• Journal of Korean Society of Coastal and Ocean Engineers
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• v.23 no.3
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• pp.236-247
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• 2011

This study investigates sea level (SL) rise due to global warming in the Northwestern Pacific (NWP) and Seas around the Korean peninsula (KP) using outputs of IPCC AR4 climate models. Particularly, components of the SL rise induced by a local steric effect, which was not considered in most climate models, were computed using model-projected 3-dimensional temperature and salinity data. Analysis of the SL data shows that the ratio of the SL rise in the NWP and KP was about two times higher than that in global mean and particularly the ratio in the Kuroshio extension region was the highest. The SL rises over 100 years estimated from MPI_ECHAM5 and GFDL_CM2.1 model by A1B scenario considering the thermosteric effect were 24 cm and 28 cm for the NWP and 27 cm and 31 cm for the Seas around the KP, respectively. Statistical analysis reveals that these SL rises are caused by the weakening of the Siberian High in winter as well as variations of pressure system in the NWP and by the resultant change of water temperature. It also found that the highest SL rise in the Kuroshio extension region of the NWP was connected with the large increase of water temperature in this area.

• Journal of Korea Water Resources Association
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• v.44 no.1
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• pp.51-64
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• 2011

The objective of this study is to develop a continuous rainfall-runoff model for flood prediction on a large-scale basin. For this study, the hourly surface runoff estimation method based on the variable retention parameter and runoff curve number is developed. This model is composed that the soil moisture to continuous rainfall can be simulated with applying the hydrologic components to the continuous equation for soil moisture. The runoff can be simulated by linking the hydrologic components with the storage function model continuously. The runoff simulation to large basins can be performed by using channel storage function model. Nakdong river basin is selected as the study area. The model accuracy is evaluated at the 8 measurement sites during flood season in 2006 (calibration period) and 2007~2008 (verification period). The calibrated model simulations are well fitted to the observations. Nash and Sutcliffe model efficiencies in the calibration and verification periods exist in the range of 0.81 to 0.95 and 0.70 to 0.94, respectively. The behavior of soil moisture depending on the rainfall and the annual loadings of simulated hydrologic components are rational. From this results, continuous rainfall-runoff model developed in this study can be used to predict the discharge on large basins.

• Journal of Wetlands Research
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• v.20 no.1
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• pp.80-93
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• 2018

Research trend about nonpoint pollution source(NPS) that have studied since 1980 was divided into 4 categories: 1) runoff characteristics of NPS, 2) treatment technique, 3) LID and green infrastructure(GI), 4) management practices and policy. This study reviews them and recommends the future research direction. The research on runoff characteristics of NPS until 2010 was mainly carried out. But recently, many researchers has been conducting studies on technology development, effect evaluation and field application. Providing best measures on NPS should be tried to conduct studies that many fields such as society, geography, meteorology and environment are fused. But it has not been enough yet. Because the cause material and optimum measures of NPS are different from each other regionally, it is considered that it needs studies to prepare measures and guidelines with regional characteristics rather than a uniform measures and guidelines by the central government. In addition, more comprehensive studies must be carried out to establish rules and regulations to manage NPS not only by government sector but also the private sector.

• Journal of Korea Water Resources Association
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• v.40 no.2 s.175
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• pp.171-182
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• 2007

In this study, as a method for decreasing the confidence interval of the estimates of Clark hydrograph's concentration time and storage coefficient, regression equations of these parameters with respect to those of rainfall, meteorology, and basin characteristics are derived and analyzed using the Monte Carlo simulation technique. The results are also reviewed by comparing them with those derived by applying the Bootstrap technique and empirical equations. Results derived from this research are summarized as follows. (1) Even in case of limited rainfall events are available, it is possible to estimate the mean runoff characteristics by considering the affecting factors to runoff characteristics. (2) It is also possible to use the Monte Carlo simulation technique for estimating and evaluating the confidence intervals for concentration time and storage coefficient. The confidence intervals estimated in this study were found much narrower than those of Yoo et al. (2006). (3) A supporting result could also be derived using the Bootstrap technique. However, at least 20 independent rainfall events are necessary to get a rather significant result for concentration time and storage coefficient. (4) No empirical equations are found to be properly applicable for the study basin. However, empirical equations like the Kraven(I) and Kraven(II) are found valid for the estimation of concentration time, on the other hand the Linsley is found valid for the storage coefficient In this study basin. But users of these empirical formula should be careful as these also provide a wide range of possible values.

• Korean Journal of Remote Sensing
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• v.23 no.4
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• pp.297-309
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• 2007

The first Korean geostationary weather satellite, Communications, Oceanography and Meteorology Satellite (COMS) will be launched in 2008. The ground station for COMS needs to perform geometric correction to improve accuracy of satellite image data and to broadcast geometrically corrected images to users within 30 minutes after image acquisition. For such a requirement, we developed automated and fast geometric correction techniques. For this, we generated control points automatically by matching images against coastline data and by applying a robust estimation called RANSAC. We used GSHHS (Global Self-consistent Hierarchical High-resolution Shoreline) shoreline database to construct 211 landmark chips. We detected clouds within the images and applied matching to cloud-free sub images. When matching visible channels, we selected sub images located in day-time. We tested the algorithm with GOES-9 images. Control points were generated by matching channel 1 and channel 2 images of GOES against the 211 landmark chips. The RANSAC correctly removed outliers from being selected as control points. The accuracy of sensor models established using the automated control points were in the range of $1{\sim}2$ pixels. Geometric correction was performed and the performance was visually inspected by projecting coastline onto the geometrically corrected images. The total processing time for matching, RANSAC and geometric correction was around 4 minutes.

• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.271-271
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• 2015

The Ecuadorian coast has two different climate regions. One is humid region where the annual rainfall is above 2000 mm and rain falls in almost all months of the year, and the other is dry region where the annual rainfall can fall below 50 mm and rainfall can be very seasonal. The agriculture is frequently limited by the seasons during the year and the availability of rainfall amounts. The corn fields in Ecuador are cultivated during the rainy season, due to this reason. The weather conditions for optimum development of corn growth require a monthly average rainfall of 120 mm to 140 mm and a temperature range of $22^{\circ}C{\sim}32^{\circ}C$ for the dry region, and a monthly average rainfall of 200 mm to 400 mm and a temperature range of $25^{\circ}C{\sim}30^{\circ}C$ for the humid area. The objective of this study is to predict how the weather conditions are going to change in corn fields of the coastal region of Ecuador in the future decades. For this purpose, this study selected six General Circulation Models (GCM) including BCC-CSM1-1, IPSL-CM5A-MR, MIROC5, MIROC-ESM, MIROC-ESM-CHEM, MRIC-CGC3 with different climate scenarios of the RCP 4.5, RCP 6.0, and RCP 8.5, and applied for the period from 2011 to 2100. The climate variables information was obtained from the INAMHI (National Institute of Meteorology and Hydrology) in Ecuador for the a base line period from 1986 to 2012. The results indicates that two regions would experience significant changes in rainfall and temperature compared to the historical data. In the case of temperature, an increment of $1^{\circ}C{\sim}1.2^{\circ}C$ in 2025s, $1.6^{\circ}C{\sim}2.2^{\circ}C$ in 2055s, $2.1^{\circ}C{\sim}3.5^{\circ}C$ in 2085s were obtained from the dry region while less increment were shown from the humid region with having an increment of $1^{\circ}C$ in 2025s, $1.4^{\circ}C{\sim}1.8^{\circ}C$ in 2055s, $1.9^{\circ}C{\sim}3.2^{\circ}C$ in 2085s. Significant changes in rainfall are also projected. The rainfall projections showed an increment of 8%~11% in 2025s, 21%~33% in 2055s, and 34%~70% in 2085s for the dry region, and an increment of 2%~10%, 14%~30% and 23%~57% in 2025s, 2055s and 2085s decade respectively for humid region.

• Korean Journal of Plant Taxonomy
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• v.36 no.1
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• pp.61-89
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• 2006

Algific talus slopes are local cold micro-environmental habitats where cool air escapes through vents and fissures of talus layer, and ice forms in summer. To access the phytogeographical significance and to develop the conservation strategy on vegetation of the algific talus, plant species composition on seven algific talus in South Korea was investigated. As a results, phytogeographically significant northern elements such as Cystopteris fragilis (L.) Bernh., Diplazium sibiricum (Turcz. ex Kunze) Sa.Kurata, Polypodium virginianum L., Vaccinium vitis-idaea L. and Hackelia deflexa (Wahlenb.) Opiz were distributed in these algific talus slopes (below $N37^{\circ}43^{\prime}$). In addition, subalpine species such as Woodsia subcordata Turcz, Rosa suavis willd., Clematis fusca var. coreana ($H.L{\acute{e}}v.$ & Vaniot) Nakai, Calamagrostis langsdorfii (Link) Trin. and Carex vaginata var. petersii (C.A.Mey.) Akiyama were also distributed as typical relictual species of these algific talus (less than alt. 400m). The algific talus slopes in Korean peninsular can be regarded as the insular refugia that northern plant species advanced southward during the latest glacial age have been isolated and adapted in some local microhabitats. Because the algific talus slopes as paleorefugia are very important in terms of phytogeography as well as meteorology ans geology, developments of strategies for in situ and ex situ conservation on these small isolated and threatened populations associated with the algific talus urgently needed.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.63-70
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• 2021

Generating a super-resolution meteological data by using a high-resolution deep neural network can provide precise research and useful real-life services. We propose a new technique of generating improved training data for super-resolution deep neural networks. To generate high-resolution meteorological data with domain specific knowledge, Lambert conformal conic projection and objective analysis were applied based on observation data and ERA5 reanalysis field data of specialized institutions. As a result, temperature and humidity analysis data based on domain specific knowledge showed improved RMSE by up to 42% and 46%, respectively. Next, a super-resolution generative adversarial network (SRGAN) which is one of the aritifial intelligence techniques was used to automate the manual data generation technique using damain specific techniques as described above. Experiments were conducted to generate high-resolution data with 1 km resolution from global model data with 10 km resolution. Finally, the results generated with SRGAN have a higher resoltuion than the global model input data, and showed a similar analysis pattern to the manually generated high-resolution analysis data, but also showed a smooth boundary.

• Journal of the Korean earth science society
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• v.40 no.2
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• pp.109-118
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• 2019

Cloud-aerosol interactions are considered to be one of the most important forcing mechanisms in the climate system. However, there is considerable disagreement on the magnitude and even on the sign of how aerosol perturbations affect cloud fraction and lifetime. Furthermore, aerosol effects on clouds and precipitation are not readily separable from the effects of meteorology. This review paper summarizes the study of precipitation susceptibility $S_o$, which qualifies how aerosol perturbations alter the magnitude of the precipitation rate (R) while minimizing the effects of macrophysical factors such as cloud depth (H) and liquid water path (LWP). The analysis shows that the precipitation susceptibility $S_o$ for the warm marine boundary layer clouds is insensitive to aerosol perturbations at low LWP (equivalently low H). However, R decreases as aerosols increase at intermediate LWP. This is because aerosols act as cloud seed and produce numerous small-sized particles, which impede the collision and coalescence process that leads to precipitation. At high LWP, $S_o$ decreases with increasing LWP as there are enough water contents in the clouds. The LWP or H dependent $S_o$ behavior differs depending on the predominant cloud physics processes in the clouds.

• Journal of the Korean earth science society
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• v.39 no.6
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• pp.533-544
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• 2018

Rainfall is one of the most important meteorological variables in meteorology, agriculture, hydrology, natural disaster, construction, and architecture. Recently, satellite remote sensing is essential to the accurate detection, estimation, and prediction of rainfall. In this study, the accuracy of Integrated Multi-satellite Retrievals for GPM (IMERG) product, a composite rainfall information based on Global Precipitation Measurement (GPM) satellite was evaluated with ground observation data in the inland of Korea. The Automatic Weather Station (AWS)-based rainfall measurement data were used for validation. The IMERG and AWS rainfall data were collocated and compared during one year from January 1, 2016 to December 31, 2016. The coastal regions and islands were also evaluated irrespective of the well-known uncertainty of satellite-based rainfall data. Consequently, the IMERG data showed a high correlation (0.95) and low error statistics of Bias (15.08 mm/mon) and RMSE (30.32 mm/mon) in comparison to AWS observations. In coastal regions and islands, the IMERG data have a high correlation more than 0.7 as well as inland regions, and the reliability of IMERG data was verified as rainfall data.