• Korean Journal of Remote Sensing
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• v.19 no.3
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• pp.223-231
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• 2003

With the negative influences and damage from Asian dust increasing, it's getting important to investigate the climate and soil condition of the source region of Asian dust. There is a high possibility that the desertification and the drastic decrease of plants in China and Mongolia make worse the situation (bad effects of Asian Dust). To detect the movement of Asian dust caused by air circulation, we need to watch the state of the source region to get useful information for the prevention of the dust pollution, and to predict what part of China will become the source region. Therefore, using TOMS aerosol index data, NCEP reanalysis data that is Remote Sensing data from 1981 to 2000 (except 1993~1996, 4 years), for 16 years, examined the relation between the dust occurrence and weather elements. Dust occurrence appeared much in spring season from March to May in study areas. It had a dry climate during that season as follows : relative humidity about 20~40%, temperature about -5~5$^{\circ}C$, precipitation about 33-180 mm, wind speed about 4-10 ms-1. Dust occurrence and weather element annual change in study areas decreased gradually till 1990, but in Gobi desert the incidence of dust occurrence increased since 1997. As a result, found out that the more the precipitation, the less dust occurrence, because the precipitation and surface wind speed had a direct influence on the soil of the source region of dust.

• The Plant Pathology Journal
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• v.35 no.1
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• pp.63-70
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• 2019

Winter wheat is susceptible to several fungal pathogens throughout the growing season and foliar fungicide application is one of the strategies used in the management of fungal diseases in winter wheat. However, for fungicides to be profitable, weather conditions conducive to fungal disease development should be present. To determine if winter wheat yield response to fungicide application at the flowering growth stage (Feekes 10.5.1) was related to the growing season precipitation, grain yield from fungicide treated plots was compared to non-treated plots for 19 to 30 hard red winter wheat cultivars planted at 8 site years from 2011 through 2015. At all locations, Prothioconazole + Tebuconazole or Tebuconazole alone was applied at flowering timing for the fungicide treated plots. Grain yield response (difference between treated and non-treated) ranged from 66-696 kg/ha across years and locations. Grain yield response had a positive and significant linear relationship with cumulative rainfall in May through June for the mid and top grain yield ranked cultivars ($R^2=54%$, 78%, respectively) indicating that a higher amount of accumulated rainfall in this period increased chances of getting a higher yield response from fungicide application. Cultivars treated with a fungicide had slightly higher protein content (up to 0.5%) compared to non-treated. These results indicate that application of fungicides when there is sufficient moisture in May and June may increase chances of profitability from fungicide application.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.3
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• pp.158-166
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• 2019

Implementing proper land management techniques, such as selecting the best crops and applying the best cultivation techniques at the farm level, is an effective way for farmers to adapt to climate change. Also it will be helpful if the farmer can get the information of agro-weather and the growth status of cultivating crops in real time and the simulated results of applying optional technologies. To test this, a system (web site) was developed to produce agro-weather data and crop growth information of farms by combining agricultural climate maps and crop growth modeling techniques to highland area for summer-season Chinese cabbage production. The system has been shown to be a viable tool for producing farm-level information and providing it directly to farmers. Further improvements will be required in the speed of information access, the microclimate models for some meteorological factors, and the crop growth models to test different options.

• Atmosphere
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• v.27 no.3
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• pp.317-329
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• 2017

Ocean mixed layer (OML) depth affects diurnal cycle of sea surface temperature (SST) induced by change of solar radiation absorption and heat budget in ocean. The diurnal SST variation can lead to convection over the ocean, which can impact on localized precipitation both over coastal and inland. In this study, we investigate the OML characteristics affecting the diurnal cycle of SST for the Korean Peninsula and surrounding areas. To analyze OML characteristics, HYCOM oceanic mixed layer depth (MLD) and wind field at 10 m from ERA-interim during 2008~2016 are used. In the winter, MLD is deeply formed when the strong wind field is located on perpendicular to continental slope over deep seafloor areas. Besides, cooling SST-induced vertical mixing in OML is reinforced by dry cold air originated from Siberia. The OML in summer is shallowly distributed about 20 m. In order to estimate the impact of OML model in high resolution NWP model, four experimental simulations are performed. At this time, the prognostic scheme of skin SST is applied in NWP to simulate diurnal SST. The simulation results show that CNTL (off-OML) overestimates diurnal cycle of SST, while EXPs (on-OML) indicate similar results to observations. The prediction performance for precipitation of EXPs shows improvement compared with CNTL over coastal as well as inland. This results suggest that the application of the OML model in summer season can contribute to improving the prediction for performance of SST and precipitation over coastal area and inland.

• Fashion & Textile Research Journal
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• v.19 no.3
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• pp.289-295
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• 2017

This study aims to develop clothing sales forecast system using weather information. As the annual temperature variation affects changes in daily sales of seasonal clothes, sales period can be predicted growth, peak and decline period by changes of temperature. From this perspective, we analyzed the correlation between temperature and sales. Moving average method was applied in order to indicate long-term trend of temperature and sales changes. 7-day moving average temperature at the start/end points of the growth, peak, and decline period of S/S clothing sales was calculated as a reference temperature for sales forecast. According to the 2013 data analysis results, when 7-day moving average temperature value becomes $4^{\circ}C$ or higher, the growth period of S/S clothing sales starts. The peak period of S/S clothing sales starts at $17^{\circ}C$, up to the highest temperature. When temperature drops below $21^{\circ}C$ after the peak temperature, the decline period of S/S clothing sales is over. The reference temperature was applied to 2014 temperature data to forecast sales period. Through comparing the forecasted sales periods with the actual sales data, validity of the sales forecast system has been verified. Finally this study proposes 'clothing sales forecast system using weather information' as the method of clothing sales forecast.

• Journal of Environmental Science International
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• v.25 no.6
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• pp.853-864
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• 2016

Meteo-tsunamis are tsunamis that are typically caused by strong atmospheric instability (e.g., pressure jumps) in low pressure systems, but some meteo-tsunamis in winter can be caused by local atmospheric instability in high pressure systems (e.g., the Siberian High). In this study, we investigated a meteo-tsunami event related to a high pressure system that occurred during winter on the Yellow Sea in 2005. Sea level data from tidal stations were analyed with a high-pass filter, and we also performed synoptic weather analyses by using various synoptic weather data (e.g., surface weather charts) collected during the winter season(DJF) of 2005. A numerical weather model (WRF) was used to analyze the atmospheric instability on the day of the selected event (21 Dec. 2005). On the basis of the results, we suggest that the meteo-tsunami triggered by the high pressure system occurred because of dynamic atmospheric instability induced by the expansion and contraction of the Siberian High.

• Journal of the Korean Geographical Society
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• v.31 no.3
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• pp.469-488
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• 1996

The defining of weather forecasting regions is possible. since the representativeness of regional weather can by reasonably clarified in terms of weather entropy and the use of information ratio. In this paper, the weather entropy and information ratio were derived numerially from using the information theory. The typical weather characteristics were clarified and defined in the homogeneous weather forecasting regions of the southern parts of Korea. The data used for this study are the daily precipitation and cloudiness during the recent five years (1990-1994) at 42 stations in southern parts of Korea. It is divided into four classes of fine, clear, cloudy and rainy. The results are summarized as follows: 1. The maximum value of weather entropy in study area is 2.009 vits in Yosu in July, and the minimum one is 1.624 bits in Kohung in October. The mean value of weather entropy is maximal in July, on the other hand, minimal in October during four season. The less the value of entropy is, the stabler the weather is. While the bigger the value of entropy is, the more changeable the weather is. 2. The deviation from mean value of weather entropy in southern parts of Korea, with the positive and the negative parts, shows remarkably the distributional tendency of the east (positive) and the west (negative) in January but of the south (positive) and the north (negative) in July. It also clearly shows the distributional tendency of the east (postive) and the west(negative) in the coastal region in April, and of X-type (southern west and northern east: negative) in Chiri Mt. in October. 3. In southern parts, the average information ratio maximaly appear 0.618 in Taegu area in July, whereas minimally 0.550 in Kwangju in October. Particularly the average information ratio of Pusan area is the greatest in April, but the smallest in October. And in Taegu, Kwangju, and Kunsan, it is the greatest in April, January, and July, but the smallest in Jyly, July, and pril. 4.The narrowest appreance of weather representativeness is in July when the Kwangju is the center of the weather forecasting. But the broadest one is in April when Taegu is the center of weather forecasting. 5. The defining of weather forecasting regions in terms of the difference of information ratio most broadly shows up in July in Pusan including the whole Honam area and the southern parts of Youngnam when the Pusan-Taegu is the basis of the application of information ratio. Meanwhile, it appears most broadly in January in Taegu including the whole southern parts except southern coastal area.

• Journal of Environmental Science International
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• v.30 no.7
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• pp.547-555
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• 2021

To compare the vitality among cool-season turfgrasses under summer weather conditions and to obtain information to improve the management of turfgrasses in golf courses and sports fields., the chlorophyll fluorescence of three cool-season turfgrasses commonly planted on golf courses in the Jeju area was measured. The turfgrasses were perennial ryegrass (Lolium perenne L.), Kentucky bluegrass (Poa pratensis L.), and creeping bentgrass (Agrostis palustris Huds.). In perennial ryegrass and Kentucky bluegrass, the chlorophyll index was low in early summer and high in late summer. In creeping bentgrass, it remained low throughout the study. Fo tended to be low in the early summer and high in late summer in the three turfgrasses. However, the difference in F_o between late summer and early summer was markedly higher in perennial ryegrass than in Kentucky bluegrass or creeping bentgrass. F_m tended to be low in early summer and high in late summer, without obvious differences among the three turfgrasses. F_v/F_m, a measure of photochemical efficiency, was also low in early summer and high in late summer in the three turfgrasses. However, F_v/F_m in late summer was mostly higher in Kentucky bluegrass and creeping bentgrass than in perennial ryegrass, indicating that the former are more resistant to the high temperature and humidity of late summer. Furthermore, Kentucky bluegrass had a high chlorophyll index in late summer and would be most resistant to the harsh conditions of late summer.

• Atmosphere
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• v.24 no.3
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• pp.433-444
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• 2014

Although the Radar-AWS Rainrate (RAR) calculation system operated by Korea Meteorological Administration estimated precipitation using 2-dimensional composite components of single polarization radars, this system has several limitations in estimating the precipitation accurately. To to overcome limitations of the RAR system, the Korea Meteorological Administration developed and operated the RMQ (Radar-based Multi-sensor Quantitative Precipitation Estimation) system, the improved version of NMQ (National Mosaic and Multi-sensor Quantitative Precipitation Estimation) system of NSSL (National Severe Storms Laboratory) for the Korean Peninsula. This study introduced the RMQ system domestically for the first time and verified the precipitation estimation performance of the RMQ system. The RMQ system consists of 4 main parts as the process of handling the single radar data, merging 3D reflectivity, QPE, and displaying result images. The first process (handling of the single radar data) has the pre-process of a radar data (transformation of data format and quality control), the production of a vertical profile of reflectivity and the correction of bright-band, and the conduction of hydrid scan reflectivity. The next process (merger of 3D reflectivity) produces the 3D composite reflectivity field after correcting the quality controlled single radar reflectivity. The QPE process classifies the precipitation types using multi-sensor information and estimates quantitative precipitation using several Z-R relationships which are proper for precipitation types. This process also corrects the precipitation using the AWS position with local gauge correction technique. The last process displays the final results transformed into images in the web-site. This study also estimated the accuracy of the RMQ system with five events in 2012 summer season and compared the results of the RAR (Radar-AWS Rainrate) and RMQ systems. The RMQ system ($2.36mm\;hr^{-1}$ in RMSE on average) is superior to the RAR system ($8.33mm\;hr^{-1}$ in RMSE) and improved by 73.25% in RMSE and 25.56% in correlation coefficient on average. The precipitation composite field images produced by the RMQ system are almost identical to the AWS (Automatic Weather Statioin) images. Therefore, the RMQ system has contributed to improve the accuracy of precipitation estimation using weather radars and operation of the RMQ system in the work field in future enables to cope with the extreme weather conditions actively.

• Journal of Korea Water Resources Association
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• v.43 no.4
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• pp.409-419
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• 2010

In this study, for the purpose of analyzing the characteristics of Korean hydrologic weather parameters, 9 hydrologic weather parameters data such as annual precipitation, annual rainy days, annual average relative humidity, annual average temperature, annual duration of sunshine, annual evaporation, annual duration of precipitation, annual snowy days and annual new snowy days are collected from 63 domestic meteorological stations that has the hydrologic weather parameters records more than 30 years. And the basic characteristics of hydrologic weather parameters through basic statistics, moving average and linear regression analysis are perceived. Also trend using the statistical methods like Hotelling-Pabst test and Mann-Kendall test about hydrologic weather parameters is analyzed. Through results of basic analysis, moving average and linear regression analysis it is shown that precipitation is concentrated in summer and deviation of precipitation for each season showed significant difference in accordance with Korean climate characteristics, besides the increase in annual precipitation and annual average temperature, annual average relative humidity and annual duration of sunshine reduction and annual rainy days is said to increase or decrease. The results of statistical analysis of trend are summarized as trend commonly appeared in annual average relative humidity and annual average temperature. and annual precipitation, annual rainy days and annual duration of sunshine showed different results according to area.