• Atmosphere
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• v.26 no.1
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• pp.141-158
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• 2016

The objective of this study is to examine the impact of urban canopy and the horizontal resolution on simulated meteorological variables such as 10-m wind speed, 2-m temperature and precipitation using WRF model for a local, convective rainfall case. We performed four sensitivity tests by varying the use of urban canopy model (UCM) and the horizontal resolution, then compared the model results with observations of AWS network. The focus of our study is over the Seoul metropolitan area for a convective rainfall that occurred on 16 August 16 2015. The analysis shows that mean diurnal variation of temperature is better simulated by the model runs with UCM before the convective rainfall. However, after rainfall, model shows significant difference in air temperature among sensitivity tests depending on the simulated rainfall amount. The rainfall amount is significantly underestimated in 0.5 km resolution model run compared to 1.5 km resolution, particularly over the urban areas. This is due to earlier occurrence of light rainfall in 0.5 km resolution model. Earlier light rainfall in the afternoon eliminates convective instability significantly, which prevents occurrence of rainfall later in the evening. The use of UCM results in a higher maximum rainfall in the domain, which is due to higher temperature in model runs with urban canopy. Earlier occurrence of rainfall in 0.5 km resolution model is related to rapid growth of PBL. Enhanced mixing and higher temperature result in rapid growth of PBL, which provides more favorable conditions for convection in the 0.5 km resolution run with urban canopy. All sensitivity tests show dry bias, which also contributes to the occurrence of light precipitation throughout the simulation period.

• Atmosphere
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• v.21 no.4
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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.

• Journal of Korean Society of Disaster and Security
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• v.8 no.2
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• pp.21-26
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• 2015

This study analyzes the failure predict of model slope due to changes in ground condition followed by heavy rainfall with a simulated rainfall system. the movement of a slope from the rainfall penetrating the unsaturated soil is investigated with respect to various conditions of pore-water pressure, earth pressure and moisture content, considering rainfall duration and permeability.

• Magazine of the Korean Society of Agricultural Engineers
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• v.35 no.1
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• pp.29-39
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• 1993

A model for estimating daily effective rainfall of upland crops was developed. The infiltration process was described by Green-Ampt infiltration model developed by Chu(1978). The model considers delayed surface ponding and surface detention storage under a uniform soil profile. The Green-Ampt parameters, that is, average hydraulic conductivity and average capillary pressure head on a sandy loam soil were determined from field experiment using Air-entry permeameter developed by Bouwer(1966). The model was verified by comparing measured and simulated surface runoff. The ratios of effective rainfall to total rainfall for red pepper, soybean, sesame and Chinese cabbage were evaluated using Borg's root growth model( 1986) respectively. The followings are a summary of this study results; 1.In a sandy loam soil average hydraulic conductivity was 3.28cm/hr and average capillary pressure head was 3.00cm. 2.The root growth of upland crops could be expressed by Borg's root growth model successively. 3.The measured and simulated surface runoff was agreed well with each other. 4.As the rainfall amount was increased, the ratio of effective rainfall to total rainfall was decreased exponentially till a certain growing period.

• The Journal of Engineering Geology
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• v.18 no.4
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• pp.523-535
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• 2008

A simulated rainfall system was built, and the unsaturated characteristics were examined by execution of simulated rainfall system test and soil water characteristic curve cell test(SWCC Cell Test) under the various rainfall and slope conditions. With the results, the applicability of infiltration behavior under rainfall and soil water characteristic curve models to the unsaturated weathered granite soil was examined. At the results of comparison the volumetric water content and matric suction measured in the wetting process(under rainfall) with those in the drying process(leaving as it was) of the simulated rainfall system, the volumetric water content showed a difference of $2{\sim}5%$ and matric suction of about $3{\sim}10\;kPa$, indicating the occurrence of hysteresis. In addition, the difference was relatively larger in matric suction than in the volumetric water content, and this tells that the hysteresis behavior is larger in matric suction. When the soil water characteristic curve derived from measurements in simulated rainfall system test were compared with those from the soil water characteristic curve cell test, both methods produced soil water characteristic curves close each other in the wetting process and the drying process, but in both, there was a difference between results obtained from in the wetting process and those from in the drying process. Thus, when soil water characteristic curves are rationally applied to the design and stability analysis considering of the properties of unsaturated soil, it is considered desirable to apply the soil water characteristic curve of the wetting process to the wetting process, and that of the drying process to the drying process.

• Journal of Environmental Science International
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• v.30 no.12
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• pp.1053-1065
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• 2021

In this study, the prediction technology of Hydrological Quantitative Precipitation Forecast (HQPF) was improved by optimizing the weather predictors used as input data for machine learning. Results comparison was conducted using bias and Root Mean Square Error (RMSE), which are predictive accuracy verification indicators, based on the heavy rain case on August 21, 2021. By comparing the rainfall simulated using the improved HQPF and the observed accumulated rainfall, it was revealed that all HQPFs (conventional HQPF and improved HQPF 1 and HQPF 2) showed a decrease in rainfall as the lead time increased for the entire grid region. Hence, the difference from the observed rainfall increased. In the accumulated rainfall evaluation due to the reduction of input factors, compared to the existing HQPF, improved HQPF 1 and 2 predicted a larger accumulated rainfall. Furthermore, HQPF 2 used the lowest number of input factors and simulated more accumulated rainfall than that projected by conventional HQPF and HQPF 1. By improving the performance of conventional machine learning despite using lesser variables, the preprocessing period and model execution time can be reduced, thereby contributing to model optimization. As an additional advanced method of HQPF 1 and 2 mentioned above, a simulated analysis of the Local ENsemble prediction System (LENS) ensemble member and low pressure, one of the observed meteorological factors, was analyzed. Based on the results of this study, if we select for the positively performing ensemble members based on the heavy rain characteristics of Korea or apply additional weights differently for each ensemble member, the prediction accuracy is expected to increase.

• 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.

• Journal of the Korean GEO-environmental Society
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• v.15 no.12
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• pp.71-77
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• 2014

Heavy rainfall induces many disasters including slope failure and infrastructure collapse. In this point of view, rainfall-simulated centrifugal model test can be a reasonable tool to evaluate the stability of geotechnical structure. In order to obtain the displacements of a model in centrifugal model test, in general, LVDT and laser displacement sensor are used. However, when the rainfall is simulated, the LVDT has the problem of excessive infiltration into the model ground, and the laser displacement sensor provides the measuring result with inaccuracy due to the dispersion of the laser radiation. Hence, in this study, horizontal displacement sensor for rainfall-simulated centrifugal model test was developed. This sensor produced with a thin elastic steel plate and gave the accurate relationship between the displacement and the strain.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.501-504
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• 2008

A non-homogeneous markov model which is able to simulate hourly rainfall series is developed for estimating reliable hydrological variables. The proposed approach is applied to simulate hourly rainfall series in Korea. The simulated rainfall is used to estimate the design rainfall and compared to observations in terms of reproducing underlying distributions of the data to assure model's validation. The model shows that the simulated rainfall series reproduce a similar statistical attribute with observations, and expecially maximum value is gradually increased as number of simulation increase.

• Journal of Wetlands Research
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• v.20 no.1
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• pp.94-104
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• 2018

In general, the rainfall-runoff simulation is performed using rainfall data from meteorological and observational rain gauge stations. However, if we only use rainfall data from meteorological and observational rain gauge stations for runoff simulation of a large watershed, the problem in the reliability of the simulated runoff can be occurred. Therefore, this study examined the influence of the rainfall data on the simulated runoff volume by a Semi-distributed model. For this, we used rainfall data from meteorological stations, meteorological and observational stations, and a spatially distributed rainfall data from hypothetical stations obtained by kriging method. And, we estimated the areal rainfall of each sub-basin. Also the estimated areal rainfall and the observed rainfall were compared and we compared the simulated runoff volumes using SWAT model by the rainfall data from meteorological and observational rain gauge stations and runoff volume from the estimated areal rainfall by Kriging method were analyzed. This study was performed to examine the accuracy of calculated runoff volume by spatially distributed areal rainfall. The analysis result of this study showed that runoff volume using areal rainfall is similar to observed runoff volume than runoff volume using the rainfall data of weather and rain gauging station. this means that spatially distributed rainfall reflect the real rainfall pattern.