• Journal of Korean Society of Coastal and Ocean Engineers
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• v.30 no.2
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• pp.84-94
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• 2018

In order to overcome the limitation of deterministic forecast, an ensemble forecasting system for regional ocean wave is developed. This system predicts ocean wind waves based on the meteorological forcing from the Ensemble Prediction System for Global of the Korea Meteorological Administration, which is consisted of 24 ensemble members. The ensemble wave forecasting system is evaluated by using the moored buoy data around Korea. The root mean squared error (RMSE) of ensemble mean showed the better performance than the deterministic forecast system after 2 days, especially RMSE of ensemble mean is improved by 15% compared with the deterministic forecast for 3-day lead time. It means that the ensemble method could reduce the uncertainty of the deterministic prediction system. The Relative Operating Characteristic as an evaluation scheme of probability prediction was bigger than 0.9 showing high predictability, meaning that the ensemble wave forecast could be usefully applied.

• The Korean Journal of Applied Statistics
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• v.21 no.4
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• pp.705-716
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• 2008

The objectives of this study are the detection and forecast of climate change signal in the annual mean of surface temperature data, which are generated by MRI/JMA CGCM over the Korean Peninsula. MRI/JMA CGCM outputs consist of control run data(experiment with no change of $CO_2$ concentration) and scenario run data($CO_2$ 1%/year increase experiment to quadrupling) during 142 years for surface temperature and precipitation. And ECMWF reanalysis data during 43 years are used as observations. All data have the same spatial structure which consists of 42 grid points. Two statistical models, the Bayesian fingerprint method and the regression model with autoregressive error(AUTOREG model), are separately applied to detect the climate change signal. The forecasts up to 2100 are generated by the estimated AUTOREG model only for detected grid points.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.45 no.2
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• pp.106-113
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• 2017

Attitude determination algorithms for aircraft and land vehicles use earth gravitational vector and geomagnetic vector; hence, magnetometers and accelerometers are employed. In dynamic situation, the output from accelerometers includes not only gravitational vector but also motional acceleration, thus it is hard to determine accurate attitude. The acceleration compensation method treated in this paper solves the problem to compensate the specific force vector for motional acceleration calculated by a GPS receiver. This paper analyzed the error from the corrected vector regarded as a constant by conventional acceleration compensation method, and improve the error by rederivation from measurements. The analyzed error factors and improvements by the proposed algorithm are verified by computer simulations.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.34-34
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• 2011

최근 우리나라에서는 기상이변과 기후변화에 의한 국지성 집중호우의 발생으로 인해 인명 및 재산 피해가 증가하는 추세이다. 따라서 이러한 기상현상을 좀 더 정확하게 예측하고 이를 대응하고자 악기상 모형의 개발과 구축 및 활용에 대한 연구들이 활발하게 진행 중에 있다. GCM이 제공하고 있는 많은 유용한 정보에도 불구하고 대부분의 모델이 시 공간 분해능과 물리 과정의 한계점으로 인해 지역적인 기후 특성이나 변화를 예측하기에는 많은 문제점들이 나타나고 있다. GCM의 한계점을 극복하기 위한 방법으로 세밀한 규모의 기후 정보를 얻기 위해 복잡한 지형과 해안선, 호수, 식생, 지표특성과 같은 아격자 규모의 강제 효과를 반영할 수 있는 고해상도 지역 기후 모델(Regional Climate Model, RCM)의 필요성이 제기되었다. 본 연구에서는 전지구 20km 격자자료를 입력장으로 하여 8km 격자로 한반도를 포함하는 도메인에 대해 비정역학 완전 압축성 중규모 모델인 WRF를 이용하여 상세예측자료를 생산하고자 하였다. 강수 예측의 경우 돌발적으로 발생하는 경우가 많아, 이를 예측하기 위해서는 상세한 강수량 정보를 빠른 시간 내에 정확히 제공할 수 있는 모델을 사용하여야 한다. 강수의 경우 온도와는 달리 공간적 편차가 매우 커 지역적으로 정확한 강수량을 예측 하는데 어려움이 있다. 상세강수 예측을 위해 미세 격자 규모의 비 정역학 모형을 사용할 경우 계산양이 매우 늘어나기 때문에 장시간의 모형 적분 시간뿐 아니라, 상당한 컴퓨터 자원을 필요로 하므로 이에 대한 대안으로 지형효과를 포함한 강수량 진단 모형인 QPM(Quantitative Precipitation Model)을 사용하였다. 최종적으로 한반도의 복잡한 지형적 영향을 반영하기 위해 1 km의 수평해상도를 가지는 고해상도 강수량 진단 모형(QPM)과 상세한 지리적, 공간적 분석을 할 수 있는 ARCGIS를 이용하여 한반도 도별 상세 강수자료를 생산하고자 한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.73-74
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• 2019

We are developing a receiver that integrates eLoran and GNSS for navigation. The receiver shows similar performance to LORADD receiver in single navigation using Loran-C. In the case of GNSS navigation, the receiver uses GPS and GLONASS or GPS and BDS, so it has better navigation performance than the LORADD receiver using only GPS. Therefore, it is possible to expect better performance than the LORADD receiver in the integrated navigation which can complete the time synchronization between the chains later and obtaion the TOA. Loran data channel decoding function is implemented for eLoran navigation and the function of eliminating error factors such as interference is being implemented.

• Ocean and Polar Research
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• v.28 no.3
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• pp.245-258
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• 2006

We investigated seasonal variations of the upper ocean temperature and the mixed layer depth (MLD) in an eddy-permitting global ocean general circulation model (OGCM) to assess the OGCM perfermance. The OGCM is based on the GFDL MOM3 which has a horizontal resolution of 0.5 degree and 30 vertical levels. The OGCM was integrated for 68 years using a monthly-mean climatological wind stress forcing. The model sea surface temperature (SST) and sea surface salinity were restored to the Levitus climatology with a time scale of 30 days. Annual-mean model SST shows a cold bias $(<\;-2^{\circ}C)$ in the summer hemisphere and a warm bias $(>\;1^{\circ}C)$ in the winter hemisphere mainly due to the restoring boundary condition of temperature. The model MLD captures well the observed features in most areas, with a slightly deep bias. However, in the Ross Sea and Weddell Sea, the model shows significantly deeper MLD than the climatology-mainly due to weak salinity stratifications in the model. For amplitude of seasonal variation, the model SST is smaller $(1{\sim}3^{\circ}C)$ than the observation largely due to the restoring surface boundary condition while the model MLD has larger seasonal variation $({\sim}50m)$. It is suggested that for more realistic simulation of the upper ocean structure in the present eddy-permitting ocean model, more refinements in the surface boundary condition for the thermohaline forcing and parameterization for vertical mixing are required, together with the incorporation of a sea-ice model.

• 한국신재생에너지학회:학술대회논문집
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• 2011.11a
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• pp.87.2-87.2
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• 2011

Many type of fuel cell stacks have been developed to improve the efficiency of reactants usage. The cascade type fuel cell stack using dead end operation is able to attain above 99% usage of hydrogen and oxygen. It is sectionalized to several parts and the residual reactants which are used previous parts would be supplied again to next parts which have less number of cells in dead end operation stack. The oversupply of reactants which is usually 120%~150% of the theoretical amount to generate current for preventing the flooding effect could be provided to each part except the last one. The final section which is called monitoring cells is supposed to be supplied insufficient the fuel or oxidant that would have some accumulated inert gas from former parts. It makes some voltage drop in the part and the fresh reactants must be supplied to the part for recovering it by venting the residual gas. So the usage of fuel and oxidant is depend on the time and frequency of opening valves for venting of residual gas and it is important to optimize the vent logic for achieving higher usage of hydrogen and oxygen. In this research, many experiments are performed to find optimal condition by evaluating the effect of time and frequency under several power conditions using over 100kW class fuel cell module. And the characteristics of the monitoring cells are studied to know the proper cell voltage which decide the condition of opening the vent valve for stable performance of the cascade type fuel cell module.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.3
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• pp.303-310
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• 2009

We processed seven years data of 142 IGS(International GNSS Service) stations were processed, which have been selected with an optimal network algorithm, to realize terrestrial reference system. To verify the result, a comparison with the ITRF2005 was given both in positions and velocities with transformation parameters estimation. The transformation parameters are within 4.3 mm in length, while the RMS(root mean square) difference of positions and velocities are 6.7 mm and 1.3 mm/yr in horizontal and 13.3 mm and 2.4 mm/yr in vertical, respectively, which represent good coincidences with ITRF2005. This research would help developing our own geodetic reference frame and may be applied for the global earth observations such as the global tectonics. A further improved TRF would be expected by applying various data processing strategies and with extension of data in number and observation period.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.5
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• pp.459-466
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• 2012

The ionospheric delay is the largest error source in GPS positioning after the SA effect has been turned off. The ionospheric error can be easily removed by using ionospheric-free combinations but it is only restricted for dual-frequency receivers. Therefore, in this study, the regional ionospheric grid model was developed for single-frequency receivers. The developed model was compared with GIM to validate its accuracy. As a result, it yielded RMSE of 3.8 TECU for 10 days. And L1 medium- and long-range relative positioning was performed to evaluate positioning accuracy improvements. The positioning accuracy was improved by 46.7% compared with that without any correction of ionosphere and troposphere and was improved by 14.5% compared with that only tropospheric correction.

• Atmosphere
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• v.30 no.2
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• pp.155-167
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• 2020

In order to produce more detailed and accurate information of river discharge and freshwater discharge, global high-resolution hydrodynamic model (CaMa-Flood) is applied to an operational land surface model of global seasonal forecast system. In addition, bias correction to grid runoff for the hydrodynamic model is attempted. CaMa-Flood is a river routing model that distributes runoff forcing from a land surface model to oceans or inland seas along continentalscale rivers, which can represent flood stage and river discharge explicitly. The runoff data generated by the land surface model are bias-corrected by using composite runoff data from UNH-GRDC. The impact of bias-correction on the runoff, which is spatially resolved on 0.5° grid, has been evaluated for 1991~2010. It is shown that bias-correction increases runoff by 30% on average over all continents, which is closer to UNH-GRDC. Two experiments with coupled CaMa-Flood are carried out to produce river discharge: one using this bias correction and the other not using. It is found that the experiment adapting bias correction exhibits significant increase of both river discharge over major rivers around the world and continental freshwater discharge into oceans (40% globally), which is closer to GRDC. These preliminary results indicate that the application of CaMa-Flood as well as bias-corrected runoff to the operational global seasonal forecast system is feasible to attain information of surface water cycle from a coupled suite of atmospheric, land surface, and hydrodynamic model.