nino+positive dipole case: 2m air temperature (left panel) and precipitation(right panel) for 1991-2010
표 Normal case and El Nino+positive dipole case: 2m air Temperature (left panel) and for near-future(2010-2030) and mid-future(2031-2060) based on RCP 4.5 scenario
표 Normal case and El Nino+positive dipole case: precipitation for Near-Future (2010-2030) and mid-future (2031-2060) based on RCP 4.5 scenario
표 Normal case and El Nino+positive dipole case: 2m air temperature (left panel) for Near-Future (2010-2030) and mid-future (2031-2060) based on RCP 8.5 scenario
표 Normal case and El Nino+positive dipole case: precipitation for Near-Future (2010-2030) and mid-future (2031-2060) based on RCP 8.5 scenario
표 Flow chart for tracking of TCs
표 Genesis locations and 3hourly tracks of TCs
표 Genesis density of TCs in the WNP basin. The best-track (upper) is a dataset in the RSMC Tokyo-Typhoon center. Blue dots in left side mean genesis locations.
표 Track density of TCs in the WNP basin. The best-track (upper) is a dataset in the RSMC Tokyo-Typhoon center.
표 The number of TCs for each regions during 1980-2009 years
표 Spatial distribution of Sea ice thickness (unit: m) of present-day climate simulation during 1979-2009 in the Northern Hemisphere for March (left) and September (right). The red line is observed 15% concentration boundary of HadlSST.
표 Spatial distribution of northern sea ice in present-day climate (black line), near-future (green line), mid-future (blue line) and far-future (red line) based on RCP scenarios (RCP4.5 and RCP8.5).
표 The ship-accessible total days by the vessel classes (PC3, PC6 and OW) during near-future (2010-2039) based on RCP scenarios (RCP4.5 and RCP8.5).
표 Antarctica region
표 Spatial distribution of Sea ice thickness (unit: m) of present-day climate simulation during 1979-2009 in the Southern Hemisphere for March and September. The red line is observed 15% concentration boundary of HadlSST.
표 Annual and monthly future change of sea ice thickness in Antarctic on RCP scenarios (RCP4.5 and RCP8.5).
표 Yearly and seasonal Antarctic sea ice extent trends for the period 2010–2040 with estimated standard deviations on RCP scenarios (RCP 8.5, RCP 4.5). ( x 10-3)
표 Objective of Research & development in this study
표 CORDEX experiment design

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고해상도 전구모델을 활용한 RCP 시나리오 기반 한반도 상세 기후전망 자료 생산
Production of detailed climate projection over korean peninsula using high-resolution global model based on RCP scenario 원문보기