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

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.20 no.1
• /
• pp.73-87
• /
• 2018

A variety of micro meteorological variables such as air temperature, wind, solar radiation and latent heat at Gwangneung forests (conifer and broadleaved forests) and AWS (Automated Weather Station) of Pocheon urban area were used to quantify the air temperature reduction effect of forests, which is considered to be an eco-friendly solution for reducing the urban heat island intensity during summer. In June, July and August of 2016 and 2017, the average maximum air temperature differences between above and below canopy of forests, and between the forests and urban areas were $-1.9^{\circ}C$ and $-3.4^{\circ}C$ respectively, and they occurred at 17:00. However, there was no difference between conifer and broadleaved forests. The effect of air temperature reduction by the forests was positively correlated with accumulated evapotranspiration and solar radiation from 14:00 to 17:00 and showed a negative correlation with wind speed. We have developed a model to quantify the effect of air temperature reduction by forests using these variables. The nighttime air temperature reduction effect by forests was due to the generation of cold air from radiative cooling and the air temperature inversion phenomenon that occurs when the generated cold air moves down the side of mountain. The model was evaluated in Seoul by using 28 AWSs. The evaluation shows that the air temperature of each district in Seoul was negatively correlated with the area and size of the surrounding tall vegetation that drives vegetation evapotranspiration during the day. During the night, however, the size of the surrounding tall vegetation and the elevations of nearby mountains were the main influencing factors on the air temperature. Our research emphasizes the importance of the establishment and management of urban forests and the composition of wind roads from mountains for urban air temperature reduction.

• Journal of Korea Water Resources Association
• /
• v.53 no.4
• /
• pp.313-322
• /
• 2020

There is always a risk of water disasters due to sudden storms in mountainous regions in Korea, which is more than 70% of the country's land. In this study, a radar-based risk prediction technique for sudden downpour is applied in the mountainous region and is evaluated for its applicability using Mt. Biseul rain radar. Eight local heavy rain events in mountain regions are selected and the information was calculated such as early detection of cumulonimbus convective cells, automatic detection of convective cells, and risk index of detected convective cells using the three-dimensional radar reflectivity, rainfall intensity, and doppler wind speed. As a result, it was possible to confirm the initial detection timing and location of convective cells that may develop as a localized heavy rain, and the magnitude and location of the risk determined according to whether or not vortices were generated. In particular, it was confirmed that the ground rain gauge network has limitations in detecting heavy rains that develop locally in a narrow area. Besides, it is possible to secure a time of at least 10 minutes to a maximum of 65 minutes until the maximum rainfall intensity occurs at the time of obtaining the risk information. Therefore, it would be useful as information to prevent flash flooding disaster and marooned accidents caused by heavy rain in the mountainous area using this technique.

• Journal of Bio-Environment Control
• /
• v.18 no.3
• /
• pp.215-224
• /
• 2009

A survey on the actual state of heating, cooling, ventilation, and air-flow and experimental measurement of temperature and humidity distribution in tomato greenhouse were performed to provide fundamental data required in the development of air-flow control technology. In single-span plastic houses, which account for most of 136 tomato greenhouses surveyed, roof windows, ventilation and air-flow fans were installed in a low rate, and installation specs of those facilities showed a very large deviation. There were no farms installed greenhouse cooling facilities. In the hot air heating system, which account for most of heating type, installation specs of hot air duct showed also a large deviation. The exhaust air temperature and wind speed in hot air duct also were measured to have a big difference depending on the distance from the heater. We are using the maximum difference as indicator to determine whether temperature distribution is uniform. However if the temperature slope is not identical in greenhouse, it can't represent the uniformity. We analyzed relation between the maximum difference and the uniformity of temperature and humidity distribution. The uniformity was calculated using the mean and standard deviation of data from 12 measuring points. They showed high correlation but were represented differently by linear in the daytime and quadratic in the nighttime. It could see that the uniformity of temperature and humidity distribution was much different according to greenhouse type and heating method. The installation guidelines for ventilation and air-flow fan, the spread of greenhouse cooling technology for year-round stable production, and improvement of air duct and heating system, etc. are needed.

• Korean Journal of Soil Science and Fertilizer
• /
• v.23 no.2
• /
• pp.87-93
• /
• 1990

A statistical model to predict soil temperature from the ambient meteorological factors including mean, maximum and minimum air temperatures, precipitation, wind speed and snow depth combined with Fourier time series expansion was developed with the data measured at the Suwon Meteorolical Service from 1979 to 1988. The stepwise elimination technique was used for statistical analysis. For the yearly oscillation model for soil temperature with 8 terms of Fourier expansion, the mean square error was decreased with soil depth showing 2.30 for the surface temperature, and 1.34-0.42 for 5 to 500-cm soil temperatures. The $r^2$ ranged from 0.913 to 0.988. The number of lag days of air temperature by remainder analysis was 0 day for the soil surface temperature, -1 day for 5 to 30-cm soil temperature, and -2 days for 50-cm soil temperature. The number of lag days for precipitaion, snow depth and wind speed was -1 day for the 0 to 10-cm soil temperatures, and -2 to -3 days for the 30 to 50-cm soil teperatures. For the statistical soil temperature prediction model combined with the yearly oscillation terms and meteorological factors as remainder terms considering the lag days obtained above, the mean square error was 1.64 for the soil surfac temperature, and ranged 1.34-0.42 for 5 to 500cm soil temperatures. The model test with 1978 data independent to model development resulted in good agreement with $r^2$ ranged 0.976 to 0.996. The magnitudes of coeffcicients implied that the soil depth where daily meteorological variables night affect soil temperature was 30 to 50 cm. In the models, solar radiation was not included as a independent variable ; however, in a seperated analysis on relationship between the difference(${\Delta}Tmxs$) of the maximum soil temperature and the maximum air temperature and solar radiation(Rs ; $J\;m^{-2}$) under a corn canopy showed linear relationship as $${\Delta}Tmxs=0.902+1.924{\times}10^{-3}$$ Rs for leaf area index lower than 2 $${\Delta}Tmxs=0.274+8.881{\times}10^{-4}$$ Rs for leaf area index higher than 2.

• Korean Journal of Remote Sensing
• /
• v.34 no.6_3
• /
• pp.1457-1468
• /
• 2018

The sigma naught (${\sigma}^0$) equation is essential to calculate geo-physical properties from Synthetic Aperture Radar (SAR) images for the applications such as ground target identification,surface classification, sea wind speed calculation, and soil moisture estimation. In this paper, we are suggesting new Kompsat-5 (K5) Radar Cross Section (RCS) and ${\sigma}^0$ equations reflecting the final SAR processor update and absolute radiometric calibration in order to increase the application of K5 SAR images. Firstly, we analyzed the accuracy of the K5 RCS equation by using trihedral corner reflectors installed in the Kompsat calibration site in Mongolia. The average difference between the calculated values using RCS equation and the measured values with K5 SAR processor was about $0.2dBm^2$ for Spotlight and Stripmap imaging modes. In addition, the verification of the K5 ${\sigma}^0$ equation was carried out using the TerraSAR-X (TSX) and Sentinel-1A (S-1A) SAR images over Amazon rainforest, where the backscattering characteristics are not significantly affected by the seasonal change. The calculated ${\sigma}^0$ difference between K5 and TSX/S-1A was less than 0.6 dB. Considering the K5 absolute radiometric accuracy requirement, which is 2.0 dB ($1{\sigma}$), the average difference of $0.2dBm^2$ for RCS equation and the maximum difference of 0.6 dB for ${\sigma}^0$ equation show that the accuracies of the suggested equations are relatively high. In the future, the validity of the suggested RCS and ${\sigma}^0$ equations is expected to be verified through the application such as sea wind speed calculation, where quantitative analysis is possible.

• Journal of The Korean Society of Grassland and Forage Science
• /
• v.42 no.2
• /
• pp.127-136
• /
• 2022

This study was conducted to estimate the damage of Whole Crop Maize (WCM) according to abnormal climate using machine learning and present the damage through mapping. The collected WCM data was 3,232. The climate data was collected from the Korea Meteorological Administration's meteorological data open portal. Deep Crossing is used for the machine learning model. The damage was calculated using climate data from the Automated Synoptic Observing System (95 sites) by machine learning. The damage was calculated by difference between the Dry matter yield (DMY)_normal and DMY_abnormal. The normal climate was set as the 40-year of climate data according to the year of WCM data (1978~2017). The level of abnormal climate was set as a multiple of the standard deviation applying the World Meteorological Organization(WMO) standard. The DMY_normal was ranged from 13,845~19,347 kg/ha. The damage of WCM was differed according to region and level of abnormal climate and ranged from -305 to 310, -54 to 89, and -610 to 813 kg/ha bnormal temperature, precipitation, and wind speed, respectively. The maximum damage was 310 kg/ha when the abnormal temperature was +2 level (+1.42 ℃), 89 kg/ha when the abnormal precipitation was -2 level (-0.12 mm) and 813 kg/ha when the abnormal wind speed was -2 level (-1.60 m/s). The damage calculated through the WMO method was presented as an mapping using QGIS. When calculating the damage of WCM due to abnormal climate, there was some blank area because there was no data. In order to calculate the damage of blank area, it would be possible to use the automatic weather system (AWS), which provides data from more sites than the automated synoptic observing system (ASOS).

• Journal of the Korean Institute of Landscape Architecture
• /
• v.45 no.6
• /
• pp.115-125
• /
• 2017

This study was to investigate the user's thermal environments under the pergola($L\;7,200{\times}W\;4,200{\times}H\;2,700mn$) covered with Wisteria floribunda(Willd.) DC. according to the variation of leaf area index(LAI). We carried out detailed measurements with two human-biometeorological stations on a popular square Jinju, Korea($N35^{\circ}10^{\prime}59.8^{{\prime}{\prime}}$, $E\;128^{\circ}05^{\prime}32.0^{{\prime}{\prime}}$, elevation: 38m). One of the stations stood under a pergola, while the other in the sun. The measurement spots were instrumented with microclimate monitoring stations to continuously measure air temperature and relative humidity, wind speed, shortwave and longwave radiation from the six cardinal directions at the height of 0.6m so as to calculate the Universal Thermal Climate Index(UTCI) from $9^{th}$ April to $27^{th}$ September 2017. The LAI was measured using the LAI-2200C Plant Canopy Analyzer. The analysis results of 18 day's 1 minute term human-biometeorological data absorbed by a man in sitting position from 10am to 4pm showed the following. During the whole observation period, daily average air temperatures under the pergola were respectively $0.7{\sim}2.3^{\circ}C$ lower compared with those in the sun, daily average wind speed and relative humidity under the pergola were respectively 0.17~0.38m/s and 0.4~3.1% higher compared with those in the sun. There was significant relationship in LAI, Julian day number and were expressed in the equation $y=-0.0004x^2+0.1719x-11.765(R^2=0.9897)$. The average $T_{mrt}$ under the pergola were $11.9{\sim}25.4^{\circ}C$ lower and maximum ${\Delta}T_{mrt}$ under the pergola were $24.1{\sim}30.2^{\circ}C$ when compared with those in the sun. There was significant relationship in LAI, reduction ratio(%) of daily average $T_{mrt}$ compared with those in the sun and was expressed in the equation $y=0.0678{\ln}(x)+0.3036(R^2=0.9454)$. The average UTCI under the pergola were $4.1{\sim}8.3^{\circ}C$ lower and maximum ${\Delta}UTCI$ under the pergola were $7.8{\sim}10.2^{\circ}C$ when compared with those in the sun. There was significant relationship in LAI, reduction ratio(%) of daily average UTCI compared with those in the sun and were expressed in the equation $y=0.0322{\ln}(x)+0.1538(R^2=0.8946)$. The shading by the pergola covered with vines was very effective for reducing daytime UTCI absorbed by a man in sitting position at summer largely through a reduction in mean radiant temperature from sun protection, lowering thermal stress from very strong(UTCI >$38^{\circ}C$) and strong(UTCI >$32^{\circ}C$) down to strong(UTCI >$32^{\circ}C$) and moderate(UTCI >$26^{\circ}C$). Therefore the pergola covered with vines used for shading outdoor spaces is essential to mitigate heat stress and can create better human thermal comfort especially in cities during summer. But the thermal environments under the pergola covered with vines during the heat wave supposed to user "very strong heat stress(UTCI>$38^{\circ}C$)". Therefore users must restrain themselves from outdoor activities during the heat waves.

• Journal of the Korea Institute of Building Construction
• /
• v.19 no.6
• /
• pp.529-538
• /
• 2019

Typhoons can cause significant financial damage worldwide. For this reason, states, local governments and insurance companies attempt to quantify and mitigate the financial risks related to these natural disasters by developing a typhoon risk assessment model. As such, the importance of typhoon risk assessment models is increasing, and it is also important to reflect local vulnerabilities to enable sophisticated assessments. Although a practical study of economic losses associated with natural disasters has identified essential risk indicators, comprehensive studies covering the correlation between vulnerability and economic loss are still needed. The purpose of this study is to identify typhoon damage indicators and to develop evaluation indicators for typhoon damage prediction functions, utilizing the loses from Typhoon Maemi as data. This study analyzes actual loss records of Typhoon Maemi provided by local insurance companies to prepare for a scenario of maximum losses. To create a vulnerability function, the authors used the wind speed and distance from the coast and the total value of property, construction type, floors, and underground floor indicators. The results and metrics of this study provide practical guidelines for government agencies and insurance companies in developing vulnerability functions that reflect the actual financial losses and regional vulnerabilities of buildings.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.37 no.2
• /
• pp.445-449
• /
• 2017

Most studies using drone is confined utilization on the ground and regulation. The drone in the water is rarely used in hydrographic surveying because of the limit of flight time and image matching. This paper is the basic research for drone hydrographic photogrammetry. The accuracy of hydrographic photogrammetry, using buoys for water reference point, was evaluated. The accuracy is influenced by the accuracy of the water reference points like the photogrammetry. The position of water reference points set up on water, keep on changing due to various environmental factors such as wind speed and water velocity. The position continuously changed of the water reference points were measured 3 times using Total Station and VRS. Experiments were conducted at two reservoirs in Gimhae City, and the accuracy of the manual image matching using the water reference points is 40 cm and 80 cm. Allowable accuracy of the ocean boundary survey is ${\pm}2m$, the results of this study are fully available. The maximum position error of the water reference point for ensuring accuracy within ${\pm}2m$ is 1.8 m.