• Journal of Korea Water Resources Association
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• v.52 no.8
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• pp.575-587
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• 2019

This study evaluated the effect of a mother wavelet in the wavelet analysis of various times series made by combining white noise and/or sine function. The result derived is also applied to short-memory arctic oscillation index (AOI) and long-memory southern oscillation index (SOI). This study, different from previous studies evaluating one or two mother wavelets, considers a total of four generally-used mother wavelets, Bump, Morlet, Paul, and Mexican Hat. Summarizing the results is as follows. First, the Bump mother wavelet is found to have some limitations to represent the unstationary behavior of the periodic components. Its application results are more or less the same as the spectrum analysis. On the other hand, the Morlet and Paul mother wavelets are found to represent the non-stationary behavior of the periodic components. Finally, the Mexican Hat mother wavelet is found to be too complicated to interpret. Additionally, it is also found that the application result of Paul mother wavelet can be inconsistent for some specific time series. As a result, the Morlet mother wavelet seems to be the most stable one for general applications, which is also assured by the recent trend that the Morlet mother wavelet is most frequently used in the wavelet analysis research.

• 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.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1299-1310
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• 2018

In this study, we analyzed distribution and movement trends using in-situ observations and particle tracking methods to understand the movement of the drift ice in the Arctic Ocean. The in-situ movement data of the drift ice in the Arctic Ocean used ITP (Ice-Tethered Profiler) provided by NOAA (National Oceanic and Atmospheric Administration) from 2009 to 2018, which was analyzed with the location and speed for each year. Particle tracking simulates the movement of the drift ice using daily current and wind data provided by HYCOM (Hybrid Coordinate Ocean Model) and ECMWF (European Centre for Medium-Range Weather Forecasts, 2009-2017). In order to simulate the movement of the drift ice throughout the Arctic Ocean, ITP data, a field observation data, were used as input to calculate the relationship between the current and wind and follow up the Lagrangian particle tracking. Particle tracking simulations were conducted with two experiments taking into account the effects of current and the combined effects of current and wind, most of which were reproduced in the same way as in-situ observations, given the effects of currents and winds. The movement of the drift ice in the Arctic Ocean was reproduced using a wind-imposed equation, which analyzed the movement of the drift ice in a particular year. In 2010, the Arctic Ocean Index (AOI) was a negative year, with particles clearly moving along the Beaufort Gyre, resulting in relatively large movements in Beaufort Sea. On the other hand, in 2017 AOI was a positive year, with most particles not affected by Gyre, resulting in relatively low speed and distance. Around the pole, the speed of the drift ice is lower in 2017 than 2010. From seasonal characteristics in 2010 and 2017, the movement of the drift ice increase in winter 2010 (0.22 m/s) and decrease to spring 2010 (0.16 m/s). In the case of 2017, the movement is increased in summer (0.22 m/s) and decreased to spring time (0.13 m/s). As a result, the particle tracking method will be appropriate to understand long-term drift ice movement trends by linking them with satellite data in place of limited field observations.

• Atmosphere
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• v.25 no.2
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• pp.323-337
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• 2015

This study explores the 6-month lead prediction skill of several climate indices that influence on East Asian climate in the GloSea5 hindcast experiment. Such indices include Nino3.4, Indian Ocean Diploe (IOD), Arctic Oscillation (AO), various summer and winter Asian monsoon indices. The model's prediction skill of these indices is evaluated by computing the anomaly correlation coefficient (ACC) and mean squared skill score (MSSS) for ensemble mean values over the period of 1996~2009. In general, climate indices that have low seasonal variability are predicted well. For example, in terms of ACC, Nino3.4 index is predicted well at least 6 months in advance. The IOD index is also well predicted in late summer and autumn. This contrasts with the prediction skill of AO index which shows essentially no skill beyond a few months except in February and August. Both summer and winter Asian monsoon indices are also poorly predicted. An exception is the Western North Pacific Monsoon (WNPM) index that exhibits a prediction skill up to 4- to 6-month lead time. However, when MSSS is considered, most climate indices, except Nino3.4 index, show a negligible prediction skill, indicating that conditional bias is significant in the model. These results are only weakly sensitive to the number of ensemble members.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.2
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• pp.61-72
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• 2007

The relationship between North Pacific chum salmon (Oncorhynchus keta) population and climate variability was investigated in the North Pacific ecosystem. Time-series for the Aleutian Low Pressure, Southern Oscillation, Arctic Oscillation, and Pacific Decadal Oscillation (PDO) indices dating back to 1950 are compared with the chum salmon catch using a cross-correlation function (CCF) and cumulative sum (CuSum) of anomalies. The results of CCF and CuSum analyses indicated that there was a major change in climate during the mid 1970s, and that the chum salmon population responded to this climate event with a time-lag. The PDO and chum salmon returns showed a highly significant correlation with a time-lag of 3 years, while the AOI with a time-lag of $6{\sim}7$ years. The favorable environments for fry chum salmon might cause better growth in the coastal areas, but higher growth rate during the early stage does not seem to be related to the improved return rate of spawning adults. Rather, growth in the Okhotsk Sea or the Bering Sea during immature stages has a significant correlation with return rate, which implies the size-related mortality process. The development of a local climate index is necessary to elucidate the effect of climate variability on the marine ecosystem around the Korean Peninsula.

• Journal of Korea Water Resources Association
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• v.52 no.11
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• pp.905-916
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• 2019

This study explores the effect of mother wavelet in the bivariate wavelet analysis. A total of four mother wavelets (Bump, Mexican hat, Morlet, and Paul) which are frequently used in the related studies is selected. These mother wavelets are applied to several bivariate time series like white noise and sine curves with different periods, whose results are then compared and evaluated. Additionally, two real time series such as the arctic oscillation index (AOI) and the southern oscillation index (SOI) are analyzed to check if the results in the analysis of generated time series are consistent with those in the analysis of real time series. The results are summarized as follows. First, the Bump and Morlet mother wavelets are found to provide well-matched results with the theoretical predictions. On the other hand, the Mexican hat and Paul mother wavelets show rather short-periodic and long-periodic fluctuations, respectively. Second, the Mexican hat and Paul mother wavelets show rather high scale intervention, but rather small in the application of the Bump and Morlet mother wavelets. The so-called co-movement can be well detected in the application of Morlet and Paul mother wavelets. Especially, the Morlet mother wavelet clearly shows this characteristic. Based on these findings, it can be concluded that the Morlet mother wavelet can be a soft option in the bivariate wavelet analysis. Finally, the bivariate wavelet analysis of AOI and SOI data shows that their periodic components of about 2-4 years co-move regularly every about 20 years.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.16 no.1
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• pp.1-13
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• 2011

The Yellow Sea Cold Water (YSCW) is formed by cold and dry wind in the previous winter, and is known to spread southward along the central trough of the Yellow Sea in summer. Water characteristics of the YSCW and its movement in the northern East China Sea (ECS) are investigated by analyzing CTD (conductivity-Temperature-Depth) data collected from summertime hydrographic surveys between 2003 and 2009. By water mass analysis, we newly define the North Western Cold Water (NWCW) as a cold water mass observed in the study area. It is characterized by temperature below $13.2^{\circ}C$, salinity of 32.6~33.7 psu, and density (${\sigma}_t$) of 24.7~25.5. The NWCW appears to flow southward at about a speed less than 2 cm/s according to the geostrophic calculation. The newly defined NWCW shows an interannual variation in the range of temperature and occupied area, which is in close relation with the sea surface temperature (SST) over the Yellow Sea and the East China Sea in the previous winter season. The winter SST is determined by winter air temperature, which shows a high correlation with the winter-mean Arctic Oscillation (AO) index. The negative winter-mean AO causes the low winter SST over the Yellow Sea and the East China Sea, resulting in the summertime expansion and lower temperature of the NWCW in the study area. This study shows a dynamic relation among the winter-mean AO index, SST, and NWCW, which helps to predict the movement of NWCW in the northern ECS in summer.