• Journal of Conservation Science
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• v.33 no.4
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• pp.283-295
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• 2017

It is crucial to measure meteorological elements in relation to the biodeterioration of building cultural heritages. The Beopjusa and Seonamsa temples located respectively in Chungbuk and Jeonnam provinces, Korea, exhibit biological damage to the building cultural heritages and cause noticeable climatic differences. To compare biodeterioration environments of the abovementioned temples, 10 meteorological elements were observed, and particulate matter (TSP) was collected at each location. Furthermore, a correlation analysis was conducted between meteorological elements, and between meteorological elements and TSP. The local meteorology at Beopjusa temple characteristically showcased high total horizontal radiation, UV radiation, evaporation, wind speed, and TSP concentration, whereas, that at Seonamsa temple showcased high temperature, humidity, dew point temperature, air pressure, precipitation and number of days with precipitation. An elemental analysis of TSP revealed the presence of sae-salts at Seonamsa temple, and compared to that of Beopjusa temple, the monthly frequencies of biogenic aerosol and Fe-containing particles were higher. The correlation analysis showed that wind speed and humidity were major meteorological factors at Beopjusa and Seonamsa temples, respectively. Subsequently, the characteristics of the local meteorology at Seonamsa temple are expected to affect the biological damage of the building cultural heritages, which is favorable for the growth of various organisms.

• Journal of the Korean Solar Energy Society
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• v.37 no.6
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• pp.93-102
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• 2017

Interpretation of relevance between long-wave radiation and meteorological elements is recognized as an essential element for understanding the underlying mechanism of urban thermal environment formation. In this study, we analyzed relation between three elements : long-wave radiation, temperature, and lower-middle class cloudiness. The correlation was analyzed through field observations. The results are as follows. (1) Temperatures and long-wave radiation increased from January to March. This phenomenon has been confirmed in urban and suburban areas. (2) Long-wave radiations showed a tendency to increase clearly with increasing cloudiness.

• Journal of Conservation Science
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• v.35 no.6
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• pp.652-663
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• 2019

To identify daily and annual changes in outdoor airborne fungi, it is necessary to shorten the collection cycle and increase the number of measurements. In this study, measurements were performed by employing an air sampler and potato dextrose agar media on the rooftop of National Research Institute of Cultural Heritage during a period of one year (August 2018 to July 2019). The collection cycle spanned the twenty-four seasonal divisions and the collection time was 2 p.m. and 11 p.m.. Meteorological elements were collected at intervals of one hour. Furthermore, the concentration of airborne fungi was monitored and correlation analysis with meteorological elements was subsequently conducted. Obtained results indicate that the concentration of airborne fungi is found to be highest in November, autumn, night, followed by autumn, summer, winter, and spring. The concentration, type, and dominant species of airborne fungi can vary depending on factors such as rainfall, typhoons, and yellow dust (fine dust). The concentration of airborne fungi indicates a strong positive linear relationship between precipitation, number of precipitation days, and relative humidity. The concentration of airborne fungi was related to the period of increase of dead plants in terms of nutrition source, and to the high relative humidity conditions including rainfall in terms of meteorological elements.

• Journal of Astronomy and Space Sciences
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• v.35 no.3
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• pp.175-183
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• 2018

Many recent satellites have mission periods longer than 10 years; thus, satellite-based local space weather monitoring is becoming more important than ever. This article describes the instruments and data applications of the Korea Space wEather Monitor (KSEM), which is a space weather payload of the GeoKompsat-2A (GK-2A) geostationary satellite. The KSEM payload consists of energetic particle detectors, magnetometers, and a satellite charging monitor. KSEM will provide accurate measurements of the energetic particle flux and three-axis magnetic field, which are the most essential elements of space weather events, and use sensors and external data such as GOES and DSCOVR to provide five essential space weather products. The longitude of GK-2A is $128.2^{\circ}E$, while those of the GOES satellite series are $75^{\circ}W$ and $135^{\circ}W$. Multi-satellite measurements of a wide distribution of geostationary equatorial orbits by KSEM/GK-2A and other satellites will enable the development, improvement, and verification of new space weather forecasting models. KSEM employs a service-oriented magnetometer designed by ESA to reduce magnetic noise from the satellite in real time with a very short boom (1 m), which demonstrates that a satellite-based magnetometer can be made simpler and more convenient without losing any performance.

• Journal of the Korean Solar Energy Society
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• v.27 no.4
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• pp.157-165
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• 2007

Typical meteorological data is fundamental to computer simulation introduced for environment-friendly architecture designs. Therefore, in order to improve accuracy of computer simulation, typical meteorological data should be established. By examining how to choose typical meteorological data, this study selected the optimized weight factor for TRY where weighting factor was not clearly set. As a result, the same weighting factor was applied to each climatic element and TRY data where the weight factor was applied could have the distribution very similar to measurement data. The weighting factor is considered to reflect geographical characteristics of Seoul and applied climatic elements.

• Atmosphere
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• v.26 no.1
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• pp.59-72
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• 2016

The comparison of prediction errors in geopotential height, temperature, and precipitation forecasts is made quantitatively to evaluate medium-range forecast skills between Global Seasonal Forecasting System version 5 (GloSea5) and Unified Model (UM) in operation by Korea Meteorological Administration during 2014. In addition, the performances in prediction of sea surface temperature anomaly in NINO3.4 region, Madden and Julian Oscillation (MJO) index, and tropical storms in western north Pacific are evaluated. The result of evaluations appears that the forecast skill of UM with lower values of root-mean square error is generally superior to GloSea5 during forecast periods (0 to 12 days). The forecast error tends to increase rapidly in GloSea5 during the first half of the forecast period, and then it shows down so that the skill difference between UM and GloSea5 becomes negligible as the forecast time increases. Precipitation forecast of GloSea5 is not as bad as expected and the skill is comparable to that of UM during 10-day forecasts. Especially, in predictions of sea surface temperature in NINO3.4 region, MJO index, and tropical storms in western Pacific, GloSea5 shows similar or better performance than UM. Throughout comparison of forecast skills for main meteorological elements and weather extremes during medium-range, the effects of initial and model errors in atmosphere-ocean coupled model are verified and it is suggested that GloSea5 is useful system for not only seasonal forecasts but also short- and medium-range forecasts.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2000.05a
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• pp.26-33
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• 2000

This study was conducted to investigate the relationships between yearly variations of elimatic elements and yearly variations of productivity in potato. In addition, correlation coefficients among yield and yield components were estimated. The data of yield and yield components were investigated for 9 years from 1987 to 1995. The meteorological data what gathered at the Goheung Weather Station for the same period of crop growing season were used to find out the relationships between climatic elements and crop productivity. Yearly variation of the daily minimum temperature in March and April were large with coefficients of variation (C.V.) of 126.0%, 368%, respectively, but the variation of the daily mean and maximum temperature in May and June were relative small. Stem length and number of stem show more C.V. of 9.3%, 14.3%, respectively, but the variation of the yield was relative small with 3.7%. Correlation coefficients between the amount of precipitation in April and yield, yield and daily mean temperature in June were negatively significant at the level of 5, 1 %, respectively. Correlation coefficients between the growth habits and yield are positively significant at the level of 5, 1 %, respectively. Simple linear regression equations by the least square method are estimated for stem length (Yl) and the precipitation in April(X) as Y,=82.47-0.11x (R2=0.3959), and for yield(Y2) and the precipitation in April(X) as Y,=2003.61-0.94X (R2=0.5418).

• Plant Resources
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• v.6 no.3
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• pp.178-182
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• 2003

This study was conducted to investigate the relationship between yearly variations of climatic elements and yearly variations of productivity in perilla. In addition, correlation coefficients among yield and yield components were estimated. The data of yield and yield components were investigated for 10 years from 1991 to 2000. The meteorological data gathered at the Yeosu Weather Station for the same period were used to find out the relationships between climatic elements and productivity. Yearly variation of the amount of precipitation in September was large with coefficients of variation(c. v.) of 11.1%, but the coefficient of variance(c. v.) in July and August were relative small with 1.8, 2.1%, respectively. Number of cluster per hill and weight of 1,000 grains were greatly with c. v. of 76.1, 79.3%, respectively, but the coefficients of variance(c. v.) of plant height and seed yield were more less with 9.58, 10.60%, respectively. Correlation coefficients between precipitation of September and seed yield were positively significant correlation at the level of 5.1%, respectively, but the duration of sunshine in September and seed yield were negatively significant at the level of 5.1%, respectively. Correlation coefficients of these, the plant height, number of branches per plant, cluster length, number of cluster per hill, weight of 1,000 grains and seed yield were positively significant at the level of 5.1% respectively.

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.4
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• pp.170-178
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• 2012

In this study, in order to provide an information for artificial cultivation of wild mushroom, the meteorological effects on wild mushroom appearance were examined using daily meteorological observations in Chiak National Park. The survey of wild mushroom appearance was carried out once a month from June to October. Under high temperature and humidity conditions in July and August, the appearance of wild mushroom was frequent. In contrast, lower number of wild mushroom appeared in October. Wild mushroom appearance was affected by solar radiation, relative humidity, precipitation, and soil water content whereas the impact of air and soil temperature was lower than that of other meteorological elements.

• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.3
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• pp.41-49
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• 2007

In order to reduce the amount of damage from natural disasters and perform the natural disaster mitigation program, the prevention activities and forecasting based on meteorological parameters and disaster datas are required. In addition, it is necessary to process prevention meteorological information for prevention activities in advance. For this, we have analyzed four data, such as Statistical yearbook of calamities and Statistics Yearbook issued by the Ministry of Government Administration and Human affairs. And Annual Climatological Report issued by the Korea Meteorological Administration and Recently 10 years for natural disaster damage from the Central Disaster and Safety Countermeasures Headquarters. We analyzed the causes, elements, occurrence frequencies, and vulnerable areas of natural disaster, using the 4 disaster datas, but these datas was not consistent with their terminology and items. Through the analysis of a kind and damage of disaster, we have selected the disaster variables, such as causes and elements, the amount of damage, vulnerable areas of natural disaster, etc and made a database. This database will be used to assess the natural disasters and develop the risk model and natural disasters mitigation plan.