• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2009년도 학술발표회 초록집
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• pp.2161-2166
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• 2009

It is important for 0-6 hour nowcasting to provide for a high-quality initial condition in a meso-scale atmospheric model by a data assimilation of several observation data. The polarimetric radar data is expected to be assimilated into the forecast model, because the radar has a possibility of measurements of the types, the shapes, and the size distributions of hydrometeors. In this paper, an impact on rainfall prediction of the data assimilation of hydrometeor types (i.e. raindrop, graupel, snowflake, etc.) is evaluated. The observed information of hydrometeor types is estimated using the fuzzy logic algorism. As an implementation, the cloud-resolving nonhydrostatic atmospheric model, CReSS, which has detail microphysical processes, is employed as a forecast model. The local ensemble transform Kalman filter, LETKF, is used as a data assimilation method, which uses an ensemble of short-term forecasts to estimate the flowdependent background error covariance required in data assimilation. A heavy rainfall event occurred in Okinawa in 2008 is chosen as an application. As a result, the rainfall prediction accuracy in the assimilation case of both hydrometeor types and the Doppler velocity and the radar echo is improved by a comparison of the no assimilation case. The effects on rainfall prediction of the assimilation of hydrometeor types appear in longer prediction lead time compared with the effects of the assimilation of radar echo only.

• 대기
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• 제33권5호
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• pp.457-475
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• 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
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• 제29권3호
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• pp.269-282
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• 2019

While it is important to obtain the accurate information on snowfall data due to the increase in damage caused by the heavy snowfall in the winter season, it is not easy to observe the snowfall quantitatively. Recently, snow measurements using a weighing precipitation gauge have been carried out, but there is a problem that high snowfall intensity results in low accuracy. Also, the observed snowfall data are sensitive depending on wind speed, temperature, and humidity. In this study, a new process of quality control for snow water equivalent (SWE) data of the weighing precipitation gauge were proposed to cover the low accuracy of snow data and maximize the data utilization. Snowfall data (SWE) observed by Pluvio, Parsivel, snow-depth meter using laser or ultrasonic, and rainfall gauge in Cloud Physics Observation Site (CPOS) were compared and analyzed. Applying the QC algorithm including the use of number of hydrometeor particles as reference, the increased SWE per the unit time was determined and the data noise was removed and marked by flag. The SWE data converted by the number concentration of hydrometeor particles are tested as a method to restore the QC-removed data, and show good agreement with those of the weighing precipitation gauge, though requiring more case studies. The three events data for heavy snowfall disaster in Pyeongchang area was analyzed. The SWE data with improved quality was showed a good correlation with the eye-measured data ($R^2$ > 0.73).

• 한국통신학회:학술대회논문집
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• 한국통신학회 2006년도 하계종합학술발표회 논문 초록집
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• pp.379-379
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• 2006

• 대한원격탐사학회지
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• 제29권3호
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• pp.293-306
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• 2013

Hydrometeor type and Drop Size Distribution (DSD) in cloud are the fundamental properties that may help explain the rain formation processes and determine the parameters of radar meteorology. This study presents a preliminary analysis of hydrometeor types and DSD data of cloud measured with a PARSIVEL (PARticle SIze and VELocity) optical disdrometer at the site of Cloud Physics Observation System (CPOS, $37^{\circ}41^{\prime}N$, $128^{\circ}45^{\prime}E$, 843 m from sea level) in Daegwallyeong mountainside of Korea. The method has been validated by comparing the observed rainfall rates with the computed ones from the fitted distribution, using the physical data such as DSD, terminal velocity, and rain intensity which were measured by a Micro-Rain Radar (MRR) and a PARSIVEL optical disdrometer. The analysis period started in three cases: on rainy days with light rain (15.5 mm), moderate rain (76 mm), and heavy rain (121 mm), from March to November 2007, respectively.

• 대한원격탐사학회지
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• 제34권2_1호
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• pp.237-248
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• 2018

본 연구에서 영동지역 강수 전(2016년 12월 13일) 운저 고도인근 수상체 분포를 스캐닝 라이다와 레윈존데 자료 및 구름분해모델(Cloud Resolving Storm Simulator; CReSS)의 모의 결과를 통해 분석하였다. 강수 전운저 인근에서 관측된 라이다의 연직 후방산란 신호와 평광비 프로파일은 유사한 특징을 보였다. 이를 모델의 재현 결과와 비교하였을 때, 찬 구름 내부(< $0^{\circ}C$)에 존재하는 운빙(ice), 눈(snow)과 운저 인근에 형성된 과냉각 수 적층, 운저 아래에서 낙하하는 부착(rimed)형 눈의 존재를 관측한 결과라 판단된다. 또한, 고도에 따른 광학속성 프로파일의 변화 형태에 따라 연직으로 구간을 세분화하여 연직 수상체의 형상과 밀도에 대해 분석한 결과를 제시하였다.

• 한국항공운항학회지
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• 제19권1호
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• pp.24-28
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• 2011

This paper reviews a ceiling prediction method based on a mesoscale meteorological modeling system in South Korea. The study was motivated by the tendency of higher model ceiling height than the observed in daily operational forecasts. The goal of the paper is to report an effort to improve the operational ceiling prediction skill by conducting numerical experiments controlling a model parameter. In a case experiment, increasing constant values used in the relationship between extinction coefficients and concentration showed better performance, indicating a short-term strategy for operational local ceiling forecast improvement.

• 대한토목학회논문집
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• 제14권5호
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• pp.1129-1136
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• 1994

지점 강우 과정을 물리적으로 모형화하였다. 모형의 입력 변수는 지상의 기상 변수이다. 모형의 성분은 관측치와 구름 물리학의 선행 연구를 토대로 매개 변수화되었다. 특별히 강조되는 것은 집적 효율을 평가하는 것이다. 수정 비대칭 모형의 수운적 크기 분포 함수를 적용한 결과 그 모형은 호우에 적합하였다. 모형에 포함된 주요 매개변수는 최적화 기법에 의하여 평가하였다. 강우 강도는 평가된 매개변수의 중앙값을 사용하여 예측하였다.

• 한국수자원학회논문집
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• 제53권11호
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• pp.999-1013
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• 2020

전세계적으로 기상조절 연구가 활발히 수행되어져 왔으나 연구 효과를 보다 정량적으로 검증할 수 있는 기술이 필요하다. 본 연구에서는 기상조절 실험에 대한 강수 증가 효율인 시딩효과(seeding effect)를 레이더 자료를 이용하여 검증하였다. 또한, 시딩물질이 대기수상체 변화에 미치는 영향을 분석하였다. 이를 위해 레이더 자료, 기상조건, 확산 수치모의 자료가 사용되었다. 먼저, 시딩전, 시딩중, 시딩후의 세 단계로 시딩효과를 분석할 수 있는 방법을 제안하였다. 제안한 방법을 강원도와 서해 지역을 대상으로 수행된 세 개의 기상조절 실험 사례에 적용하였다. 그 결과, 자연강수가 없을 때는 강수 변화가 예측된 구역에서 감지된 레이더 반사도가 시딩효과로 판단되었다. 자연강수가 발생하면 관측된 최대 반사도에서 자연강수의 영향을 제외하여 시딩효과를 결정하였다. 적용사례에 대해 시딩효과로 강수강도가 0.1 mm/h 증가한 것으로 나타났다. 아울러 시딩 구름에 빙정이나 과냉각 수적, 혼합상의 수상체가 분포한 것으로 나타났다. 이러한 기상조절 연구 결과는 수자원 확보와 구름 물리 연구에 활용할 수 있을 것으로 판단된다.

• 한국지구과학회지
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• 제23권1호
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• pp.59-71
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• 2002

Theoretical models of radiative transfer are developed to simulate the 85 GHz brightness temperature (T85) observed by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) radiometer as a function of rain rate. These simulations are performed separately over regions of the convective and stratiform rain. TRMM Precipitation Radar (PR) observations are utilized to construct vertical profiles of hydrometeors in the regions. For a given rain rate, the extinction in 85 GHz due to hydrometeors above the freezing level is found to be relatively weak in the convective regions compared to that in the stratiform. The hydrometeor profile above the freezing level responsible for the weak extinction in convective regions is inferred from theoretical considerations to contain two layers: 1) a mixed (or mixed-phase) layer of 2 km thickness with mixed-phase particles, liquid drops and graupel above the freezing level, and 2) a layer of graupel extending from the top of the mixed layer to the cloud top. Strong extinction in the stratiform regions is inferred to result from slowly-falling, low-density ice aggregates (snow) above the freezing level. These theoretical results are consistent with the T85 measured by TMI, and with the rain rate deduced from PR for the convective and stratiform rain regions. On the basis of this study, the accuracy of the rain rate sensed by TMI is inferred to depend critically on the specification of the convective or stratiform nature of the rain.