• Ocean and Polar Research
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• v.44 no.3
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• pp.221-233
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• 2022

A sediment trap had been deployed at 1250 m depth in the Eastern Tropical Pacific (ETP) from September 2009 to July 2010, with the aim of understanding the temporal and vertical variability of particle flux. During the monitoring period, total particle flux varied from 12.4 to 101.0 mg m^-2day^-1, with the higher fluxes in January-March 2010. Biogenic particle flux varied in phase with the total particle flux. The increase in total particle flux during January-March 2010 was attributed to the enhanced biological production in the surface layer caused by wind-driven mixing in response to the seasonal shifts in the location of the Intertropical convergence zone. The export ratio (e-ratio) was estimated using the particulate organic carbon flux and satellite-derived net primary production data. The estimated e-ratios changed between 0.8% and 2.8% (1.4±0.6% on average). The ratio recorded in the negative phase of Pacific decadal oscillation (PDO) was similar to the previous results obtained from the ETP during the 1992/93 periods in the positive phase of PDO. This suggests that the regime shift of the PDO is not related to the carbon export ratio.

• Fisheries and Aquatic Sciences
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• v.10 no.3
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• pp.150-158
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• 2007

Data on squid catches, water temperature, and climatic factors collected for the Northwest and subtropical North Pacific were analyzed to examine the influence of oceanic and climatic conditions in spawning grounds on catches of Japanese common squid, Todarodes pacificus, in the East (Japan) Sea. The main spawning ground was divided into four sub-areas: the South Sea of Korea (R1), the southern waters off Jeju, Korea (R2), the southwestern part of Kyushu, Japan (R3), and the northern part of Okinawa, Japan (R4). Interannual and decadal fluctuations in water temperatures correlated well with squid catches in the East/Japan Sea. In particular, water temperatures at a depth of 50 to 100 m in sub-areas R3 and R4 showed higher correlation coefficients (0.54 to 0.59, p<0.01) in relation to squid catches in the East/Japan Sea than for R1 and R2, which had correlation coefficients of 0.40 or less (p>0.05). Air temperature and wind velocity fluctuations in each sub-area are correlated with water temperature fluctuations and were closely connected with variations in the surface mixed layers. Water, air temperatures and wind velocities at the main spawning grounds are linked to the Southern Oscillation Index (SOI) with higher signals in the ca. 2-4-year band. Strong changes in a specific band and phase occurred around 1976/77 and 1986/87, coincident with changes in squid catches.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.537-537
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• 2015

In recent decades, the independence and identical distribution (iid) assumption for extreme events has been shown to be invalid in many cases because long-term climate variability resulting from phenomena such as the Pacific decadal variability and El Nino-Southern Oscillation may induce varying meteorological systems such as persistent wet years and dry years. Therefore, in the current study we propose a new parameter estimation method for probability distribution models to more accurately predict the magnitude of future extreme events when the iid assumption of probability distributions for large-scale climate variability is not adequate. The proposed parameter estimation is based on a metaheuristic approach and is derived from the objective function of the rth power probability-weighted sum of observations in increasing order. The combination of two distributions, gamma and generalized extreme value (GEV), was fitted to the GEV distribution in a simulation study. In addition, a case study examining the annual hourly maximum precipitation of all stations in South Korea was performed to evaluate the performance of the proposed approach. The results of the simulation study and case study indicate that the proposed metaheuristic parameter estimation method is an effective alternative for accurately selecting the rth power when the iid assumption of extreme hydrometeorological events is not valid for large-scale climate variability. The maximum likelihood estimate is more accurate with a low mixing probability, and the probability-weighted moment method is a moderately effective option.

• Ocean and Polar Research
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• v.41 no.3
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• pp.121-133
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• 2019

Natural variability associated with a variety of large-scale climate modes causes regional differences in sea level rise (SLR), which is particularly remarkable in the Pacific Ocean. Because the superposition of the natural variability and the background anthropogenic trend in sea level can potentially threaten to inundate low-lying and heavily populated coastal regions, it is important to quantify sea level variability associated with internal climate variability and understand their interaction when projecting future SLR impacts. This study seeks to identify the dominant modes of sea level variability in the tropical Pacific and quantify how these modes contribute to regional sea level changes, particularly on the two strong El $Ni{\tilde{n}}o$ events that occurred in the winter of 1997/1998 and 2015/2016. To do so, an adaptive data analysis approach, Ensemble Empirical Mode Decomposition (EEMD), was undertaken with regard to two datasets of altimetry-based and in situ-based steric sea levels. Using this EEMD analysis, we identified distinct internal modes associated with El $Ni{\tilde{n}}o$-Southern Oscillation (ENSO) varying from 1.5 to 7 years and low-frequency variability with a period of ~12 years that were clearly distinct from the secular trend. The ENSO-scale frequencies strongly impact on an east-west dipole of sea levels across the tropical Pacific, while the low-frequency (i.e., decadal) mode is predominant in the North Pacific with a horseshoe shape connecting tropical and extratropical sea levels. Of particular interest is that the low-frequency mode resulted in different responses in regional SLR to ENSO events. The low-frequency mode contributed to a sharp increase (decrease) of sea level in the eastern (western) tropical Pacific in the 2015/2016 El $Ni{\tilde{n}}o$ but made a negative contribution to the sea level signals in the 1997/1998 El $Ni{\tilde{n}}o$. This indicates that the SLR signals of the ENSO can be amplified or depressed at times of transition in the low-frequency mode in the tropical Pacific.

• Journal of the Korean earth science society
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• v.36 no.7
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• pp.611-616
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• 2015

El Nino and Southern Oscillation (ENSO) presents a broad band (2-8 year) variability and slowly changing amplitude and period, which are respectively referred to as ENSO irregularity and ENSO modulation. In this study, we developed a nonlinear low-order climate model by combining the Lorenz-63 model of nonlinear atmospheric variability and a simple ENSO model with recharge oscillator characteristics. The model successfully reproduced the ENSO-like variations in the sea surface temperature of eastern Pacific, such as the peak period, wide periodicity, and decadal modulations. The results show that the chaotic atmospheric forcing can lead to ENSO irregularity and ENSO modulation. It is also suggested the high probability of La Nina development could be associated with strong convection of the western warm pool. Although it is simple, this model is expected to be used in research on long-term climate change because it well captures the nonlinear air-sea interactions in the equatorial Pacific.

• Ocean Science Journal
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• v.43 no.1
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• pp.1-7
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• 2008

Physical and biological environmental variations in the East Sea were investigated by analysing time-series of oceanographic data and meteorological indices. From 1971 to 2000, dominant periodicity in water temperature variations had two apparent periods of 3 to 4 years and of decades, especially in the southwestern part of the East Sea affected by the influence of inflowing Tsushima warm current. Fluctuating water temperature within a certain period appears to respond to El $Ni{\tilde{n}}o$ events with a time lag. It was found that there was a strong correlation between water temperature and El $Ni{\tilde{n}}o$ events with a time lag of 1.5 and 5.5 years for periods of 3 to 6 years and of decades, respectively. Corresponding with El $Ni{\tilde{n}}o$ events, water temperature variability also showed strong correlation with shift and/or changes in biological and chemical environments of nutrient concentrations, zooplankton biomass, and fisheries. However, there also occurred a short-term periodicity of water temperature variations. Within a period of 1 to 4 years, a relatively short-term cycle of water temperature variation had strong correlation with other climate indices such as Pacific Decadal Oscillation and monsoon index. After comparing coherence and phase spectrum between water temperature and different climate indices, we found that there was a shift of coherent periods to another climate index during the years when climate regime shift was reported.