• Journal of Environmental Science International
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• v.29 no.3
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• pp.257-272
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• 2020

This study investigates the temporal and spatial variations of marine meterological elements (air temperature (Temp), Sea Surface Temperature (SST), and Significant Wave Height (SWH)) in seven coastal waters of South Korea, using hourly data observed at marine meteorological buoys (10 sites), Automatic Weather System on lighthouse (lighthouse AWS) (9 sites), and AWS (20 sites) during 2013-2017. We also compared the characteristics of Temp, SST, and air-sea temperature difference (Temp-SST) between sea fog and non-sea-fog events. In general, annual mean values of Temp and SST in most of the coastal waters were highest (especially in the southern part of Jeju Island) in 2016, due to heat waves, and lowest (especially in the middle of the West Sea) in 2013 or 2014. The SWH did not vary significantly by year. Wind patterns varied according to coastal waters, but their yearly variations for each coastal water were similar. The maximum monthly/seasonal mean values of Temp and SST occurred in summer (especially in August), and the minimum values in winter (January for Temp and February for SST). Monthly/seasonal mean SWH was highest in winter (especially in December) and lowest in summer (June), while the monthly/seasonal variations in wind speed over most of the coastal waters (except for the southern part of Jeju Island) were similar to those of SWH. In addition, sea fog during spring and summer was likely to be in the form of advection fog, possibly because of the high Temp and low SST (especially clear SST cooling in the eastern part of South Sea in summer), while autumn sea fog varied between different coastal waters (either advection fog or steam fog). The SST (and Temp-SST) during sea fog events in all coastal waters was lower (and more variable) than during non-sea-fog events, and was up to -5.7℃ for SST (up to 5.8℃ for Temp-SST).

• Korean Journal of Agricultural and Forest Meteorology
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• v.14 no.1
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• pp.1-10
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• 2012

Digital Forecast of the Korea Meteorological Administration (KMA) represents 5 km gridded weather forecast over the Korean Peninsula and the surrounding oceanic regions in Korean territory. Digital Forecast provides 12 weather forecast elements such as three-hour interval temperature, sky condition, wind direction, wind speed, relative humidity, wave height, probability of precipitation, 12 hour accumulated rain and snow, as well as daily minimum and maximum temperatures. These forecast elements are updated every three-hour for the next 48 hours regularly. The objective of this study was to construct Forest Fire Danger Rating Systems on the Korean Peninsula (FFDRS_KORP) based on the daily weather index (DWI) and to improve the accuracy using the digital forecast data. We produced the thematic maps of temperature, humidity, and wind speed over the Korean Peninsula to analyze DWI. To calculate DWI of the Korean Peninsula it was applied forest fire occurrence probability model by logistic regression analysis, i.e. $[1+{\exp}\{-(2.494+(0.004{\times}T_{max})-(0.008{\times}EF))\}]^{-1}$. The result of verification test among the real-time observatory data, digital forecast and RDAPS data showed that predicting values of the digital forecast advanced more than those of RDAPS data. The results of the comparison with the average forest fire danger rating index (sampled at 233 administrative districts) and those with the digital weather showed higher relative accuracy than those with the RDAPS data. The coefficient of determination of forest fire danger rating was shown as $R^2$=0.854. There was a difference of 0.5 between the national mean fire danger rating index (70) with the application of the real-time observatory data and that with the digital forecast (70.5).

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.501-512
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• 2015

Landfast sea ice (LFI) in Terra Nova Bay, East Antarctica where the Jangbogo Antarctic Research Station is located, has significant influences on marine ecosystem and the sailing of an icebreaker. Therefore, it is essential to analyze the spatio-temporal variation of the LFI in Terra Nova Bay. In this study, we chose interferometric pairs with the temporal baseline from 1 to 9 days out of a total of 62 COSMO-SkyMed synthetic aperture radar (SAR) images over Terra Nova Bay obtained from December 2010 to January 2012, and then constructed the coherence image of each pair. The LFI showed coherence values higher than 0.3 even in the interferometric SAR (InSAR) pairs of up to 9-days of temporal baseline. This was because the LFI was fixed at coastline and thus showed low temporal phase decorrelation. Based on the characteristics of the coherence on LFI, We defined the areas of LFI that show spatially homogeneous coherence values higher than 0.5. Pack ice (PI) and open water showed low coherence values due to large temporal phase decorreation caused by current and wind. Distinguishing PI from open water in the coherence images was difficult due to their similarly low coherence values. PI was identified in SAR amplitude images by investigating cracks on the ice. The extents of the LFI and PI were estimated from the coherence and SAR amplitude images and their temporal variations were analyzed. The extent of the LFI increased from March to July (maximum extent of $170.7km^2$) and decreased from October. The extent of the PI increased from February to May and decreased from May to July when the LFI increases dramatically. The extent of the LFI and air temperature showed an inverse correlation with a time lag of about 2 months, i.e., the extent of the LFI decreases after 2 months of the increase in the air temperature. Meanwhile the correlation between wind speed and the extent of the LFI was very low. This represents that the extent of LFI in Terra Nova Bay are influenced more by the air temperature than wind speed.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.1
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• pp.68-77
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• 2022

The human thermal environment in an apartment complex located in Seoul was quantitatively analyzed to devise methods to modify human heat-related stresses in landscape and urban planning. Microclimatic data (air temperature, relative humidity, wind speed, and short- and long-wave radiation) were collected at 6 locations [Apt-center, roof (cement), roof (grass), ground, playground, and a tree-lined road] in the late spring and summer, and the data were used to estimate the human thermal sensation, physiological equivalent temperature (PET) and universal thermal climate index (UTCI). As a result, the playground location had the highest thermal environment, and the roof (grass) location had the lowest. The mean difference between the two locations was 0.8-1.1℃ in air temperature, 1.8-4.0% in relative humidity, and 7.5-8.0℃ in mean radiant temperature. In open space locations, the wind speed was 0.4-0.5 ms-1 higher than others. Also, a wind tunnel effect happened at the Apt-center location during the afternoon. For the human thermal sensation, PET and UTCI, the mean differences between the playground and roof (grass) locations were: 5.2℃ (Max. 11.7℃) in late spring and 5.4℃ (Max. 18.1℃) in summer in PET; and 3.0℃ (Max. 6.1℃) in late spring and 2.6℃ (Max. 9.8℃) in summer in UTCI. The mean differences indicated a level change in PET and 1/2 level in UTCI, and the maximum differences showed greater changes, 2-3 levels in PET, and 1-1.5 levels in UTCI. Moreover, the roof (grass) location gave 4.6℃ PET reduction and a 2.5℃ UTCI reduction in late spring, and a 4.4℃ PET reduction and a 2.0℃ UTCI reduction in the summer when compared with the roof (cement) location, which results in a 2/3 level change in PET and a 1/3 level in UTCI. Green infrastructure locations [roof (grass), ground, and a tree-lined road] were not statistically significant in the reduction of PET and UTCI in thermal environment modifying effects. The implementation of green infrastructure, such as rooftop gardens, grass pavement, and street tree planting, should be adopted in landscape planning and be employed for human thermal environment modification.

• 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.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.1
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• pp.73-87
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• 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
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• v.53 no.4
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• pp.313-322
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• 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
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• v.18 no.3
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• pp.215-224
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• 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
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• v.23 no.2
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• pp.87-93
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• 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
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• v.34 no.6_3
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• pp.1457-1468
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• 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.