• 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.

• 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.

• Atmosphere
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• v.26 no.4
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• pp.495-508
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• 2016

In order to determine the prediction possibility of heavy rainfall, a variety of analyses was conducted by using three-dimensional data obtained from Korea Local Analysis and Prediction System (KLAPS) re-analysis data. Strong moisture convergence occurring around the time of the heavy rainfall is consistent with the results of previous studies on such continuous production. Heavy rainfall occurred in the cloud system with a thick convective clouds. The moisture convergence, temperature and potential temperature advection showed increase into the heavy rainfall occurrence area. The distribution of integrated liquid water content tended to decrease as rainfall increased and was characterized by accelerated convective instability along with increased buoyant energy. In addition, changes were noted in the various characteristics of instability indices such as K-index (KI), Showalter Stability Index (SSI), and lifted index (LI). The meteorological variables used in the analysis showed clear increases or decreases according to the changes in rainfall amount. These rapid changes as well as the meteorological variables changes are attributed to the surrounding and meteorological conditions. Thus, we verified that heavy rainfall can be predicted according to such increase, decrease, or changes. This study focused on quantitative values and change characteristics of diagnostic variables calculated by using numerical models rather than by focusing on synoptic analysis at the time of the heavy rainfall occurrence, thereby utilizing them as prognostic variables in the study of the predictability of heavy rainfall. These results can contribute to the identification of production and development mechanisms of heavy rainfall and can be used in applied research for prediction of such precipitation. In the analysis of various case studies of heavy rainfall in the future, our study result can be utilized to show the development of the prediction of severe weather.

• Atmosphere
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• v.25 no.3
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• pp.389-405
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• 2015

In this study, the occurrence circumstances of 3 cases (12 Jan 2006, 11 Jan 2008, 22 Feb 2009) when the freezing rain was observed at more than two observatories in a day with more than three times each observatory, were investigated. Following the advanced study about the same cases, we have tried to find more delicate differences in using the Korea Local Analysis and Prediction System (KLAPS; 5 km reanalysis data) that has the smallest grid scale at current situation. As results, three common characteristics are found: (1) Just before the occurrence of the freezing rain, the wind direction was consistently continuous and the wind speed was constant or gradually increased for at least 3 hr more. (2) Surface air temperature (Relative humidity) was respectively $3.08^{\circ}C$ (28.76%), $0.47^{\circ}C$ (50.07%) and $-3.60^{\circ}C$ (71.07%) 3 hr ago to break out the freezing rain. It means the freezing rain occurs in a wide range of atmospheric environments. However, the closer it got to the occurrence time of the freezing rain, the closer the surface air temperature was to $0^{\circ}C$, and the bigger the humidity of the surface air was. (3) The liquid precipitation formed in the upper atmosphere, met a cold advection bellower than 950 hPa level and suspected to be changed to the super-cooled condition.

• Journal of the Korean Association of Geographic Information Studies
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• v.20 no.2
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• pp.47-59
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• 2017

This study aims to assess offshore wind energy resources around Jeju Island using the InVEST Offshore Wind model. First the wind power density around the coast of Jeju was calculated using reanalysis data from the Korean Local Analysis and Prediction System (KLAPS). Next, the net present value (NPV) for the 168MW offshore wind farm scenario was evaluated taking into consideration factors like costs (turbine development, submarine cable installation, maintenance), turbine operation efficiency, and a 20year operation period. It was determined that there are high wind resources along both the western and eastern coasts of Jeju Island, with high wind power densities of $400W/m^2$ calculated. To visually evaluate the NPV around Jeju Island, a classification of five grades was employed, and results showed that the western sea area has a high NPV, with wind power resources over $400W/m^2$. The InVEST Offshore Wind model can quickly provide optimal spatial information for various wind farm scenarios. The InVEST model can be used in combination with results of marine ecosystem service evaluation to design an efficient marine spatial plan around Jeju Island.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.57-81
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• 2019

Satellite images can be integrated into a crop model to strengthen the advantages of each technique for crop monitoring and to compensate for weaknesses of each other, which can be systematically applied for monitoring inaccessible croplands. The objective of this study was to outline the productivity of paddy rice based on simulation of the yield of all paddy fields in North Korea, using a grid crop model combined with optical satellite imagery. The grid GRAMI-rice model was used to simulate paddy rice yields for inaccessible North Korea based on the bidirectional reflectance distribution function-adjusted vegetation indices (VIs) and the solar insolation. VIs and solar insolation for the model simulation were obtained from the Geostationary Ocean Color Imager (GOCI) and the Meteorological Imager (MI) sensors of the Communication Ocean and Meteorological Satellite (COMS). Reanalysis data of air temperature were achieved from the Korea Local Analysis and Prediction System (KLAPS). Study results showed that the yields of paddy rice were reproduced with a statistically significant range of accuracy. The regional characteristics of crops for all of the sites in North Korea were successfully defined into four clusters through a spatial analysis using the K-means clustering approach. The current study has demonstrated the potential effectiveness of characterization of crop productivity based on incorporation of a crop model with satellite images, which is a proven consistent technique for monitoring of crop productivity in inaccessible regions.