Kim H.-L.,Weather Radar Center |
Suk M.-K.,Weather Radar Center |
Park H.-S.,National Meteorological Satellite Center |
Lee G.-W.,Kyungpook National University |
Ko J.-S.,Weather Radar Center
Atmospheric Measurement Techniques | Year: 2016
Polarimetric measurements are sensitive to the sizes, concentrations, orientations, and shapes of raindrops. Thus, rainfall rates calculated from polarimetric radar are influenced by the raindrop shapes and canting. The mean raindrop shape can be obtained from long-term raindrop size distribution (DSD) observations, and the shapes of raindrops can play an important role in polarimetric rainfall algorithms based on differential reflectivity (ZDR) and specific differential phase (KDP). However, the mean raindrop shape is associated with the variation of the DSD, which can change depending on precipitation types and climatic regimes. Furthermore, these relationships have not been studied extensively on the Korean Peninsula. In this study, we present a method to find optimal polarimetric rainfall algorithms for the Korean Peninsula by using data provided by both a two-dimensional video disdrometer (2DVD) and the Bislsan S-band dual-polarization radar. First, a new axis-ratio relation was developed to improve radar rainfall estimations. Second, polarimetric rainfall algorithms were derived by using different axis-ratio relations. The rain gauge data were used to represent the ground truth situation, and the estimated radar-point hourly mean rain rates obtained from the different polarimetric rainfall algorithms were compared with the hourly rain rates measured by a rain gauge. The daily calibration biases of horizontal reflectivity (ZH) and differential reflectivity (ZDR) were calculated by comparing ZH and ZDR radar measurements with the same parameters simulated by the 2DVD. Overall, the derived new axis ratio was similar to the existing axis ratio except for both small particles (≤ 2ĝ€mm) and large particles (≥ 5.5ĝ€mm). The shapes of raindrops obtained by the new axis-ratio relation carried out with the 2DVD were more oblate than the shapes obtained by the existing relations. The combined polarimetric rainfall relations using ZDR and KDP were more efficient than the single-parameter rainfall relation for estimated 2DVD rainfall; however, the R(ZH, ZDR) algorithm showed the best performance for radar rainfall estimations, because the rainfall events used in the analysis consisted mainly of weak precipitation and KDP is relatively noisy at lower rain rates (≤ 10ĝ€mmĝ€hĝ'1). Some of the polarimetric rainfall algorithms can be further improved by new axis-ratio relations. © Author(s) 2016.
Park S.-G.,Weather Radar Center |
Kim J.-H.,Weather Radar Center |
Ko J.-S.,Weather Radar Center |
Lee G.,Kyungpook National University
Journal of Atmospheric and Oceanic Technology | Year: 2016
The Ministry of Land, Infrastructure and Transport (MOLIT) of South Korea operates two S-band dualpolarimetric radars, as of 2013, to manage water resources through quantitative rainfall estimations at the surface level. However, the radar measurements suffer from range ambiguity. In this study, an algorithm based on fuzzy logic is developed to identify range overlaid echoes using seven inputs: standard deviations of differential reflectivity SD(ZDR), differential propagation phase SD(φDP), correlation coefficient SD(ρHV) and spectrum width SD(σν), mean of ρHV and σν, and difference of φDP from the system offset ΔφDP. An examination of the algorithm's performance shows that these echoes can be well identified and that echoes strongly affected by second trip are highlighted by high probabilities, over 0.6; echoes weakly affected have probabilities from 0.4 to 0.6; and those with low probabilities, below 0.4, are assigned as echoes without range ambiguity. Aquantitative analysis of a limited number of cases using the usual skill scores shows that when the probability of 0.4 is considered as a threshold for identifying the range overlaid echoes, they can be identified with a probability of detection of 90%, a false alarm rate of 6%, and a critical success index of 84%. © 2016 American Meteorological Society.
Oh Y.-A.,Kyungpook National University |
Lee D.,Kyungpook National University |
Jung S.-H.,Weather Radar Center |
Nam K.-Y.,Weather Radar Center |
Lee G.,Kyungpook National University
Advances in Meteorology | Year: 2016
The effects of attenuation correction in rainfall estimation with X-band dual-polarization radar were investigated with a dense rain gauge network. The calibration bias in reflectivity (Z H) was corrected using a self-consistency principle. The attenuation correction of Z H and the differential reflectivity (Z D R) were performed by a path integration method. After attenuation correction, Z H and Z D R were significantly improved, and their scatter plots matched well with the theoretical relationship between Z H and Z D R. The comparisons between the radar rainfall estimation and the rain gauge rainfall were investigated using the bulk statistics with different temporal accumulations and spatial averages. The bias significantly improves from 70% to 0% with R (Z H). However, the improvement with R (Z H, Z D R) was relatively small, from 3% to 1%. This indicated that rainfall estimation using a polarimetric variable was more robust at attenuation than was a single polarimetric variable method. The bias did not show improvement in comparisons between the temporal accumulations or the spatial averages in either rainfall estimation method. However, the random error improved from 68% to 25% with different temporal accumulations or spatial averages. This result indicates that temporal accumulation or spatial average (aggregation) is important to reduce random error. © 2016 Young-A Oh et al.
Suk M.-K.,Kyungpook National University |
Chang K.-H.,National typhoon Center |
Cha J.-W.,Weather Radar Center |
Kim K.-E.,Kyungpook National University
Journal of the Meteorological Society of Japan | Year: 2013
An operational real-time adjusted radar-automatic weather station (AWS) rain rate (RAD-RAR) system, using 10 radars of the Korea Meteorological Administration (KMA), has been developed for the South Korea region. The procedure of the RAD-RAR system consists of four steps for real-time operation: 1) the quality control of volumetric reflectivity for each radar, 2) the computation of the rain-gauge rain rate every 10 min. within each radar, 3) the real-time (updated every 10 min.) rainfall estimation by the Z-R relationship minimizing the difference between the 10-min constant altitude plan position indicator and rain-gauge rain rate based on window probability matching method (WPMM) andby the real-time bias correction of RAD-RAR conductedat 10 min. intervals for each radar by making the bias, and4) the composition of estimated rainfall data of the 10 radars. It is noted that this RAD-RAR system is available only for summer rainfall cases with the absence of bright bandaround1.5 km in height, as the system does not include bright bandcorrection. The performance of RAD-RAR was examinedfor the 10 heavy rainfall events of 2006, andwe obtainedresults suggesting that the real-time Z-R adjustment of RAD-RAR is better in terms of the agreement with the rain-gauge rain rate than that of the previously fixedZ-R relationship, andthe additional bias correction of RAD-RAR yields slightly better results. A square of correlation coefficient R2 = 0.84 was obtained between the daily accumulatedobservedandRAD-RAR estimatedrainfall. © 2013, Meteorological Society of Japan.
Jeong J.-H.,Pukyong National University |
Lee D.-I.,Pukyong National University |
Wang C.-C.,National Taiwan Normal University |
Jang S.-M.,Pukyong National University |
And 2 more authors.
Annales Geophysicae | Year: 2012
To understand the different environment and morphology for heavy rainfall during 9-10 July 2007, over the Korean Peninsula, mesoscale convective systems (MCSs) that accompanied the Changma front in two different regions were investigated. The sub-synoptic conditions were analysed using mesoscale analysis data (MANAL), reanalysis data, weather charts and Multi-functional Transport Satellite (MTSAT-IR) data. Dual-Doppler radar observations were used to analyse the wind fields within the precipitation systems. During both the case periods, the surface low-pressure field intensified and moved northeastward along the Changma front. A low-level warm front gradually formed with an east-west orientation, and the cold front near the low pressure was aligned from northeast to southwest. The northern convective systems (meso-α-scale) were embedded within an area of stratiform cloud north of the warm front. The development of low-level pressure resulted in horizontal and vertical wind shear due to cyclonic circulation. The wind direction was apparently different across the warm front. In addition, the southeasterly flow (below 4 km) played an important role in generating new convective cells behind the prevailing convective cell. Each isolated southern convective cell (meso-β-scale) moved along the line ahead of the cold front within the prefrontal warm sector. These convective cells developed when a strong southwesterly low-level jet (LLJ) intensified and moisture was deeply advected into the sloping frontal zone. A high equivalent potential temperature region transported warm moist air in a strong southwesterly flow, where the convectively unstable air led to updraft and downdraft with a strong reflectivity core. © 2012 Author(s). CC Attribution 3.0 License.
Yoon J.,Weather Radar Center |
Yoo C.,Korea University |
Ha E.,Yonsei University
Advances in Meteorology | Year: 2015
Ground-truthing is a major problem in the satellite estimation of rain rate. This problem is that the measurement taken by the satellite sensor is fundamentally different from the one it is compared with on the ground. Additionally, since the satellite has the limited capability to measure the light rain rate exactly, the comparison should also consider the threshold value of satellite rain rate. This paper proposes a ground-truth design with threshold for the satellite rain rate. This ground-truth design is the generalization of the conventional ground-truth design which considered the only (zero, nonzero) and (nonzero, nonzero) measurement pairs. The mean-square error is used as an index of accuracy in estimating the ground measurement by satellite measurement. An application to the artificial random field shows that the proposed ground-truth design with threshold is valid as the design bias is zero. The same result is also derived in the application to the COMS (Communication, Ocean, and Meteorological Satellite) rain rate data in Korea. Copyright © 2015 Jungsoo Yoon et al.
Jang M.,Pukyong National University |
Lee D.-I.,Pukyong National University |
You C.-H.,Weather Radar Center |
Kim D.-S.,Japan National Research Institute for Earth Science and Disaster Prevention |
And 3 more authors.
Atmospheric Research | Year: 2012
In order to improve the accuracy of quantitative precipitation estimates, we correct radar reflectivity measurements by a "sorting and moving average" (SMA) method and with a POSS (precipitation occurrence sensing system) disdrometer. The correction procedure, optimized by a polynomial least-square fit of the data, greatly reduces errors in rainfall estimates. The Zc-R relationships for different cloud types are calculated using a classification algorithm. A VPR threshold algorithm is used to investigate the accuracy of rainfall estimates depending on the cloud type. For stratiform and convective cloud types, rainfall estimates were more accurate when the correction was taken into account, with statistical errors substantially reduced.The developed algorithm successfully reduced errors in the rainfall estimates and improved their accuracy. This new quantitative precipitation estimate (QPE) algorithm will improve the reliability of radar-based quantitative rainfall measurements and the accuracy of weather forecasts. © 2011 Elsevier B.V.
Lee Y.-R.,Yonsei University |
Shin D.-B.,Yonsei University |
Kim J.-H.,Yonsei University |
Park H.-S.,Weather Radar Center
Atmospheric Measurement Techniques | Year: 2015
Continuous rainfall measurements from ground-based radars are crucial for monitoring and forecasting heavy rainfall-related events such as floods and landslides. However, complete coverage by ground-based radars is often hampered by terrain blockage and beam-related errors. In this study, we presented a method to fill the radar gap using surrounding radar-estimated precipitation and observations from a geostationary satellite. The method first estimated the precipitation over radar gap areas using data from the Communication, Ocean, and Meteorological Satellite (COMS); the first geostationary satellite of Korea. The initial precipitation estimation from COMS was based on the rain rate-brightness temperature relationships of a priori databases. The databases were built with temporally and spatially collocated brightness temperatures at four channels (3.7, 6.7, 10.8, and 12 Î1/4m) and Jindo (126.3° E, 34.5° N) radar rain rate observations. The databases were updated with collocated data sets in a timespan of approximately one hour prior to the designated retrieval. Then, bias correction based on an ensemble bias factor field (Tesfagiorgis et al., 2011b) from radar precipitation was applied to the estimated precipitation field. Over the radar gap areas, this method finally merged the bias-corrected satellite precipitation with the radar precipitation obtained by interpolating the adjacent radar observation data. The merging was based on optimal weights determined from the root-mean-square error (RMSE) with the reference sensor observation or equal weights in the absence of reference data. This method was tested for major precipitation events during the summer of 2011 with assumed radar gap areas. The results suggested that successful merging appears to be closely related to the quality of the satellite precipitation estimates. © Author(s) 2015.
Jeong J.-H.,Weather Radar Center |
Lee D.-I.,Pukyong National University |
Wang C.-C.,National Taiwan Normal University |
Han I.-S.,National Institute of Fisheries Science
Natural Hazards and Earth System Sciences | Year: 2016
An extreme-rainfall-producing mesoscale convective system (MCS) associated with the Changma front in southeastern South Korea was investigated using observational data. This event recorded historic rainfall and led to devastating flash floods and landslides in the Busan metropolitan area on 7 July 2009. The aim of the present study is to analyse the influences for the synoptic and mesoscale environment, and the reasons that the quasi-stationary MCS causes extreme rainfall. Synoptic and mesoscale analyses indicate that the MCS and heavy rainfall occurred in association with a stationary front which resembled a warm front in structure. A strong southwesterly low-level jet (LLJ) transported warm and humid air and supplied the moisture toward the front, and the air rose upwards above the frontal surface. As the moist air was conditionally unstable, repeated upstream initiation of deep convection by back-building occurred at the coastline, while old cells moved downstream parallel to the convective line with training effect. Because the motion of convective cells nearly opposed the backward propagation, the system as a whole moved slowly. The back-building behaviour was linked to the convectively generated cold pool and its outflow boundary, which played a role in the propagation and maintenance of the rainfall system. As a result, the quasi-stationary MCS caused a prolonged duration of heavy rainfall, leading to extreme rainfall over the Busan metropolitan area. © 2016 Author(s).
Kim J.,Pusan National University |
Han H.,Weather Radar Center |
Yu J.,Pusan National University |
Lee H.,Pusan National University |
Kim S.,Pusan National University
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013
This paper proposes genetic-based k-nearest neighbor method for chaff echo identification. Weather radar provides various data: location, velocity, direction, and range of typhoon or precipitation, precipitation intensity, altitude and location of thunderstorm and rainfall. Above this data, topography echo, anomalous echo, second echo and chaff echo are observed from weather radar, and they are disrupt weather forecasting. They are called non-weather echo. In order to improve weather forecasting, we propose genetic-basedk-nearest neighbor for chaff echo identification. Experimental result shows that chaff echoes are well removed, so performance weather forecasting will also be improved. © 2013 Springer-Verlag Berlin Heidelberg.