• Journal of the Korean earth science society
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• v.38 no.3
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• pp.182-193
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• 2017

A typical snowfall pattern occurs over the east coastal region of the Korean Peninsula, known as the Yeongdong region. The precipitation over the Yeongdong region is influenced by the cold and dry northeasterly wind which advects over warm and moist sea surface of the East Sea of Korea. This study reveals the influence of large-scale factors, affecting local to remote areas, on the mesoscale snowfall system over the Yeongdong region. The National Centers for Environmental Prediction-Department of Energy reanalysis dataset, Extended Reconstructed sea surface temperature, and observed snowfall data are analyzed to reveal the relationship between February snowfall and large-scale factors from 1981 to 2014. The Yeongdong snowfall is associated with the sea level pressure patterns over the Gaema Plateau and North Pacific near the Bering Sea, which is remotely associated to the sea surface temperature (SST) variability over the North Pacific. It is presented that the relationship between the Yeongdong snowfall and large-scale factors is strengthened after 1999 when the central north Pacific has warm anomalous SST. These enhanced relationships explain the atmospheric patterns of recent strong snowfall years (2010, 2011, and 2014). It is suggested that the newly defined index in this study based on related SST variability can be used for a seasonal predictor of the Yeongdong snowfall with 2-month leading.

• Atmosphere
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• v.25 no.3
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• pp.461-472
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• 2015

The sudden stratospheric warming (SSW), which is characterized by an abrupt increase of polar stratospheric temperature by several tens of degrees in a week, has been known to affect tropospheric weather and climate on sub-seasonal time scale in the boreal winter. Such downward coupling has been often examined in North Atlantic and Europe, but rarely examined in East Asia. In this study, by applying the two definitions of SSW to the reanalysis data, the possible impacts of the SSW events on the surface air temperature (SAT) and tropospheric circulation in East Asia are analyzed. It is found that Eurasian continent, including Siberia and the Northeast Asia, tends to experience anomalously cold SAT for up to sixty days after the SSW events. The resulting SAT anomalies largely resemble those associated with negative Artic Oscillation. However, over East Asia, SSW-related SAT change is weak and not statistically significant. Only during the extreme SSW events when the downward coupling between the stratosphere and troposphere is strong, East Asia exhibits significantly cold SAT anomalies. This relationship is presented by grouping SSW events into those followed by cold SAT anomalies over East Asia and those by warm anomalies for varying threshold values of the SSW events.

• Atmosphere
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• v.23 no.4
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• pp.401-412
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• 2013

East Asia experienced extremely cold weather in January 2011, while the previous December and the following February had normal winter temperature. In this study National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis data are used to investigate the characteristic features observed in the meteorological fields such as temperature, sea-level pressure, geopotential height, and wind during this winter period. In January the planetary-wave pattern is dominated by stationary-wave form in the mid-to-high latitude region, while transient waves are significant in the previous month. To understand the planetary-wave features quantitatively, harmonic analyses have been done for the 500-hPa geopotential height field. In the climatological-mean geopotential heights the wave numbers 1, 2, and 3 are dominant during the whole winter. In January 2011 the waves of number 1, 2, and 3 are dominant and stationary as in the climatological-mean field. In December 2010 and February 2011, however, the waves of number 4, 5, and 6 play a major role and show a transient pattern. In addition to the distinctive features in each month the planetary-wave patterns dependent on the latitude are also discussed.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.37-42
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• 1998

Latent and sensible heat fluxes over the global oceans are estimated using SSM/I (Special Sensor Microwave Imager) and AVHRR MCSST (Advanced Very High Resolution Radiometer Multi-Channel Sea Surface Temperature). The heat fluxes are computed from SSM/I wind speeds and surface humidity, the MCSST, and NCEP Reanalysis sea level pressures and 2-m temperatures from 1996 to 1997. The diabatic conditions bulk formula (Kondo, 1975) is used to compute the heat fluxes. To validate, the derived fluxes are compared to the measurements of 3 JMA buoys. The wind speeds and surface humidity derived from SSM/I have accuracies of 1.37m/s and 1.7g/kg, respectively. The heat fluxes were estimated these factors and the standard error of the latent and sensible heat fluxes are 5.53 W/m$^2$ and 3.33 W/m$^2$. The latest El-Nino phenomenon started at the beginning of 1997 and this event was larger than any others. We compare the heat fluxes in 1997 with the fluxes in 1996 and investigate the spatial movement of meteorological factors as well as the heat fluxes associated with El-Nino appearance.

• Atmosphere
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• v.21 no.2
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• pp.143-149
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• 2011

A new multi-timescale analysis method, Ensemble Empirical Mode Decomposition (EEMD), is used to diagnose the variation of the MJO activity determined by 850hPa and 200hPa zonal winds from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) Reanalysis data for the 56-yr period from 1950 to 2005. The results show that MJO activity can be decomposed into 9 quasi-periodic oscillations and a trend. With each level of contribution of the quasi-periodic oscillation discussed, the bi-seasonal oscillation, the interannual oscillation and the trend of the MJO activity are the most prominent features. The trend increases almost linearly, so that prior to around 1978 the activity of the MJO is lower than that during the latter part. This may be related to the tropical sea surface temperature(SST). It is speculated that the interdecadal change in the MJO activity appeared in around 1978 is related to the warmer SST in the equatorial warm pool, especially over the Indian Ocean.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1635-1639
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• 2010

기후변화가 수자원에 미치는 영향을 파악하기 위해서는 물 순환 및 물 수지의 변화 경향 파악이 필수적이며, 대기 중의 가강수량 파악은 가뭄 호우 등에 대한 기본 조사로서 수자원 연구에 필요하다. 본 연구에서는 MODIS 위성자료로부터 가강수량을 산출하여 검증하고, 전구 및 동아시아의 분포 특성 및 변화 경향을 분석하였다. MODIS 위성자료는 NASA의 홈페이지로부터 입수하여 가강수량을 산출하였고, 산출한 가강수량은 NCEP Reanalysis2 자료를 이용하여 검증하였다. MODIS 위성자료를 이용하여 전구 가강수량의 경년변화 및 분포 분석을 실시한 결과 가강수량의 분포는 ITCZ의 움직임과 잘 일치하였고, 6월에 가장 많은 가강수량을 나타내며 10월에 가장 적은 가강수량을 나타냈다. 경년변화는 2000년대 중반까지는 증가하는 경향을 보이고 있었지만 최근 3년 정도는 감소하는 추세를 보이고 있다. MODIS 위성자료를 이용하여 동아시아 지역 가강수량의 경년변화 및 분포 분석을 실시한 결과 가강수량의 분포는 계절적인 특징을 잘 나타내고 있으며, 7월에 가장 많은 가강수량을 나타내고 있으며 11월에 가장 적은 가강수량을 나타내고 있고, 경년변화는 큰 변화는 보이지 않았다. MODIS 위성으로부터 산출한 가강수량과 표면온도를 비교한 결과 가강수량은 계절적인 특징은 거의 비슷한 변화를 가지고 있으며 년 변화에서는 동아시아 가을의 변화가 통계적으로 유의한 양의 상관관계를 가지고 있었으며, 동아시아 가을의 가강수량은 표면온도와 함께 증가하는 경향을 나타내고 있다.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.45-45
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• 2023

본 연구에서는 도시 내 및 주변 지역을 대상으로 기상학적 가뭄 발생 여부에 따른 토양수분량 변화 정도를 파악하고, 그에 따른 열섬 현상의 변동 정도를 분석·평가하였다. 먼저, 대상 지역 내 기상학적 가뭄의 시공간적 특성을 분석하기 위해 인공위성, 재분석 자료 및 지상 관측 정보를 활용하여 SPI (Standard Precipitation Index)와 SPEI (Standard Precipitation Evapotranspiration Index) 등 두 가지의 가뭄 지수를 산정하였다. 또한, ERA5 (The Fifth Generation ECMWF Atmospheric Reanalysis)와 GLDAS (Global Land Data Assimilation System) 등의 재분석 자료 및 지상 관측 정보를 활용하여 토양수분 자료 및 기타 기상 관련 주요 정보들을 얻고, 이를 ENVI-met 모형의 초기 입력자료로 고려하였다. 다양한 시나리오 기반의 모의 결과들을 바탕으로 복합 재난의 관점에서 가뭄-토양수분량-열섬 간의 연관성을 분석하고, 주요 영향 인자 및 극한 사상 유발 조건 등에 대한 정보를 파악하였다.

• Atmosphere
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• v.19 no.1
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• pp.9-36
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• 2009

Two heavy snowfall events occurred in Yeongnam and Yeongdong regions of the Korean Peninsula during the period from 4 to 6 March 2005 are analyzed. The events were developed by two different meso-scale snow clouds associated with an extratropical low passing over the Western Pacific. Based on synoptic data, GOES-9 satellite images, and precipitation amount data, the events were named as Sokcho and Busan cases, respectively. We analyzed the development mechanism of the events using meterological variables from the NCEP(National Centers for Environmental Prediction) /NCAR(National Centers for Atmospheric Research) reanalysis data such as potential vorticity(PV), divergence, tropopause undulation, static stability, and meridional wind circulation. The present analyses show that in the case of Sokcho, the cyclonic circulation in the lower atmosphere in the strong baroclinic region induced the cyclonic circulation in the upper atmosphere. The cyclonic circulation in the lower and upper atmosphere caused a heavy snowfall in the Sokcho region. In the case of Busan, the strong cyclonic circulation in the upper atmosphere was initiated by the stratospheric air intrusion with the high positive PV into the troposphere during the tropopause folding. The upper strong cyclonic circulation enhanced the cyclonic circulation in the lower disturbed atmosphere due to the extratropical low. This lower cyclonic circulation in turn, intensified the upper cyclonic circulation, that caused a heavy snowfall in the Busan region.

• Atmosphere
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• v.26 no.4
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• pp.495-508
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• 2016

In order to determine the prediction possibility of heavy rainfall, a variety of analyses was conducted by using three-dimensional data obtained from Korea Local Analysis and Prediction System (KLAPS) re-analysis data. Strong moisture convergence occurring around the time of the heavy rainfall is consistent with the results of previous studies on such continuous production. Heavy rainfall occurred in the cloud system with a thick convective clouds. The moisture convergence, temperature and potential temperature advection showed increase into the heavy rainfall occurrence area. The distribution of integrated liquid water content tended to decrease as rainfall increased and was characterized by accelerated convective instability along with increased buoyant energy. In addition, changes were noted in the various characteristics of instability indices such as K-index (KI), Showalter Stability Index (SSI), and lifted index (LI). The meteorological variables used in the analysis showed clear increases or decreases according to the changes in rainfall amount. These rapid changes as well as the meteorological variables changes are attributed to the surrounding and meteorological conditions. Thus, we verified that heavy rainfall can be predicted according to such increase, decrease, or changes. This study focused on quantitative values and change characteristics of diagnostic variables calculated by using numerical models rather than by focusing on synoptic analysis at the time of the heavy rainfall occurrence, thereby utilizing them as prognostic variables in the study of the predictability of heavy rainfall. These results can contribute to the identification of production and development mechanisms of heavy rainfall and can be used in applied research for prediction of such precipitation. In the analysis of various case studies of heavy rainfall in the future, our study result can be utilized to show the development of the prediction of severe weather.

• Journal of Korea Water Resources Association
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• v.51 no.3
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• pp.273-280
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• 2018

Accurate estimation of evapotranspiration is mightily important for understanding and analyzing the hydrological cycle. There are various methods for estimating evapotranspiration and each method has its own advantages and limitations. Therefore, it is necessary to develop an optimal evapotranspiration product by combing different evapotranspiration products. In this study, we developed an optimal evapotranspiration by fusing two satellite- and model-based evapotranspiration estimates, including revised remote sensing-based Penman-Monteith (RS-PM) and Modified Satellite-Based Priestley-Taylor (MS-PT) methods, Global Land Data Assimilation System (GLDAS), and Global Land Evaporation Amsterdam Model (GLEAM). The statistical analysis (i.e., correlation coefficients, index of agreement, MAE, and RMSE) of combined evapotranspiration product showed to be improved compared to the individual model results. After confirming the overall results, in future studies, advanced data fusion techniques will be used to obtained improved results.