• Journal of Environmental Science International
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• v.9 no.4
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• pp.303-309
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• 2000

The relationship between air temperature and sea surface temperature and studied using the daily air temperature and sea surface temperature data for 25 years (1970~1994) at 9 coastal stations in Korea. Seasonal variations of air temperature have larger amplitudes than those of sea surface temperature. The seasonal variations of air temperature leads those of sea surface temperature by 2 to 3 weeks. The anomalies of sea surface temperature and air temperature with time scales more than 1 month are more ghighly correlated than those of short term, with time scales less than 1 month. Accumulated monthly anomalies of sea surface temperature and air temperature for 6 months shwoed higher correlation than the anomailes of each month. The magnitudes of sea surface temperature and air temperature anomalies are related with the duration of anomalies. Their magnitudes are large when the durations of anomalies are long.

• Journal of Climate Change Research
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• v.34 no.16
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• pp.6565-6581
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• 2021

This study investigates the role of the background meridional moisture gradient (MMG) on the propagation of the Madden-Julian oscillation (MJO) across the Maritime Continent (MC) region. It is found that the interannual variability of the seasonal mean MMG over the southern MC area is associated with the meridional expansion and contraction of the moist area in the vicinity of the MC. Sea surface temperature anomalies associated with relatively high and low seasonal mean MMG exhibit patterns that resemble those of El Niño-Southern Oscillation. By contrasting the years with anomalously low and high MMG, we show that MJO propagation through the MC is enhanced (suppressed) in years with higher (lower) seasonal mean MMG, although the effect is less robust when MMG anomalies are weak. Column-integrated moisture budget analysis further shows that sufficiently large MMG anomalies affect MJO activity by modulating the meridional advection of the mean moisture via MJO wind anomalies. Our results suggest that the background moisture distribution has a strong control over the propagation characteristics of the MJO in the MC region.

• Journal of the Korean earth science society
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• v.35 no.1
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• pp.88-94
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• 2014

The seasonal predictability of the intensity of the Northeast Asian summer monsoon is low while that of the western North subtropical high variability is, when state-of-the-art general circulation models are used, relatively high. The western North Pacific subtropical high dominates the climate anomalies in the western North Pacific-East Asian region. This study discusses the predictability of the western North Pacific subtropical High variability in the National Centers for Environmental Prediction Climate Forecast System (NCEP CFS). The interannual variability of the Northeast Asian summer monsoon is highly correlated with one of the western North Pacific subtropical Highs. Based on this relationship, we suggest a seasonal prediction model using NCEP CFS and canonical correlation analysis for Northeast Asian summer precipitation anomalies and assess the predictability of the prediction model. This methodology provides significant skill in the seasonal prediction of the Northeast Asian summer rainfall anomalies.

• Bulletin of the Korean Space Science Society
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• 2009.10a
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• pp.38.2-38.2
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• 2009

The ionosphere displays variations on a wide variety of time-scales, ranging from few hours to days and up to solar cycles and even more. In this paper, we examine the ionospheric F2-layer variability in mid latitude by analyzing the foF2 and hmF2 from the Anyang ionosonde. Especially, we investigate how ionospheric semi-annual and seasonal anomalies vary with local time and solar activity. In addition to the characterization of the ionospheric semi-annual an seasonal anomalies, our study extends to the investigation of the relationship between ionospheric variability and geomagnetic activity. Finally we also discuss the coupling between ionospheric F2-layer variability and thermospheric neutral composition.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.21 no.6
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• pp.351-360
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• 1988

Based on historic data of monthly means of sea surface temperatures (SST) for 24 years $(1921\~1944) $ at 23 Korean and Japanese coastal stations in the East Sea (the Japan Sea), we analyzed spatio-temporal characteristics of coastal SST and SST anomalies. The means of SST at Korean coast are higher than those at Japanese coast of the same latitudes, and the annual range of SST at Korean coast are larger than those at Japanese coast. Empirical orthogonal function analysis shows that almost all $(96\%)$ of the SST fluctuations are described by simultaneous seasonal variations. The flurtuations of SST anomalies are small in the Korea Strait and large at the boundaries between the warm and told currents in the basin. The fluctuations of SST anomalies along Korean coast are correlated each other The same is true for SST anomalies along Japanese coast. However, there is only weak correlation between the SST anomalies at Korean coast and those at Japanese coast. Empirical orthogonal function analysis shows that $27\%$ of the coastal SST anomalies in the East Sea are described by simultaneous fluctuations, and $12\%$ of them are described by alternating fluctuations between Korean and Japanese coasts.

• The Bulletin of The Korean Astronomical Society
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• v.35 no.1
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• pp.30.2-30.2
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• 2010

Numerous operational anomalies and satellite failures have been reported since the beginnings of the "space age". Space weather effects on modern spacecraft systems have been emphasized more and more as increasing their complexity and capability. Energetic particles potentially can destroy and degrade electronic components in satellites. We analyzed the geostationary (GEO) satellite anomalies during 1997-2009 to search possible influences of space weather on the satellite anomalies like power problem, control processor problem, attitude control problem, etc. For this we use particle data from GOES and LANL satellites to investigate space weather effects on the GEO satellites' anomalies depending on Kp index, local time, seasonal variation, and high-energy electron contribution. As results, we obtained following results: (1) there is a good correlation between geomagnetic index(Kp) and anomaly occurrences of the GEO satellite; (2) especially during the solar minimum, occurrence of the satellite anomalies are related to electron flux increase due to high speed solar wind; (3) satellite anomalies occurred more preferentially in the midnight and dawn sector than noon and dusk sector; (4) and the anomalies occurred twice more in Spring and Fall than Summer and Winter; (5) the electron with the lowest energy channel (50-75keV) has the highest correlation (cc=0.758) with the anomalies. High association between the anomalies and the low energy electrons could be understand by the facts that electron fluxes in the spring and fall are stronger than those in the summer and winter, and low-energy electron flux is more concentrated in the dawn sector where the GEO satellite anomalies occurred more frequently than high-energy electron flux. While we could not identify what cause such local time dependences, our results shows that low-energy electrons (~100keV) could be main source of the satellite anomaly, which should be carefully taken into account of operating satellites.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.741-749
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• 2021

The research paper endeavors to investigate the presence of seasonal anomalies in the Indian equity market. It also aims to verify the notion that equity markets are for long-term investors. The study employs daily index data of Sensex, Bombay Stock Exchange, to understand its volatility for the period ranging from January 2001 to August 2020. To analyze the seasonal effects in the stock market of India, multiple regression techniques along with descriptive analysis, graphical analysis and various statistical tests are used. The study also employs the rolling returns at different time intervals in order to understand the underlying risks and volatility involved in equity returns. The results from the analysis reveal that daily and monthly seasonality is not present in Sensex returns i.e., investors cannot earn abnormal returns by timing their investment decisions. Hence, the major finding of this study is that the Indian stock market performance is random, and the returns are efficient. The other major conclusion of the research is that the equity returns are profitable in the long run providing investors a hope that they can make gains and compensate for the loss in one period by a superior performance in some other periods.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.17 no.6
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• pp.557-565
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• 1984

The year-to-year fluctuations of seasonal variation of sea surface temperatures (SST) in the Korea Strait are studied based on monthly SST data for more than 50 years at Mitsushima ana Okinoshima in the strait. The frequency distribution of SST has two peaks at temperatures below and above the multi-year average, but that of SST anomalies has only one peak at the zero anomaly. More than $95\%$ of the anomalies are in the range of ${\pm}2^{\circ}C$. The harmonic constansts of seasonal SST variation vary from year to year. The standard deviations of annual means, annual amplitudes, ana semi-annual amplitudes are less than $1^{\circ}C$, and those of the annual ana semi-annual phases are about $5^{\circ}$ and less than $50^{\circ}$, respectively. The SST in the Korea Strait have a tendency to decrease their amplitudes as the annual means increase. Physical mechanisms responsible for the analyzed results are discussed in this paper.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.236-241
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• 1998

The NOAA AVHRR remote sense SST data, collected by the National Fisheries Research and Development Institute (NFRDI), are analyzed in order to understand the spatial and temporal distributions of SST in the seas adjacent to Korea. Our study is based on 10-day SST images during last 7 years (1991-1997). For a time series analysis of multiple 557 images, all of images must be aligned exactly at the same position by adjusting the scales and positions of each SST image. We devised an algorithm which yields automatic detections of cloud pixels from multiple SST images. The cloud detection algorithm is based on a physical constraint that SST anomalies in the ocean do not exceed certain limits (we used $\pm$ 3$^{\circ}C$ as a criterion of SST anomalies). The remote sense SST data are tuned by comparing remote sense data with observed SST at coastal stations. Seasonal variations of SST are studied by harmonic fit of SST normals at each pixel. The SST anomalies are studied by statistical method. We found that the SST anomalies are rather persistent with time scales between 1 and 2 months. Utilizing the persistency of SST anomalies, we devised an algorithm for a prediction of future SST Model fit of SST anomalies to the Markov process model yields that autoregression coefficients of SST anomalies during a time elapse of 10 days are between 0.5 and 0.7. We plan to improve our algorithms of automatic cloud pixel detection and prediction of future SST. Our algorithm is expected to be incorporated to the operational real time service of SST around Korea.

• Korean Journal of Remote Sensing
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• v.17 no.2
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• pp.183-188
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• 2001

The NOAA AVHRR remotely sensed SST data, collected by the National Fisheries Research and Development Institute (NFRDI), are analyzed in order to understand the spatial and temporal distributions of SST in the sea near korea. Our study is based on 10-day SST images during last 7 years (1991-1997). For a time series analysis of multiple SST images, all of images must be consistent exactly at the same position by adjusting the scales and positions of each SST image. We devised an algorithm which automatically detects cloud pixels from multiple SST images. The cloud detection algorithm is based on a physical constraint that SST anomalies in the ocean do not exceed certain limits (we used $\pm$3$^{\circ}C$ as a criterion of SST anomalies). The remotely sensed SST data are tuned by comparing remotely sensed data with observed SST at coastal stations. Seasonal variations of SST are studied by harmonic fit of SST normals at each pixel and the SST anomalies are studied by statistical method. It was found that the SST anomalies are rather persistent for one or two months. Utilizing the persistency of SST anomalies, we devised an algorithm for a prediction of future SST. In the Markov lprocess model of SST anomalies, autoregression coefficients of SST anomalies during a time elapse of 10 days are between 0.5 and 0.7. The developed algorithm with automatic cloud pixel detection and rediction of future SST is expected to be incorporated to the operational real time service of SST around Korea.