• Atmosphere
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• v.29 no.3
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• pp.295-309
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• 2019

Due to frequent occurrence of abnormal weather, the need to improve the accuracy of subseasonal prediction has increased. Here we analyze the performance of weekly predictions out to 6 weeks by GloSea5 climate model. The performance in circulation field from January 1991 to December 2010 is first analyzed at each grid point using the 500-hPa geopotential height. The anomaly correlation coefficient and mean-square skill score, calculated each week against the ECWMF ERA-Interim reanalysis data, illustrate better prediction skills regionally in the tropics and over the ocean and seasonally during winter. Secondly, we evaluate the predictability of 7 major teleconnection patterns in the Northern Hemisphere: North Atlantic Oscillation (NAO), East Atlantic (EA), East Atlantic/Western Russia (EAWR), Scandinavia (SCAND), Polar/Eurasia (PE), West Pacific (WP), Pacific-North American (PNA). Skillful predictability of the patterns turns out to be approximately 1~2 weeks. During summer, the EAWR and SCAND, which exhibit a wave pattern propagating over Eurasia, show a considerably lower skill than the other 5 patterns, while in winter, the WP and PNA, occurring in the Pacific region, maintain the skill up to 2 weeks. To account for the model's bias in reproducing the teleconnection patterns, we measure the similarity between the teleconnection patterns obtained in each lead time. In January, the model's teleconnection pattern remains similar until lead time 3, while a sharp decrease of similarity can be seen from lead time 2 in July.

• 한국지구과학회:학술대회논문집
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• 2004.02a
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• pp.84-85
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• 2004

• Journal of the Korean earth science society
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• v.34 no.4
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• pp.336-344
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• 2013

This study has developed a multiple linear regression model (MLRM) for the seasonal prediction of the summer tropical cyclone genesis frequency (TCGF) over the western North Pacific (WNP) using the four teleconnection patterns. These patterns are representative of the Siberian high Oscillation (SHO) in the East Asian continent, the North Pacific Oscillation (NPO) in the North Pacific, Antarctic oscillation (AAO) near Australia, and the circulation in the equatorial central Pacific during the boreal spring (April-May). This statistical model is verified by analyzing the differences hindcasted for the high and low TCGF years. The high TCGF years are characterized by the following anomalous features: four anomalous teleconnection patterns such as anticyclonic circulation (positive SHO phase) in the East Asian continent, pressure pattern like north-high and south-low in the North Pacific, and cyclonic circulation (positive AAO phase) near Australia, and cyclonic circulation in the Nino3.4 region were strengthened during the period from boreal spring to boreal summer. Thus, anomalous trade winds in the tropical western Pacific (TWP) were weakened by anomalous cyclonic circulations that located in the subtropical western Pacific (SWP) in both hemispheres. Consequently, this spatial distribution of anomalous pressure pattern suppressed convection in the TWP, strengthened convection in the SWP instead.

• Atmosphere
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• v.28 no.3
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• pp.305-315
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• 2018

This study investigates the characteristic spatial patterns and dynamic processes associated with the summertime extreme temperature events in South Korea during the last 20 years (1995~2014) using Self-Organizing Map (SOM). The classified SOM patterns commonly have high temperature and anticyclonic circulation anomalies over South Korea. The two major teleconnection patterns are identified: one is from the subtropical western North Pacific (WNP) affecting to the north and the other is from the North Atlantic (NA) affecting downstream region. The meridional teleconnection pattern is related to the forcing of positive sea surface temperature (SST) anomaly over the WNP. The northward propagating Rossby wave generates the East Asia-Pacific (EAP) pattern to form an anticyclonic circulation anomaly over South Korea. On the other hand, NA SST anomalies generate an eastward Rossby wave train across the Eurasian continent, leading to the development of an anticyclonic circulation anomaly over South Korea. The EAP pattern occurs more frequently in July and August, whereas the midlatitude teleconnection pattern associated with NA SST anomalies develops more frequently in early summer (June).

• Atmosphere
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• v.24 no.1
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• pp.89-99
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• 2014

Recently, several studies pointed out that there are distinct two types of El Ni$\tilde{n}$o events based on the spatial pattern of SST. Since the two types of El Ni$\tilde{n}$o have different impacts on global climate, it is quite important to identify the type to assess and predict the regional climate variability. So far, however, there are still many different definitions to identify the two types of El Ni$\tilde{n}$o from the different studies. In this study, we investigated a sensitivity of the impacts on climate variability over the Korean Peninsula corresponding to the definition of two-types of El Ni$\tilde{n}$o. After checking pre-existing definitions and other possible definition, it is suggested here that two different definitions exhibit relatively strong relationship between El Ni$\tilde{n}$o events and the Korean climate variables when two types of El Ni$\tilde{n}$o are separated. In addition to the Korean climate, the two types of El Ni$\tilde{n}$o show quite distinct global teleconnection patterns when the definitions are used.

• The Korean Journal of Quaternary Research
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• v.33 no.1_2
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• pp.25-35
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• 2021

In this study, we identified characteristics of heatwaves on the Korean Peninsula and related atmospheric circulation patterns using data on the daily maximum temperature (TMX) and reanalysis data for the past 42 years (1979-2020) and analyzed their connection to the Arctic oscillation (AO). The heatwave on the Korean Peninsula showed to be stronger and more frequent in the 2000s. The recent strong and frequent heatwaves on the Korean Peninsula are mainly affected by abnormal high-pressure over the Korean Peninsula on the middle/upper-level atmosphere and the strengthening of the North Pacific high pressure. Interestingly, composite difference of sea level pressure showed very similar results to the positive AO pattern. The correlation coefficients between the summertime AO and the TMX and HWD of the Korean Peninsula were 0.407 and 0.437, respectively, which showed a statistical significance in 1%, and showed a clear relationship with the abnormal high-pressure over the Korean Peninsula and the strengthening of the North Pacific high pressure. In addition, in the positive AO phase, the TMX and HWD of the Korean peninsula were approximately 30.1 ℃ and 14.6 days, which were about 1.2 ℃ and 8.8 days higher than in the negative AO phase, respectively. As a result of the 15-year moving average correlation analysis, the relationship between the heatwave and AO on the Korean Peninsula has increased significantly since 2003, and the linear relationship between them has become more apparent. Moreover, after the 2000s, when the relationship developed, AO had more strongly induced the atmospheric circulation pattern to be more favorable to the occurrence of heatwaves in the Korean Peninsula. This study implies that understanding the AO, which is the large-scale variability in the Northern Hemisphere, and the Arctic-mid latitude teleconnection, can improve the performance of global climate models and help predict the seasonality of the summer heatwave on the Korean Peninsula.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.38-38
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• 2012

The East Asia (EA) region including China, Taiwan, Japan, and Korea are especially vulnerable to hydrometerological extremes during the boreal summer (June-September). This study, therefore, pursued an exploratory analysis to improve better understanding of the potential impacts of the two types of PJ patterns on WNP Tropical cyclone (TC) activities and TC-induced extreme moisture fluxes over Korea's five major river basins. This study shows that during positive PJ years, the large-scale atmospheric environments are more favorable for the TC activities than those in negative PJ years. During positive PJ year, it is found that there are weaker wind shear, stronger rising motion, as well as large relative humidity over the Korean peninsula (KP) compared to negative PJ years. As a result, TCs making landfall are more exhibited over the southeastern portions of South Korea. Despite the relatively modest sample size, we expect that insights and results presented here will be useful for developing a critical support system for the effective reduction and mitigation of TC-caused disasters, as well as for water supply management in coupled human and natural systems.

• Journal of Ecology and Environment
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• v.45 no.4
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• pp.228-236
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• 2021

Background: A review of the literature was carried out to study dust and sandstorm (DSS) in terms of its ecosystem processes and relationship to other dryland disasters in Northeast Asia. Drylands are ecosystems that include grasslands, semi-deserts, and deserts, and these types of ecosystems are vulnerable due to their low primary productivity that depends on a small amount of precipitation. Results: Drought, dust, desertification, and winter livestock disasters (called dzud) are unique natural disasters that affect the region. These disasters are related in that they share major causes, such as dryness and low vegetation cover that combine with other conditions, wind, cold waves, livestock, and land-surface energy, to dramatically impact the ecosystem. Conclusions: The literature review in this study illustrates the macroscopic context of the spatial and temporal patterns of DSS according to geography, climate, and vegetation growth in the drylands of Northeast Asia. The effects of ocean climates and human activities were discussed to infer a possible teleconnection effect of DSS and its relations to desertification and dzud.

• Journal of Korea Water Resources Association
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• v.54 no.9
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• pp.731-745
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• 2021

In this study, the monthly temperature of the Han River basin was predicted by statistical multiple regression models that use global climate indices and weather data of the target region as predictors. The optimal predictors were selected through teleconnection analysis between the monthly temperature and the preceding patterns of each climate index, and forecast models capable of predicting up to 12 months in advance were constructed by combining the selected predictors and cross-validating the past period. Fore each target month, 1000 optimized models were derived and forecast ranges were presented. As a result of analyzing the predictability of monthly temperature from January 1992 to December 2020, PBIAS was -1.4 to -0.7%, RSR was 0.15 to 0.16, NSE was 0.98, and r was 0.99, indicating a high goodness-of-fit. The probability of each monthly observation being included in the forecast range was about 64.4% on average, and by month, the predictability was relatively high in September, December, February, and January, and low in April, August, and March. The predicted range and median were in good agreement with the observations, except for some periods when temperature was dramatically lower or higher than in normal years. The quantitative temperature forecast information derived from this study will be useful not only for forecasting changes in temperature in the future period (1 to 12 months in advance), but also in predicting changes in the hydro-ecological environment, including evapotranspiration highly correlated with temperature.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.723-736
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• 2022

In this study, monthly precipitation forecasting models that can predict up to 12 months in advance were constructed for the Geum River basin, and two statistical techniques, multiple linear regression (MLR) and artificial neural network (ANN), were applied to the model construction. As predictor candidates, a total of 47 climate indices were used, including 39 global climate patterns provided by the National Oceanic and Atmospheric Administration (NOAA) and 8 meteorological factors for the basin. Forecast models were constructed by using climate indices with high correlation by analyzing the teleconnection between the monthly precipitation and each climate index for the past 40 years based on the forecast month. In the goodness-of-fit test results for the average value of forecasts of each month for 1991 to 2021, the MLR models showed -3.3 to -0.1% for the percent bias (PBIAS), 0.45 to 0.50 for the Nash-Sutcliffe efficiency (NSE), and 0.69 to 0.70 for the Pearson correlation coefficient (r), whereas, the ANN models showed PBIAS -5.0~+0.5%, NSE 0.35~0.47, and r 0.64~0.70. The mean values predicted by the MLR models were found to be closer to the observation than the ANN models. The probability of including observations within the forecast range for each month was 57.5 to 83.6% (average 72.9%) for the MLR models, and 71.5 to 88.7% (average 81.1%) for the ANN models, indicating that the ANN models showed better results. The tercile probability by month was 25.9 to 41.9% (average 34.6%) for the MLR models, and 30.3 to 39.1% (average 34.7%) for the ANN models. Both models showed long-term predictability of monthly precipitation with an average of 33.3% or more in tercile probability. In conclusion, the difference in predictability between the two models was found to be relatively small. However, when judging from the hit rate for the prediction range or the tercile probability, the monthly deviation for predictability was found to be relatively small for the ANN models.