• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.1085-1092
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• 2009

The ozone data is one of the important environmental data for measurement of the atmospheric condition of the country. In this article, the Autoregressive Error (ARE) model and Neural Networks (NN) model have been considered for analyzing the ozone data at the northern part of the Gyeonggi-Do, Paju monitoring site in Korea. In the both ARE model and NN model, seven meteorological variables and four pollution variables are used as the explanatory variables for the ozone data set. The seven meteorological variables are daily maximum temperature, wind speed, relative humidity, rainfall, dew point temperature, steam pressure, and amount of cloud. The four air pollution explanatory variables are Sulfur dioxide ($SO_2$), Nitrogen dioxide ($NO_2$), Cobalt (CO), and Promethium 10 (PM10). The result showed that the NN model is generally better suited for describing the ozone concentration than the ARE model. However, the ARE model will be expected also good when we add the explanatory variables in the model.

• Journal of KIISE
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• v.42 no.3
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• pp.281-288
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• 2015

A volcano disaster damage prediction system supports decision making for counteracting volcanic disasters by simulating meteorological condition and volcanic eruptions. In this system, a program called Fall3D generates predicted results for the diffusion of ash after a volcanic eruption on the basis of meteorological information. The relevant meteorological information is generated by a weather numerical prediction model known as Weather Research & Forecasting (WRF). In order to reduce the entire processing time without modifying these two simulation programs, pipelining can be used by partly executing Fall3D whenever the hourly (partial) results of WRF are generated. To reduce the processing time, successor programs such as Fall3D require that certain features be suspended until the part of the results that is based on prior calculation is generated by a predecessor. Even though Fall3D does not have a suspend or resume feature, pipelining effect can be produced by using the program's restart feature, which resumes simulation from the previous session. In this study, we suggest a workflow that can control the execution type.

• Atmosphere
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• v.19 no.3
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• pp.269-287
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• 2009

CAT (clear-air turbulence) forecasting algorithm, the Graphical Turbulence Guidance (GTG) system developed at NCAR (national center for atmospheric research), is evaluated with available observations (e.g., pilot reports; PIREPs) reported in South Korea during the recent 5 years (2003-2008, excluding 2005). The GTG system includes several steps. First, 44 CAT indices are calculated in the domain of the Regional Data Assimilation and Prediction System (RDAPS) analysis data with 30 km horizontal grid spacing provided by KMA (Korean Meteorological Administration). Second, 10 indices that performed ten best forecasting scores are selected. Finally, 10 indices are combined by measuring the score based on the probability of detection, which is calculated using PIREPs exclusively of moderate-or-greater intensity. In order to investigate the best performance of the GTG system in Korea, various statistical examinations and sensitivity tests of the GTG system are performed by yearly and seasonally classified PIREPs. Performances of the GTG system based on yearly distributed PIREPs have annual variations because the compositions of indices are different from each year. Seasonal forecasting is generally better than yearly forecasting, because selected CAT indices in each season represent meteorological condition much more properly than applying the selected CAT indices to all seasons. Wintertime forecasting is the best among the four seasonal forecastings. This is likely due to that the GTG system consists of many CAT indices related to the jet stream, and turbulence associated with the jet stream can be activated mostly in wintertime under strong jet magnitude. On the other hand, summertime forecasting skill is much less than other seasons. Compared with current operational CAT prediction system (KITFA; Korean Integrated Turbulence Forecasting System), overall performance of the GTG system is better when CAT indices are selected seasonally.

• Atmosphere
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• v.27 no.3
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• pp.345-358
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• 2017

The decadal change in rainfall for Changma period over the South Korea in early-2000s is detected in this study. The Changma rainfall in P1 (1992~2002) decade is remarkably less than in P2 (2003~2013) decade. The much rainfall in P2 decade is associated with the increase of rainy day frequency during Changma period, including the frequent occurrences of rainy day with a intensity of 30 mm/day or more in P2 decade. This decadal change in the Changma rainfall is due to the decadal change of atmospheric circulation around the Korean Peninsula which affects the intensity and location of Changma rainfall. During P2 decade, the anomalous anti-cyclone over the south of the Korean Peninsula, which represents the expansion of the North Pacific high with warm and wet air mass toward East Asia, is stronger than in P1 decade. In addition, the upper level zonal wind and meridional gradient of low-level equivalent potential temperature in P2 decade is relatively strengthened over the northern part of the Korean Peninsula than in P1 decade, which corresponds with the intensification of meridional gradient between air mass related to the East Asian summer monsoon nearby the Korean Peninsula in P2 decade. The enhanced meridional gradient of atir mass during P2 decade is favorable condition for the intensification of Changma rainfall band and more Changma rainfall. The atmospheric conditions related to enhanced Changma rainfall during P2 decade is likely to be influenced by the teleconnection linked to the suppressed convection anomaly over the southern part of China and South China Sea in P2 decade.

• Atmosphere
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• v.27 no.3
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• pp.291-300
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• 2017

The monthly-mean irradiance of ultra violet (UV)-B and UV-A observed from 2005 to 2014 and 2012 to 2014, respectively, at noon in Gosan, Jeju, South Korea are analyzed. We compare cloudiness, total ozone, visibility, and relative humidity with an emphasis on the four months from May to August (MJJA), which shows the largest UV radiation. While the incoming UV-B radiation at the top of the atmosphere in Gosan is the largest in June due to the small solar zenith angle, the observed surface UV-B shows an unexpected smaller value in June than those in May, July or August. In June, the meteorological conditions affecting Gosan are completely dominated by cloudiness and thus, frequent overcast seems to determine the minimum UV-B. Another important UV-determining factor is the total ozone, which exhibits a monotonic decrease during MJJA without agreeing to the characteristic feature of UV. The ratio of UV-B to UV-A is not generally influenced by cloudiness. Thus, the ratio is a useful indicator of atmospheric turbidity showing larger values for increasing visibility, except in June. A simple model has been used to estimate surface UV by using the observed ozone and visibility in the cloudless condition. The result shows that UV has the lowest value in June with small variation during MJJA. Model estimation also shows that the different characteristic features observed in July between surface UV-B and UV-A is the result of less absorption of UV-B by ozone than that of UV-A by a smaller amount of total ozone.

• Journal of Satellite, Information and Communications
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• v.8 no.3
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• pp.32-40
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• 2013

The Boltwood Cloud Sensor is meteorological sensor that is used to estimate an amount of clouds in the sky. This sensor will be installed for OWL(Optical Wide-field patroL) telescope and observatory system of Korea Astronomy and Space Science. Before applying this sensor to an observatory system, we performed test observations at Chungbuk University Observatory at Jincheon, Chungbuk. During the test run, a significant correlation between air temperature difference and the number of visible stars recorded in the CCD frames has not been found. This preliminary result can be attributed to test environment of the observation and our lack of knowledge on calculation algorithm as well as the hardware system of the Boltwood Cloud Sensor.In this paper, we present the procedure and the result of the performance test employing the cloud sensor.

• Journal of Environmental Science International
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• v.15 no.5
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• pp.417-430
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• 2006

We focused on improvement in simulation of wind fields for the complex coastal area. Local Analysis and Prediction System(LAPS) was used as a data assimilation method to improve initial conditions. Case studies of different LAPS inputs were performed to compare improvement of wind fields. Five cases have been employed : I) non data assimilation, II) all available data, III) AWS, buoy, QuikSCAT, IV) AWS, buoy, wind profiler, V) AWS, buoy, AMEDAS. Data assimilation can supplement insufficiency of the mesoscale model which does not represent detailed terrain effect and small scale atmospheric flow fields. Result assimilated all available data showed a good agreement to the observations rather than other cases and estimated veil the local meteorological characteristics including sea breeze and up-slope winds. Result using wind profiler data was the next best thing. This implies that data assimilation with many high-resolution sounding data could contribute to the improvements of good initial condition in the complex coastal area. As a result, these indicated that effective data assimilation process and application of the selective LAPS inputs played an important role in simulating wind fields accurately in a complex area.

• Journal of the Korean Solar Energy Society
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• v.34 no.2
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• pp.60-65
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• 2014

A meteorological(met) tower is the first structure installed during the planning stages of offshore wind farm. The purpose of this paper is to design the met tower with tripod bucket type support structure and to install the sensors. The support structure consist of a central steel shaft connected to three cylindrical steel suction buckets which is more cheaper than monopile or jacket type. And the remote wind condition sensors and marine monitoring equipment, including adcp, pressure type tide gauge, wave height sensors, and scour sensors, remote power supply are installed. The manufactured met tower constructed on sea area which is in front of Gasa island. All of functions of met tower showed normal operation conditions and the wind data got by remote data collection system successfully.

• Proceedings of the Korean Environmental Sciences Society Conference
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• 2003.11a
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• pp.51-54
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• 2003

We analyzed radiative properties of aerosols, $CO^{2}$ and clouds using Optical Properties of Aerosols and Clouds(OPAC) and the Column Radiation Model (CRM). From OPAC, if the soot component is disregarded, dust-like components depict the highest extinction values in the solar spectral range and the lowest. single scattering albedoes, which are attributable to the presence of large particles. In the dust aerosol, the high absorptivity in the infrared may induce a warming of the lower atmospheric layer in the nighttime. The radiative properties of aerosols, clouds and double $CO^{2}$ using the CRM model at Seoul (37N, 127.4 E) on 3 April 2003 were calculated. The solar zenith angle is 65˚ and the surface albedo is 0.1836 during the clear day. The aerosol optical depth change 0.14 to 1.7, which is derived during Asian dust days in Korea. At this time, abedo by aerosols is considered as 0.3. In cloudy condition, the short wave cloud forcing on both the TOA and the surface is -193.89 $Wm^{-2}$ and -195.03 $Wm^{-2}$, respectively, and the long wave cloud forcing is 19.58 $Wm^{-2}$ and 62.08 $Wm^{-2}$, respectively. As a result, the net radiative cloud forcing is -174.31 $Wm^{-2}$ and -132.95 $Wm^{-2}$, respectively. We calculate also radiative heating rates by double $CO^{2}$ during the clear day. The $CO^{2}$ volumn mixing ratio is 3.55E-4.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.11
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• pp.1787-1796
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• 2020

Objective: The objective of this study was to determine the digestible energy (DE) and metabolizable energy (ME) of yellow dent corn sourced from different meteorological origins fed to growing pigs and develop equations to predict the DE and ME of yellow dent corn from southwestern China. Methods: Sixty crossbred barrows were allotted to 20 treatments in a triplicate 20×2 incomplete Latin square design with 3 replicated pigs per dietary treatment during 2 consecutive periods. Each period lasted for 12 days, and total feces and urine during the last 5 days of each period were collected to calculate the energy contents. Results: On dry matter (DM) basis, the DE and ME in 20 corn grain samples ranged from 15.38 to 16.78 MJ/kg and from 14.93 to 16.16 MJ/kg, respectively. Selected best-fit prediction equations for DE and ME (MJ/kg DM basis) for yellow dent corn (n = 16) sourced from southwestern China were as follows: DE = 28.58-(0.12×% hemicellulose)+(0.35×% ether extract)-(0.83×MJ/kg gross energy)+(0.20×% crude protein)+(0.49×% ash); ME = 30.42-(0.11×% hemicellulose)+(0.31×% ether extract)-(0.81×MJ/kg gross energy). Conclusion: Our results indicated that the chemical compositions, but not the meteorological conditions or physical characteristics could explain the variation of energy contents in yellow dent corn sourced from southwestern China fed to growing pigs.