• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.327-327
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• 2022

지구온난화로 전 세계는 기후위기에 직면해있다. 특히, 아시아의 경우 복사강제력과 대규모 대기순환인 몬순이 지역기후에 영향을 주기 때문에 지리적 위치 및 계절에 따라 폭염, 홍수, 가뭄 등 다양한 기상이변 및 수재해 문제를 겪고 있다. 더욱이, 아시아 지역은 온난화가 심화됨에 따라 식량 및 물 안보위기가 더욱 증가할 것으로 전망됨에 따라 이와 직결되는 기후 및 수문특성에 대한 기후변화 영향평가 및 분석이 요구된다. 본 연구에서는 미래 기온상승 조건을 고려하여 아시아 지역의 기후특성을 전망하고, 수문모형(VIC)을 활용하여 수문전망을 수행하였다. 미래 기후전망을 위해 적정 CMIP6 기후모델과 공통사회경제경로(SSP5-8.5) 시나리오를 활용하였다. 시나리오로부터 산출된 기온자료 및 CPC (Climate Prediction Center) 전 지구 관측 기온자료를 활용하여 산업화 이전 대비 잠재적인 전지구 기온상승(1.5℃~5.0℃) 조건을 추정하였다. 통계적상세화 기법을 적용하여 아시아 지역에 대하여 기후변화 시나리오를 상세화하고, 기후구분법을 적용하여 기후대를 구분하였다. 미래 기온상승 조건 하에서 아시아 지역의 기후특성을 전망하고 기후대의 분포변화를 분석하였다. 전 지구 기온이 상승함에 따라 지역별 기후특성이 변화하였으며, 이는 기온 및 강수량 변화에 기인하는 것으로 분석되었다. 최고 및 최저기온은 모든 기후대의 전 지역에서 상승하며, 이는 평균적으로 전 지구 평균 기온을 상회하였다. 강수량 및 강수일수는 대체로 증가하였으나, 기후특성에 따라 지역별 편차를 보였다. 기상성분의 변화로 기후대별 수문성분(증발산량, 유출량)은 대체로 증가하였으며, 극한 유출량의 변화경향은 모든 기후대에서 증가할 것으로 전망되었다. 지속적인 지구온난화는 아시아 지역의 수문순환은 가속화할 것으로 전망되며, 기후대별 수문기상성분의 변화는 지역의 기후특성에 따라 편차가 있는 것으로 분석되었다. 지구온난화 조건별 아시아 지역의 미래 기후 및 수문기상성분 변화 특성은 기상 및 수자원에 대한 기후변화 영향평가 시 기초자료로 활용될 수 있다.

• Atmosphere
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• v.33 no.5
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• pp.531-548
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• 2023

We developed the Aviation Convective Index (ACI) for predicting deep convective area using the operational global Numerical Weather Prediction model of the Korea Meteorological Administration. Seasonally optimized ACI (ACI_SnOpt) was developed to consider seasonal variabilities on deep convections in Korea. Yearly optimized ACI (ACI_YrOpt) in Part 1 showed that seasonally averaged values of Area Under the ROC Curve (AUC) and True Skill Statistics (TSS) were decreased by 0.420% and 5.797%, respectively, due to the significant degradation in winter season. In Part 2, we developed new membership function (MF) and weight combination of input variables in the ACI algorithm, which were optimized in each season. Finally, the seasonally optimized ACI (ACI_SnOpt) showed better performance skills with the significant improvements in AUC and TSS by 0.983% and 25.641% respectively, compared with those from the ACI_YrOpt. To confirm the improvements in new algorithm, we also conducted two case studies in winter and spring with observed Convectively-Induced Turbulence (CIT) events from the aircraft data. In these cases, the ACI_SnOpt predicted a better spatial distribution and intensity of deep convection. Enhancements in the forecast fields from the ACI_YrOpt to ACI_SnOpt in the selected cases explained well the changes in overall performance skills of the probability of detection for both "yes" and "no" occurrences of deep convection during 1-yr period of the data. These results imply that the ACI forecast should be optimized seasonally to take into account the variabilities in the background conditions for deep convections in Korea.

• Atmosphere
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• v.33 no.5
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• pp.519-530
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• 2023

Deep convection can make adverse effects on safe and efficient aviation operations by causing various weather hazards such as convectively-induced turbulence, icing, lightning, and downburst. To prevent such damage, it is necessary to accurately predict spatiotemporal distribution of deep convective area near the airport and airspace. This study developed a new index, the Aviation Convective Index (ACI), for deep convection, using the operational global Unified Model of the Korea Meteorological Administration. The ACI was computed from combination of three different variables: 3-hour maximum of Convective Available Potential Energy, averaged Outgoing Longwave Radiation, and accumulative precipitation using the fuzzy logic algorithm. In this algorithm, the individual membership function was newly developed following the cumulative distribution function for each variable in Korean Peninsula. This index was validated and optimized by using the 1-yr period of radar mosaic data. According to the Receiver Operating Characteristics curve (AUC) and True Skill Score (TSS), the yearly optimized ACI (ACI_YrOpt) based on the optimal weighting coefficients for 1-yr period shows a better skill than the no optimized one (ACI_NoOpt) with the uniform weights. In all forecast time from 6-hour to 48-hour, the AUC and TSS value of ACI_YrOpt were higher than those of ACI_NoOpt, showing the improvement of averaged value of AUC and TSS by 1.67% and 4.20%, respectively.

• Journal of the Korean earth science society
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• v.21 no.6
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• pp.703-718
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• 2000

In order to investigate interannual variation of total ozone and reflectivity over the globe, Nimbus-7/TOMS data were used on the monthly mean and its anomaly for the period of 1979-92. This study also examined MSU channel 4(Ch4; lower-stratosphere) brightness temperature data and two model reanalyses of NCEP and GEOS to compare the ozone variation with atmospheric thermal condition. In addition, the MSU channel 1(Ch1 ; lower-troposphere) brightness temperature was used to compare with the reflectivity. The ozone showed strong annual cycle with downward trend(-6.3${\pm}$0.6 DU/decade) over the globe, and more distinct response to volcanic eruption than El Ni${\tilde{n}$o. The relationship between total ozone and MSU Ch4 observation, and between the ozone and model reanalyses of lower stratosphere temperature showed positive correlation(0.2-0.7) during the period of 1980-92. Reflectivity increased interannually by 0.2${\pm}$0.06%/decade over the globe during the above period and reflected El Ni${\tilde{n}$o(1982-83, 1991-92) well. Its variability in annual cycle was remarkably smaller in tropics than in higher latitudes. This is inferred due to cloud suppression and tropical upwelling regions. Reflectivity correlated negatively(-0.9) to the Ch1 temperature over the globe, but positively(0.2) over tropical ocean. The positive value over the ocean results from the effect of microwave emissivity which increases the Ch1 temperature with enhanced hydrometeor activity. Significant correlations between total ozone and the Ch4 temperature, and between reflectivity and the Ch1 Suggest that the TOMS data may use valuably to better understand the feedback mechanism of climate change.

• Economic and Environmental Geology
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• v.36 no.3
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• pp.213-223
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• 2003

We estimated the Moho depth of Korean Peninsula from gravity anomalies and digital elevation model. The satellite radar altimetry-derived global free-air gravity model was used to ensure the homogeneity in both data and frequency domains of the original data. Two different methods were implemented to calculate the Moho depth; the wavenumber correlation analysis (Kim et al., 2000a) and the power spectrum analysis. The former method calculates depth-to-the-Moho by correlating topographic gravity effect with free-air gravity anomaly in the wavenumber domain under the assumption that the study area is not isostatically compensated. The latter one, on the other hand, considers the different density layers (i.e., Conrad and Moho), using complete Bouguer gravity anomaly in the Frequency domain of the Fourier transform. The correlation coefficient of the two Moho model is 0.53, and methodology and numerical error are mainly responsible for any mismatch between the two models. In order to integrate the two independentely-estimated models, we applied least-squares adjustment using the differenced depth. The resultant model has mean and standard deviation Moho depths of 32.0 km and 2.5 km with (min, max) depths of (20.3, 36.6) kms. Although this result does not include any topographic gravity effect, however, the validity of isostasy and the role of local stress field in the study area should be further studied.

• Journal of the Korean earth science society
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• v.21 no.5
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• pp.525-540
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• 2000

Global temperature trends of middle and upper tropospheres have been investigated using the data of satellite-observed Microwave Sounding Unit (MSU) channels 2-3(Ch2, Ch3) during the period of 1980-97 and three GCM (NCEP, ECMWF, GEOS) reanalyses during 1981-93. The global, hemispheric and tropical anomalies, computed from the data during the common period, have been intercompared in the following regions; ocean, land, and both ocean and land. The correlation with MSU in midtropospheric temperatures is the best (r=0.81${\sim}$0.95) in ECMWF, particularly over the tropics. The correlations in upper troposphere are lower (r=0.06${\sim}$0.34) due to poor quality of MSU Ch3 data consistent with previous result. The midtropospheric trends during 1981-93, obtained from MSU and three GCMs, show the global warming of 0.01${\sim}$0.18K decade$^{-1}$. The warmest years have been 1987 and 1991 in El Ni${\tilde{n}$o while the coolest 1993 and 1994 in La Ni${\tilde{n}$a. The warming (0.12${\sim}$0.13K decade$^{-1}$) in MSU over global ocean is similar to that over global land. The largest discrepancy in upper troposphere between MSU and GCMs has been found in the transition period (1984. 12-1985. 1) from NOAA 9 to 10, because of a sizable error in the MSU Ch3. The midtropospheric trends near the Korean peninsula during 1981-93 are almost negligible(-0.02K decade$^{-1}$) in MSU, but indicate significant warming (0.25-0.43K decade$^{-1}$) in GCMs. The trends are crosschecked and discussed with other two independent MSU data of Spencer and Christy (1992a, 1992b).

• Journal of Korea Water Resources Association
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• v.49 no.9
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• pp.761-771
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• 2016

The GloSea5 (Global Seasonal forecasting system version 5) is provided and operated by the KMA (Korea Meteorological Administration). GloSea5 provides Forecast (FCST) and Hindcast (HCST) data and its horizontal resolution is about 60km ($0.83^{\circ}{\times}0.56^{\circ}$) in the mid-latitudes. In order to use this data in watershed-scale water management, GloSea5 needs spatial-temporal downscaling. As such, statistical downscaling was used to correct for systematic biases of variables and to improve data reliability. HCST data is provided in ensemble format, and the highest statistical correlation ($R^2=0.60$, RMSE = 88.92, NSE = 0.57) of ensemble precipitation was reported for the Yongdam Dam watershed on the #6 grid. Additionally, the original GloSea5 (600.1 mm) showed the greatest difference (-26.5%) compared to observations (816.1 mm) during the summer flood season. However, downscaled GloSea5 was shown to have only a -3.1% error rate. Most of the underestimated results corresponded to precipitation levels during the flood season and the downscaled GloSea5 showed important results of restoration in precipitation levels. Per the analysis results of spatial autocorrelation using seasonal Moran's I, the spatial distribution was shown to be statistically significant. These results can improve the uncertainty of original GloSea5 and substantiate its spatial-temporal accuracy and validity. The spatial-temporal reproducibility assessment will play a very important role as basic data for watershed-scale water management.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1589-1597
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• 2021

Submarine groundwater discharge (SGD) in coastal areas is gaining importance as a major transport route that bring nutrients and trace metals into the ocean. This paper describes the analysis of the seasonal changes and spatiotemporal characteristicsthrough the modeling monthly SGD for 35 years from 1986 to 2020 for the Nakdong river basin. In this study, we extracted 210 watersheds and SGD estimation points using the SRTM (Shuttle Radar Topography Mission) DEM (Digital Elevation Model). The average annual SGD of the Nakdong River basin was estimated to be 466.7 m²/yr from the FLDAS (Famine Early Warning Systems Network Land Data Assimilation System) recharge data of 10 km which is the highest resolution global model applicable to Korea. There was no significant time-series variation of SGD in the Nakdong river basin, but the concentrated period of SGD was expanded from summer to autumn. In addition, it was confirmed that there is a large amount of SGD regardless of the season in coastal area nearby large rivers, and the trend has slightly increased since the 1980s. The characteristics are considered to be related to the change in the major precipitation period in the study area, and spatially it is due to the high baseflow-groundwater in the vicinity of large rivers. This study is a precedentstudy that presents a modeling technique to explore the characteristics of SGD in Korea, and is expected to be useful as foundational information for coastal management and evaluating the impact of SGD to the ocean.

• Korean Journal of Remote Sensing
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• v.14 no.1
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• pp.53-68
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• 1998

Observation of hydrometeors' behavior in the atmosphere is important to understand weather and climate. By conventional observations, we can get the distribution of water vapor at limited number of points on the earth. In this study, the precipitable water has been estimated from the split window channel data on GMS-5 based upon the technique developed by Chesters et al.(1983). To retrieve the precipitable water, water vapor absorption parameter depending on filter function of sensor has been derived using the regression analysis between the split window channel data and the radiosonde data observed at Osan, Pohang, Kwangiu and Cheju staions for 4 months. The air temperature of 700 hPa from the Global Spectral Model of Korea Meteorological Administration (GSM/KMA) has been used as mean air temperature for single layer radiation model. The retrieved precipitable water for the period from August 1996 through December 1996 are compared to radiosonde data. It is shown that the root mean square differences between radiosonde observations and the GMS-5 retrievals range from 0.65 g/$cm^2$ to 1.09 g/$cm^2$ with correlation coefficient of 0.46 on hourly basis. The monthly distribution of precipitable water from GMS-5 shows almost good representation in large scale. Precipitable water is produced 4 times a day at Korea Meteorological Administration in the form of grid point data with 0.5 degree lat./lon. resolution. The data can be used in the objective analysis for numerical weather prediction and to increase the accuracy of humidity analysis especially under clear sky condition. And also, the data is a useful complement to existing data set for climatological research. But it is necessary to get higher correlation between radiosonde observations and the GMS-5 retrievals for operational applications.

• Atmosphere
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• v.24 no.3
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• pp.303-315
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• 2014

Terrestrial ecosystem plays the important role as carbon sink in the global carbon cycle. Understanding of interactions of terrestrial carbon cycle with climate is important for better prediction of future climate change. In this paper, terrestrial carbon cycle is investigated by Hadley Centre Global Environmental Model, version 2, Carbon Cycle (HadGEM2-CC) that considers vegetation dynamics and an interactive carbon cycle with climate. The simulation for future projection is based on the three (8.5/4.5/2.6) representative concentration pathways (RCPs) from 2006 to 2100 and compared with historical land carbon uptake from 1979 to 2005. Projected changes in ecological features such as production, respiration, net ecosystem exchange and climate condition show similar pattern in three RCPs, while the response amplitude in each RCPs are different. For all RCP scenarios, temperature and precipitation increase with rising of the atmospheric $CO_2$. Such climate conditions are favorable for vegetation growth and extension, causing future increase of terrestrial carbon uptakes in all RCPs. At the end of 21st century, the global average of gross and net primary productions and respiration increase in all RCPs and terrestrial ecosystem remains as carbon sink. This enhancement of land $CO_2$ uptake is attributed by the vegetated area expansion, increasing LAI, and early onset of growing season. After mid-21st century, temperature rising leads to excessive increase of soil respiration than net primary production and thus the terrestrial carbon uptake begins to fall since that time. Regionally the NEE average value of East-Asia ($90^{\circ}E-140^{\circ}E$, $20^{\circ}N{\sim}60^{\circ}N$) area is bigger than that of the same latitude band. In the end-$21^{st}$ the NEE mean values in East-Asia area are $-2.09PgC\;yr^{-1}$, $-1.12PgC\;yr^{-1}$, $-0.47PgC\;yr^{-1}$ and zonal mean NEEs of the same latitude region are $-1.12PgC\;yr^{-1}$, $-0.55PgC\;yr^{-1}$, $-0.17PgC\;yr^{-1}$ for RCP 8.5, 4.5, 2.6.