• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.5
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• pp.473-478
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• 2013

In this paper, we develop the Heavy Rain Advisory Decision Model based on intelligent neuro-fuzzy algorithm RBFNNs by using KLAPS(Korea Local Analysis and Prediction System) Reanalysis data. the prediction ability of existing heavy rainfall forecasting systems is usually affected by the processing techniques of meteorological data. In this study, we introduce the heavy rain forecast method using the pre-processing techniques of meteorological data are in order to improve these drawbacks of conventional system. The pre-processing techniques of meteorological data are designed by using point conversion, cumulative precipitation generation, time series data processing and heavy rain warning extraction methods based on KLAPS data. Finally, the proposed system forecasts cumulative rainfall for six hours after future t(t=1,2,3) hours and offers information to determine heavy rain advisory. The essential parameters of the proposed model such as polynomial order, the number of rules, and fuzzification coefficient are optimized by means of Differential Evolution.

• Journal of Integrative Natural Science
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• v.4 no.4
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• pp.298-310
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• 2011

Recently the traffics and transportation hazzards by fog are tremendously Increased. There occurred the greater traffic disaster by Dense Fog of Oct.2006. In this study frequent occurrences of advection fogs centerd over Honam Prov are investigated. Increment of transportation during the Fog period for 1996~2005(decade)are statistically analyzed with Honam Prov.'s fogs. For Honam west coast(Gunsan, Mokpo), inland of Honam(Junju, Gwangju, Suncheon), Honam south coast(Wando, Yepsu), Wind, Dew point, Diff. of air and sea temp. relative humidity are classified between 12 hours before and on time of fog with three Dimensional Analysis System(KLAPS). High frequencies of advection-radiation Fog occurrence in western Coasts except for Suncheon. The application of fog characteristics analyzed by KLAPS for denser fog over the western coast in Fall to Fog prediction and special advisory issues. The advection-radiation fog can occure favorably when the moisture index is less than $2^{\circ}C$, relative humidity is greater than 90%, but the moisture depth is under 1.5 km. In addition when the height of 925 hPa is rising, then fog occurs, but for sinking is disappearing.

• Atmosphere
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• v.22 no.4
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• pp.387-400
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• 2012

This study aims at examining the sensitivity of numerical simulations to the resolution of initial and boundary data, and to an application of WRF (Weather Research and Forecasting) 3DVAR (Three Dimension Variational data Assimilation). To do this, we ran the WRF model by using GDAS (Global Data Assimilation System) FNL (Final analyses) and the KLAPS (Korea Local Analysis and Prediction System) analyses as the WRF's initial and boundary data, and by using an initial field made by assimilating the radar data to the KLAPS analyses. For the sensitivity experiment, we selected a heavy rainfall case of 21 September 2010, where there was localized torrential rain, which was recorded as 259.5 mm precipitation in a day at Seoul. The result of the simulation using the FNL as initial and boundary data (FNL exp) showed that the localized heavy rainfall area was not accurately simulated and that the simulated amount of precipitation was about 4% of the observed accumulated precipitation. That of the simulation using KLAPS analyses as initial and boundary data (KLAPC exp) showed that the localized heavy rainfall area was simulated on the northern area of Seoul-Gyeonggi area, which renders rather difference in location, and that the simulated amount was underestimated as about 6.4% of the precipitation. Finally, that of the simulation using an initial field made by assimilating the radar data to the KLAPS using 3DVAR system (KLAP3D exp) showed that the localized heavy rainfall area was located properly on Seoul-Gyeonggi area, but still the amount itself was underestimated as about 29% of the precipitation. Even though KLAP3D exp still showed an underestimation in the precipitation, it showed the best result among them. Even if it is difficult to generalize the effect of data assimilation by one case, this study showed that the radar data assimilation can somewhat improve the accuracy of the simulated precipitation.

• 한국지구과학회:학술대회논문집
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• 2010.04a
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• pp.95-97
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• 2010

최근 겨울철 온난화 경향이 뚜렷해지면서 강수형태가 비로 내리는 경우가 잦아지고 있다. 또한 대륙고기압이 확장할 때는 기압골의 영향으로 강우에서 강설로 변하는 예가 종종 나타나고 있다. 강수유형의 판단은 겨울철 중요한 예보요소 중 하나로 본 연구는 중서부지방의 2010년 2월 4일부터 12일까지의 사례기간동안 일기도, AWS관측자료, 위성, KLAPS(층후, 빙결고도, 상당온위) 자료를 바탕으로 하여 강우에서 강설로 변하는 강수형태를 분석한 것이다.

• Journal of Environmental Science International
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• v.18 no.11
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• pp.1271-1281
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• 2009

The heavy snowfall event over the eastern part of Seoul, Korea on Mar. 04, 2008 has been abruptly occurred after the frontal system with the heavy snowfall event had been past over the Korean peninsula on Mar. 03, 2008. Therefore, this heavy snowfall event couldn't be predicted well by any means of theoretical knowledges and models. After the cold front passed by, the cold air mass was flown over the peninsula immediately and became clear expectedly except the eastern part and southwestern part of peninsula with some large amount of snowfall. Even though the wide and intense massive cold anticyclone was expanded and enhanced by the lowest tropospheric baroclinicity over the Yellow Sea, but the intrusion and eastward movement of cold air to Seoul was too slow than normally predicted. Using the data of numerical model, satellite and radar images, three dimensional analysis Products(KLAPS : Korea Local Analysis and Prediction System) of the environmental conditions of this event such as temperature, equivalent potential temperature, wind, vertical circulation, divergence, moisture flux divergence and relative vorticity could be analyzed precisely. Through the analysis of this event, the formation and westward advection of lower cyclonic circulation with continuously horizontal movement of air into the eastern part of Seoul by the analyses of KLAPS fields have been affected by occurring the heavy snowfall event. As the predictability of abrupt snowfall event was very hard and dependent on not only the synoptic atmospheric circulation but also for mesoscale atmospheric circulation, the forecaster can be predicted well this event which may be occurred and developed within the very short time period using sequential satellite images and KLAPS products.

• Atmosphere
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• v.26 no.1
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• pp.97-109
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• 2016

Heavy rainfall (over $80mm\;hr^{-1}$) system associated with unstable atmospheric conditions occurred over the Seoul metropolitan area on 27 July 2011. To investigate the heavy rainfall system, we used three-dimensional data from Korea Local Analysis and Prediction System (KLAPS) reanalysis data and analysed the structure of the precipitation system, kinematic characteristics, thermodynamic properties, and Meteorological condition. The existence of Upper-Level Jet (ULJ) and Low-Level Jet (LLJ) are accelerated the heavy rainfall. Convective cloud developed when a strong southwesterly LLJ and strong moisture convergence occurring around the time of the heavy rainfall is consistent with the results of previous studies on such continuous production. Environmental conditions included high equivalent potential temperature of over 355 K at low levels, and low equivalent potential temperature of under 330 K at middle levels, causing vertical instability. The tip of the band shaped precipitation system was made up of line-shaped convective systems (LSCSs) that caused flooding and landslides, and the LSCSs were continuously enhanced by merging between new cells and the pre-existing cell. Difference of wind direction between low and middle levels has also been considered an important factor favouring the occurrence of precipitation systems similar to LSCSs. Development of LSCs from the wind direction difference at heights of the severe precipitation occurrence area was also identified. This study can contribute to the identification of production and development mechanisms of heavy rainfall and can be used in applied research for prediction of severe weather.

• Korean Journal of Remote Sensing
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• v.31 no.2
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• pp.137-148
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• 2015

The National Institute of Meteorological Research (NIMR) has operated the Fourier Transform InfraRed (FTIR) spectrometer which is the Atmospheric Emitted Radiance Interferometer (AERI) in Anmyeon island, Korea since June 2010. The ground-based AERI with similar hyper-spectral infrared sensor to satellite could be an alternative way to validate satellite-based remote sensing. In this regard, the NIMR has focused on the improvement of retrieval quality from the AERI, particularly cloud-data filtering method. The AERI spectrum which is measured on a typical clear day is selected reference spectrum and we used region of atmospheric window. We performed test of threshold in order to select valid threshold. We retrieved methane using new method which is used reference spectrum, and the other method which is used KLAPS cloud cover information, each retrieved methane was compared with that of ground-based in-situ measurements. The quality of AERI methane retrievals of new method was significantly more improved than method of used KLAPS. In addition, the comparison of vertical total column of methane from AERI and GOSAT shows good result.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.3
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• pp.171-177
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• 2013

The purpose of this study is to find a scheme to scale down the KMA (Korea Meteorological Administration) digital precipitation maps to the grid cell resolution comparable to the rural landscape scale in Korea. As a result, we suggest two steps procedure called RATER (Radar Assisted Topography and Elevation Revision) based on both radar echo data and a mountain precipitation model. In this scheme, the radar reflection intensity at the constant altitude of 1.5 km is applied first to the KMA local analysis and prediction system (KLAPS) 5 km grid cell to obtain 1 km resolution. For the second step the elevation and topography effect on the basis of 270 m digital elevation model (DEM) which represented by the Parameter-elevation Regressions on Independent Slopes Model (PRISM) is applied to the 1 km resolution data to produce the 270 m precipitation map. An experimental watershed with about $50km^2$ catchment area was selected for evaluating this scheme and automated rain gauges were deployed to 13 locations with the various elevations and slope aspects. 19 cases with 1 mm or more precipitation per day were collected from January to May in 2013 and the corresponding KLAPS daily precipitation data were treated with the second step procedure. For the first step, the 24-hour integrated radar echo data were applied to the KLAPS daily precipitation to produce the 1 km resolution data across the watershed. Estimated precipitation at each 1 km grid cell was then regarded as the real world precipitation observed at the center location of the grid cell in order to derive the elevation regressions in the PRISM step. We produced the digital precipitation maps for all the 19 cases by using RATER and extracted the grid cell values corresponding to 13 points from the maps to compare with the observed data. For the cases of 10 mm or more observed precipitation, significant improvement was found in the estimated precipitation at all 13 sites with RATER, compared with the untreated KLAPS 5 km data. Especially, reduction in RMSE was 35% on 30 mm or more observed precipitation.

• Journal of the Korean earth science society
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• v.36 no.6
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• pp.567-579
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• 2015

The accurate simulation of micro-scale weather phenomena such as fog using the mesoscale meteorological models is a very complex task. Especially, the uncertainty arisen from initial input data of the numerical models has a decisive effect on the accuracy of numerical models. The data assimilation is required to reduce the uncertainty of initial input data. In this study, the limitation of the mesoscale meteorological model was verified by WRF (Weather Research and Forecasting) model for a summer fog event around the Nakdong river in Korea. The sensitivity analyses of simulation accuracy from the numerical model were conducted using two different initial and boundary conditions: KLAPS (Korea Local Analysis and Prediction System) and LDAPS (Local Data Assimilation and Prediction System) data. In addition, the improvement of numerical model performance by FDDA (Four-Dimensional Data Assimilation) using the observational data from AWS (Automatic Weather System) was investigated. The result of sensitivity analysis showed that the accuracy of simulated air temperature, dew point temperature, and relative humidity with LDAPS data was higher than those of KLAPS, but the accuracy of the wind speed of LDAPS was lower than that of KLAPS. Significant difference was found in case of relative humidity where RMSE (Root Mean Square Error) for LDAPS and KLAPS was 15.7 and 35.6%, respectively. The RMSE for air temperature, wind speed, and relative humidity was improved by approximately $0.3^{\circ}C$, $0.2m\;s^{-1}$, and 2.2%, respectively after incorporating the FDDA.

• Atmosphere
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• v.21 no.1
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• pp.1-16
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• 2011

Numerical prediction capability has been improved over the decades, but progress of prediction for high-impact weather (HIW) was unsatisfactory. One reason of low predictability for HIW is lack of observation data. The National Institute of Meteorological Research (NIMR) has been performed observation program for improvement of predictability, and reduction in social and economical cost for HIW. As part of this observation program, summer intensive observation program (ProbeX-2009) was performed at the observation-gap areas from 25 August to 6 September 2009. Sounding observations using radiosonde were conducted in the Gisang2000 research vessel (R/V) from the Korea Meteorological Administration (KMA) over the West Sea and the Eardo R/V from the Korea Ocean Research and Development Institute (KORDI) over the South Sea. Observation System Experiment (OSE) is carried out to examine the effect of ProbeX-2009 data. OSEs using Korea Local Analysis and Prediction System (KLAPS) and Weather Research and Forecasting (WRF) Model are conducted to investigate the predictability for a short time forecast. And, OSEs using WRF/3DVAR system and WRF forecast model are conducted to study the predictability for an extended time. Control experiment (K_CTL and CNTL) used only GTS observation and experiment (K_EXP and SWEXP) used ProbeX-2009 data from two system are performed. ETS for 3hr accumulated rainfall simulated by KLAPS-WRF shows that K_EXP is higher than K_CTL. Also, ETS for 12hr accumulated rainfall of SWEXP from 3DVAR-WRF is higher than CNTL. The results indicate that observation over the ocean has positive impact on HIW prediction.