• Proceedings of the Korea Water Resources Association Conference
• /
• 2015.05a
• /
• pp.65-69
• /
• 2015

하천에서 유사이동은 하천환경과 하천형상을 결정하는 주요 요소이므로 이를 해석하는 것은 매우 중요하다. 그러나 유사이동은 일반적으로 이상흐름 (two-phase flow)이며 난류를 동반하기에 이를 해석하기에는 쉽지 않다. 이상흐름을 해석하는 방법으로는 유사를 연속상인 유사구름(sediment cloud)으로 표현하여 해석하는 Euler-Euler 모형이 있으며 입자를 직접 추적하여 해석하는 Euler-Lagrange 모형이 있다. 본 연구에서는 유사이동 해석을 위하여 Euler-Lagrange 모형을 사용하였으며 흐름의 진동성분을 고려하기 위하여 EIM (Eddy Interaction Model)을 사용하였다. 유체의 유속은 Dou (1987)가 제시한 경험식을 사용하였고 난류운동에너지와 소산률은 Nezu and Nakagawa (1993)가 제시한 식을 사용하였다. EIM에서 입자에 발생하는 와의 영향시간(eddy interaction time)을 계산하기 위해 Gosman and Ioannides (1983)가 제시한 eddy lifetime과 eddy crossing time을 사용하였다. 유사입자는 입자의 운동량방정식을 풀어 그 거동을 추적하였으며 일정 시간 후 입자의 수를 이용하여 농도를 계산하였다. 유체에 발생하는 유속의 진동성분에 의해 입자가 부상하고 중력에 의해 흐름에 따른 일정한 농도분포 형태를 가지는 것을 확인하였다. 유사의 입자크기와 흐름에 따른 농도분포를 계산하였으며, 이를 측정치와 비교하여 EIM의 적용성을 확인하였다.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.14 no.4
• /
• pp.63-76
• /
• 2011

This study purposes to develop a model to analyze soil loss in estimating prior disaster influence. The model of analyzing soil loss develops the soil loss analysis system on the basis of Internet by introducing cloud computing system, and also develops a standalone type in connection with HyGIS. The soil loss analysis system is developed to draw a distribution chart without requiring a S/W license as well as without preparing basic data such as DEM, soil map and land cover map. Besides, it can help users to draw a soil loss distribution chart by applying various factors like direct rain factors. The tools of Soil Loss Anaysis Model in connection with HyGiS are developed as add-on type of GMMap2009 in GEOMania, and also are developed to draw Soil Loss Hazard Map suggested by OECD. As a result of using both models, they are developed very conveniently to analyze soil loss. Hereafter, these models will be able to be improved continuously through researches to analyze sediment a watershed outlet and to calculate R value using data of many rain stations.

• Atmosphere
• /
• v.20 no.1
• /
• pp.37-47
• /
• 2010

The methods measuring the precipitation drop size distribution(hereafter referred to as DSD) at Cloud Physics Observation System (CPOS) in Daegwallyeong are to use PARSIVEL (PARticle SIze and VELocity) disdrometer (hereafter referred to as PARSIVEL) and Micro Rain Radar (hereafter referred to as MRR). First of all, PARSIVEL and MRR give good correlation coefficients between their rain rates and those of rain gage: $R^2=0.93$ and 0.91, respectively. For the DSD, the rain rates are classified in 3 categories (Category 1: rr (Rain Rate) ${\leq}0.5\;mm\;h^{-1}$, Category 2: $0.5\;mm\;h^-1$ < rr < $4.0\;mm\;h^{-1}$, Category 3: rr ${\geq}4\;mm\;h^{-1}$). The shapes of PARSIVEL and MRR DSD are relatively most similar in category 2. In addition, we retrieve the vertical rain rate and liquid water content from MRR under melting layer, calculated by Cha et al's method, in Daegwallyeong ($37^{\circ}41{\prime}N$, $128^{\circ}45^{\prime}E$, 843 m ASL, mountain area) and Haenam ($34^{\circ}33^{\prime}N$, $126^{\circ}34^{\prime}E$, 4.6 m ASL, coast area). The vertical variations of rain rate and liquid water content in Daegwallyeong are smaller than those in Haenam. We think that this different vertical rain rate characteristic for both sites is due to the vertical different cloud type (convective and stratiform cloud seem dominant at Haenam and Daegwallyeong, respectively). This suggests that the statistical precipitation DSD model, for the application of weather radar and numerical simulation of precipitation processes, be considered differently for the region, which will be performed in near future.

• Atmosphere
• /
• v.22 no.1
• /
• pp.29-45
• /
• 2012

An unusual autumn storm developed rapidly in the western part of the East sea on the early morning of 23 October 2006. This storm produced a record-breaking heavy rain and strong wind in the northern and middle part of the Yeong-dong region; 24-h rainfall of 304 mm over Gangneung and wind speed exceeding 63.7 m $s^{-1}$ over Sokcho. In this study, MTSAT-1R (Multi-fuctional Transport Satellite) water vapor and infrared channel imagery are examined to find out some features which are dynamically associated with the development of the storm. These features may be the precursor signals of the rapidly developing storm and can be employed for very short range forecast and nowcasting of severe storm. The satellite features are summarized: 1) MTSAT-1R Water Vapor imagery exhibited that distinct dark region develops over the Yellow sea at about 12 hours before the occurrence of maximum rainfall about 1100 KST on 23 October 2006. After then, it changes gradually into dry intrusion. This dark region in the water vapor image is closely related with the positive anomaly in 500 hPa Potential Vorticity field. 2) In the Infrared imagery, low stratus (brightness temperature: $0{\sim}5^{\circ}C$) develops from near Bo-Hai bay and Shanfung peninsula and then dissipates partially on the western coast of Korean peninsula. These features are found at 10~12 hours before the maximum rainfall occurrence, which are associated with the cold and warm advection in the lower troposphere. 3) The IR imagery reveals that two convective cloud cells (brightness temperature below $-50^{\circ}C$) merge each other and after merging it grows up rapidly over the western part of East sea at about 5 hours before the maximum rainfall occurrence. These features remind that there must be the upward flow in the upper troposphere and the low-layer convergence over the same region of East sea. The time of maximum growth of the convective cloud agrees well with the time of the maximum rainfall.

• Journal of Korea Water Resources Association
• /
• v.53 no.11
• /
• pp.999-1013
• /
• 2020

Weather modification research has been actively performed worldwide, but a technology that can more quantitatively prove the research effects are needed. In this study, the seeding effect, the efficiency of precipitation enhancement in weather modification experiment, was verified using the radar data. Also, the effects of seeding material on hydrometeor change was analyzed. For this, radar data, weather conditions, and numerical simulation data for diffusion were applied. First, a method to analyze the seeding effect in three steps was proposed: before seeding, during seeding, and after seeding. The proposed method was applied to three cases of weather modification experiments conducted in Gangwon-do and the West Sea regions. As a result, when there is no natural precipitation, the radar reflectivity detected in the area where precipitation change is expected was determined as the seeding effect. When natural precipitation occurs, the seeding effect was determined by excluding the effect of natural precipitation from the maximum reflectivity detected. For the application results, it was found that the precipitation intensity increased by 0.1 mm/h through the seeding effect. In addition, it was confirmed that ice crystals, supercooled water droplets, and mixed-phase precipitation were distributed in the seeding cloud. The results of these weather modification research can be used to secure water resources as well as for future study of cloud physics.

• Korean Journal of Remote Sensing
• /
• v.37 no.5_3
• /
• pp.1405-1423
• /
• 2021

Precipitation is one of the main factors that affect water and energy cycles, and its estimation plays a very important role in securing water resources and timely responding to water disasters. Satellite-based quantitative precipitation estimation (QPE) has the advantage of covering large areas at high spatiotemporal resolution. In this study, machine learning-based rainfall intensity models were developed using Himawari-8 Advanced Himawari Imager (AHI) water vapor channel (6.7 ㎛), infrared channel (10.8 ㎛), and weather radar Column Max (CMAX) composite data based on random forest (RF). The target variables were weather radar reflectivity (dBZ) and rainfall intensity (mm/hr) converted by the Z-R relationship. The results showed that the model which learned CMAX reflectivity produced the Critical Success Index (CSI) of 0.34 and the Mean-Absolute-Error (MAE) of 4.82 mm/hr. When compared to the GeoKompsat-2 and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN)-Cloud Classification System (CCS) rainfall intensity products, the accuracies improved by 21.73% and 10.81% for CSI, and 31.33% and 23.49% for MAE, respectively. The spatial distribution of the estimated rainfall intensity was much more similar to the radar data than the existing products.

• Journal of Environmental Science International
• /
• v.25 no.3
• /
• pp.405-415
• /
• 2016

We analyzed the micro-meteorological characteristics during typical steam fog over the Gumi Reservoir of Nakdong river with the field observation data for recent 2 year(1 April 2013~31 March 2015) collected by the national institute of meteorological research, KMA. Steam fog occur when the cold drainage flows over the warm water surface. As the sensible and latent heat from water are provided to the air, the instability of lower atmosphere is increased. The resultant vertical mixing of warm, moist air near water surface and cold air aloft causes the formation of status cloud. The convection strengthened by radiative cooling of the upper part of the stratus causes the fog to propagate downward. Also, the temperature at the lowest atmosphere is increased rapidly and the inversion near surface disappear by these processes when the fog forms. The increase of wind speed is observed because the downward transportation of momentum is caused by vertical mixing.

• Polymer(Korea)
• /
• v.26 no.6
• /
• pp.821-828
• /
• 2002

Regular and highly interconnected macroporous poly(L-lactic acid) (PLLA) scaffolds with pore size of 10∼300 ㎛ were fabricated through thermally induced phase separation of a PLLA-dioxane-water ternary system in the presence of a small amount of Pluronics. Addition of Pluronics to the ternary system raised the cloud-point temperature curve in the order of P-123< F-68< F-127. The Pluronics act as nuclei for the phase separation. This assistance is enhanced with increasing length of the hydrophilic PEO blocks in the Pluronics molecules. Liquid-liquid spinodal phase separation was induced at higher temperatures in the systems containing Pluronics because the spinodal region is raised to higher temperature. The absorption of Pluronics onto the interface stabilizes a macro scale structure and increases the interconnection of pores.

• Journal of The Geomorphological Association of Korea
• /
• v.25 no.1
• /
• pp.67-80
• /
• 2018

This study used aerial and terrestrial images to build a three-dimensional model of cliffs located in Pado beach using SfM (Structure from Motion) techniques. Using both images, the study purposed to reduce the shadow areas that were found when using only aerial images. Accuracy of the two campaigns was assessed by root mean square error, and monitored by M3C2 (Multiscale Model to Model Cloud Comparison) method. The result of the M3C2 in closed areas such as sea cave and notch did not express the landforms partly. However, eroded debris on sea cliffs were detected as eroded area by M3C2, as well as in captured pictures by multi-camera. The result of this study showed the applicability of multi-camera and SfM in monitoring changes of sea cliffs.

• Korean Journal of Remote Sensing
• /
• v.32 no.2
• /
• pp.119-131
• /
• 2016

Descriptions are provided of the automated aerosol-type classification and mass concentration calculation algorithm for real-time data processing and aerosol products in Korea Aerosol Lidar Observation Network (KALION, http://www.kalion.kr). The KALION algorithm provides aerosol-cloud classification and three aerosol types (clean continental, dust, and polluted continental/urban pollution aerosols). It also generates vertically resolved distributions of aerosol extinction coefficient and mass concentration. An extinction-to-backscatter ratio (lidar ratio) of 63.31 sr and aerosol mass extinction efficiency of $3.36m^2g^{-1}$ ($1.39m^2g^{-1}$ for dust), determined from co-located sky radiometer and $PM_{10}$ mass concentration measurements in Seoul from June 2006 to December 2015, are deployed in the algorithm. To assess the robustness of the algorithm, we investigate the pollution and dust events in Seoul on 28-30 March, 2015. The aerosol-type identification, especially for dust particles, is agreed with the official Asian dust report by Korean Meteorological Administration. The lidar-derived mass concentrations also well match with $PM_{10}$ mass concentrations. Mean bias difference between $PM_{10}$ and lidar-derived mass concentrations estimated from June 2006 to December 2015 in Seoul is about $3{\mu}g\;m^{-3}$. Lidar ratio and aerosol mass extinction efficiency for each aerosol types will be developed and implemented into the KALION algorithm. More products, such as ice and water-droplet cloud discrimination, cloud base height, and boundary layer height will be produced by the KALION algorithm.