• 대기
• /
• 제21권4호
• /
• pp.391-404
• /
• 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.

• 한국수자원학회논문집
• /
• 제52권2호
• /
• pp.125-132
• /
• 2019

본 연구에서는 기존의 정량적인 강수량 정보를 제공하는 방식에서 벗어나 호우발생에 따른 생활환경의 변화에 끼치는 영향을 고려한 호우영향예보서비스의 필요성을 기반으로 호우위험영향도 평가가 가능한 호우재해 위험영향 매트릭스를 개발하고, 이를 통해 호우위험영향을 평가하는 방법을 제시하였다. 사당동 일대를 대상으로 실제 발생 호우사상(2011년 7월 27일)을 적용하였으며, 호우에 의한 침수로 영향을 받는 대상별(사람, 교통, 시설) 호우위험영향평가를 수행하였다. 이를 위해 1 km 격자기반으로 호우위험정도(Impact Level)를 산정하고, 침수심 결과를 조합하여 격자기반의 잠재호우위험영향(Potential Risk Impact)을 산정하였다. 여기에 강우발생가능성 Likelihood와의 조합을 통해 호우영향예보가 가능한 호우위험영향(Heavy Rainfall Risk Impact) 값을 산정하여 사당동 지역의 호우영향정도를 격자기반으로 4개의 등급으로 분석, 제시하였다.

• 한국방재안전학회논문집
• /
• 제15권4호
• /
• pp.87-98
• /
• 2022

최근 짧은 시간 동안 많은 강우가 내리는 국지성 집중호우가 빈번히 발생하고 이로 인한 침수피해가 증가하고 있다. 국지성 집중호우로 인한 피해를 예방하기 위하여 기상청이 제공하는 지역 앙상블 예측시스템(Local ENsemble prediction System, LENS)과 관측자료와 동네예보 자료를 활용한 기계학습과 확률 매칭(Probability Matching, PM) 기법을 이용하여 수문학적 정량강우예측정보(Hydrological Quantative Precipitation Forecast, HQPF)을 개발하였다. 국지성 집중호우로 인한 침수피해 대비를 위한 호우 영향정보로 HQPF를 생산하고 있지만, 낮은 강우강도에 대하여 과대예측하는 경향이 나타났다. 본 연구에서는 HQPF의 예측정확도 향상과 과대예측 성향을 개선하기 위하여 머신러닝 학습자료 기간확대, 앙상블 기법 분석 및 확률매칭(PM) 기법 프로세스 변경을 통하여 HQPF 개선하였다. 개선된 HQPF의 예측성능을 평가하기 위해 2021년 8월 27일 ~ 2021년 9월 3일 장마전선으로 인한 호우 사례를 대상으로 예측성능 검증을 수행하였다. 10 mm 이하의 강우에 대하여 예측정확도가 크게 향상되었고, 관측과 유사한 발생가능성 및 강우영역을 예측하는 등 과대예측 성향이 개선되었음을 확인하였다.

• 대기
• /
• 제33권5호
• /
• 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.

• 대기
• /
• 제27권2호
• /
• pp.189-197
• /
• 2017

Progressing from weather forecasts and warnings to multi-hazard impact-based forecast and warning services represents a paradigm shift in service delivery. Urban flooding is a typical meteorological disaster. This study proposes support plan for urban flooding impact-based forecast by providing inundation risk matrix. To achieve this goal, we first configured storm sewer management model (SWMM) to analyze 1D pipe networks and then grid based inundation analysis model (GIAM) to analyze 2D inundation depth over the Gangnam drainage area with $7.4km^2$. The accuracy of the simulated inundation results for heavy rainfall in 2010 and 2011 are 0.61 and 0.57 in POD index, respectively. 20 inundation scenarios responding on rainfall scenarios with 10~200 mm interval are produced for 60 and 120 minutes of rainfall duration. When the inundation damage thresholds are defined as pre-occurrence stage, occurrence stage to $0.01km^2$, 0.01 to $0.1km^2$, and $0.1km^2$ or more in area with a depth of 0.5 m or more, rainfall thresholds responding on each inundation damage threshold results in: 0 to 20 mm, 20 to 50 mm, 50 to 80 mm, and 80 mm or more in the rainfall duration 60 minutes and 0 to 30 mm, 30 to 70 mm, 70 to 110 mm, and 110 mm or more in the rainfall duration 120 minutes. Rainfall thresholds as a trigger of urban inundation damage can be used to form an inundation risk matrix. It is expected to be used for urban flood impact forecasting.

• 한국지구과학회지
• /
• 제36권5호
• /
• pp.460-475
• /
• 2015

A number of heavy rainfall events on the Korean Peninsula are indirectly influenced by tropical cyclones (TCs) when they are located in southeastern China. In this study, a heavy rainfall case in the middle Korean region is selected to examine the influence of typhoon simulation performance on predictability of remote rainfall over Korea as well as direct rainfall over Taiwan. Four different numerical experiments are conducted using Weather Research and Forecasting (WRF) model, toggling on and off two different improvements on typhoon in the model initial condition (IC), which are TC bogussing initialization and dropwindsonde observation data assimilation (DA). The Geophysical Fluid Dynamics Laboratory TC initialization algorithm is implemented to generate the bogused vortex instead of the initial typhoon, while the airborne observation obtained from dropwindsonde is applied by WRF Three-dimensional variational data assimilation. Results show that use of both TC initialization and DA improves predictability of TC track as well as rainfall over Korea and Taiwan. Without any of IC improvement usage, the intensity of TC is underestimated during the simulation. Using TC initialization alone improves simulation of direct rainfall but not of indirect rainfall, while using DA alone has a negative impact on the TC track forecast. This study confirms that the well-suited TC simulation over southeastern China improves remote rainfall predictability over Korea as well as TC direct rainfall over Taiwan.

• 대기
• /
• 제25권4호
• /
• pp.623-637
• /
• 2015

The accurate analysis of water vapor in initial of numerical weather prediction (NWP) model is required as one of the necessary conditions for the improvement of heavy rainfall prediction and reduction of spin-up time on a very-short-range forecast. To study this effect, the impact of a ground-based Global Positioning System (GPS)-Precipitable Water Vapor (PWV) on very-short-range forecast are examined. Data assimilation experiments of GPS-PWV data from 19 sites over the Korean Peninsula were conducted with Advanced Storm-scale Analysis and Prediction System (ASAPS) based on the Korea Meteorological Administration's Korea Local Analysis and Prediction System (KLAPS) included "Hot Start" as very-short-range forecast system. The GPS total water vapor was used as constraint for integrated water vapor in a variational humidity analysis in KLAPS. Two simulations of heavy rainfall events show that the precipitation forecast have improved in terms of ETS score compared to the simulation without GPS-PWV data. In the first case, the ETS for 0.5 mm of rainfall accumulated during 3 hrs over the Seoul-Gyeonggi area shows an improvement of 0.059 for initial forecast time. In other cases, the ETS improved 0.082 for late forecast time. According to a qualitative analysis, the assimilation of GPS-PWV improved on the intensity of precipitation in the strong rain band, and reduced overestimated small amounts of precipitation on the out of rain band. In the case of heavy rainfall during the rainy season in Gyeonggi province, 8 mm accompanied by the typhoon in the case was shown to increase to 15 mm of precipitation in the southern metropolitan area. The GPS-PWV assimilation was extremely beneficial to improving the initial moisture analysis and heavy rainfall forecast within 3 hrs. The GPS-PWV data on variational data assimilation have provided more useful information to improve the predictability of precipitation for very short range forecasts.

• 한국환경과학회지
• /
• 제30권12호
• /
• pp.1053-1065
• /
• 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.

• 대기
• /
• 제24권2호
• /
• pp.159-171
• /
• 2014

This study investigated the temporal and spatial characteristics of summertime (June-August) precipitation over Korean peninsula, using Korea Meteorological Administration (KMA)is Automated Synoptic Observing System (ASOS) data for the period of 1973-2010 and Automatic Weather System (AWS) data for the period of 1998-2010.The authors looked through climatological features of the summertime precipitation, then examined the degree of locality of the precipitation, and probable precipitation amount and its return period of 100 years (i.e., an extreme precipitation event). The amount of monthly total precipitation showed increasing trends for all the summer months during the investigated 38-year period. In particular, the increasing trends were more significant for the months of July and August. The increasing trend of July was seen to be more attributable to the increase of precipitation intensity than that of frequency, while the increasing trend of August was seen to be played more importantly by the increase of the precipitation frequency. The e-folding distance, which is calculated using the correlation of the precipitation at the reference station with those at all other stations, revealed that it is August that has the highest locality of hourly precipitation, indicating higher potential of localized heavy rainfall in August compared to other summer months. More localized precipitation was observed over the western parts of the Korean peninsula where terrain is relatively smooth. Using the 38-years long series of maximum daily and hourly precipitation as input for FARD2006 (Frequency Analysis of Rainfall Data Program 2006), it was revealed that precipitation events with either 360 mm $day^{-1}$ or 80 mm $h^{-1}$ can occur with the return period of 100 years over the Korean Peninsula.

• 대기
• /
• 제28권2호
• /
• pp.187-200
• /
• 2018

The heavy snowfall phenomenon with thunder and lightning occurred in Yeongdong coastal region on 20 January 2017. Amount of snow on that day was a maximum of 47 cm and was concentrated in a short time (2 hours) at the Yeongdong coastal area. The mechanism of thundersnow was investigated to describe in detail using observational data and numerical simulation (Weather Research and Forecast, WRF) applied lightning option. The results show that a convective cloud occurred at the Yeongdong coastal area. The east wind flow was generated and the pressure gradient force was maximized by the rapidly developed cyclone. The cold and dry air in the upper atmosphere has descended (so called tropopause folding) atmospheric lower layer at precipitation peak time (1200 LST). In addition, latent heat in the lower atmosphere layer and warm sea surface temperature caused thermal instability. The convective cloud caused by the strong thermal instability was developed up to 6 km at that time. And the backdoor cold front was determined by the change characteristics of meteorological elements and shear line in the east sea. Instability indexes such as Total totals Index (TT) and Lightning Potential Index (LPI) are also confirmed as one of good predictability indicates for the explosive precipitation of convective rainfall.