• 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.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.435-440
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• 2002

The objective of this study is to analyze the relationship between polarimetric radar backscatters and stand characteristics over the mountainous forest area. L- and P-band full polarimetric airborne SAR data obtained in September 2000 were processed to compare with forest stand maps and ground collected stand variables. After the geometric registration of SAR image, mean radar backscatters were extracted for those ground plots where the stand parameters, such as tree height, DBH, and basal area, were measured during and after the SAR data acquisition. Preliminary analysis was focused on the topographic influence of radar backscattering under the homogeneous forest stand condition. Topographic effects, assessed by the local incidence angles, were different obvious in L-band data while it was not clear with P-band data.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1329-1338
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• 2021

Rain radar provides high spatio-temporal radar rainfall that can be used as input data to short-term precipitation forecasting models. Korea Institute of Civil Engineering and Building Technology (KICT) has developed a flash flood forecasting system that is providing flash flood forecasting based on short-term rainfall forecasts estimated by the radar rainfall. Accuracy of the radar rainfall as well as the short-term rainfall forecasts, however, can deteriorate when radar polarimetric variables have error. In this study, we develope real-time program that can correct the error inherent in the radar polarimetric variables. First, effect according to the correction of the error was verified using 363 rainfall events on non real-time. The accuracy (1-NE) of the radar rainfall was approximately 70% and correlation coefficient was higher than 0.8 after correcting the error on non real-time. The accuracy (1-NE) using the real-time program was also approximately 70% after correcting the error.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5B
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• pp.487-495
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• 2010

Soil moisture is a crucial factor in hydrological system which influences runoff, energy balance, evaporation, and atmosphere. United States National Aeronautic and Space Administration (NASA) and Department of Agriculture (USDA) have established Soil Moisture Experiment (SMEX) since 2002 for the global observations. SMEX provides useful data for the hydrological science including soil moisture and hydrometeorological variables. The purpose of this study is to investigate the relationship between remotely sensed soil moisture data from aircraft and satellite and ground based experiment. C-band of Polarimetric Scanning Radiometer (PSR) that observed the brightness temperature provides soil moisture data using a retrieval algorithm. It was compared with the In-situ data for 2-30 cm depth at four sites. The most significant depth is 2-10 cm from the correlation analysis. Most of the sites, two data are similar to the mean of data at 10 cm and the median at 7 cm and 10 cm at the 10% significant level using the Rank Sum test and t-test. In general, soil moisture data using the C-band of the PSR was established to fit the Normal, Log-normal and Gumbel distribution. Soil moisture data using the aircraft and satellites will be used in hydrological science as fundamental data. Especially, the C-band of PSR will be used to prove soil moisture at 7-10 cm depths.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.283-285
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• 2005

To account for the importance of variable in multi-sensor data fusion, random forests are applied to supervised land-cover classification. The random forests approach is a non-parametric ensemble classifier based on CART-like trees. Its distinguished feature is that the importance of variable can be estimated by randomly permuting the variable of interest in all the out-of-bag samples for each classifier. Supervised classification with a multi-sensor remote sensing data set including optical and polarimetric SAR data was carried out to illustrate the applicability of random forests. From the experimental result, the random forests approach could extract important variables or bands for land-cover discrimination and showed good performance, as compared with other non-parametric data fusion algorithms.

• Korean Journal of Remote Sensing
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• v.22 no.3
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• pp.211-219
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• 2006

A random forests classifier is applied to multi-sensor data fusion for supervised land-cover classification in order to account for the importance of variable. The random forests approach is a non-parametric ensemble classifier based on CART-like trees. The distinguished feature is that the importance of variable can be estimated by randomly permuting the variable of interest in all the out-of-bag samples for each classifier. Two different multi-sensor data sets for supervised classification were used to illustrate the applicability of random forests: one with optical and polarimetric SAR data and the other with multi-temporal Radarsat-l and ENVISAT ASAR data sets. From the experimental results, the random forests approach could extract important variables or bands for land-cover discrimination and showed reasonably good performance in terms of classification accuracy.

• Journal of Korea Water Resources Association
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• v.47 no.12
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• pp.1227-1237
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• 2014

Dual-polarization can distinguish precipitation type and dual-polarization is provide not only meteorological phenomena in the atmosphere but also non-precipitation echoes. Therefore dual-polarization radar can improve radar estimates of rainfall. However polarimetric measurements by transmitting vertically vibration waves and horizontally vibrating waves simultaneously is contain systematic bias of the radar itself. Thus the calibration bias is necessary to improve quantitative precipitation estimation. In this study, the calibration bias of reflectivity (Z) and differential reflectivity ($Z_{DR}$) from the Bislsan dual-polarization radar is calculated using the 2-Dimensional Video Disdrometer (2DVD) data. And an improvement in rainfall estimation is investigated by applying derived calibration bias. A total of 33 rainfall cases occurring in Daegu from 2011 to 2012 were selected. As a results, the calibration bias of Z is about -0.3 to 5.5 dB, and $Z_{DR}$ is about -0.1 dB to 0.6 dB. In most cases, the Bislsan radar generally observes Z and $Z_{DR}$ variables lower than the simulated variables. Before and after calibration bias, compared estimated rainfall from the dual-polarization radar with AWS rain gauge in Daegu found that the mean bias has fallen by 1.69 to 1.54 mm/hr, and the RMSE has decreased by 2.54 to 1.73 mm/hr. And estimated rainfall comparing to the surface rain gauge as ground truth, rainfall estimation is improved about 7-61%.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.324-327
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• 2008

Microwave remote sensing has great potential, especially in monsoon Asia, since optical observations are often hampered by cloudy conditions. The radar backscattering characteristics of rice crop were investigated with a ground-based automatic scatterometer system. The system was installed inside a shelter in an experimental paddy field at the National Institute of Agricultural Science and Technology (NIAST) before transplanting. The rice cultivar was a kind of Japonica type, called Chuchung. The scatterometer system consists of X-band antennas, HP8720D vector network analyzer, RF cables, and a personal computer that controls frequency, polarization and data storage. This system automatically measures fully-polarimatric backscattering coefficients of rice crop every 10 minutes, accompanied by a digital camera that takes pictures in a fixed position with the same interval. The backscattering coefficients were calculated by applying a radar equation. Plant variables, such as leaf area index (LAI), biomass, plant height and weather conditions were measured periodically throughout the rice growth season. We have performed polarimetric decomposition of paddy data such as single, double and volume scattering to extract the scattering information effectively. We investigated the relationships between backscattering coefficients and the plant variables.

• Journal of Astronomy and Space Sciences
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• v.29 no.1
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• pp.69-77
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• 2012

This report describes the inception, development and extensive use over 30 years of elliptical polarimeters at the University of Pennsylvania. The initial Mark I polarimeter design utilized oriented retarder plates and a calcite Foster-Clarke prism as the analyzer. The Mark I polarimeter was used on the Kitt Peak 0.9 m in 1969-70 to accomplish a survey of approximately 70 objects before the device was relocated to the 0.72 m reflector at the Flower and Cook Observatory. Successive generations of automation and improvements included the early-80's optical redesign to utilize a photoelastic modulated wave plate and an Ithaco lock-in amplifier-the photoelastic modulating polarimeter. The final design in 2000 concluded with a fully remote operable device. The legacy of the polarimetric programs includes studies of close binaries, pulsating hot stars, and luminous late-type variables.

• Journal of Korea Water Resources Association
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• v.49 no.7
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• pp.625-634
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• 2016

Three leading agencies under different ministries - Korea Meteorological Administration (KMA) in the ministry of Environment, Han river control office in the Ministry of Land, Infrastructure and Transport (MOLIT) and Weather Group of ROK Air Force in the Ministry of National Defense (MND) - have been operated radars in the purpose of observing weather, hydrology and military operational weather in Korea. Eight S-band dual-pol. radars have been newly installed or replaced by these ministries over different places by 2015. However each ministry has different aims of operating radars, observation strategies, data processing algorithms, etc. Due to the differences, there is a wide level of accuracy on observed radar data as well as the composite images made of the cross governmental radar measurement. Gaining fairly high level of accuracy on radar data obtained by different agencies has been shared as a great concern by the ministries. Thus, "an agreement of harmonizing weather and hydrological radar products" was made by the three ministries in 2010. Particularly, this is very important to produce better rainfall estimation using the cross governmental radar measurement. Weather Radar Center(WRC) in KMA has been developed an empirical method using measurements observed by Yongin testbed radar. This study is aiming to examine the efficiency of the empirical method to improve the accuracies of radar rainfalls estimated from cross governmental dual-pol. radar measurements. As a result, the radar rainfalls of three radars (Baengnyeongdo, Biseulsan, and, Sobaeksan Radar) were shown improvement in accuracy (1-NE) up to 70% using data from May to October in 2015. Also, the range of the accuracies in radar rainfall estimation, which were from 30% to 60% before adjusting polarimetric variables, were decreased from 65% to 70% after adjusting polarimetric variables.