• Journal of the Korean association of regional geographers
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• v.20 no.4
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• pp.393-408
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• 2014

In this study, the spatio-temporal characteristics of summer extreme precipitation events in the Republic of Korea are examined based on the daily precipitation data observed at approximately 360 sites of both Automatic Weather Station (AWS) and Automated Synoptic Observation System (ASOS) networks by the Korea Meteorological Administration for the recent decade(2002~2011). During the summer Changma period(late June~mid July), both the frequency of extreme precipitation events exceeding 80mm of daily precipitation and their decadal maximum values are greatest at most of weather stations. In contrast, during the Changma pause period (late July~early August), these patterns are observed only in the northern regions of Geyeonggi province and western Kangwon province as such patterns are detected around Mt. Sobaek and Mt. Halla as well as in the southern regions of Geyeonggi province and western Kangwon province during the late Changma period (mid August~early September) due to north-south oscillation of the Changma front. Investigation of their regional patterns confirms that not only migration of the Changma front but also topological components in response to the advection of moistures such as elevation and aspect of major mountain ridges are detrimental to spatio-temporal patterns of extreme precipitation events. These results indicate that each local administration needs differentiated strategies to mitigate the potential damages by extreme precipitation events due to the spatiotemporal heterogeneity of their frequency and intensity during each Changma period.

• Journal of Korea Water Resources Association
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• v.50 no.10
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• pp.691-701
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• 2017

The objective of this study is to evaluate the long-term drought outlook information based on long-term forecast data for the 2015 drought event. In order to estimate the Standardized Precipitation Index (SPI) for different durations (3-, 6-, 9-, 12-months), we used the observation precipitation of 59 Automated Synoptic Observing System (ASOS) sites, forecast and hindcast data of GloSea5. The Receiver Operating Characteristic (ROC) analysis and statistical analysis (Correlation Coefficient, CC; Root Mean Square Error, RMSE) were used to evaluate the utilization of drought outlook information for the forecast lead-times (1~6months). As a result of ROC analysis, ROC scores of SPI(3), SPI(6), SPI(9) and SPI(12) were estimated to be over 0.70 until the 2-, 3-, 4- and 5-months. The CC and RMSE values of SPI(3), SPI(6), SPI(9) and SPI(12) for forecast lead-time were estimated as (0.60, 0.87), (0.72, 0.95), (0.75, 0.95) and (0.77, 0.89) until the 2-, 4-, 5- and 6-months respectively.

• Journal of Korea Water Resources Association
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• v.53 no.9
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• pp.701-715
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• 2020

This study compared several reference evapotranspiration estimated using eight methods such as FAO-56 Penman-Monteith (FAO PM), Hamon, Hansen, Hargreaves-Samani, Jensen-Haise, Makkink, Priestley-Taylor, and Thornthwaite. In addition, by analyzing the monthly deviations of the results by the FAO PM and the remaining seven methods, monthly optimized correction coefficients were derived and the improvement effect was evaluated. These methods were applied to 73 automated synoptic observation system (ASOS) stations of the Korea Meteorological Administration, where the climatological data are available at least 20 years. As a result of evaluating the reference evapotranspiration by applying the default coefficients of each method, a large fluctuation happened depending on the method, and the Hansen method was relatively similar to FAO PM. However, the Hamon and Jensen-Haise methods showed more large values than other methods in summer, and the deviation from FAO PM method was also large significantly. When comparing based on the region, the comparison with FAO PM method provided that the reference evapotranspiration estimated by other methods was overestimated in most regions except for eastern coastal areas. Based on the deviation from the FAO PM method, the monthly correction coefficients were derived for each station. The monthly deviation average that ranged from -46 mm to +88 mm before correction was improved to -11 mm to +1 mm after correction, and the annual average deviation was also significantly reduced by correction from -393 mm to +354 mm (before correction) to -33 mm to +9 mm (after correction). In particular, Hamon, Hargreaves-Samani, and Thornthwaite methods using only temperature data also produced results that were not significantly different from FAO PM after correction. It can be also useful for forecasting long-term reference evapotranspiration using temperature data in climate change scenarios or predicting evapotranspiration using monthly or seasonal temperature forecasted values.