• Journal of Astronomy and Space Sciences
• /
• v.27 no.4
• /
• pp.319-327
• /
• 2010

We examine the ionospheric F2-layer electron density variation by solar activity in middle latitude by using foF2 observed at the Kokubunji ionosonde station in Japan for the period from 1997 to 2008. The semi-annual variation of foF2 shows obviously in high solar activity (2000-2002) than low solar activity (2006-2008). It seems that variation of geomagnetic activity by solar activity influences on the semi-annual variation of the ionospheric F2-layer electron density. According to the Lomb-Scargle periodogram analysis of foF2 and Ap index, interplanetary magnetic field (IMF) Bs (IMF Bz <0) component, solar wind speed, solar wind number density and flow pressure which influence the geomagnetic activity, we examine how the geomagnetic activity affects the ionospheric F2-layer electron density variation. We find that the semi-annual variation of daily foF2, Ap index and IMF Bs appear clearly during the high solar activity. It suggests that the semi-annual variation of geomagnetic activity, caused by Russell-McPherron effect, contributes greatly to the ionospheric F2-layer semi-annual electron density variation, except dynamical effects in the thermosphere.

• Journal of the Korean Geophysical Society
• /
• v.7 no.1
• /
• pp.11-21
• /
• 2004

The variation of geomagnetic field and absolute magnetic field at the geomagnetic observatory of King Sejong Station has been measured with 3-component ring core fluxgate magnetometer, proton magnetometer and D-I magnetometer. With data obtained from King Sejong Station during 2003, thediurnal and annual variations of geomagnetic field were researched and compared with those at other observatories. The deviation of daily variation of magnetic field in antarctica decreased gradually during winter season due to sun effect. The rates of componental annual variation of magnetic field at King Sejong Station were calculated using the least-square method under the assumption that the annual variation of magnetic field is linear. The rates are -55.93 nT/year in horizontal intensity, -0.87 min./year in declination, 58.30 nT/year in vertical intensity, and -69.85 nT/year in total intensity of magnetic field. A remarkable variation was caused by the magnetic storms occurred on 29~30 October, which were so powerful that the variation was observed in mid latitudes as well as high latitudes. The values of variation are generally 1500 2000 nT in Antarctica including King Sejong Station, 350 500 nT in East Asia. The measurement of absolute magnetic field shows that ring core fluxgate magnetometer has relatively large error range under cold temperature.

• Korean Journal of Microbiology
• /
• v.20 no.3
• /
• pp.113-118
• /
• 1982

The distribution and annual variation of detergent-degrading bacteria which were isolated from the Han River downstream running through the center of Seoul area were studied. The concentration of dissolved detergent was the lowest, 2.16 ppm at site 1 and it was gradually increased to downstream, the highest, 2.67 ppm at site 4. Population density of detergent degrading bacteria was about $10^2{\sim}10^3 cells/ml$. The density of LAS degrading bacteria was 1.1 - 1.8 times larger than that of SDBS-degrading bacteria. In annual variation the lowest density was appeared on January and the highest on July. In seasonal distribution of LAS-degrading bacteria, annual dominant group was genus Pseudomonas. There were few except genus Pseudomonas in winter and the subdomiannt group in spring and summer was genus Aeromonas and Enterobacteriaceae respectively. In autumn genus Pseudomonas, Aeromonas and Enterobacteriaceae were equally distributed. In SDBS-degrading bacteria, the annual dominant group was also genus Pseudomonas.

• Fisheries and Aquatic Sciences
• /
• v.3 no.2
• /
• pp.163-171
• /
• 2000

A series of numerical experiments are performed to examine the generation of inter-annual variations by an inertial current in an idealized semi-enclosed basin with dimension comparable to that of the East Sea. Model results indicate that the inter-annual variations dominate the kinetic energy spectrum with a peak around the time scales of 2-3 years. These variations are mostly due to the westward propagating meanders and large eddies induced by the instability of current, indicating their dependency on the eddy-resolving capacity of the model. They are generated in the interior of the basin but their energy is largely confined near the western boundary such that the east-west dimension of the basin cannot be considered as a critical factor as long as the basin covers enough western boundary region. Overall, this study suggests that the inter-annual variation observed in the East Sea is due to the meandering and large eddies induced by the instability of the current.

• Environmental Analysis Health and Toxicology
• /
• v.22 no.2 s.57
• /
• pp.111-118
• /
• 2007

This study was performed to measure gaseous Organochlorine Pesticides (OCPs : heptachlor epoxide, ${\alpha}/{\gamma}-chlordane$, trans-nonachlor, endosulfan, ${\gamma}-HCH$ and p, p'-DDE) concentration using PUF high volume sampler from June, 2000 to June, 2002 in the semi-rural atmosphere. Using monitoring data for two years, we tried to investigate the annual cycles of gaseous OCPs. We considered three functions to describe the annual cycle: Gaussian, Lorentzian and sinusoidal functions. These functions accounted for $54{\sim}91%$ of the variability in concentration for each gaseous OCPs, and the sinusoidal function gave the best fits. It was seen that the gaseous OCPs concentration increased during the warmer weather while decreased during colder weather. The variation of the gaseous OCPs concentration was closely similar to the variations of ambient temperature. The annual cycle of endosulfan was strongly higher than in comparison with other gaseous OCPs, while for ${\gamma}-HCH$, the cycle was weakly high and did not show apparent seasonal variation. The position of the annual maximum exists generally late July to early August. The period that showed levels more than a half maximum was from late June to early September.

• Journal of Positioning, Navigation, and Timing
• /
• v.5 no.2
• /
• pp.87-96
• /
• 2016

The ionospheric error, which is one of many error elements considered during the Global Navigation Satellite System (GNSS) positioning, is hard to be predicted due to the influence of geomagnetic activity and irregular solar activities. Thus, the present study analyzed a change pattern in the ionosphere through Global Ionosphere Map (GIM) data for 12 years from 2003 to 2014 and a variation in the Slant Total Electron Content (STEC) between Sinuiju and Busan which was the longest range in the southeastern direction of the Korean Peninsula. The variation in the STEC verified the diurnal, annual, and solar cycle variations due to the influence of solar activity. The diurnal variation was characterized that the variation in the STEC started to increase from 6-7 am and reached the maximum at 13-14 pm followed by being decreased. The seasonal variation was characterized that the variation in the STEC was high in spring and autumn whereas it was low in summer and winter. The solar cycle variation revealed that the variation in the STEC increased during solar maximum and decreased during solar minimum. The variation in the STEC was up to 20 Total Electron Content Unit (TECU) during the solar minimum and up to 60 TECU during solar maximum.

• 한국해양학회지
• /
• v.19 no.2
• /
• pp.105-110
• /
• 1984

We study the annual variation of salinity at the sea surface and at 30m depth in the neighbouring seas of korea by the harmonic method. The analysis based on the monthly salinity data at 182 stations collected regularly by the Fisheries Research and Development Agency during 15 years (1961∼1975). The annual mean salinity in the West Sea is lower than that in the East Sea. In the amplitude of annual salinity variation decreases and the phase delays with the downstream distance of the Tsushima Current. The salinity at 30m has a higher mean, a smaller amplitude and a delayed phase than the corresponding ones at the surface. The annual variations of salinity in the South and East Seas are caused mainly by the annual variations of the local precipitation and that of the fresh water discharge from the Yangtze River.

• Journal of the Korean Geographical Society
• /
• v.30 no.3
• /
• pp.207-229
• /
• 1995

The characteristics of weather and climate in South Korea has great influences on the annual variation pattern and the appearance of the prevailing weather. The purpose of this paper is to induce the quantity of the weather entropy and annual variation pattern using the information theory and the principal component analysis. And author tried to classify the region according to the variation of its space scale, The raw materials used for this study are the daily cloudiness and precipitation during the years 1990-1994 at 69 stations in South Korea. It is divided into four classes of fine, clear, cloudy and rainy. The rcsults of this study can be summarized as follows: 1. Thc characteristics of annual variation pattern of weather entropy can be chiefly divided into five categories and the accumulated contributory rate of these is 73.1%. 2. Annual variation pattern of the first principal component reaches smaller in May, April and September than national average, and becomes greater when the winter comes. This weather entropy's quantity(Rs1) is positive in most area to the western sife of Soback Mountains and negative in most seaside area to the eastern side of Soback Mountains. 3. The characteristics of annual variation pattern of the second principal component shows that the entropy is more smaller in summer than national average and the rest of seasons shows larger, especially in January, May and September. This weather entropy's quantity(Rs2) is positive in most Honam Inland area to the western side of Soback Mountains and negative in most Youngnam Inland area to the eastern side of Soback Mountains. 4. Eight type regions (S1-S11) are classified based on the occurrences of minimum weather entropy in South Korea, and annual variation pattern of weather entropy by principal component analysis may be classified into sixteen type regions (Rs1-Rs9). Putting these things together, South Korea can be classifieed into thirty one type regions (Rs1S7-Rs9S10).

• Proceedings of the KSRS Conference
• /
• 1999.11a
• /
• pp.140-143
• /
• 1999

SSH(Sea Surface Height) from TOPEX/Poseidon and SST data are analyzed to estimate characteristics of annual and inter-annual variations in the East Asian seas(110E - l80E, 20N - 50N) from November 1992 to May 1998. In EOF analysis of SSH and SST, 57% and 97% of the variance are represented by the first two modes. The first mode of SSH and SST shows strong annual variations expected for steric changes. The second mode of SSH shows a long-term variation, but that of SST shows 3 - 4month offset from annual variation. In the EOF analysis of the SSH and SST, 61% and 54% of the total variance are represented by the first three modes. The first mode represented a long-term variation, and the third mode reflected the bi-ennial variation. The first three mode were not strongly correlated with ENSO. We further apply Canonical Correlation Analysis(CCA) to find the dominant correlation patterns with ENSO.

• Journal of Korean Society for Atmospheric Environment
• /
• v.19 no.2
• /
• pp.231-245
• /
• 2003

Hourly PM$_{10}$ concentrations measured at 11 sites in Seoul and 10 sites in the large cities over South Korea for the period from March 1995 to February 2000 are analyzed to examine annual trend and monthly variations of the PM$_{10}$ concentrations. Further analysis has been carried out by using the one year data from March 1999 to February 2000 to see the seasonal variation, diurnal variation and weekly variation of the seasonally averaged PM$_{10}$ concentrations at each site. Weekly variations of the CO concentrations at the same sites for the same one year period are compared with that of the PM$_{10}$ concentration. There is no significant annual trend in the variation of the PM$_{10}$ concentration at all the sites analyzed. The seasonal and monthly mean concentrations show a minimum concentration in summer and alternative maximum concentration in spring and winter for most sites. The diurnal variation of the seasonally averaged mean PM$_{10}$ concentrations is strongly affected by traffic loads and meteorological conditions. The weekly variation of seasonal averaged concentrations of CO and PM$_{10}$ shows a high concentration for weekdays in spring, autumn and winter while high concentration for weekends in summer.nds in summer.