• Wind and Structures
• /
• v.12 no.4
• /
• pp.349-381
• /
• 2009

Since 1998, several institutions have deployed mobile instrumented towers to collect research-grade meteorological data from landfalling tropical cyclones. This study examines the wind flow characteristics from seven landfalling tropical cyclones using data collected from eight individual mobile tower deployments which occurred from 1998-2005. Gust factor, turbulence intensity, and integral scale statistics are inspected relative to changing surface roughness, mean wind speed and storm-relative position. Radar data, acquired from the National Weather Service (NWS) Weather Surveillance Radar - 1988 Doppler (WSR-88D) network, are examined to explore potential relationships with respect to radar reflectivity and precipitation structure (convective versus stratiform). The results indicate tropical cyclone wind flow characteristics are strongly influenced by the surrounding surface roughness (i.e., exposure) at each observation site, but some secondary storm dependencies are also documented.

• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.361-365
• /
• 2002

Rain-rate retrieval using the NOAA/AMSU (Advanced Microwave Sounding Unit) (Zaho et al., 2001) has been implemented at METRI/KMA since 2001. Here, we present the results of the AMSU derived rain-rate and validation result, especially for the rainfall associated with the tropical cyclone for 2001. For the validation, we use rain-rate derived from the ground based radar and/or rainfall observation from the rain gauge in Korea. We estimate the bias score, threat score, bias, RMSE and correlation coefficient for total of 16 tropical cyclone cases. Bias score shows around 1.3 and it increases with the increasing threshold value of rain-rate, while the threat score extends from 0.4 to 0.6 with the increasing threshold value of precipitation. The averaged rain-rate for at all 16 cases is 3.96mm/hr and 1.41mm/hr for the retrieved from AMSU and the ground observation, respectively. On the other hand, AMSU rain-rate shows a much better agreement with the ground based observation over inner part of tropical cyclone than over the outer part (Correlation coefficient for convective region is about 0.7, while it is only about 0.3 over the stratiform region). The larger discrepancy of tile correlation coefficient with the different part of the tropical cyclone is partly due to the time difference in between ice water path and surface rainfall. This results indicates that it might be better to develop the algorithm for different rain classes such as convective and stratiform.

• Korean Journal of Remote Sensing
• /
• v.34 no.3
• /
• pp.465-480
• /
• 2018

On 20 January 2017, the fresh snow cover which is more than 20 cm, accompaning with lightning occurred over Yeongdong coastal region for the first 3-hour of the heavy snowfall event. This study analyzed sounding observations in the heavy snow period which were including the measurements of wind profiler, radiometer and rawinsonde. The features examined from the vertical wind and temperature data at the two adjacent stations, Bukgangneung and Gangneung-Wonju National University, are summarized as follows: 1) The strong (30-40 kts) north-east winds were observed in the level from 2 to 6 km. The Strong atmospheric instability was found from 4 to 6 km, in which the lapse rate of temperature was about $-18^{\circ}C\;km^{-1}$. These features indicate that the deep convective cloud develops up to the height of 6 km in the heavy snowfall period, which is shown in the satellite infrared images. 2) The cooling was observed in the level below 1 km. At this time, the surface air temperature at Bukgangneung station decreased by $4^{\circ}C$. The narrow cooling zone estimated from AWS and buoy data was located in east-west direction. These are the features observed in the cold front of extratropical cyclone. The distributions of radar echo and lightning also show the same shape in east-west direction. Therefore, the results indicate that the Yeongdong thundersnow event was the combined precipitation system of deep convective cloud and cold frontal precipitation.

• Journal of the Korean earth science society
• /
• v.23 no.4
• /
• pp.369-379
• /
• 2002

The characteristics of the East Asian summer monsoon circulation associated with the cool and wet summer of 1993 and the warm and dry summer of 1994 are investigated by analyzing the atmospheric circulations features in the upper and lower troposphere and by examining the global SST and associated tropical convective precipitation fields. The negative geopotential height anomalies at 500 hPa and 200 hPa in 1993 over East Asia, the central North Pacific, and the western United States were replaced by positive ones in 1994. In addition, the 200 hPa zonal wind anomaly averaged over the East Asian summer monsoon region is negatively correlated with the Korean summer temperature anomaly. The subtropical jet stream in 1993 was displaced into the central part of Korea well south of its normal position. The western Pacific subtropical high was shifted southward, and the East Asian summer rainfall and temperature was above-normal and below-normal, respectively due to the southwestward extension of a cold and dry polar airmass from the Sea of Okhotsk to the Est Sea. In contrast, the subtropical jet stream in 1994 was displaced well north of its normal position. The abrupt northward shift of the western Pacific subtropical high was accompanied with the rapid northward movement of the rain band of the East Asian summer monsoon rainfall. The anomaly patterns of the East Asia summer rainfall and temperature were opposite to those of 1993. Large sea surface temperature anomalies of opposite signs existed in the tropical Pacific with a mature El $Ni{\~{n}o$ in 1993 and a weak La $Ni{\~{n}a$ condition in 1994. The role of the anomalous convective precipitation in the western Pacific and the Indian Ocean related with the variations in the low-level cross-equatorial flow along the northwestern periphery of the Australian high and the Mascarene high is probably to influence a large-scale atmospheric circulation over the East Asia during both the years.

• Journal of the Korean earth science society
• /
• v.33 no.2
• /
• pp.113-125
• /
• 2012

The estimations of the surface rain intensity and rain-related physical variables derived from two independent Tropical Rainfall Measuring Mission (TRMM) satellite sensors, TRMM Microwave Imager (TMI) and Precipitation Radar (PR), were compared over four different oceans. The precipitating clouds developed most frequently in the warmest sea surface temperature (SST) region of the west Pacific, which is 1.5 times more frequent than in the east Pacific and the tropical Atlantic oceans. However, the east Pacific exhibited the most intense rain intensity for the convective and mixed rain types while the tropical Atlantic showed the most intense rain intensity for all TMI rainy pixels. It was found that the deviation of TMI-derived rain rate yielded a big difference in region-to-region and rain type-to-type if the PR rain intensity value is assumed to be closer to the truth. Furthermore, the deviation by rain types showed opposite signs between convective and non-convective rain types. It was found that the region-to-region deviation differences reached more than 200% even though the selected tropical oceans have relatively similar geophysical environments. Therefore, the validation for the microwave rain estimation needs to be performed according to both rain types and climate regimes, and it also requires more sophisticated TMI algorithm which reflects the locality of rainfall characteristics.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2002.05a
• /
• pp.43-50
• /
• 2002

Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict streamflow and flash floods. Previously, neural networks were used to develop a Quantitative Precipitation Forecasting (QPF) model that highly improved forecasting skill at specific locations in Pennsylvania, using both Numerical Weather Prediction (NWP) output and rainfall and radiosonde data. The objective of this study was to improve an existing artificial neural network model and incorporate the evolving structure and frequency of intense weather systems in the mid-Atlantic region of the United States for improved flood forecasting. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as life time, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. The new Quantitative Flood Forecasting (QFF) model was applied to predict streamflow peaks with lead-times of 18 and 24 hours over a five year period in 4 watersheds on the leeward side of the Appalachian mountains in the mid-Atlantic region. Threat scores consistently above .6 and close to 0.8 ∼ 0.9 were obtained fur 18 hour lead-time forecasts, and skill scores of at least 4％ and up to 6％ were attained for the 24 hour lead-time forecasts. This work demonstrates that multisensor data cast into an expert information system such as neural networks, if built upon scientific understanding of regional hydrometeorology, can lead to significant gains in the forecast skill of extreme rainfall and associated floods. In particular, this study validates our hypothesis that accurate and extended flood forecast lead-times can be attained by taking into consideration the synoptic evolution of atmospheric conditions extracted from the analysis of large-area remotely sensed imagery While physically-based numerical weather prediction and river routing models cannot accurately depict complex natural non-linear processes, and thus have difficulty in simulating extreme events such as heavy rainfall and floods, data-driven approaches should be viewed as a strong alternative in operational hydrology. This is especially more pertinent at a time when the diversity of sensors in satellites and ground-based operational weather monitoring systems provide large volumes of data on a real-time basis.

• Atmosphere
• /
• v.18 no.3
• /
• pp.183-197
• /
• 2008

The purpose of this study is to summarize tropical cyclone activity in 2007. 24 tropical cyclones of tropical storm (TS) intensity or higher formed in the western North Pacific and the South China Sea in 2007. The total number is less than the thirty-year (1971~2000) average frequency of 26.7. Out of twenty four tropical cyclones, 14 TCs reached typhoon (TY) intensity, while the rest 10 only reached severe tropical storm (STS) and tropical storm (TS) intensity - four STS and six TS storms. The tropical cyclone season in 2007 began in April with the formation of KONG-REY (0701). From April to May, two TCs formed in the western North Pacific in response to enhanced convective activity there. From June to July, convective activity turned inactive over the sea around the Philippines and in the South China Sea, and the subtropical high was weak over the south of Japan. MAN-YI (0704) and USAGI (0705) moved northwestward and hit Japan, bringing serious damage to the country. After August, convective activity became enhanced over the sea east of the Philippines, and the subtropical high turned strong over the sea south of Japan. Many TCs, which formed over the sea east of the Philippines and in the South China Sea, moved westward and hit China and Vietnam. PABUK (0706), WUTIP (0707), SEPAT (0708), WIPHA (0712), LEKIMA (0714) and KROSA (0715) brought serious damage to some countries including China, the Philippines and Vietnam. On the other hand, FITOW (0709) and NARI (0711) moved northward, bringing serious damage to Japan and Korea. After HAIYAN (0716), all four TCs except FAXAI (0720) formed over the sea east of $140^{\circ}E$. Three typhoons among them affected Republic of Korea, MAN-YI (0704), USAGI (0705) and NARI (0711). Particularly, NARI (0711) moved northward and made landfall at Goheng Peninsula ($34.5^{\circ}N$, $127.4^{\circ}E$) in 1815 KST 16 September. Due to $11^{th}$ typhoon NARI, strong wind and record-breaking rainfall amount was observed in Jeju Island. It was reported that the daily precipitation was 420.0 mm at Jeju city, Jeju Island on 16 September the highest daily rainfall since Jeju began keeping records in 1927. This typhoon hit the southern part of the Korean peninsula and Jeju Island. 18 people lost their lives, 14,170 people were evacuated and US$ 1.6 billion property damage was occurred.

• Atmosphere
• /
• v.20 no.1
• /
• pp.37-47
• /
• 2010

The methods measuring the precipitation drop size distribution(hereafter referred to as DSD) at Cloud Physics Observation System (CPOS) in Daegwallyeong are to use PARSIVEL (PARticle SIze and VELocity) disdrometer (hereafter referred to as PARSIVEL) and Micro Rain Radar (hereafter referred to as MRR). First of all, PARSIVEL and MRR give good correlation coefficients between their rain rates and those of rain gage: $R^2=0.93$ and 0.91, respectively. For the DSD, the rain rates are classified in 3 categories (Category 1: rr (Rain Rate) ${\leq}0.5\;mm\;h^{-1}$, Category 2: $0.5\;mm\;h^-1$ < rr < $4.0\;mm\;h^{-1}$, Category 3: rr ${\geq}4\;mm\;h^{-1}$). The shapes of PARSIVEL and MRR DSD are relatively most similar in category 2. In addition, we retrieve the vertical rain rate and liquid water content from MRR under melting layer, calculated by Cha et al's method, in Daegwallyeong ($37^{\circ}41{\prime}N$, $128^{\circ}45^{\prime}E$, 843 m ASL, mountain area) and Haenam ($34^{\circ}33^{\prime}N$, $126^{\circ}34^{\prime}E$, 4.6 m ASL, coast area). The vertical variations of rain rate and liquid water content in Daegwallyeong are smaller than those in Haenam. We think that this different vertical rain rate characteristic for both sites is due to the vertical different cloud type (convective and stratiform cloud seem dominant at Haenam and Daegwallyeong, respectively). This suggests that the statistical precipitation DSD model, for the application of weather radar and numerical simulation of precipitation processes, be considered differently for the region, which will be performed in near future.

• Atmosphere
• /
• v.14 no.1
• /
• pp.24-43
• /
• 2004

This paper describes the detailed characteristics of heavy rainfall events occurred in Chungcheong province on 15 and 16 April and from 6 to 8 August 2002 based on the analysis of raingauge rainfall rate and radar reflectivity from the METRI's X-band Weather Radar located in Cheongju. A synoptic analysis of the case is carried out, first, and then the analysis is devoted to seeing how the radar observes the case and how much information we obtain. The highly resolved radar reflectivity of horizontal and vertical resolutions of 1 km and 500 m, respectively shows a three-dimensional structure of the precipitating system, in a similar sequence with the ground rainfall rate. The radar echo classification algorithm for convective/stratiform cloud is applied. In the convectively-classified area, the radar reflectivity pattern shows a fair agreement with that of the surface rainfall rate. This kind of classification using radar reflectivity is considered to be useful for the precipitation forecasting. Another noteworthy aspect of the case includes the effect of topography on the precipitating system, following the analysis of the surface rainfall rate, topography, and precipitating system. The results from this case study offer a unique opportunity of the usefulness of weather radar for better understanding of structural and variable characteristics of flash flood-producing heavy rainfall events, in particular for their improved forecasting.

• Journal of Korea Water Resources Association
• /
• v.50 no.5
• /
• pp.335-346
• /
• 2017

This study generated the radar-based forecasted rainfall using spatial-scale decomposition method (SCDM) and evaluated the hydrological applicability with forecasted rainfall by KMA (MAPLE, KONOS) in terms of urban flood forecasting. SCDM is to separate the small-scale field (convective cell) and large-scale field (straitform cell) from radar rainfield. And each separated field is forecasted by translation model and storm tracker nowcasting model for improvement of QPF accuracy. As the evaluated results of various QPF for three rainfall events in Seoul and Metropolitan area, proposed method showed better prediction accuracy than MAPLE and KONOS considering the simplicity of the methodology. In addition, this study assessed the urban hydrological applicability for Gangnam basin. As the results, KONOS simulated the peak of water depth more accurately than MAPLE and SCDM, however cannot simulated the timeseries pattern of water depth. In the case of SCDM, the quantitative error was larger than observed water depth, but the simulated pattern was similar to observation. The SCDM will be useful information for flood forecasting if quantitative accuracy is improved through the adjustment technique and blending with NWP.