• Korean Journal of Remote Sensing
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• v.34 no.1
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• pp.25-43
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• 2018

The effects of hydro-meteorological and surface variables on the frequency of Asian dust events (FAE) were investigated using ground station and satellite-based data. Present weather codes 7, 8, and 9 derived from surface synoptic observations (SYNOP)were used for counting FAE. Surface wind speed (SWS), air temperature (Ta), relative humidity (RH), and precipitation were analyzed as hydro-meteorological variables for FAE. The Normalized Difference Vegetation Index (NDVI), land surface temperature (LST), and snow cover fraction (SCF) were used to consider the effects of surface variables on FAE. The relationships between FAE and hydro-meteorological variables were analyzed using Z-score and empirical orthogonal function (EOF) analysis. Although all variables expressed the change of FAE, the degrees of expression were different. SWS, LST, and Ta (indices applicable when Z-score was < 0) explained about 63.01, 58.00, and 56.17% of the FAE,respectively. For NDVI, precipitation, and RH, Asian dust events occurred with a frequency of about 55.38, 67.37, and 62.87% when the Z-scores were > 0. EOF analysis for the FAE showed the seasonal cycle, change pattern, and surface influences related to dryness condition for the FAE. The intensity of SWS was the main cause for change of FAE, but surface variables such as LST, SCF, and NDVI also were expressed because wet surface conditions suppress FAE. These results demonstrate that not only SWS and precipitation, but also surface variables, are important and useful precursors for monitoring Asian dust events.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.3
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• pp.9-22
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• 2018

Korea meteorological administration(KMA) has started to levy air meteorological service charge on both national and foreign carriers since 2005. The charge has grown on 2010 and 2014 twice. However, KMA has still kept asking airlines to agree with another increase in the charge due to the low cost of goods recovery ratio of 7%. The air meteorological charge has changed from 2,210 KRW at the beginning to 11,400 KRW as of June 2018. According to ARIMA intervention time series analysis, it was proven national carriers would make a payment of 831 million KRW 2018 and 1,024 million KRW 2019, showing 186.2% and 123.2% increase compared to last year respectively. The total amount of charge for both national LCC and foreign airlines was aggregated up to 1,952 million KRW 2019, 227% bigger than the charge paid at 2017. Considering the 50% increase of consumer price index last decade, the increased charge would impair the global competitiveness of national carriers. It could be suggested that current air meteorological charge scheme be improved to apply overseas trend and for national carriers to have a competitive advantage in global aviation market.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.278-281
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• 2007

The purpose of this study is to develop snow and sea ice detection algorithm in Communication, Ocean and Meteorological Satellite (COMS) meteorological data processing system. Since COMS has only five channels, it is not affordable to use microwave or shortwave infrared data which are effective and generally used for snow detection. In order to estimate snow and sea ice coverage, combinations between available channel data(mostly visible and 3.7 ${\mu}m$) are applied to the algorithm based on threshold method. As a result, the COMS snow and sea ice detection algorithm shows reliable performance compared to MODIS products with channel limitation. Specifically, there is partial underestimation over the complicated vegetation area and overestimation over the area of high level clouds such as cirrus. Some corrections are performed by using water vapor and infrared channels to remove cloud contamination and by applying NDVI to detect more snow pixels for the underestimated area.

• Journal of Korean Society for Atmospheric Environment
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• v.20 no.4
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• pp.523-537
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• 2004

In order to raise the accuracy of meteorological data, several numerical experiments about the usefulness of data assimilation to prediction of air pollution was carried out. Used data for data assimilation are surface meteorological components observed by Automatical Weather System with high spatial density. The usage of surface data assimilation gives changes of temperature and wind fields and the change caused by the influence of land-use on meterological simulation is more sensitive at night than noon. The data quality in assimilation it also one of the important factors to predict the meteorological field precisely and through the static IOA (Index of Agreement), simulated meteorological components with selected limited surface data assimilation are agree well with observations.

• Journal of the Korean earth science society
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• v.27 no.7
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• pp.804-815
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• 2006

Meteorologists define a drought as a period of common dry weather. This may sound straightforward, but it is not so in reality. In this study, we attempted to identify meteorological drought conditions over South Korea. To evaluate the temporal and spatial variability of drought, we calculated two commonly used drought indices, the percent of normal precipitation (PNP) and the Palmer drought severity index (PDSI) calculated from fifty-eight meteorological stations below the Korean Meteorological Administration (KMA). The yearly precipitation has been growing gradually, and the amplitude between maximum and minimum also grow more explicitly from 1960's. According to the analysis of percentile anomaly of monthly precipitation, major drought duration was $1927{\sim}1929,\;1937{\sim}1939,\;1942{\sim}1944,\;1967{\sim}1968,\;1976{\sim}1977,\;1982{\sim}1983,\;1988,\;and\;1994{\sim}1995$. The severe drought occurred most frequently in Mokpo, Daegu, Jeonju, Busan, and Gangneung; it tended to occur more frequently in south sector than in mid sector of Korea and in south west sector than in south east sector. According to the analysis of seasonal distribution, extreme droughts occurred frequently in winter at Seoul, Gangneung, Jeonju, Daegu, and Busan. Severe droughts in summer were formed frequently at Seoul, Gangneung, and Mokpo, while that for spring at Jeonju, Daegu, and Busan. The results of PDSI distribution for the $1994{\sim}1995$ drought period were one of the most severe and widely spreaded droughts; it occurred most frequently in the south sector of South Korea. The comparison of time series between PDSI and Normal Percent showed that they exhibit a strong compatibility for the entire study period; it implies that both drought indices are useful method to indicate drought severity.

• Atmosphere
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• v.22 no.2
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• pp.267-277
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• 2012

The objectives of this study are to develop a real-time drought monitoring and prediction system on the East Asia domain and to evaluate the performance of the system by using past historical drought records. The system is mainly composed of two parts: drought monitoring for providing current drought indices with meteorological and hydrological conditions; drought outlooks for suggesting future drought indices and future hydrometeorological conditions. Both parts represent the drought conditions on the East Asia domain (latitude $21.15{\sim}50.15^{\circ}$, longitude $104.40{\sim}149.65^{\circ}$), Korea domain (latitude $30.40{\sim}43.15^{\circ}$, longitude $118.65{\sim}135.65^{\circ}$) and South Korea domain (latitude $30.40{\sim}43.15^{\circ}$, longitude $118.65{\sim}135.65^{\circ}$), respectively. The observed meteorological data from ASOS (Automated Surface Observing System) and AWS (Automatic Weather System) of KMA (Korean Meteorological Administration) and model-driven hydrological data from LSM (Land Surface model) are used for the real-time drought monitoring, while the monthly and seasonal weather forecast information from UM (Unified Model) of KMA are utilized for drought outlooks. For the evaluation of the system, past historical drought records occurred in Korea are surveyed and are compared with the application results of the system. The results demonstrated that the selected drought indices such as KMA drought index, SPI (3), SPI (6), PDSI, SRI and SSI are reasonable, especially, the performance of SRI and SSI provides higher accuracy that the others.

• Journal of The Korean Society of Agricultural Engineers
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• v.61 no.3
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• pp.77-88
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• 2019

Drought is the recurrent natural disasters which harshly affect agricultural production and society in various parts in Bangladesh. Information on the spatiotemporal variability of drought events plays a vital role to take necessary action towards drought mitigation and sustainable development. This study aims to analyze the spatial and temporal variation of meteorological drought in Bangladesh during 1981-2015 using Effective Drought Index (EDI). Monthly precipitation data for 36 years (1980-2015) were obtained from 27 meteorological stations. Drought frequency (DF) and areal extent of drought were considered to investigate the spatiotemporal structure of drought. The DF analysis showed that the northern, southwestern and central regions of the country are comparatively vulnerable to meteorological drought. The frequency of drought in all categories has considerably increased during the recent five years from 2011 to 2015. Furthermore, the most significant increasing trend of the drought-affected area was found over the central region especially for pre-monsoon (March-May) season during this period while the decreasing trend of the affected area was found within the eastern region during the study period. To prevent and mitigate the damages of drought disasters in Bangladesh, agricultural and government managers should pay more attention to those regional drought events that occur in pre-monsoon season. The outcome of the present study can be used as explanatory data in building the strategies to drought monitoring and mitigation activities in Bangladesh.

• Atmosphere
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• v.21 no.3
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• pp.319-336
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• 2011

The objective of this study was to assess the meteorological capability of Korea by comparing with that of the U.S. and Japan as of 2010. The research was conducted based on various indices and surveys, and quantified the results using the Gordon's scoring model. The index assessment used 11 items derived from 9 segments - surface observation, advanced observation and observations quality in the observation field; data assimilation, numerical model and infrastructure in the data processing field; forecast accuracy in the forecast field; climate prediction and climate change in the climate field - in this research, we classified the meteorological technology into four fields. In the survey assessment, another 10 items in addition to the above 11 ones (total 21 items) were used. In the field of climate, Korea was found to lag far behind the U.S. (96.5p) and Japan (90.5p) with 77.6 points out of 100, which is 18.9 and 12.9 points lower than them respectively. On the other hand, Korea showed the narrowest gap with Japan (95.3p) and the U.S. (94.2) in the forecasting field, recording 90.3 points. Particularly, in surface observation, infrastructure and forecast accuracy segment, Korea was on a par with the U.S. and Japan, boasting 100.5 percent compared to their counterparts. However, in advanced observation, data quality and climate change segment, Korea was only at the level of 81.5 percent compared to that of the U.S. and Japan. All in all, the technological prowess of Korea, scoring 84.6 points, stood at 89.7 percent of that of the U.S. (94.3p) and 91.9 percent of Japan (92.1p).

• Journal of Wetlands Research
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• v.21 no.spc
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• pp.80-89
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• 2019

The purpose of this study is to analyze the relationship between SPI (Standardized Precipitation Index) meteorological drought and RDI (Reservoir Drought Index) agricultural drought for Geum river basin. Drought Indices was calculated by collecting data of precipitation and agricultural reservoir water storage rate from 2014 to 2016. To evaluated the correlation between meteorological and agricultural drought, the Pearson correlation and the Receiver Operation Characteristic (ROC) analysis were conducted to evaluate the correlation between meteorological and agricultural droughts. The SPI-6 and RDI showed the highest relationship with Pearson coefficient 0.606 and ROC hit rates 0.722 respectively, and the spatial occurrence patterns of drought using overlapped SPI-6 and RDI, the big differences between the 2 indices were occurred in the upstream areas of Miho stream and Nonsan stream from August to October 2015. The analysis using reservoirs specifications for areas where reservoir droughts occurred was conducted, and the areas showing severe drought of RDI were the reservoir areas having relatively small value of basin magnifying power (BMP). This means that a reservoir has the reaction capability for agricultural drought mainly depending on the reservoir BMP.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.3
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• pp.19-34
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• 2018

The purpose of this study is to estimate monthly agricultural reservoir storage with multiple linear regression model(MLRM) based on reservoir storage and meteorological data. The regression model was developed using 15 years(2002 to 2016) of 3,067 reservoirs by KRC(Korea Rural Community) and 63 meteorological stations by KMA (Korean Meteorological Administration), and the MLRM showed the determination coefficient($R^2$) of 0.51~0.95. The MLRM was applied to 9 selected reservoirs among the whole reservoirs and validated with $R^2$ of 0.44~0.81. The ROC(Receiver Operating Characteristics) analysis of Reservoir Drought Index(RDI) classified by comparing the present reservoir storage with normal year(1976~2005 average) reservoir storage showed average value of 0.64 for 2 years(2015~2016) with the highest value of 0.70 for winter period, lowest value of 0.58 for summer period. If 1 to 3 months weather forecasting data such as Glosea5 produced by KMA are applied, the predicted monthly reservoir storage from the MLRM can be a useful information for agricultural drought pre-preparation.