• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.26 no.3
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• pp.254-264
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• 1990

Using the meteorological data, surface weather map, and oceanographic data for 5 years(1984-1988). I investigated the characteristics of the fog occurrence and the role of the inshore in Pusan about the fog occurrence. And the meteorological data and sea surface temperature(SST), which were observed in July, 1989 in Suyoung Bay, were compared with those in Pusan. The fogs in Pusan concentrate in May, June and July. And at fog occurrence time the principal wind directions are Southwest(SW) winds, which easily supply with water vapor, and a series of Northeast(NE) wind. At the fog days pressure patterns are pattern 7 in spring time (March, April, and May) and pattern 10 and pattern 13 in summer time (June, July, and August). Also the advection fog(sea fog) is closely related with the relationship between warm and cold advection in 850~700mb and cold and warm SST rather than the increase of the instability of atmosphere in 850~500mb. The fogs in Taegu, which is the inland region, mainly occur at dawn in fall time due to the strong night radiation fog. On the other hand in Pusan the coastal region, the fogs occur from late spring time to summer time (May, June, and July). Because there is the abundant supply of the water vapor from the ocean owing to a series of South(S) wind at this time. Then the atmosphere, which has high relative humidity, reaches easily the supersaturation by the radiation cooling. In Suyoung Bay and Pusan the meteorological observation data, SST and fog days are almost similar. And I think that the mechanism of the fog occurrence nearly accords with both regions.

• Journal of Korea Water Resources Association
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• v.39 no.10 s.171
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• pp.823-832
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• 2006

Precipitation is the most important component to the study of water and energy cycle in hydrology. In this study we investigate rainfall retrieval uncertainty from different sources of remotely sensed precipitation field and then probable error propagation in the simulation of hydrologic variables especially, runoff on different vegetation cover. Two remotely sensed rainfall retrievals (space-borne IR-only and ground radar rainfall) are explored and compared visually and statistically. Then, an offline Community Land Model (CLM) is forced with in situ meteorological data to simulate the amount of runoff and determine their impact on model predictions. A fundamental assumption made in this study is that CLM can adequately represent the physical land surface processes. Results show there are big differences between different sources of precipitation fields in terms of the magnitude and temporal variability. The study provides some intuitions on the uncertainty of hydrologic prediction via the interaction between the land surface and near atmosphere fluxes in the modelling approach. Eventually it will contribute to the understanding of water resources redistribution to the climate change in Korean Peninsula.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.925-939
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• 2018

Absorbed shortwave radiation at the surface is an important component of energy analysis among the atmosphere, land, and ocean. In this study, the absorbed shortwave radiation was calculated using a radiation model and surface broadband albedo data for application to Geostationary Earth Orbit Korea Multi-Purpose SATellite (GEO-KOMPSAT-2A; GK-2A). And the results (GWNU algorithm) were compared with CERES data and calculation results using pyranometer and MODIS (Moderate Resolution Imaging Spectroradiometer) data to be selected as the reference absorbed shortwave radiation. This GWNU algorithm was also compared with the physical and statistical algorithms of GOSE-R ABI and two algorithms (Li et al., 1993; Kim and Jeong, 2016) using regression equation. As a result, the absorbed shortwave radiation calculated by GWNU algorithm was more accurate than the values calculated by the other algorithms. However, if the problem about computing time and accuracy of albedo data arise when absorbed shortwave radiation is calculated by GWNU algorithm, then the empirical algorithms explained above should be used with GWNU algorithm.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6B
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• pp.597-603
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• 2006

The purpose of this study is to improve the short term rainfall forecast skill using neural network model that can deal with the non-linear behavior between satellite data and ground observation, and minimize the flood damage. To overcome the geographical limitation of Korean peninsula and get the long forecast lead time of 3 to 6 hour, the developed rainfall forecast model took satellite imageries and wide range AWS data. The architecture of neural network model is a multi-layer neural network which consists of one input layer, one hidden layer, and one output layer. Neural network is trained using a momentum back propagation algorithm. Flood was estimated using rainfall forecasts. We developed a dynamic flood inundation model which is associated with 1-dimensional flood routing model. Therefore the model can forecast flood aspect in a protected lowland by levee failure of river. In the case of multiple levee breaks at main stream and tributaries, the developed flood inundation model can estimate flood level in a river and inundation level and area in a protected lowland simultaneously.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.215-231
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• 2020

Forest landscape models (FLMs) can be used to investigate the complex interactions of various ecological processes and patterns, which makes them useful tools to evaluate how environmental and anthropogenic variables can influence forest ecosystems. However, due to the large spatio-temporal scales in FLMs studies, parameterization and validation can be extremely challenging when applying to new study areas. To address this issue, we focused on the parameterization and application of a spatially explicit forest landscape model, LANDIS-II, to Mt. Gyebang, South Korea, with the use of the National Forest Inventory (NFI) and long-term ecological research (LTER) site data. In this study, we present the followings for the biomass succession extension of LANDIS-II: 1) species-specific and spatial parameters estimation for the biomass succession extension of LANDIS-II, 2) calibration, and 3) application and validation for Mt. Gyebang. For the biomass succession extension, we selected 14 tree species, and parameterized ecoregion map, initial community map, species growth characteristics. We produced ecoregion map using elevation, aspect, and topographic wetness index based on digital elevation model. Initial community map was produced based on NFI and sub-alpine survey data. Tree species growth parameters, such as aboveground net primary production and maximum aboveground biomass, were estimated from PnET-II model based on species physiological factors and environmental variables. Literature data were used to estimate species physiological factors, such as FolN, SLWmax, HalfSat, growing temperature, and shade tolerance. For calibration and validation purposes, we compared species-specific aboveground biomass of model outputs and NFI and sub-alpine survey data and calculated coefficient of determination (R²) and root mean square error (RMSE). The final model performed very well, with 0. 98 R² and 8. 9 RMSE. This study can serve as a foundation for the use of FLMs to other applications such as comparing alternative forest management scenarios and natural disturbance effects.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.908-908
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• 2012

국내 기후 특성상 하절기에 집중되는 강우로 인해 댐의 건설을 홍수조절, 용수확보 및 전력생산 등의 목적에 있어서 불가피하다. 이와 같은 저수지와 하류하천은 댐 수문 개폐에 따라 흐름변화로 인하여 수체의 거동 및 수질 변화가 발생하며, 일반적인 하천과는 다른 특성을 지니게 된다. 또한 수심이 깊은 저수지의 경우에는 흐름방향과 더불어 수심 방향의 특성도 중요하며, 수리 및 수질 모형의 연계를 통한 3차원적인 해석을 필요로 한다. 유역 내 지상 또는 대기에서 발생한 모든 오염물질은 강우에 의해 하천과 호수와 같은 수체로 유입되며, 강우가 발생했을 때 유역의 토지피복 상태와 수리, 지형, 강우강도, 토양의 특성에 의해 하천으로 유입되는 오염물질의 농도와 부하특성이 달라진다. 비점오염물질의 축적이 가능한 호수나 저수지에서는 비점오염원의 유입이 더 큰 문제가 되며, 유량이 극히 미미한 하천의 경우에는 강우초기에 일시에 집중적으로 유입되는 초기 오염 부하량이 문제가 된다. 강우유출수의 하천 유입은 강우 현상과 밀접한 관계를 맺고 있으므로 그 제어가 쉽지 않다. 이러므로 이를 총괄하는 유역통합관리기술이 필요로 하며, 기존의 유역통합관리기술은 댐 상류유역을 중심으로 개발되고 있으며, 댐 상류유역과 저수지, 하류하천으로 구분되어 연구되어 왔다. 또한 각각의 모형이 개별적으로 적용되어 통합적인 평가시스템이 표준화되지 않은 관계로 댐 상하류 모니터링 자료가 연계된 실무 적용이 이루어지지 않고 있다. 따라서 하천 수리 수문학적 역학구조를 이해하고 그 특성에 적합하게 평가할 수 있는 표준화된 시스템이 구축되어야 한다. 또한 효과적인 유역통합관리를 위해서는 하천의 현재 뿐만 아니라 장래에 대한 예측부분도 포함되어야 한다. 본 연구에서는 댐 유역에서의 유출과 수질 변화를 모의하고 이를 이용하여 저수지 내에서의 오염물질 거동에 대해서 해석하였다. 또한 기후변화에 따른 유역, 저수지 및 하천에 미치는 영향을 고려하기 위하여 고해상도 지역기후전망 모의자료를 이용하여 수문학적 스케일로 통계적 상세화한 후 지역별 상세수문시나리오를 생산하여 미래 예측에 활용하였다. 기후변화 시나리오의 상세화를 통한 상세지역의 기후를 예측하고, 예측된 기상자료를 이용하여 유역모델을 모의하여 미래의 유출 및 수질 변화를 파악할 수 있는 기술 개발로 인해 저수지의 운영에 도움을 주고, 주수지의 치수증대 사업 등 유출의 변화에 따른 하류하천 변화를 파악할 수 있고, 기후변화에 따른 하류하천에 대한 홍수기 때 치수, 이수 및 방재에 대하여 기초자료를 제공할 수 있을 것으로 판단된다.

• Journal of the Korean earth science society
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• v.43 no.6
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• pp.691-711
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• 2022

The state-of-the-art Earth system model as a virtual Earth is required for studies of current and future climate change or climate crises. This complex numerical model can account for almost all human activities and natural phenomena affecting the atmosphere of Earth. The Unified Model (UM) from the United Kingdom Meteorological Office (UK Met Office) is among the best Earth system models as a scientific tool for studying the atmosphere. However, owing to the expansive numerical integration cost and substantial output size required to maintain the UM, individual research groups have had to rely only on supercomputers. The limitations of computer resources, especially the computer environment being blocked from outside network connections, reduce the efficiency and effectiveness of conducting research using the model, as well as improving the component codes. Therefore, this study has presented detailed guidance for installing a new version of the UM on high-performance parallel computers (Linux clusters) owned by individual researchers, which would help researchers to easily work with the UM. The numerical integration performance of the UM on Linux clusters was also evaluated for two different model resolutions, namely N96L85 (1.875° ×1.25° with 85 vertical levels up to 85 km) and N48L70 (3.75° ×2.5° with 70 vertical levels up to 80 km). The one-month integration times using 256 cores for the AMIP and CMIP simulations of N96L85 resolution were 169 and 205 min, respectively. The one-month integration time for an N48L70 AMIP run using 252 cores was 33 min. Simulated results on 2-m surface temperature and precipitation intensity were compared with ERA5 re-analysis data. The spatial distributions of the simulated results were qualitatively compared to those of ERA5 in terms of spatial distribution, despite the quantitative differences caused by different resolutions and atmosphere-ocean coupling. In conclusion, this study has confirmed that UM can be successfully installed and used in high-performance Linux clusters.

• Korean Journal of Remote Sensing
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• v.33 no.5_1
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• pp.607-615
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• 2017

The aerosol optical thickness data retrieved by Moderate Resolution Imaging Spectrometer (MODIS) of Terra & Aqua and Meteorological Imager (MI) of Communication Ocean and Meteorological Satellite (COMS) are analyzed and compared with the measurement data of Aerosol Robotic Network (AERONET) in Northeast Asia. As the result, the aerosol optical thickness retrieved by MODIS and MI were well agreed at ocean region but quite different at cloud edge and barren surface. The reason was that MODIS aerosol optical thickness was retrieved using the visible and infrared channels but MI was retrieved with the visible channel only. Consequentially, the thin cloud be misinterpreted as aerosol by MI and the difference between MODIS and MI aerosol optical thicknesses could be occurred with Normal Distribution Vegetation Index (NDVI) and land surface property. Therefore, the accuracies of clear/cloud region and surface reflectivity are required in order to improve the aerosol optical thickness algorithm by MI.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.483-492
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• 2017

Precipitation is one of key components in hydrological modeling and water balance studies. A comprehensive, optimized and sustainable water balance monitoring requires the availability of accurate precipitation data. The amount of precipitation measured in a gauge is less than the actual precipitation reaching the ground. The objective of this study is to determine the wind-induced under-catch of solid precipitation and develop a continuous adjustment function for measurements of all types of winter precipitation (from rain to dry snow), which can be used for operational measurements based on data available at standard automatic weather stations. This study provides Bayesian analysis for the systematic structure of catch ratio in precipitation measurement.

• Journal of Korea Water Resources Association
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• v.42 no.11
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• pp.1017-1028
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• 2009

NSRPM (Neyman-Scott Rectangular Pulse Model) is one of the common model for generating future precipitation time series in stochastical hydrology. There are 5 parameters to compose the NSRPM model for generating precipitation time series. Generally parameter estimation using moment has some problems related with increased objective functions and shows different results in accordance with random variable generating models. In this study, direct parameter estimation method was proposed to cover with disadvantages of parameter estimation using moment. To apply the direct parameter estimation, generating stochastical data variance in accordance with numbers of precipitation events of NSRPM was done. Both kinds of methods were applied at the Cheongju gauge station data. Precipitation time series were generated using 4 different random variable generator, and compared with observed time series to check the accuracies. As a results, direct method showed more stable and better results.