• Atmosphere
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• v.23 no.2
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• pp.161-169
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• 2013

We examine the effects of the sea surface temperature (SST) distribution on heavy snowfall over the Yellow Sea using high-resolution SST products and WRF (Weather Research and Forecasting) model simulations in 30 December 2010. First, we evaluate the model by comparing the simulated and observed fresh snowfall over the Korean peninsula (Ho-Nam province). The comparison shows that the model reproduces the distributions and magnitudes of the observed snowfall. We then conduct sensitivity model simulations where SST perturbations by ${\pm}1.1^{\circ}C$ relative to baseline SST values (averaged SST for $5{\sim}15^{\circ}C$) are uniformly specified over the region of interest. Results show that ${\pm}1.1^{\circ}C$ SST perturbation simulations result in changes of air temperature by $+0.37/-0.38^{\circ}C$, and by ${\pm}0.31^{\circ}C$ hPa for sea level pressure, respectively, relative to the baseline simulation. Atmospheric responses to SST perturbations are found to be relatively linear. The changes in SST appear to perturb precipitation variability accounting for 10% of snow and graupel, and 18% of snowfall over the Yellow Sea and Ho- Nam province, respectively. We find that anomalies of air temperature, pressure, and hydrometeors due to SST perturbation propagate to the upper part of cloud top up to 500 hPa and show symmetric responses with respect to SST changes.

• Proceedings of the Korea Water Resources Association Conference
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• 2009.05a
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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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.2
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• pp.123-130
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• 1992

We check up on whether the one-dimensional station precipitation model of Geogakakos and Bras is suitable to the storm model for Chonju station or not. The fundamental variables of the physically based model consists of the pressure at the cloud top, the hight-averaged updraft velocity(HAUV), and the inverse of the average diameter of the hydrometeors(ADH) at cloud base. And they are parameterized by input variables. The parameters are eastimated by the direct search algorithm of Hooke and Jeeves in this paper. The results show that HAUV and ADH are dominant factors to minimize root mean square error between the calculated and the observed rainfall. In this numerical analysis, the deviation between the calculated and the total observed rainfall is small, otherwise the gap for the time distribution is quite big.

• Atmosphere
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• v.18 no.4
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• pp.317-338
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• 2008

Analyses of observational data and numerical simulations were performed to understand the mechanism of MCSs (Mesoscale Convective Systems) occurred on 13-14 July 2004 over Jindo area of the Korean Peninsula. Observations indicated that synoptic environment was favorable for the occurrence of heavy rainfall. This heavy rainfall appeared to have been enhanced by convergence around the Changma front and synoptic scale lifting. From the analyses of storm environment using Haenam upper-air observation data, it was confirmed that strong convective instability was present around the Jindo area. Instability indices such as K-index, SSI-index showed favorable condition for strong convection. In addition, warm advection in the lower troposphere and cold advection in the middle troposphere were detected from wind profiler data. The size of storm, that produced heavy rainfall over Jindo area, was smaller than $50{\times}50km^2$ according to radar observation. The storm developed more than 10 km in height, but high reflectivity (rain rate 30 mm/hr) was limited under 6 km. It can be judged that convection cells, which form cloud clusters, occurred on the inflow area of the Changma front. In numerical simulation, high CAPE (Convective Available Potential Energy) was found in the southwest of the Korean Peninsula. However, heavy rainfall was restricted to the Jindo area with high CIN (Convective INhibition) and high CAPE. From the observations of vertical drop size distribution from MRR (Micro Rain Radar) and the analyses of numerically simulated hydrometeors such as graupel etc., it can be inferred that melted graupels enhanced collision and coalescence process of heavy precipitation systems.

• Atmosphere
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• v.24 no.2
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• pp.173-188
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• 2014

The KMA has cooperated with the Oklahoma University in USA to develop a Polarimetric Radar Data (PRD) simulator to improve the microphysical processes in Korea Local Analysis and Prediction System (KLAPS), which is critical for the utilization of PRD into Numerical Weather Prediction (NWP) field. The simulator is like a tool to convert NWP data into PRD, so it enables us to compare NWP data with PRD directly. The simulator can simulate polarimetric radar variables such as reflectivity (Z), differential reflectivity ($Z_{DR}$), specific differential phase ($K_{DP}$), and cross-correlation coefficient (${\rho}_{hv}$) with input of the Drop Size Distribution (DSD) and scattering calculation of the hydrometeors. However, the simulator is being developed based on the foreign observation data, therefore the PRD simulator development reflecting rainfall characteristics of Korea is needed. This study analyzed a potential application of the 2-Dimension Video Disdrometer (2DVD) data by calculating the raindrop axis ratio according to the rain-types to reflect Korea's rainfall characteristics into scattering module in the simulator. The 2DVD instrument measures the precipitation DSD including the fall velocity and the shape of individual raindrops. We calculated raindrop axis ratio for stratiform, convective and mixed rainfall cases after checking the accuracy of 2DVD data, which usually represent the scattering characteristics of precipitation. The raindrop axis ratio obtained from 2DVD data are compared with those from foreign database in the simulator. The calculated the dual-polarimetric radar variables from the simulator using the obtained raindrop axis ratio are also compared with in situ dual-polarimetric observation data at Bislsan (BSL). 2DVD observation data show high accuracies in the range of 0.7~4.8% compared with in situ rain gauge data which represents 2DVD data are sufficient for the use to simulator. There are small differences of axis ratio in the diameter below 1~2 mm and above 4~5 mm, which are more obvious for bigger raindrops especially for a strong convective rainfall case. These differences of raindrop axis ratio between domestic and foreign rainfall data base suggest that the potential use of disdrometer observation can develop of a PRD simulated suitable to the Korea precipitation system.

• Atmosphere
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• v.29 no.3
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• pp.311-324
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• 2019

We employed a Multi-Angle Snowflake Camera (MASC) to quantitatively analyze snow particles at the ground level in the Yeongdong region of Korea. The MASC captures high-resolution photographs of hydrometeors from three angles and simultaneously measures fallspeed. Based on snowflake images of the several episodes in 2017 and 2018, we derived statistics of size, aspect ratio, orientation, complexity, and fallspeed of snow crystals, which generally showed similar characteristics to the previous studies in other regions of the world. Dominant snow crystal habits of January 22, 2018 generated by northerly were melted aggregates when 850 hPa temperature was about $-6{\sim}-8^{\circ}C$. Average fallspeed of snow crystals was $1.0m\;s^{-1}$ though its size gradually increased as temperature decreased. Another snowfall event (March 8, 2018) was driven by the baroclinic instability as accompanied with a deep trough. Snow crystal habits were largely rimed aggregates (complexity ~1.8) and melting particles of dark images. Meanwhile, in the extreme snowfall event whose snow rate was greater than $10cm\;hr^{-1}$ on January 20, 2017, main snow crystals appeared to be heavily rimed particles with relatively smaller size when convective clouds developed vertically up to 9 km in association with tropopause folding. MASC also could successfully measure a decrease in snow crystal size and an increase in riming degree after AgI seeding at Daegwallyeong on March 14, 2017.

• Korean Journal of Remote Sensing
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• v.14 no.1
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• pp.53-68
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• 1998

Observation of hydrometeors' behavior in the atmosphere is important to understand weather and climate. By conventional observations, we can get the distribution of water vapor at limited number of points on the earth. In this study, the precipitable water has been estimated from the split window channel data on GMS-5 based upon the technique developed by Chesters et al.(1983). To retrieve the precipitable water, water vapor absorption parameter depending on filter function of sensor has been derived using the regression analysis between the split window channel data and the radiosonde data observed at Osan, Pohang, Kwangiu and Cheju staions for 4 months. The air temperature of 700 hPa from the Global Spectral Model of Korea Meteorological Administration (GSM/KMA) has been used as mean air temperature for single layer radiation model. The retrieved precipitable water for the period from August 1996 through December 1996 are compared to radiosonde data. It is shown that the root mean square differences between radiosonde observations and the GMS-5 retrievals range from 0.65 g/$cm^2$ to 1.09 g/$cm^2$ with correlation coefficient of 0.46 on hourly basis. The monthly distribution of precipitable water from GMS-5 shows almost good representation in large scale. Precipitable water is produced 4 times a day at Korea Meteorological Administration in the form of grid point data with 0.5 degree lat./lon. resolution. The data can be used in the objective analysis for numerical weather prediction and to increase the accuracy of humidity analysis especially under clear sky condition. And also, the data is a useful complement to existing data set for climatological research. But it is necessary to get higher correlation between radiosonde observations and the GMS-5 retrievals for operational applications.