• Ocean and Polar Research
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• v.34 no.1
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• pp.29-35
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• 2012

We investigated the interannual relationship between chlorophyll concentrations in the western North Pacific and tropical cyclones (TCs) in the western North Pacific by analyzing data collected for >12 years. Despite the short-term scale (2~3 weeks) in the contribution of tropical cyclones to phytoplankton, the current study revealed that the long-term chlorophyll variability in the western North Pacific is profoundly related to long-term variability in the frequency of TCs. It was also found that the Pacific decadal oscillation (PDO) tends to control such relationships between the 2 bio-physical systems. This result suggests a significant climatic relationship between TC activity and marine phytoplankton, and also suggests the possibility of more accurate estimations of primary production in the western North Pacific.

• Atmosphere
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• v.20 no.4
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• pp.451-466
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• 2010

This edition has continued since 2006 tropical cyclone season our effort to provide standard tropical cyclone summaries by the western North Pacific basin and detailed reviews of operationally or meteorologically significant tropical cyclones to document significant challenges and shortfalls in the tropical cyclone warning system to serve as a focal point for research and development efforts. The tropical cyclone season of 2009 in the western North Pacific basin is summarized and the main characteristics of general atmospheric circulation are described. Also, the official track and intensity forecasts of these cyclones are verified. The total number is less than 59-year (1951~2009) average frequency of 26.4. The 2009 western North Pacific season was an inactive one, in which 22 tropical storms generated. Of these, 13 TCs reached typhoon (TY) intensity, while the rest 9 TCs only reached severe tropical storm (STS) and tropical storm (TS) intensity - three STS and six TS storms. On average of 22 TCs in 2009, the Korea Meteorological Administration official track forecast error for 48 hours was 219 km. There was a big challenge for individual cyclones such as 0902 CHAN-HOM, 0909 ETAU, and 0920 LUPIT resulting in significant forecast error, with both intricate tracks and irregular moving speed. There was no tropical cyclone causing significant direct impact to the country. The tropical cyclone season in 2009 began in May with the formation of KUJIRA (0901). In September and October, ten TSs formed in the western North Pacific in response to enhanced convective activity. On the other hand, the TC activity was very weak from June to July. It is found that the unusual anti-cyclonic circulation in the lower level and weak convection near the Philippines are dominant during summertime. The convection and atmospheric circulation in the western North Pacific contributed unfavorable condition for TC activity in the 2009 summertime. Year 2009 has continued the below normal condition since mid 1990s which is apparent in the decadal variability in TC activity.

• Ocean and Polar Research
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• v.35 no.3
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• pp.259-272
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• 2013

One of the factors influencing the climate around Korea is the oceanic-atmospheric variability in the tropical region between the eastern Indian and the western Pacific Oceans. Lack of knowledge about the air-sea interaction in the tropical Indo-Pacific region continues to make it problematic forecasting the ocean climate in the East Asia. The 'Tropical Indo-Pacific water transport and ecosystem monitoring EXperiment (TIPEX)' is a program for monitoring the ocean circulation variability between Pacific and Indian Oceans and for improving the accuracy of future climate forecasting. The main goal of the TIPEX program is to quantify the climate and ocean circulation change between the Indian and the Pacific Oceans. The contents of the program are 1) to observe the mixing process of different water masses and water transport in the eastern Indian and the western Pacific, 2) to understand the large-scale oceanic-climatic variation including El Nino-Southern Oscillation (ENSO)/Warm Pool/Pacific Decadal Oscillation (PDO)/Indian Ocean Dipole (IOD), and 3) to monitor the biogeochemical processes, material flux, and biological changes due to the climate change. In order to effectively carry out the monitoring program, close international cooperation and the proper co-work sharing of tasks between China, Japan, Indonesia, and India as well as USA is required.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.51 no.3
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• pp.338-343
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• 2018

Recently, commercial catches of the common squid Todarodes pacificus have dramatically decreased in Korean and Japanese waters. The relationship between common squid catches and environmental factors was investigated using squid catches, climate indices and observed seawater temperatures in Korean waters. Common squid consist of three spawning stocks: autumn, winter, and summer. The autumn stock is the largest in Korea, and its main fishing season appears to have shifted from September in the 1980s to October in the 1990s. We observed negative correlations between the spring Southern Oscillation Index and Korean catches and between the winter Pacific Decadal Oscillation and Japanese catches. Despite global warming, no conspicuous increases in October seawater temperatures have been observed at 10 and 50 m in Korean waters since the mid-1900s. Instead, the 50 m water layer of the East Sea appears to be gradually cooling. Moreover, temperatures at 50 m in the East Sea and the South Sea were significantly negatively correlated with squid catches in Korea and Japan, respectively. Our preliminary analysis indicates a link between climate change, seawater temperature, and squid catches in Korean waters, which helps to inform the direction of subsequent research to identify the cause of rapid decreases in this squid resource.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.587-596
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• 2022

Sea levels are rising as a result of climate change, and low-lying areas along the coast are at risk of flooding. Therefore, we tried to investigate the relationship between sea level change and climate indices using satellite altimeter data (Topex/Poseidon, Jason-1/2/3) and southern oscillation index (SOI) and the Pacific decadal oscillation (PDO) data. If time domain data were converted to frequency domain, the original data can be analyzed in terms of the periodic components. Fourier transform and Wavelet transform are representative periodic analysis methods. Fourier transform can provide only the periodic signals, whereas wavelet transform can obtain both the periodic signals and their corresponding time location. The cross-wavelet transformation and the wavelet coherence are ideal for analyzing the common periods, correlation and phase difference for two time domain datasets. Our cross-wavelet transform analysis shows that two climate indices (SOI, PDO) and sea level height was a significant in 1-year period. PDO and sea level height were anti-phase. Also, our wavelet coherence analysis reveals when sea level height and climate indices were correlated in short (less than one year) and long periods, which did not appear in the cross wavelet transform. The two wavelet analyses provide the frequency domains of two different time domain datasets but also characterize the periodic components and relative phase difference. Therefore, our research results demonstrates that the wavelet analyses are useful to analyze the periodic component of climatic data and monitor the various oceanic phenomena that are difficult to find in time series analysis.

• Ocean and Polar Research
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• v.40 no.3
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• pp.127-143
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• 2018

This study analyzed the influence of climate change on the spawning ground area of the common squid, Todarodes pacificus. To estimate long term changes in the area of the spawning ground of the common squid, water temperature at 50 m deep that can be inferred from sea surface temperature (SST) based on both NOAA/AVHRR (1981.07-2002.12) and MODIS/AQUA (2003.01-2009.12) ocean color data was analyzed. In addition, five climate indices, Arctic Oscillation Index (AO), Siberian High Index (SH), Aleutian Low Pressure Index (ALP), East Asia Winter Monsoon Index (EAWM) and Pacific Decadal Oscillation (PDO) which are the main indicators of climate changes in the northwestern Pacific were used to study the relationship between the magnitude of the estimated spawning ground and climate indices. The area of the estimated spawning ground was highly correlated with the total catch of common squid throughout four decades. The area of the estimated spawning ground was negatively correlated with SH and EAWM. Especially, PDO was negatively correlated with the area of the spawning ground in the northwestern Pacific (r = -0.39) and in the southern part of the East Sea (r = -0.38). There was a positive relationship between the AO and the area of the spawning ground in the northwestern Pacific (r = 0.46) as well as in the southern part of the East Sea (r = 0.32). Temporally, the area of the winter spawning ground in the southern part of the East Sea in the 1980s was smaller than those areas in the 1990s and 2000s, because the area was disconnected with the western coastal spawning ground of Japan in the 1980s, while the area had been made wider and more continuous from the Korea strait to the western coastal water of Honshu in the 1990s and 2000s.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.312-312
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• 2019

지구온난화로 인하여 기상학적 변동성 증가 및 수질, 수자원, 생태계 등의 다양한 영역에 영향을 야기하고 있으며, 이를 통한 피해가 전 세계적으로 증가하고 있는 추세이다. 이에 본 연구에서는 최근 다양한 분야에서 수문학적 빈도에 영향을 미친다고 알려진 AO(Arctic Oscillation), NAO(North Atlantic Oscillation), ENSO(El $Ni{\tilde{n}}o$-Southern Oscillation), PDO(Pacific Decadal Oscillation), MJO(Madden-Julian Oscillation)등의 외부인자중 SST, MJO를 활용하여 계절단위의 수문량 정도에서 기상학적 변량과 관측유역 강수량의 관계를 정립하고 발생 가능한 24시간 지속시간 극치강수량을 모의하였다. 이를 위하여 Bayesian 통계기법을 이용한 비정상성 빈도해석모형을 근간으로 외부 기상인자에 의한 계절강수량 예측모형인 계층적 베이지안 네트워크(Hierarchical Bayesian Network, HBN)를 구축한 후 산정된 결과를 입력 자료로 하여 직접적으로 일단위 이하의 극치강수량을 상세화 시킬 수 있는 베타 모델(four parameter beta, 4PB)을 연계한 계층적 베이지안 네트워크 베타모델(Hierarchical Bayesian Network-4beta Model, HBN4BM)을 개발하여 기상변동성을 고려한 상세화 모형을 개발하였다. 여름강수량 산정 결과 한강 유역의 경우 2016년은 관측값 573.85mm, 모의 값 567.15mm를 나타내어 약 1.2%의 오차를 나타냈으며, 2017년 및 2018년은 4.5%, 6.8%의 오차에서 모의가 이루어졌다. 금강의 경우 2016년은 다른 연도에 비하여 35.2%라는 큰 오차를 보였지만 불확실성 구간에서 모의가 이루어 졌으며, 2017년 및 2018년은 0.3%, 2.1%의 작은 오차가 발생하였다. 24시간 모의 결과는 최소 0.7%에서 최대 27.1%의 오차를 나타냈으며, 평균적으로 16.4%의 오차 결과가 모의되어 모형의 신뢰성을 확인하였다.

• Atmosphere
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• v.15 no.2
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• pp.101-118
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• 2005

Atmospheric ozone changes temporally and spatially according to both anthropogenic and natural causes. It is essential to quantify the natural contributions to total ozone variations for the estimation of trend caused by anthropogenic processes. The aims of this study are to understand the intrinsic natural variability of long-term total ozone changes and to estimate more reliable ozone trend caused by anthropogenic ozone-depleting materials. For doing that, long-term time series for Seoul of monthly total ozone which were measured from both ground-based Dobson Spectrophotometer (Beck #124)(1985-2004) and satellite TOMS (1979-1984) are analyzed for selected period, after dividing the whole period (1979~2004) into two periods; the former period (1979~1991) and the latter period (1992~2004). In this study, ozone trends for the time series are calculated using multiple regression models with explanatory natural oscillations for the Arctic Oscillation(AO), North Atlantic Oscillation(NAO), North Pacific Oscillation(NPO), Pacific Decadal Oscillation(PDO), Quasi Biennial Oscillation(QBO), Southern Oscillation(SO), and Solar Cycle(SC) including tropopause pressure(TROPP). Using the developed models, more reliable anthropogenic ozone trend is estimated than previous studies that considered only QBO and SC as natural oscillations (eg; WMO, 1999). The quasi-anthropogenic ozone trend in Seoul is estimated to -0.12 %/decade during the whole period, -2.39 %/decade during the former period, and +0.10 %/decade during the latter period, respectively. Consequently, the net forcing mechanism of the natural oscillations on the ozone variability might be noticeably different in two time intervals with positive forcing for the former period (1979-1991) and negative forcing for the latter period (1992-2004). These results are also found to be consistent with those analyzed from the data observed at ground stations (Sapporo, Tateno) of Japan. In addition, the recent trend analyses for Seoul show positive change-in-trend estimates of +0.75 %/decade since 1997 relative to negative trend of -1.49 %/decade existing prior to 1997, showing -0.74 %/decade for the recent 8-year period since 1997. Also, additional supporting evidence for a slowdown in ozone depletion in the upper stratosphere has been obtained by Newchurch et al.(2003).

• Atmosphere
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• v.19 no.2
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• pp.183-198
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• 2009

The purpose of this study is to summarize the tropical cyclone (TC) activity of 2008 over the western North Pacific including the verification of the official track and intensity forecast errors of these TCs. The TC activity - frequency, Normalized Typhoon Activity (NTA), and life span - was lower than 58-year (1951-2008) average. 22 tropical cyclones of tropical storm (TS) intensity or higher formed in the western North Pacific and the South China Sea in 2008. The total number is less than 58-year average frequency of 26.4. Out of 22 tropical cyclones, 11 TCs reached typhoon (TY) intensity, while the rest 11 TCs only reached severe tropical storm (STS) and tropical storm (TS) intensity - six STS and five TS storms. One typhoon KALMAEGI (0807) among them affected the Korea peninsula. However, no significant impact - casualty or property damage - was reported. On average of 22 TCs in 2008, the Korea Meteorological Administration (KMA) official track forecast error for 48 hours was 229 km. There was a big challenge for individual cyclones such as 0806 FENGSHEN and 0817 HIGOS presenting significant forecast error, with both intricate tracks and irregular moving speed. The tropical cyclone season in 2008 began in April with the formation of NEOGURI (0801). In May, four TCs formed in the western North Pacific in response to enhanced convective activity. On the other hand, the TC activity was very weak from June to August. It is found that the unusual anti-cyclonic circulation in the lower level and weak convection near the Philippines are dominant during summertime. The convection and atmospheric circulation in the western North Pacific contributed unfavorable condition for TC activity in the 2008 summertime. The 2008 TC activity has continued the below normal state since mid 1990s which is apparent the decadal variability in TC activity.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.27 no.2
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• pp.49-70
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• 2022

Sea Surface Temperature (SST), one of the ocean features, has a significant impact on climate, marine ecosystem and human activities. Therefore, SST prediction has been always an important issue. Recently, deep learning has drawn much attentions, since it can predict SST by training past SST patterns. Compared to the numerical simulations, deep learning model is highly efficient, since it can estimate nonlinear relationships between input data. With the recent development of Graphics Processing Unit (GPU) in computer, large amounts of data can be calculated repeatedly and rapidly. In this study, Short-term SST will be predicted through Convolutional Neural Network (CNN)-based U-Net that can handle spatiotemporal data concurrently and overcome the drawbacks of previously existing deep learning-based models. The SST prediction performance depends on the seasonal and interannual SST variabilities around the southern coast of Korea. The predicted SST has a wide range of variance during spring and summer, while it has small range of variance during fall and winter. A wide range of variance also has a significant correlation with the change of the Pacific Decadal Oscillation (PDO) index. These results are found to be affected by the intensity of the seasonal and PDO-related interannual SST fronts and their intensity variations along the southern Korean seas. This study implies that the SST prediction performance using the developed deep learning model can be significantly varied by seasonal and interannual variabilities in SST.