[보고서]RegCM 지역기후모델을 이용한 SSP 시나리오 기반 동아시아 상세 기후변화 정보 산출

차동현

보고서 정보

주관연구기관

울산과학기술원
Ulsan National Institute of Science and Technology

연구책임자

차동현

보고서유형

최종보고서

발행국가

대한민국

언어

한국어

발행년월

2023-04

과제시작연도

2022

주관부처

기상청
Korea Meteorological Administration(KMA)

등록번호

TRKO202300003729

과제고유번호

1365003586

사업명

기후및기후변화감시∙예측정보응용기술개발

DB 구축일자

2023-07-19

키워드

지역기후 상세화 국제협력사업-동아시아에서의 태풍연구.기후변화 적응 정책수립.기후변화에 관한 정부 간 패널 6차 평가보고서.대기-해양 결합지역 기후모델.역학적 상세화.Typhoon research in CORDEX-EA.Establishment of climate change adaptation policy.IPCC 6th assessment report.Coupled regional climate model.Dynamical downscaling.

표 Simulation domain (CORDEX Ⅱ-EA) with topography used in this study
표 Model configuration of RegCM4 used in ths study
표 Description of vertically parallelized spectral nudging method in RegCM4
표 The decrease of integration time in parallelized spectral nudging experiment compared to the serial spectral nudging experiment
표 (a,c) Precipitation and (b,d) near-surface air temperature averaged over East Asia and the Korea for 1985-2100
표 Precipitation of observation data (GPCP), UK-ESM, and RegCM4 over East Asia for 1979-2014 JJA (top row) and DJF (bottom row)
표 Precipitation over East Asia for 1979-2014 JJA (top row) and DJF (bottom row): observation data (GPCP) (left), the systematic errors of UK-ESM (middle), and the difference between RegCM4 and UK-ESM (right)
표 Same as Figure 2.1.1.4 except for near-surface air temperature (°C) of observation data (APHRODITE)
표 Same as Figure 2.1.1.5 except for near-surface air temperature (°C) of observation data (APHRODITE)
표 The climatology and future change of Precipitation (mm d-1) simulated in UK-ESM and RegCM4 for historical period and SSP scenarios (SSP1-26, SSP2-45,SSP3-70, and SSP5-85)
표 Same as Figure 2.1.1.8 except for near-surface air temperature (°C)
표 Figure 2.1.1.10 Time-latitude plots of precipitation (mm d-1) in UK-ESM, RegCM4, observation data for historical period (1999-2014), in RegCM4 for future climate (2084-2099) under SSP scenarios (SSP1-26, SSP2-45, SSP3-70, and SSP5-85).
표 30-year (1985-2014) annual mean (left panels) surface air temperature (℃) and (right panels) precipitation (mm·day-1) of (1st row) observation and (2nd row) Ensembles_UKE for historical experiment
표 30-year (1985-2014) seasonal mean surface air temperature (℃) of (1st column) observation and (2nd column) Ensembles_UKE for historical experiment
표 30-year (1985-2014) seasonal mean surface air temperature (℃) of (1st column) observation and (2nd column) Ensembles_UKE for historical experiment
표 Spatial distribution of annual mean surface air temperature changes (℃) of Ensembles_UKE for late-21st century (2071-2100) compared to present climate(1985-2014) according to SSP126(left column)/585(right column) scenarios
표 Spatial distribution of annual mean precipitation (mm·day-1) of Ensembles_UKE for late-21st century (2071-2100) compared to present climate (1985-2014) according to SSP126(left column)/585(right column) scenarios
표 Spatial distribution of seasonal mean surface air temperature changes (℃) of Ensembles_UKE for during late-21st century (2071-2100) compared to present climate(1985-2014) according to SSP126(left column)/585(right column) scenarios
표 Spatial distribution of seasonal mean surface precipitation (mm·day-1) of Ensembles_UKE for during late-21st century (2071-2100) compared to present climate(1985-2014) according to SSP126(left column)/585(right column) scenarios
표 Interannual variations of annual mean surface air temperature (℃) and precipitation (mm·day-1) of (black line) obseravation, (green line) MME, (red line)CCLM_UKE, (blue line) WRF_UKE, (brown line) GRIMs_UKE, and (yellow line) RegCM_UKE for the present climate (1985-2014) averaged over South Korea for historical experiment
표 Seasonal variations of surface air temperature (℃) and precipitation(mm·day-1) of (black line) obseravation, (green line) MME, (red line) CCLM_UKE, (blue line)WRF_UKE, (brown line) GRIMs_UKE, and (yellow line) RegCM_UKE for the present climate (1985-2014) averaged over South Korea for historical experiment
표 Interannual variations of annual mean surface air temperature (℃) and precipitation (mm·day-1) of (green line) MME, (red line) CCLM_UKE, (blue line) WRF_UKE,and (gold line), (brown line) GRIMs_UKE, (yellow line) RegCM_UKE for late-21st century(2071-2100) averaged over South Korea for SSP126(left column)/SSP585(left column) scenarios experiment
표 Seasonal variations of surface air temperature (℃) and precipitation (mm·day-1) of (green line) MME, (red line) CCLM_UKE, (blue line) WRF_UKE, and (goldline), (brown line) GRIMs_UKE, (yellow line) RegCM_UKE for late-21st century (2071-2100) averaged over South Korea for SSP126(left column)/SSP585(left column) scenarios experiment
표 (수식)Description of the 5 EAWM indices. Here, U300: 300-hPa zonal wind (m s- ), Z500: 500-hPa geopotential height (gpm), V850: 850-hPa meridional speed (m s- ), SH: Siberian high, SLP: sea level pressure; and VAS: 10m meridional wind (m s- )
표 (a) The 32-year (1982-2013) averaged DJF mean near-surface air temperature (SAT, °C) observation from APRODITE_ERA5 and (b-d) the normalized SAT biases of the model (SNURCM, WRF, HadGEM3-RA, CCLM, and RegCM) compared to APRODITE_ERA5 over CORDEX-East Asia phase Ⅱ domain
표 (a) The 32-year (1982-2013) averaged DJF mean near-surface air temperature (SAT, °C) observation from APRODITE_ERA5 and (b-d) the normalized SAT biases of the model (MME, SNURCM, and WRF) compared to APRODITE_ERA5 over East Asia. The black box is the Manchuria region and the value averaged over it is in Figure 2a
표 Scatterplots of the normalized ensemble-mean EAWM index (IEns) and the normalized SAT biases between model [(a) SNURCM and (b) WRF] and APRODITE_ERA5 averaged over the Manchuria for 32-year (1982-2013). The black line is linear fits, with correlation coefficients noted in a bottom-right table (asterisks denoting significant correlation at the 0.05 level). The zero value of normalized EAWMI is shown in a vertical dashed line. The R and IEns indicate regression coefficients and ensemble mean of five EAWM indices, respectively
표 Interannual variations of the normalized EAWM indices anomaly defined by Table 2 for 33 years (1982-2013) in the ERA5 (bar), SNURCM (blue line and circlessymbol), and WRF (red line and asterisks symbol). All lines of the two RCMs are satisfied at a significance level of 0.05. The dashed lines indicate +σ and -σ of the ERA5 data. The TCC and SPC in Figure 4 are Pearson correlation coefficients and Spearman rank order correlation coefficients, respectively
표 for 33 years (1982-2013) in the ERA5 (bar), SNURCM (blue line and circles geopotential height (Z500, gpm); and (b) 850-hPa meridional speed (V850, m s-1), sea level pressure (SLP, hPa), and 10m meridional wind (VAS, m s-1) for two RCMs of the present climate reproduction experiment over East Asia
표 Interannaul variation of the EAWM index anomaly (Jhun and Lee, 2004) in (a) GCM (HadGEM2-AO, UK-ESM) and ERA5, and (b) multi-RCMs and ERA5 for 33years(1982-2014) (a) GCM (HadGEM2-AO, UK-ESM) and ERA5, and (b) multi-RCMs and ERA5 for 33years (1982-2014)
표 Standard deviation of the EAWM index anomaly (Jhun and Lee, 2004) in HadGEM2-AO, UK-ESM, and ERA5
표 Standard deviation of EAWMI in multi-RCMs and ERA5, and the correlation coefficients between model and reanalysis for EAWMI anomaly (Jhun and Lee, 2004)
표 Interannaul variation of the EAWM index anomaly (Jhun and Lee, 2004) in GCM (UK-ESM), ERA5, and multi-RCMs for 33years (1982-2014). The dotted lines indicate the value of +1.0 σ, - 1.0 σ, and zero
표 Standard deviation of EAWMI in UK-ESM, multi-RCMs, and ERA5 for EAWMI anomaly (Jhun and Lee, 2004) in Figure 2.2.2.7
표 Interannaul variation of the EAWM index anomaly (Jhun and Lee, 2004) in GCM (UK-ESM) and multi-RCMs for 33years (2068-2100) under SSP126 (left) and SSP585 (right). The dotted lines indicate the value of +1.0 σ, - 1.0 σ, and zero
표 Standard deviation of EAWMI in UK-ESM and multi-RCMs for EAWMI anomaly (Jhun and Lee, 2004) in Figure 2.2.2.8
표 Tropical Cyclone (TC) tracking threshold of RCMs forced by UKESM
표 Climatological mean of TC genesis density from (a) RSMC best track data and historical run of (b) RegCM, (c) GRIMs, (d) WRF, (e) CCLM, and (f) HadGEM3-RA during 30 years (1985-2014)
표 Climatological mean of TC track density from (a) RSMC best track data and historical run of (b) RegCM, (c) GRIMs, (d) WRF, (e) CCLM, and (f) HadGEM3-RA during 30 years (1985-2014)
표 TC Statistics for RSMC best track data and historical run of RCMs during 30 years (1985-2014). NTC indicate of number of all TCs
표 Probability density function of TC intensity in the RSMC best track data and historical run of RCMs (RegCM, GRIMs, WRF, CCLM, and HadGEM3-RA) during 1985-2014 forced by UKESM. (a) Maximum wind speed (m s-1) and (b) Minimum sea level pressure (hPa)
표 Climatological mean from RSMC best track data of (a) TC genesis density and (c) track density (left). Differences between historical run of Ensemble_UKESM and RSMC best track data (b) TC genesis density and (d) track density during 30 years (1985-2014) (right)
표 Sea surface temperature (K) from June to November for (a) climatological climatological mean of ERA5 reanalysis data and (b) difference of historical run and ERA5 reanalysis data during 30 years (1985-2014). 850 hPa specific humidity (shading, kg kg-1) and wind (vector, m s-1) from June to November for (c) climatological mean of ERA5 reanalysis data and (d) difference of historical run and ERA5 reanalysis data during 30 years (1985-2014)
표 Differences of TC genesis density between SSP1_26 run (2031-2060) and historical run (1985-2014) of (a) RegCM, (b) GRIMs, (c) WRF, (d) CCLM, and (e) HadGEM3-RA forced by UKESM
표 Differences of TC genesis density between SSP2_45 run (2031-2060) and historical run (1985-2014) of (a) RegCM, (b) GRIMs, (c) WRF, (d) CCLM, and (e) HadGEM3-RA forced by UKESM
표 Differences of TC genesis density between SSP3_70 run (2031-2060) and historical run (1985-2014) of (a) RegCM, (b) GRIMs, (c) WRF, (d) CCLM, and (e) HadGEM3-RA forced by UKESM
표 Differences of TC genesis density between SSP5_85 run (2031-2060) and historical run (1985-2014) of (a) RegCM, (b) GRIMs, (c) WRF, (d) CCLM, and (e) HadGEM3-RA forced by UKESM
표 Differences of TC track density between SSP1_26 run (2031-2060) and historical run (1985-2014) of (a) RegCM, (b) GRIMs, (c) WRF, (d) CCLM, and (e) HadGEM3-RA forced by UKESM
표 Differences of TC track density between SSP2_45 run (2031-2060) and historical run (1985-2014) of (a) RegCM, (b) GRIMs, (c) WRF, (d) CCLM, and (e) HadGEM3-RA forced by UKESM
표 Differences of TC track density between SSP3_70 run (2031-2060) and historical run (1985-2014) of (a) RegCM, (b) GRIMs, (c) WRF, (d) CCLM, and (e) HadGEM3-RA forced by UKESM
표 Differences of TC track density between SSP5_85 run (2031-2060) and historical run (1985-2014) of (a) RegCM, (b) GRIMs, (c) WRF, (d) CCLM, and (e) HadGEM3-RA forced by UKESM
표 Probability density function of TC intensity of RSMC best track data during 1985-2014 and SSP1_26 run of RCMs (RegCM, GRIMs, WRF, CCLM, and HadGEM3-RA) during 2031-2060 forced by UKESM. (a) Maximum wind speed (m s-1) and (b) Minimum sea level pressure (hPa)
표 Probability density function of TC intensity of RSMC best track data during 1985-2014 and SSP2_45 run of RCMs (RegCM, GRIMs, WRF, CCLM, and HadGEM3-RA) during 2031-2060 forced by UKESM. (a) Maximum wind speed (m s-1) and (b) Minimum sea level pressure (hPa)
표 Probability density function of TC intensity of RSMC best track data during 1985-2014 and SSP3_70 run of RCMs (RegCM, GRIMs, WRF, CCLM, and HadGEM3-RA) during 2031-2060 forced by UKESM. (a) Maximum wind speed (m s-1) and (b) Minimum sea level pressure (hPa)
표 Probability density function of TC intensity of RSMC best track data during 1985-2014 and SSP5_85 run of RCMs (RegCM, GRIMs, WRF, CCLM, and HadGEM3-RA) during 2031-2060 forced by UKESM. (a) Maximum wind speed (m s-1) and (b) Minimum sea level pressure (hPa)
표 TC genesis density for (a) climatological mean of historical run (1985-2014) and differences between (b) SSP1_26, (c) SSP2_45, (d) SSP3_70 and (e) SSP5_85 and historical run for period of 2031-2060
표 TC track density for (a) climatological mean of historical run (1985-2014) and differences between (b) SSP1_26, (c) SSP2_45, (d) SSP3_70 and (e) SSP5_85 and historical run for period of 2031-2060
표 (수식)850 hPa relative vorticity (10-5 s- ) from June to November for (a) climatological mean for historical run (1985-2014) and differences between (b) SSP1_26, (c) SSP2_45, (d) SSP3_70, and (e) SSP5_85 scenarios (2031-2060) and historical run
표 (수식)850 hPa specific humidity (kg kg- ) and wind (m s- ) from June to November for (a) climatological mean for historical run (1985-2014) and differences between (b) SSP1_26, (c) SSP2_45, (d) SSP3_70, and (e) SSP5_85 scenarios (2031-2060) and historical run
표 Sea surface temperature (K) from June to November for (a) climatological mean for historical run (1985-2014) and differences between (b) SSP1_26, (c) SSP2_45, (d) SSP3_70, and (e) SSP5_85 scenarios (2031-2060) and historical run
표 (수식)Vertical wind shear (m s- ) from June to November for (a) climatological mean for historical run (1985-2014) and differences between (b) SSP1_26, (c) SSP2_45, (d) SSP3_70, and (e) SSP5_85 scenarios (2031-2060) and historical run
표 Differences of TC genesis density between SSP1_26 run (2071-2100) and historical run (1985-2014) of (a) RegCM, (b) GRIMs, (c) WRF, (d) CCLM, and (e) HadGEM3-RA forced by UKESM
표 Differences of TC genesis density between SSP2_45 run (2071-2100) and historical run (1985-2014) of (a) RegCM, (b) GRIMs, (c) WRF, (d) CCLM, and (e) HadGEM3-RA forced by UKESM
표 Differences of TC genesis density between SSP3_70 run (2071-2100) and historical run (1985-2014) of (a) RegCM, (b) GRIMs, (c) WRF, (d) CCLM, and (e) HadGEM3-RA forced by UKESM
표 Differences of TC genesis density between SSP5_85 run (2071-2100) and historical run (1985-2014) of (a) RegCM, (b) GRIMs, (c) WRF, (d) CCLM, and (e) HadGEM3-RA forced by UKESM
표 Differences of TC track density between SSP1_26 run (2071-2100) and historical run (1985-2014) of (a) RegCM, (b) GRIMs, (c) WRF, (d) CCLM, and (e) HadGEM3-RA forced by UKESM
표 Differences of TC track density between SSP2_45 run (2071-2100) and historical run (1985-2014) of (a) RegCM, (b) GRIMs, (c) WRF, (d) CCLM, and (e) HadGEM3-RA forced by UKESM
표 Differences of TC track density between SSP3_70 run (2071-2100) and historical run (1985-2014) of (a) RegCM, (b) GRIMs, (c) WRF, (d) CCLM, and (e) HadGEM3-RA forced by UKESM
표 Differences of TC track density between SSP5_85 run (2071-2100) and historical run (1985-2014) of (a) RegCM, (b) GRIMs, (c) WRF, (d) CCLM, and (e) HadGEM3-RA forced by UKESM
표 (수식)Probability density function of TC intensity of RSMC best track data during 1985-2014 and SSP1_26 run of RCMs (RegCM, GRIMs, WRF, CCLM, and HadGEM3-RA) during 2071-2100 forced by UKESM. (a) Maximum wind speed (m s- ) and (b) Minimum sea level pressure (hPa)
표 (수식)Probability density function of TC intensity of RSMC best track data during 1985-2014 and SSP2_45 run of RCMs (RegCM, GRIMs, WRF, CCLM, and HadGEM3-RA) during 2071-2100 forced by UKESM. (a) Maximum wind speed (m s- ) and (b) Minimum sea level pressure (hPa)
표 (수식)Probability density function of TC intensity of RSMC best track data during 1985-2014 and SSP3_70 run of RCMs (RegCM, GRIMs, WRF, CCLM, and HadGEM3-RA) during 2071-2100 forced by UKESM. (a) Maximum wind speed (m s- ) and (b) Minimum sea level pressure (hPa)
표 (수식)Probability density function of TC intensity of RSMC best track data during 1985-2014 and SSP5_85 run of RCMs (RegCM, GRIMs, WRF, CCLM, and HadGEM3-RA) during 2071-2100 forced by UKESM. (a) Maximum wind speed (m s- ) and (b) Minimum sea level pressure (hPa)
표 TC genesis density for (a) climatological mean of historical run (1985-2014) and differences between (b) SSP1_26, (c) SSP2_45, (d) SSP3_70 and (e) SSP5_85 and historical run for period of 2071-2100
표 TC track density for (a) climatological mean of historical run (1985-2014) and differences between (b) SSP1_26, (c) SSP2_45, (d) SSP3_70 and (e) SSP5_85 and historical run for period of 2071-2100
표 Time series of (a) Number of TC and (b) Lifetime maximum wind speed of Ensembles_UKESM during 1979-2100. Solid black lines indicate historical run, blue lines indicate SSP1_26, green lines indicate SSP2_45, yellow lines indicate SSP3_70 and red lines indicate SSP5_85 run. Dashed lines indicate the linear trends
표 (수식)850 hPa relative vorticity (10- s- ) from June to November for (a)climatological mean for historical run (1985-2014) and differences between (b) SSP1_26,(c) SSP2_45, (d) SSP3_70, and (e) SSP5_85 scenarios (2071-2100) and historical run
표 (수식)850 hPa specific humidity (kg kg- ) and wind (m s- ) from June to November for (a) climatological mean for historical run (1985-2014) and differences between (b) SSP1_26, (c) SSP2_45, (d) SSP3_70, and (e) SSP5_85 scenarios (2071-2100) and historical run
표 Sea surface temperature (K) from June to November for (a) climatological mean for historical run (1985-2014) and differences between (b) SSP1_26, (c) SSP2_45, (d) SSP3_70, and (e) SSP5_85 scenarios (2071-2100) and historical run
표 (수식)Vertical wind shear (m s- ) from June to November for (a) climatological mean for historical run (1985-2014) and differences between (b) SSP1_26, (c) SSP2_45, (d) SSP3_70, and (e) SSP5_85 scenarios (2071-2100) and historical run
표 Distribution of available daily data for 11 data. The orange bar indicates the available period of each. The light orange box indicates the period in which all data is available
표 Properties of the 11 global air-sea heat flux datasets
표 Surface Latent heat flux (W·m⁻²) in (a, c, e) DJF, (b, d, f) JJA seasonal mean. (top) The ICOADS, (middle) the average of 10 data, and (bottom) the standard deviation of the seasonal mean. The fields represent the average over the 23-year period from 1992 to 2013. Positive (negative) values represent upward (downward) fluxes. (Noh et al. 2022 submitted)
표 Same as Figure 2.3.1.2 but the fields represented surface sensible heat flux. (Noh et al. 2022 submitted)
표 Zonal-mean of averaged air-sea heat flux during(a,d) ANNUAL, (b,e) DJF, (c,f) JJA for each group. The ICOADS (black line), satellite data (red line), reanalysis data (blue line), and blended data (green line). (Noh et al. 2022 submitted)
표 Annual cycle of monthly latent heat flux (solid lines) and sensible heat flux (dashed lines) averaged over the three regions for 1992 to 2013. The thick black line indicates the ensemble mean. (Noh et al. 2022 submitted)
표 Seasonal mean of (upper) latent heat flux and (lower) sensible heat flux for the period 1992 to 2013. Each color bar indicates the 11 data values for the different sources. The bar groups represent the Northwestern Pacific, North Atlantic, and South Indian Ocean (from left to right). The hatched bars indicate latent and sensible heat flux, which was calculated by the COARE 3.0 algorithm. (Noh et al. 2022 submitted)
표 Zonal-mean of averaged ICOADS air-sea heat flux. The original ICOADS (black line), reproduced ICOADS with COARE3.0 algorithm (blue dashed line), COARE3.6 algorithm (green dashed line), ECMWF algorithm (yellow dashed line), and NCAR algorithm (red dashed line)
표 Surface Latent heat flux (W·m⁻²) in (top) ANN, (middle) DJF, (bottom) JJA seasonal mean. The ICOADS (left) with COARE3.0 algorithm, (right) NCAR algorithm
표 Difference of the surface latent heat flux (W·m⁻²) in (top) ANN, (middle) DJF, (bottom) JJA seasonal mean between COARE3.0 and NCAR algorithm
표 Difference of the surface latent heat flux (W·m⁻²) in ANN mean between COARE3.0 and NCAR algorithm with six reanalysis data
표 Same as Figure 2.3.1.9. but for DJF mean
표 Same as Figure 2.3.1.9. but for JJA mean
표 Testbed for verification of atmosphere-ocean interaction
표 Result of selection of recent typhoon cases and cold surge cases to be used for model verification
표 CHABA latent heat flux (left) ERA5, (middle) OAFlux, (right) difference
표 CHABA sensible heat flux(left) ERA5, (middle) OAFlux, (right) difference
표 SOULIK latent heat flux (left) ERA5, (middle) OAFlux, (right) difference
표 SOULIK sensible heat flux (left) ERA5, (middle) OAFlux, (right) difference
표 KONG-REY Latent heat flux (left) ERA5, (middle) OAFlux, (right) difference
표 KONG-REY sensible heat flux (left) ERA5, (middle) OAFlux, (right) difference
표 Distribution of latent heat flux during cold surge in the high emissions
표 Distribution of latent heat flux during cold surge in the low emissions
표 Distribution of sensible heat flux during cold surge in the high emissions
표 Distribution of sensible heat flux during cold surge in the low emissions
표 Distribution of mean and spread of 1000hPa (left) wind, (middle) temperature, (right) specific humidity of the ensemble initial conditions
표 Bulk flux algorithm overview
표 Difference latent heat flux distribution between UA and Control algorithm in (left) annual mean, (right panel) sesonal mean. The dots highlight statistically significant difference at the p<0.05 level, determined frome the two-tailed Student’s t-test
표 Difference sensible heat flux distribution between UA and Control algorithm in (left) annual mean, (right panel) seasonal mean. The dots highlight statistically significant difference at the p<0.05 level, determined from the two-tailed Student’s t-test
표 Difference (up) specific humidity, (down) temperature at reference height map between UA and Control algorithm in (left) annual mean, (right panel) seasonal mean. The dots highlight statistically significant difference at the p<0.05 level, determined from the two-tailed Student’s t-test
표 Difference latent heat flux distribution between COARE3.0 and Control algorithm in (left) annual mean, (right panel) seasonal mean. The dots highlight statistically significant difference at the p<0.05 level, determined from the two-tailed Student’s t-test
표 Difference sensible heat flux distribution between COARE3.0 and Control algorithm in (left) annual mean, (right panel) seasonal mean. The dots highlight statistically significant difference at the p<0.05 level, determined from the two-tailed Student’s t-test
표 Difference (up) specific humidity, (down) temperature at reference height map between COARE3.0 and Control algorithm in (left) annual mean, (right panel) seasonal mean. The dots highlight statistically significant difference at the p<0.05 level, determined from the two-tailed Student’s t-test
표 The composition of COAWST system
표 Overview of data exchange in the COAWST system
표 Data exchange between WRF and ROMS in the COAWST system
표 Experiment design used in the COAWST modeling system for present
표 Experiment design used in the COAWST modeling system for pseudo
표 Sea surface temperature (2001.05-2001.08) of a) OISST, b) WRF, c)COAWST of ROMS without stabilization, d) COAWST of ROMS stabilization
표 Precipitation (2001.05-2001.08) of a) IMERG, b) WRF, c) COAWST of without stabilization, d) COAWST of ROMS stabilization
표 Description of the Pseudo global warming

과제명(ProjectTitle) :	-
연구책임자(Manager) :	-
과제기간(DetailSeriesProject) :	-
총연구비 (DetailSeriesProject) :	-
키워드(keyword) :	-
과제수행기간(LeadAgency) :	-
연구목표(Goal) :	-
연구내용(Abstract) :	-
기대효과(Effect) :	-

내보내기 구분	파일저장 인쇄 메일전송
구성항목	기본정보 상세정보 관리번호, 제목(한글), 저자명(한글), 발행일자, 전자원문, 초록(한글), 초록(영문) 관리번호, 제목(한글), 제목(영문), 저자명(한글), 저자명(영문), 주관연구기관(한글), 주관연구기관(영문), 발행일자, 총페이지수, 주관부처명, 과제시작일, 보고서번호, 과제종료일, 주제분류, 키워드(한글), 전자원문, 키워드(영문), 입수제어번호, 초록(한글), 초록(영문), 목차
저장형식	Text(ASCII format) Excel format
메일정보	받는사람 (필수) @ 보내는사람 (선택) @ 제목 내용 KISTI 검색결과 이메일 서비스
안내	총 건의 자료가 검색되었습니다. 다운받으실 자료의 인덱스를 입력하세요. (1-10,000) 검색결과의 순서대로 최대 10,000건 까지 다운로드가 가능합니다. 데이타가 많을 경우 속도가 느려질 수 있습니다.(최대 2~3분 소요) 다운로드 파일은 UTF-8 형태로 저장됩니다. 파일의 내용이 제대로 보이지 않을실 때는 웹브라우저 상단의 보기 -> 인코딩 -> 자동선택 여부를 확인하십시오. ~ Text(ASCII format) Excel format

연합인증

RegCM 지역기후모델을 이용한 SSP 시나리오 기반 동아시아 상세 기후변화 정보 산출
Production of detailed climate change information over East Asia based on the SSP scenarios by utilizing the RegCM regional climate model 원문보기

초록 ▼

목차 Contents

표/그림 (121)

표/그림 (121)

참고문헌 (25)

연구과제 타임라인

관련 콘텐츠

원문 보기

이 보고서와 함께 이용한 콘텐츠

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

선택된 텍스트

연합인증

RegCM 지역기후모델을 이용한 SSP 시나리오 기반 동아시아 상세 기후변화 정보 산출 Production of detailed climate change information over East Asia based on the SSP scenarios by utilizing the RegCM regional climate model 원문보기

초록 ▼

목차 Contents

표/그림 (121) 모든 표/그림 보기

표/그림 (121) 슬라이드로 보기

참고문헌 (25)

연구과제 타임라인

전체(0) 논문(0) 특허(0) 보고서(0)

전체(0) 논문(0) 특허(0) 보고서(0)

관련 콘텐츠

원문 보기

이 보고서와 함께 이용한 콘텐츠

AI-Helper ※ AI-Helper는 오픈소스 모델을 사용합니다.

선택된 텍스트

RegCM 지역기후모델을 이용한 SSP 시나리오 기반 동아시아 상세 기후변화 정보 산출
Production of detailed climate change information over East Asia based on the SSP scenarios by utilizing the RegCM regional climate model 원문보기

표/그림 (121)

표/그림 (121)