• Korean Journal of Fisheries and Aquatic Sciences
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• v.24 no.6
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• pp.413-427
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• 1991

Variability of sea levels at Mukho and Ullungdo and sea level difference(SLD) associated with current is investigated. Time series of adjusted sea levels at both places have very similar pattern of change. Two components appear to contribute to the correlation between sea level and SLD. Low frequency thermosteric effect causes the sea level to rise and fall at the same time. Geostrophic effect of major currents is responsible for the sea level change in opposite ways at both sides. Two contributions have a cancelling effect for sea level change at Mukho while they are additive at Ullungdo. Characteristics of time series in frequency domain are divided into two parts with respect to 0.01 cycles per day(cpd). At Mukho, the cancelling effect yields small values of coherence for low-frequency bands whereas the dominant geostrophic influence may be responsible for the phase relations of about $\pm 180^{\circ}$ between sea level and SLD at higher frequency. Bimonthly dynamic height difference(DHD) between Mukho and Ullungdo is very significantly correlated with SLD. This result suggests that DHD thus the average velocity of current through the Mukho-Ullungdo section can successfully be diagnosed by the sea level records at both locations. For the annual variations, maximum SLD occurs at Mukho-Ullungdo section about 40 days later than the Korea Strait.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.8
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• pp.573-581
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• 2022

This paper deals with the development of CanSat system, which ejects two maple seed-type autorotating science payloads and collects weather information. The CanSat consists of two autorotating science payloads and a container. The container is equipped with devices for launching science payloads and communication with the ground station, and launches science payloads one by one at different designated altitudes. The science payload consists of a space for loading and a large wing, and rotates to generate lift for slowing down the fall speed. Specifically, after being ejected, it descends at a speed of 20 m/s or less, measures the rotation rate, atmospheric pressure, and temperature, and transmits the measured value to the container at a rate of once per second. The communication system is a master-slave structure, and the science payload transmits all data to the master container, which aggregates both the received data and its own data, and transmits it to the ground station. All telemetry can be checked in real time using the ground station software developed in-house. A simulation was performed in the simulation environment, and the performance of the CanSat system that satisfies the mission requirements was confirmed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.5B
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• pp.485-493
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• 2008

The Artificial Neural Network (ANN) model was suggested for predicting probability of precipitation (PoP) using RDAPS NWP model, observation at AWS and upper-air sounding station. The prediction work was implemented for flood season and the data period is the July, August of 2001 and June of 2002. Neural network input variables (predictors) were composed of geopotential height 500/750/1000 hPa, atmospheric thickness 500-1000 hPa, X & Y-component of wind at 500 hPa, X & Y-component of wind at 750 hPa, wind speed at surface, temperature at 500/750 hPa/surface, mean sea level pressure, 3-hr accumulated precipitation, occurrence of observed precipitation, precipitation accumulated in 6 & 12 hrs previous to RDAPS run, precipitation occurrence in 6 & 12 hrs previous to RDAPS run, relative humidity measured 0 & 12 hrs before RDAPS run, precipitable water measured 0 & 12 hrs before RDAPS run, precipitable water difference in 12 hrs previous to RDAPS run. The suggested ANN has a 3-layer perceptron (multi layer perceptron; MLP) and back-propagation learning algorithm. The result shows that there were 6.8% increase in Hit rate (H), especially 99.2% and 148.1% increase in Threat Score (TS) and Probability of Detection (POD). It illustrates that the suggested ANN model can be a useful tool for predicting rainfall event prediction. The Kuipers Skill Score (KSS) was increased 92.8%, which the ANN model improves the rainfall occurrence prediction over RDAPS.

• Journal of the Korean Geographical Society
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• v.29 no.3
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• pp.266-280
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• 1994

Upper-air synoptic data and surface weather elements such as temperature, relative humidity, wind speed, cloud and precipitation were analyzed in some detail to determine the characteristics of Nopsae, a foehn-like surface wind over the Youngsuh region of Central Korea. NOAA AVHRR and GMS images are also referenced to identify the distribution of clouds and precipitation to classify the tpyes of foehn over the study area. The data period examined is from 1982 until 1993 of spring and summer months from March through August. Results of the anaylsis are as follows. Warm and dry air penetration over the Younesuh region has experienced on foehn days occured between March 21 and August 10 during study perion. The mean annual number of foehn the days were 28. Foehn phenomena were prominent during March 21-25, April 5-15, May 25-June 10, and June 26-30 pentads. The intensity of the phenomena can be evaluated as the difference of daily maximum temperature and relative humidity between windward sites and leeward sites. The intensity of daily maximum temperature reached 14.5$^{\circ}C$, but most values were in the range of 5.0-7.5$^{\circ}C$ (61%). Although strong intensity of foehns usually develop in June, it is common that farmers in the region experince more aridity during the foehnday of April and May due to the transplantation of rice seedlings. Long-run foehn are not common phenomena and 55% of foehn terminate in one day, but there is a record that Nopsae persisted up to 9 days continuously. The author identified using the cloud and precipitation data out of NOAA-11, AVHRR and GMS images is that one of them has no precipitation over windward side. The available data and the results of the analysis are somewhat inadequate. Since the results imply that wave phenomenon is potentially important in terms of local surface weather and vertical momentum transport, more detailed theoretical and observational studies are necessary to clarify the mechanism and the impacts of Nopsae.

• Journal of Climate Change Research
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• v.9 no.4
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• pp.423-433
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• 2018

Particulate matter air pollution is a serious problem affecting human health and visibility. The variations in $PM_{10}$ concentrations are influenced by not only local emission sources, but also atmospheric circulation conditions. In this study, we investigate the temporal features of $PM_{10}$ concentrations in South Korea and the atmospheric circulation patterns associated with high concentration episodes of $PM_{10}$ during winter (December-January-February) 2001-2016. Based on those analyses, a Korea Particulate matter Index (KPI) is developed to represent the large-scale atmospheric pattern associated with high concentration episodes of $PM_{10}$. The atmospheric patterns are characterized by persistent high-pressure anomalies, weakened lower-level north-westerly anomalies, and northward shift of the upper-level meridional wind anomalies near the Korean Peninsula. To evaluate the change in occurrence of high concentration episodes of $PM_{10}$ under a possible future warmer climate, we apply KPI analysis to CMIP5 climate simulations. Here, historical and two representative concentration pathway (RCP) scenarios (RCP 4.5 and RCP 8.5) are used. It is found that the occurrence of atmospheric conditions favorable for high $PM_{10}$ concentration episodes tends to increase over South Korea in response to climate change. This suggests that large-scale atmospheric circulation changes under future warmer climate can contribute to increasing high $PM_{10}$ concentration episodes in South Korea.