• Water Engineering Research
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• 제3권2호
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• pp.113-122
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• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict flash floods. In this study, a Quantitative Flood Forecasting (QFF) model was developed by incorporating the evolving structure and frequency of intense weather systems and by using neural network approach. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as lifetime, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. All these processes stretched leadtime up to 18 hours. The QFF model will be applied to the mid-Atlantic region of United States in a forthcoming paper.

• 대기
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• 제21권3호
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• pp.243-256
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• 2011

This paper presents the development of new algorithm for identifying and tracking the convective cells in three dimensional reflectivity fields in Cartesian coordinates. First, the radar volume data in spherical coordinate system has been converted into Cartesian coordinate system by the bilinear interpolation. The three-dimensional convective cell has then been identified as a group of spatially consecutive grid points using reflectivity and volume thresholds. The tracking algorithm utilizes a fuzzy logic with four membership functions and their weights. The four fuzzy parameters of speed, area change ratio, reflectivity change ratio, and axis transformation ratio have been newly defined. In order to make their membership functions, the normalized frequency distributions are calculated using the pairs of manually matched cells in the consecutive radar reflectivity fields. The algorithms have been verified for two convective events in summer season. Results show that the algorithms have properly identified storm cells and tracked the same cells successively. The developed algorithms may provide useful short-term forecasting or nowcasting capability of convective storm cells and provide the statistical characteristics of severe weather.

• 한국수자원학회논문집
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• 제36권3호
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• pp.495-505
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• 2003

Meteosat-5 IR 위성영상을 사용하여 1999년과 2000년 여름몬순기간 동안 발생한 네팔과 인디아 북쪽 히말라야 산악지역에 발생하는 여러 형태의 대류계 즉, 중규모 대류계들 (Mesoscale Convective Complex, MCC and Convective Cloud Clusters, CCC) 와 보다 약한 Disorganized Short-lived Convection (DSL)의 이동특성 및 시공간적인 생성특성 등을 조사하였다. 대상지역에 발생하는 중규모 대류계의 전형적인 지속시간은 약 11시간이며 크기는 약 $300,000km^2$ 이다. 중규모 대류계의 중심은 히말라야산맥으로부터 원거리에 위치함에도 불구하고 집중강운-는 위도 $25^{\circ}-30^{\circ}N$ 사이의 히말라야 하단에 발생하는 중규모 대류계와 직접적 상관관계를 가진다. 결과는 히말라야 고도 500-4000m에 설치된 강우계로부터 획득된 강우자료의 변화 특성과 대류계 거동 특성이 유사함을 보여주었다(Barros et al. 2000). 집중호우의 강력한 야간발생과 Gangetic Plains에서 발생한 중규모 대류계와의 연관성을 보여주었다(Barros et al. 2000).

• 한국지구과학회지
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• 제33권5호
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• pp.377-394
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• 2012

To elucidate the mechanism associated with the development of heavy precipitation system, a field experiment was carried out in Jejudo (or Jeju Island) and Marado, Korea from 22 June to 12 July 2006. The synoptic atmospheric conditions were analyzed using the National Centers for Environmental Prediction-National Center for Atmospheric Research's (NCEP/NCAR) reanalyzed data, weather maps, and sounding data. The kinematic characteristics of each precipitation system were investigated by dual Doppler radar analysis. During the field experiment, data of four precipitation events with more than 20 mm rainfall were collected. In F case (frontal precipitation), a typical Changma front was dominant and the observation field was fully saturated. However there was no convective instability near the surface. LF case (low pressure accompanied with Changma front) showed strong convective instability near the surface, while a strong convergence corresponded to the low pressure from China accompanied with Changma front. In FT case (Changma front indirectly influenced by typhoon), the presence of a convective instability indicated the transport of near surface, strong additional moisture from the typhoon 'EWINIAR'. The convergence wind field was ground to be located at a low level. The convective instability was not significant in T case (precipitation of the typhoon 'EWINIAR'), since the typhoon passed through Jejudo and the Changma front was disappeared toward the northeastern region of the Korean peninsula. The kinematic (convergence and divergence) characteristics of wind fields, convective instability, and additional moisture inflow played important roles in the formation and development of heavy precipitation.

• 대기
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• 제15권3호
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• pp.155-165
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• 2005

The characteristics of six precipitation systems occurred around Cheongju in 2002 are analyzed after the convective/stratiform radar echo classification using radar reflectivity from the Meteorological Research Institute"s X-band Doppler weather radar. The Biggerstaff and Listemaa (2000) algorithm is applied for the classification and reveals a physical characteristics of the convective and stratiform rain diagnosed from the three-dimensional structure of the radar reflectivity. The area satisfying the vertical profile of radar reflectivity is well classified, while the area near the radar site and the topography-shielded area show a mis-classification. The seasonal characteristics of the precipitation system are also analyzed using the contoured frequency by altitude diagrams (CFADs). The heights of maximum reflectivity are 4 km and 5.5 km in spring and summer, respectively, and the vertical gradient of radar reflectivity from 1.5 km to the melting layer in spring is larger than in summer.

• 대한원격탐사학회지
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• 제25권6호
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• pp.465-474
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• 2009

Convective/stratiform radar echo classification schemes by Steiner et al. (1995) and Biggerstaff and Listemaa (2000) are examined on a monsoonal front during the summer monsoon-Changma period, which is organized as a cloud cluster with mesoscale convective complex. Target radar is S-band with wavelength of 10cm, spatial resolution of 1km, elevation angle interval of 0.5-1.0 degree, and minimum elevation angle of 0.19 degree at Jindo over the Korean Peninsula. For verification of rainfall amount retrieved from the echo classification, ground-based rain gauge observations (Automatic Weather Stations) are examined, converting the radar echo grid data to the station values using the inverse distance weighted method. Improvement from the echo classification is evaluated based on the correlation coefficient and the scattered diagram. Additionally, an optimal use method was designed to produce combined rainfalls from the radar echo and Tropical Rainfall Measuring Mission Precipitation Radar (TRMM/PR) data. Optimal values for the radar rain and TRMM/PR rain are inversely weighted according to the error variance statistics for each single station. It is noted how the rainfall distribution during the summer monsoon frontal system is improved from the classification of convective/stratiform echo and the use of the optimal use technique.

• 대기
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• 제24권4호
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• pp.457-470
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• 2014

Thermodynamic conditions related with localized torrential rainfall in the middle west region of Korean peninsula are examined using radar rain rate and radiosonde observational data. Localized torrential rainfall events in this study are defined by three criteria base on 1) any one of Automated Synoptic Observing System (ASOS) hourly rainfall exceeds $30mmhr^{-1}$ around Osan, 2) the rain (> $1mmhr^{-1}$) area estimated from radar reflectivity is less than $20,000km^2$, and 3) the rain (> $10mmhr^{-1}$) cell is detected clearly and duration is short than 24 hr. As a result, 13 cases were selected during the summer season of 10 years (2004-13). It was found that the duration, the maximum rain area, and the maximum volumetric rain rate of convective cells (> $30mmhr^{-1}$) are less than 9hr, smaller than $1,000km^2$, and $15,000{\sim}60,000m^3s^{-1}$ in these cases. And a majority of cases shows the following thermodynamic characteristics: 1) Convective Available Potential Energy (CAPE) > $800Jkg^{-1}$, 2) Convective Inhibition (CIN) < $40Jkg^{-1}$, 3) Total Precipitable Water (TPW) ${\approx}$ 55 mm, and 4) Storm Relative Helicity (SRH) < $120m^2s^{-2}$. These cases mostly occurred in the afternoon. These thermodynamic conditions indicated that these cases were caused by strong atmospheric instability, lifting to overcome CIN, and sufficient moisture. The localized torrential rainfall occurred with deep moisture convection result from the instability caused by convective heating.

• 대기
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• 제26권1호
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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.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2002년도 학술발표회 논문집(I)
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• pp.43-50
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• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4％ and up to 6％ were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.

• 대기
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• 제21권4호
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• pp.391-404
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• 2011

This study investigates the impact of cumulus parameterization scheme (CPS) with different horizontal grid sizes on the simulation of the local heavy rainfall case over the Korean Peninsula. The Weather Research and Forecasting (WRF)-based real-time forecast system of the Joint Center for High-impact Weather and Climate Research (JHWC) is used. Three CPSs are used for sensitivity experiments: the BMJ (Betts-Miller-Janjic), GD (Grell-Devenyi ensemble), and KF (Kain-Fritsch) CPSs. The heavy rainfall case selected in this study is characterized by low-level jet and low-level transport of warm and moist air. In 27-km simulations (DM1), simulated precipitation is overestimated in the experiment with BMJ scheme, and it is underestimated with GD scheme. The experiment with KF scheme shows well-developed precipitation cells in the southern and the central region of the Korean Peninsula, which are similar to the observations. All schemes show wet bias and cold bias in the lower troposphere. The simulated rainfall in 27-km horizontal resolution has influence on rainfall forecast in 9-km horizontal resolution, so the statements on 27-km horizontal resolution can be applied to 9-km horizontal resolution. In the sensitivity experiments of CPS for DM3 (3-km resolution), the experiment with BMJ scheme shows better heavy rainfall forecast than the other experiments. The experiments with CPS in 3-km horizontal resolution improve rainfall forecasts compared to the experiments without CPS, especially in rainfall distribution. The experiments with CPS show lower LCL(Lifted Condensation Level) than those without CPS at the maximum rainfall point, and weaker vertical velocity is simulated in the experiments with CPS compared to the experiments without CPS. It means that CPS suppresses convective instability and influences mainly convective rainfall. Consequently, heavy rainfall simulation with BMJ CPS is better than the other CPSs, and even in 3-km horizontal resolution, CPS should be applied to control convective instability. This conclusion can be generalized by conducting more experiments for a variety of cases over the Korean Peninsula.