• Title/Summary/Keyword: continuous data assimilation

Search Result 16, Processing Time 0.025 seconds

CONTINUOUS DATA ASSIMILATION FOR THE THREE-DIMENSIONAL SIMPLIFIED BARDINA MODEL UTILIZING MEASUREMENTS OF ONLY TWO COMPONENTS OF THE VELOCITY FIELD

  • Anh, Cung The;Bach, Bui Huy
    • Journal of the Korean Mathematical Society
    • /
    • v.58 no.1
    • /
    • pp.1-28
    • /
    • 2021
  • We study a continuous data assimilation algorithm for the three-dimensional simplified Bardina model utilizing measurements of only two components of the velocity field. Under suitable conditions on the relaxation (nudging) parameter and the spatial mesh resolution, we obtain an asymptotic in time estimate of the difference between the approximating solution and the unknown reference solution corresponding to the measurements, in an appropriate norm, which shows exponential convergence up to zero.

CONTINUOUS DATA ASSIMILATION FOR THE THREE-DIMENSIONAL LERAY-α MODEL WITH STOCHASTICALLY NOISY DATA

  • Bui Kim, My;Tran Quoc, Tuan
    • Bulletin of the Korean Mathematical Society
    • /
    • v.60 no.1
    • /
    • pp.93-111
    • /
    • 2023
  • In this paper we study a nudging continuous data assimilation algorithm for the three-dimensional Leray-α model, where measurement errors are represented by stochastic noise. First, we show that the stochastic data assimilation equations are well-posed. Then we provide explicit conditions on the observation density (resolution) and the relaxation (nudging) parameter which guarantee explicit asymptotic bounds, as the time tends to infinity, on the error between the approximate solution and the actual solution which is corresponding to these measurements, in terms of the variance of the noise in the measurements.

Streamflow Forecast Model on Nakdong River Basin (낙동강유역 하천유량 예측모형 구축)

  • Lee, Byong-Ju;Bae, Deg-Hyo
    • Journal of Korea Water Resources Association
    • /
    • v.44 no.11
    • /
    • pp.853-861
    • /
    • 2011
  • The objective of this study is to assess Sejong University River Forecast (SURF) model which consists of a continuous rainfall-runoff model and measured streamflow assimilation using ensemble Kalman filter technique for streamflow forecast on Nakdong river basin. The study area is divided into 43 subbasins. The forecasted streamflows are evaluated at 12 measurement sites during flood season from 2006 to 2007. The forecasted ones are improved due to the impact of the measured streamflows assimilation. In effectiveness indices corresponding to 1~5 h forecast lead times, the accuracy of the forecasted streamflows with the assimilation approach is improved by 46.2~30.1% compared with that using only the rainfall-runoff model. The mean normalized absolute error of forecasted peak flow without and with data assimilation approach in entering 50% of the measured rainfall, respectively, the accuracy of the latter is improved about 40% than that of the former. From these results, SURF model is able to be used as a real-time river forecast model.

Development of Real-Time River Flow Forecasting Model with Data Assimilation Technique (자료동화 기법을 연계한 실시간 하천유량 예측모형 개발)

  • Lee, Byong-Ju;Bae, Deg-Hyo
    • Journal of Korea Water Resources Association
    • /
    • v.44 no.3
    • /
    • pp.199-208
    • /
    • 2011
  • The objective of this study is to develop real-time river flow forecast model by linking continuous rainfall-runoff model with ensemble Kalman filter technique. Andong dam basin is selected as study area and the model performance is evaluated for two periods, 2006. 7.1~8.18 and 2007. 8.1~9.30. The model state variables for data assimilation are defined as soil water content, basin storage and channel storage. This model is designed so as to be updated the state variables using measured inflow data at Andong dam. The analysing result from the behavior of the state variables, predicted state variable as simulated discharge is updated 74% toward measured one. Under the condition of assuming that the forecasted rainfall is equal to the measured one, the model accuracy with and without data assimilation is analyzed. The model performance of the former is better than that of the latter as much as 49.6% and 33.1% for 1 h-lead time during the evaluation period, 2006 and 2007. The real-time river flow forecast model using rainfall-runoff model linking with data assimilation process can show better forecasting result than the existing methods using rainfall-runoff model only in view of the results so far achieved.

The Effect of Radar Data Assimilation in Numerical Models on Precipitation Forecasting (수치모델에서 레이더 자료동화가 강수 예측에 미치는 영향)

  • Ji-Won Lee;Ki-Hong Min
    • Atmosphere
    • /
    • v.33 no.5
    • /
    • pp.457-475
    • /
    • 2023
  • Accurately predicting localized heavy rainfall is challenging without high-resolution mesoscale cloud information in the numerical model's initial field, as precipitation intensity and amount vary significantly across regions. In the Korean Peninsula, the radar observation network covers the entire country, providing high-resolution data on hydrometeors which is suitable for data assimilation (DA). During the pre-processing stage, radar reflectivity is classified into hydrometeors (e.g., rain, snow, graupel) using the background temperature field. The mixing ratio of each hydrometeor is converted and inputted into a numerical model. Moreover, assimilating saturated water vapor mixing ratio and decomposing radar radial velocity into a three-dimensional wind vector improves the atmospheric dynamic field. This study presents radar DA experiments using a numerical prediction model to enhance the wind, water vapor, and hydrometeor mixing ratio information. The impact of radar DA on precipitation prediction is analyzed separately for each radar component. Assimilating radial velocity improves the dynamic field, while assimilating hydrometeor mixing ratio reduces the spin-up period in cloud microphysical processes, simulating initial precipitation growth. Assimilating water vapor mixing ratio further captures a moist atmospheric environment, maintaining continuous growth of hydrometeors, resulting in concentrated heavy rainfall. Overall, the radar DA experiment showed a 32.78% improvement in precipitation forecast accuracy compared to experiments without DA across four cases. Further research in related fields is necessary to improve predictions of mesoscale heavy rainfall in South Korea, mitigating its impact on human life and property.

컨버전스 서비스의 MDS 동화정도가 서비스 선호와 지속적 사용에 미치는 영향에 관한 연구: 모바일 서비스의 제도화 관점에서

  • Lee, Sang-Hun;Jeong, Yu-Jeong;Lee, Ho-Geun;Park, Hyeon-Ji
    • 한국경영정보학회:학술대회논문집
    • /
    • 2008.06a
    • /
    • pp.35-51
    • /
    • 2008
  • This study is to investigate factors that affect preference to CMDS(convergence mobile data service) on institutionalization of MDS. A research model was proposed and subsequent hypotheses were empirically tested with partial least square (PLS) based on 400 responses from the users of CMDS(DMB: 200 / m-Banking: 200). It was learned that institutionalization of technology related building MDS was positively associated with assimilation of MDS(represent a institutionalization of MDS) rather than service quality and use gratification. It means that users decided use of MDS refereed from its level of assimilation to MDS channel. Also, attractiveness of alternatives to CMDS is negatively associated with continuous use of CMDS and preference to CMDS. Lastly, their association strength was partially moderated by the type of motivation for using CMDS.

  • PDF

Development of Realtime Dam's Hydrologic Variables Prediction Model using Observed Data Assimilation and Reservoir Operation Techniques (관측자료 동화기법과 댐운영을 고려한 실시간 댐 수문량 예측모형 개발)

  • Lee, Byong Ju;Jung, Il-Won;Jung, Hyun-Sook;Bae, Deg Hyo
    • Journal of Korea Water Resources Association
    • /
    • v.46 no.7
    • /
    • pp.755-765
    • /
    • 2013
  • This study developed a real-time dam's hydrologic variables prediction model (DHVPM) and evaluated its performance for simulating historical dam inflow and outflow in the Chungju dam basin. The DHVPM consists of the Sejong University River Forecast (SURF) model for hydrologic modeling and an autoreservoir operation method (Auto ROM) for dam operation. SURF model is continuous rainfall-runoff model with data assimilation using an ensemble Kalman filter technique. The four extreme events including the maximum inflow of each year for 2006~2009 were selected to examine the performance of DHVPM. The statistical criteria, the relative error in peak flow, root mean square error, and model efficiency, demonstrated that DHVPM with data assimilation can simulate more close to observed inflow than those with no data assimilation at both 1-hour lead time, except the relative error in peak flow in 2007. Especially, DHVPM with data assimilation until 10-hour lead time reduced the biases of inflow forecast attributed to observed precipitation error. In conclusion, DHVPM with data assimilation can be useful to improve the accuracy of inflow forecast in the basin where real-time observed inflow are available.

Molybdate Alters Sulfate Assimilation and Induces Oxidative Stress in White Clover (Trifolium repens L.)

  • Zhang, Qian;Lee, Bok-Rye;Park, Sang-Hyun;Jeong, Gi-Ok;Kim, Tae-Hwan
    • Journal of The Korean Society of Grassland and Forage Science
    • /
    • v.33 no.3
    • /
    • pp.153-158
    • /
    • 2013
  • Molybdenum (Mo) in rhizosphere influences sulfate assimilation as well as a number of other physiological aspects. In this study, the activity of key enzymes in sulfate assimilatory pathways, such as ATP sulfurylase (ATPs), adenosine 5'-phosphosulphate reductase (APR), as well as the responses of reactive oxygen species (ROS), were analyzed to elucidate the metabolic and physiological effects of external Mo supply to detached leaves of Trifolium repens L. Mo supply with a range from 1 mM to 40 mM depressed the activity of ATPs throughout the entire time course. In the leaves exposed to 1 mM Mo, a continuous decrease in the activity of ATPs was confirmed by Native-PAGE. The APR activity was also declined by Mo treatment. The accumulation of $H_2O_2$ and ${O_2}^{{\cdot}-}$ were not significant up to 10 mM Mo, whereas a remarked accumulation was detected under 40 mM Mo supply. The data suggest that an external supply of Mo has an inhibitory effect on sulfate assimilation, and induces oxidative stress only at an extremely high concentration.

Stochastic Continuous Storage Function Model with Ensemble Kalman Filtering (I) : Model Development (앙상블 칼만필터를 연계한 추계학적 연속형 저류함수모형 (I) : - 모형 개발 -)

  • Bae, Deg-Hyo;Lee, Byong-Ju;Georgakakos, Konstantine P.
    • Journal of Korea Water Resources Association
    • /
    • v.42 no.11
    • /
    • pp.953-961
    • /
    • 2009
  • The objective of this study is to develop a stochastic continuous storage function model for enhancement of an event-oriented watershed and channel storage function models which have been used as an official flood forecast model in Korea. For this study, soil moisture accounting component is added to the original storage function model and each hydrologic component, such as surface flow, subsurface flow, groundwater flow and actual evaportranspiration, is simulated as a function of soil water content. And also, ensemble Kalman filtering technique is used for real-time assimilation of measured streamflow from various stream locations in the watershed. Therefore the enhanced model will be able to simulate hydrologic components for long-term period without additional estimation of model parameters and to give more accurate and reliable results than those from the existing deterministic model due to the assimilation of measured streamflow data.

A Study on the Precursors of Aviation Turbulence via QAR Data Analysis (QAR 데이터 분석을 통한 항공난류 조기 인지 가능성 연구)

  • Kim, In Gyu;Chang, Jo Won
    • Journal of the Korean Society for Aviation and Aeronautics
    • /
    • v.26 no.4
    • /
    • pp.36-42
    • /
    • 2018
  • Although continuous passenger injuries and physical damages are repeated due to the unexpected aviation turbulence encountered during operations, there is still exist the limitation for preventing recurrence of similar events because the lack of real-time information and delay in technological developments regarding various operating conditions and variable weather phenomena. The purpose of this study is to compare and analyze the meteorological data of the aviation turbulence occurred and actual flight data extracted from the Quick Access Recorder(QAR) to provide some precursors that the pilot can identify aviation turbulence early by referring thru the flight instrumentation indications. The case applied for this study was recent event, a scheduled flight from Incheon Airport, Korea to Narita Airport, Japan that suddenly encountered turbulence at an altitude of approximately 14,000 feet during approach. According to the Korea Meteorological Administration(KMA)'s Regional Data Assessment and Prediction System(RDAPS) data, it was observed that the strong amount of vorticity in the rear area of jet stream, which existed near Mount Fuji at that time. The QAR data analysis shows significant changes in the aircraft's parameters such as Pitch and Roll angle, Static Air Temperature(SAT), and wind speed and direction in tens of seconds to minutes before encounter the turbulence. If the accumulate reliability of the data in addition and verification of various parameters with continuous analysis of additional cases, it can be the precursors for the pilot's effective and pre-emptive action and conservative prevention measures against aviation turbulence to reduce subsequent passenger injuries in the aviation operations.