• Title/Summary/Keyword: Reanalysis Method

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Improvement of Soil Moisture Initialization for a Global Seasonal Forecast System (전지구 계절 예측 시스템의 토양수분 초기화 방법 개선)

  • Seo, Eunkyo;Lee, Myong-In;Jeong, Jee-Hoon;Kang, Hyun-Suk;Won, Duk-Jin
    • Atmosphere
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    • v.26 no.1
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    • pp.35-45
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    • 2016
  • Initialization of the global seasonal forecast system is as much important as the quality of the embedded climate model for the climate prediction in sub-seasonal time scale. Recent studies have emphasized the important role of soil moisture initialization, suggesting a significant increase in the prediction skill particularly in the mid-latitude land area where the influence of sea surface temperature in the tropics is less crucial and the potential predictability is supplemented by land-atmosphere interaction. This study developed a new soil moisture initialization method applicable to the KMA operational seasonal forecasting system. The method includes first the long-term integration of the offline land surface model driven by observed atmospheric forcing and precipitation. This soil moisture reanalysis is given for the initial state in the ensemble seasonal forecasts through a simple anomaly initialization technique to avoid the simulation drift caused by the systematic model bias. To evaluate the impact of the soil moisture initialization, two sets of long-term, 10-member ensemble experiment runs have been conducted for 1996~2009. As a result, the soil moisture initialization improves the prediction skill of surface air temperature significantly at the zero to one month forecast lead (up to ~60 days forecast lead), although the skill increase in precipitation is less significant. This study suggests that improvements of the prediction in the sub-seasonal timescale require the improvement in the quality of initial data as well as the adequate treatment of the model systematic bias.

Dynamical Predictions of the Structural Connection by the Reduced Approach (축약법에 의한 구조물 결합부의 동적 거동 예측)

  • Yun, Seong-Ho
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.27 no.6
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    • pp.589-596
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    • 2014
  • Joints, fasteners or connected parts frequently have a significant effect on the dynamical behavior of assembled mechanical structures. Therefore, the analytical prediction of structural responses depends on the accuracy of joint modeling. This paper deals with the formulation and analysis of dynamic mechanism for joint flexibilities whose relevant magnitudes of stiffnesses are investigated by using linear and torsional springs. The equation of motion is derived by using a generic joint in the middle of clamped-clamped beam. A reanalysis due to changes in magnitudes of joint stiffnesses is based on the reduced analysis where the binomial series terms are used as basis vectors. The solution procedures are straightforward and the method can be readily used with a general finite element method. The computational effort needed by this approach is usually much smaller than the effort needed for complete vibration analysis. Two numerical examples show that accurate results are obtained efficiently by reducing the number of degree in the reduced model.

Development of a Deep Learning-based Midterm PM2.5 Prediction Model Adapting to Trend Changes (경향성 변화에 대응하는 딥러닝 기반 초미세먼지 중기 예측 모델 개발)

  • Dong Jun Min;Hyerim Kim;Sangkyun Lee
    • The Transactions of the Korea Information Processing Society
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    • v.13 no.6
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    • pp.251-259
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    • 2024
  • Fine particulate matter, especially PM2.5 with a diameter of less than 2.5 micrometers, poses significant health and economic risks. This study focuses on the Seoul region of South Korea, aiming to analyze PM2.5 data and trends from 2017 to 2022 and develop a mid-term prediction model for PM2.5 concentrations. Utilizing collected and produced air quality and weather data, reanalysis data, and numerical model prediction data, this research proposes an ensemble evaluation method capable of adapting to trend changes. The ensemble method proposed in this study demonstrated superior performance in predicting PM2.5 concentrations, outperforming existing models by an average F1 Score of approximately 42.16% in 2019, 58.92% in 2021, and 34.79% in 2022 for future 3 to 6-day predictions. The model maintains performance under changing environmental conditions, offering stable predictions and presenting a mid-term prediction model that extends beyond the capabilities of existing deep learning-based short-term PM2.5 forecasts.

Sensitivity Analysis of Dynamic Characteristics of Structural Systems by the Transfer Matrix Method and the Combined Finite Element-Transfer Matrix Method (전달매트릭스법 및 유한요소-전달매트릭스 결합방법에 의한 구조계의 동특성 감도해석)

  • D.S. Cho;K.C. Kim
    • Journal of the Society of Naval Architects of Korea
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    • v.29 no.1
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    • pp.143-157
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    • 1992
  • For the design of structural systems having the prescribed or optimum dynamic characteristics, some design changes of the initially designed system are required. In these cases, if the sensitivity analysis which can predict the changes of dynamic characteristics due to the changes of design variables is applied, the design changes can be carried out rationally and very efficiently. For many structural systems, it is well known that the analysis by the transfer matrix method(TMM) and the combined finite element-transfer matrix method(FETMM) is more efficient than the analysis by the finite element method. However, most known studies on the sensitivity analysis of structural systems premise using the finite element method. In this paper, the sensitivity analysis methods by the TMM and the FETMM are presented and some numerical investigations on the beam-column with elastically restrained ends and intermediate contraints and the stiffened plate having subsystems are carried out. The results of the numerical examples show good accuracy and computational efficiency of the presented methods, and show that the application of sensitivity analysis in the dynamic characteristic reanalysis give good results within the practically changeable range of design variables.

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Multi-Level Optimization of Framed Structures Using Automatic Differentiation (자동미분을 이용한 뼈대구조의 다단계 최적설계)

  • Cho, Hyo-Nam;Chung, Jee-Sung;Min, Dae-Hong;Lee, Kwang-Min
    • Journal of Korean Society of Steel Construction
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    • v.12 no.5 s.48
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    • pp.569-579
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    • 2000
  • An improved multi-level (IML) optimization algorithm using automatic differentiation (AD) of framed structures is proposed in this paper. For the efficiency of the proposed algorithm, multi-level optimization techniques using a decomposition method that separates both system-level and element-level optimizations, that utilizes and an artificial constraint deletion technique, are incorporated in the algorithm. And also to save the numerical efforts, an efficient reanalysis technique through approximated structural responses such as moments and frequencies with respect to intermediate variables is proposed in the paper. Sensitivity analysis of dynamic structural response is executed by AD that is a powerful technique for computing complex or implicit derivatives accurately and efficiently with minimal human effort. The efficiency and robustness of the IML algorithm, compared with a plain multi-level (PML) algorithm, is successfully demonstrated in the numerical examples.

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Wind Vector Retrieval from SIR-C SAR Data off the East Coast of Korea

  • Kim, Tai-Sung;Park, Kyung-Ae;Moon, Woo-Il
    • Journal of the Korean earth science society
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    • v.31 no.5
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    • pp.475-487
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    • 2010
  • Sea surface wind field was retrieved from high-resolution SIR-C SAR data by using CMOD algorithms off the east coast of Korea. In order to extract wind direction information from SAR data, a two-dimensional spectral analysis method was applied to the normalized radar cross section of the image. An $180^{\circ}$-ambiguity problem in the determination of wind direction was solved by selecting a direction nearest to the wind vector of the ECMWF reanalysis data. Comparison of the wind retrieval patterns with the ECMWF and NCEP/NCAR dataset showed RMS errors in the range of 1.30 to $1.72\;ms^{-1}$. In contrast, comparison of wind directions revealed large errors of greater than $60^{\circ}$, which is enormously higher than the permitted limit of about $20^{\circ}$ for satellite scatterometer winds. Compared with wind speed results from different algorithms, wind vectors based on commonly-used CMOD4 algorithm showed good agreement with those derived by other algorithms such as CMOD_IFR2 and CMOD5, particularly at medium winds from 4 to $8\;ms^{-1}$. However, apparent discrepancy appeared at low winds (< $4\;ms^{-1}$). This study also addressed an importance of accurate wind direction data to improve the accuracy of wind speed retrieval and discussed potential causes of wind retrieval errors from SAR data.

Characteristics of Sensible Heat and Latent Heat Fluxes over the East Sea Related with Yeongdong Heavy Snowfall Events (영동대설 사례와 관련된 동해상의 현열속과 잠열속 분포 특성)

  • Kim, Ji-Eon;Kwon, Tae-Yong;Lee, Bang-Yong
    • Ocean and Polar Research
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    • v.27 no.3
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    • pp.237-250
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    • 2005
  • To investigate the air mass modification related with Yeongdong Heavy snowfall events, we examined sensible and latent heat fluxes on the East Sea, the energy exchange between atmosphere and ocean in this study. Sensible and latent heats were calculated by a bulk aerodynamic method, in which NCEP/NCAR reanalysis data and NOAA/AVHRR weekly SST data with high resolution were used. Among winter precipitation events in the Yeongdong region, 19 heavy precipitation events $(1995{\sim}2001)$ were selected and classified into three types (mountain, cold-coastal, and warm types). Mountain-type precipitation shows highly positive anomalies of sensible and latent heats over the southwestern part of the East Set When separating them into the two components due to variability of wind and temperature/ specific Humidity, it is shown that the wind components are dominant. Cold-coastal-type precipitation also shows strong positive anomalies of sensible and latent heats over the northern part and over the central-northern part of the East Sea, respectively. It is shown that the sensible heat anomalies are caused mostly by the decrease of surface air temperature. So it can be explained that cold-coastal-type precipitation is closely related with the air mass modification due to cold air advection over warm ocean surface. But in warm-type precipitation, negative anomalies are found in the sensible and latent heat distributions. From this result, it may be postulated that warm-type precipitation is affected by the internal process of the atmosphere rather than the atmosphere-ocean interaction.

Assessment of Global Air Quality Reanalysis and Its Impact as Chemical Boundary Conditions for a Local PM Modeling System (전지구 대기질 재분석 자료의 평가와 국지규모 미세먼지 예보모델에 미치는 영향)

  • Lee, Kangyeol;Lee, Soon-Hwan;Kim, EunJi
    • Journal of Environmental Science International
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    • v.25 no.7
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    • pp.1029-1042
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    • 2016
  • The initial and boundary conditions are important factors in regional chemical transport modeling systems. The method of generating the chemical boundary conditions for regional air quality models tends to be different from the dynamically varying boundary conditions in global chemical transport models. In this study, the impact of real time Copernicus atmosphere monitoring service (CAMS) re-analysis data from the modeling atmospheric composition and climate project interim implementation (MACC) on the regional air quality in the Korean Peninsula was carried out using the community multi-scale air quality modeling system (CMAQ). A comparison between conventional global data and CAMS for numerical assessments was also conducted. Although the horizontal resolution of the CAMS re-analysis data is not higher than the conventionally provided data, the simulated particulate matter (PM) concentrations with boundary conditions for CAMS re-analysis is more reasonable than any other data, and the estimation accuracy over the entire Korean peninsula, including the Seoul and Daegu metropolitan areas, was improved. Although an inland area such as the Daegu metropolitan area often has large uncertainty in PM prediction, the level of improvement in the prediction for the Daegu metropolitan area is higher than in the coastal area of the western part of the Korean peninsula.

A Study on Uterine Leiomyoma Patients' Experience of Total Hysterectomy (자궁근종 환자의 자궁적출경험)

  • Cho, Hyeon-Ae;Kwon, Hye-Jin;Yeoum, Soon-Gyo
    • Women's Health Nursing
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    • v.5 no.3
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    • pp.349-361
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    • 1999
  • This study is designed to describe and analyze the experiences of hysterectomy. It also attempts to develop the practical theory of their experiences and thus suggest a fundamental frame that can help nurses broaden their clinical understanding of hysterectomy patients and take better care. The data was collected through interviewing the selected subjects. The subjects were five hysterectomy patients. They were interviewed at first hand by this researcher and recorded under their permissions. Each interview took one hour or two hours per interviewer. The data was collected through the interview. The method of "the Ground Theory" by Strauss & Corbin (1990) was used for data analysis. A total of 129 concepts were extracted from the data analysis. which were classified into 27 subcategories through reanalysis. The subcategories were grouped under 12 higher categories. During the process of the data analysis the following three propositions repeatedly appeared. (1) The higher importance of sexual life and pregnancy, the greater the patients' despair. The support system was not satisfied. The closed defense intensified their despair. They felt that the operation result was out of control. (2) The lower the importance of sexual life and pregnancy, the lesser the patients' despair. The support system proved to be highly satisfactory. As a result more favorably. (3) The lower physical change, the lesser importance of pregnancy. the lesser the patients' despair, the patients' thought turned out to be more positive, which, in turn, left the patients the less despaired. As a results the patients accept the operation result more favorably.

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Estimation of the optimal evapotranspiration by using satellite- and reanalysis model-based evapotranspiration estimations (인공위성과 재분석모델 자료의 다중 증발산 자료를 활용하여 최적 증발산 산정 연구)

  • Baik, Jongjin;Jeong, Jaehwan;Choi, Minha
    • 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.