• Journal of Environmental Science International
• /
• v.16 no.10
• /
• pp.1127-1137
• /
• 2007

We focused on effects on data assimilation of simulated wind fields by using upper-air observations (wind profiler and sonde data). Local Analysis Prediction System (LAPS), a type of data assimilation system, was used for wind field modeling. Five cases of simulation experiments for sensitivity analysis were performed: which are EXP0) non data assimilation, EXP1) surface data, EXP2) surface data and sonde data, EXP3) surface data and wind profiler data, EXP4) surface data, sonde data and wind profiler data. These were compared with observation data. The result showed that the effects of data assimilation with wind profiler data were found to be greater than sonde data. The delicate wind fields in complex coastal area were simulated well in EXP3. EXP3 and EXP4 using wind profiler data with vertically high resolution represented well sophisticated differences of wind speed compared with EXP1 and EXP2, this is because the effects of wind profiler data assimilation were sensitively adjusted to first guess field than those of sonde observations.

• Journal of Environmental Science International
• /
• v.19 no.8
• /
• pp.983-999
• /
• 2010

Wind power energy is one of the favorable and fast growing renewable energies. It is most important for exact analysis of wind to evaluate and forecast the wind power energy. The purpose of this study is to improve the performance of numerical atmospheric model by data assimilation over a complex coastal area. The benefit of the profiler is its high temporal resolution and dense observation data at the lower troposphere. Three wind profiler sites used in this study are inhomogeneously situated near south-western coastal area of Korean Peninsula. The method of the data assimilation for using the profiler to the model simulation is the three-dimensional variational data assimilation (3DVAR). The experiment of two cases, with/without assimilation, were conducted for how to effect on model results with wind profiler data. It was found that the assimilated case shows the more reasonable results than the other case compared with vertical observation and surface Automatic Weather Station(AWS) data. Although the effect of sonde data was better than profiler at a higher altitude, the profiler data improves the model performance at lower atmosphere. Comparison with the results of 4 June and 5 June suggests that the efficiency with hourly assimilated profiler data is strongly influenced by synoptic conditions. The reduction rate of Normalized Mean Error(NME), mean bias normalized by averaged wind speed of observation, on 4 June was 28% which was larger than 13% of 5 June. In order to examine the difference in wind power energy, the wind power density(WPD) was calculated and compared.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.14 no.2
• /
• pp.275-282
• /
• 2019

Clusters generated by features such as mountains or buildings are considered as the contaminated data that are independent of atmospheric phenomena. The basic way to reduce the clutter signal is to install a clutter fence around the wind profiler. In order to investigate the effect of clutter fence on the wind profiler data, the wind vector collection rate and wind vector accuracy of wind profiler was investigated before and after clutter fence installation. The clutter fence of wind profiler contributed to improve the data quality as well as the data collection rate.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.14 no.1
• /
• pp.61-68
• /
• 2019

In addition to non-meteorological echoes, meteorological echoes with large scattering effects, such as precipitation, cause errors in wind data measured by wind profiler. In the rainfall situation, the Doppler spectrum of wind profiler shows both the rainfall signal and the atmospheric signal as two peaks. The vertical radial velocity is very large due to the falling rain drop. The radial velocity contaminated by rainfall decreases the accuracy of the horizontal wind vector and leads to inaccurate weather analysis. In this study, we developed an algorithm to process raw data of wind profiler and distinguished rainfall signal and wind signal by partitioning bimodal peak for Doppler spectrum in rainfall environment.

• Asian Journal of Atmospheric Environment
• /
• v.4 no.3
• /
• pp.198-210
• /
• 2010

Precise analysis of local winds for the prediction of atmospheric phenomena in the planetary boundary layer is extremely important. In this study, wind profiler data with fine time resolution and density in the lower troposphere were used to improve the performance of a numerical atmospheric model of a complex coastal area. Three-dimensional variational data assimilation (3DVAR) was used to assimilate profiler data. Two experiments were conducted to determine the effects of the profiler data on model results. First, we performed an observing system experiment. Second, we implemented a sensitivity test of data assimilation intervals to extend the advantages of the profiler to data assimilation. The lowest errors were observed when using both radio sonde and profiler data to interpret vertical and surface observation data. The sensitivity to the assimilation interval differed according to the synoptic conditions when the focus was on the surface results. The sensitivity to the weak synoptic effect was much larger than to the strong synoptic effect. The hourly-assimilated case showed the lowest root mean square error (RMSE, 1.62 m/s) and highest index of agreement (IOA, 0.82) under weak synoptic conditions, whereas the statistics in the 1, 3, and 6 hourly-assimilated cases were similar under strong synoptic conditions. This indicates that the profiler data better represent complex local circulation in the model with high time and vertical resolution, particularly when the synoptic effect is weak.

• Journal of Integrative Natural Science
• /
• v.8 no.3
• /
• pp.221-232
• /
• 2015

In this study, the vertical characteristics of wind were analyzed using the horizontal wind, vertical wind, and vertical wind shear, which are generated from a wind profiler during concentrated heavy rain, and the quantitative characteristics of concentrated heavy rain were analyzed using CAPE, SWEAT, and SRH, among the stability indexes. The analysis of the horizontal wind showed that 9 cases out of 10 had a low level jet of 25 kts at altitudes lower than 1.5 km, and that the precipitation varied according to the altitude and distribution of the low-level jet. The analysis of the vertical wind showed that it ascended up to about 3 km before precipitation. The analysis of the vertical wind shear showed that it increased up to a 1 km altitude before precipitation and had a strong value near 3 km during heavy rains. In the stability index analysis, CAPE, which represents thermal buoyancy, and SRH, which represents dynamic vorticity, were used for the interpretation of the period of heavy rain. As SWEAT contains dynamic upper level wind and thermal energy, it had a high correlation coefficient with concentrated-heavy-rain analysis. Through the case studies conducted on August 12-13, 2012, it was confirmed that the interpretation of the prediction of the period of heavy rain was possible when using the intensive observation data from a wind profiler and the stability index.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.15 no.6
• /
• pp.1037-1044
• /
• 2020

Since radar wind profiler (RWP) provides wind field data with high time and space resolution in all weather conditions, their verification of the accuracy and quality is essential. The simultaneous wind measurement from rawinsonde is commonly used to evaluate wind vectors from RWP. In this study, the simulation algorithm which produces the spectrum and raw time series (I/Q) data from the average values of moments is presented as a step-by-step verification method for the signal processing algorithm. The possibility of the simulation algorithm was also confirmed through comparison with the raw data of LAP-3000. The Doppler power spectrum was generated by assuming the density function of the skew-normal distribution and by using the moment values as the parameter. The simulated spectrum was generated through random numbers. In addition, the coherent averaged I/Q data was generated by random phase and inverse discrete Fourier transform, and raw I/Q data was generated through the Dirichlet distribution.

• Journal of Environmental Science International
• /
• v.19 no.6
• /
• pp.689-701
• /
• 2010

The effects of high-resolution wind profiler (HWP) data on the wind distributions were evaluated in two different coastal areas during the study period (23-26 August, 2007), indicating weak-gradient flows. The analysis was performed using the Weather Research and Forecasting (WRF) model coupled with a three-dimensional variational (3DVAR) data assimilation system. For the comparison purpose, two coastal regions were selected as: a southwestern coastal (SWC) region characterized by a complex shoreline and a eastern coastal (EC) region surrounding a simple coastline and high mountains. The influence of data assimilation using the HWP data on the wind distributions in the SWC region was moderately higher than that of the EC region. In comparison between the wind speed and direction in the two coastal areas, the application of the HWP data contributed to improvement of the wind direction distribution in the SWC region and the wind strength in the EC region, respectively. This study suggests that the application of the HWP data exerts a large impact on the change in wind distributions over the sea and thus can contribute to the solution to lack of satellite and buoy data with their observational uncertainty.

• Korean Journal of Remote Sensing
• /
• v.34 no.2_1
• /
• pp.249-265
• /
• 2018

The Korea Meteorological Administration has been operating wind profiler at 9 stations since the year of 2007. Among these stations, Bukgangneung is the only one that produces regularly both rawinsonde and wind profiler wind measurements at the same time. In this study, wind profiler measurements were compared with rawinsonde wind at Bukgangneung. Unlike most other studies which have used the temporal measurements for several days in summer season, in this study the routine rawinsonde measurments during almost one year (2016) were employed for the accuracy test of the wind. The monthly mean maximum observation height in Bukgangneung shows a large seasonal variation; it was relatively high in summer (4,310 m in July) and low in winter (2,130 m in December). The vertical observation rates at the altitude above these heights were less than 50%. The monthly and vertical wind comparison between rawinsonde and wind profiler shows that absolute bias and RMSE of zonal and meridional wind velocity are mostly less than 1 m/s and less than 2 m/s, respectively. In winter season the RMSE of wind velocity increased to 2~3 m/s. However, at some high altitudes and certain months, large errors were found. It is shown that these errors were related with very weak wind (less than 1 m/s) of wind profiler at 3,500~4,000 m from January to May and dramatic changes of wind the height of 1,500~2,500 m for in April. For Snow events the errors were lower than those for the winter season and for the heavy rain events the errors increased to 3~4 m/s at the height of 4~5 km.

• Journal of Korea Multimedia Society
• /
• v.22 no.12
• /
• pp.1396-1403
• /
• 2019

The radar wind profiler data contaminates with various non-atmospheric components that produce errors in moments and wind velocity estimations. This study implemented an adaptive Gaussian model to detect and remove the clutter from the radar return. This model includes DC filtering, ground clutter recognition, Gaussian fitting, and cost function to mitigate the clutter component. The adaptive model tested for the various types of clutter components and found that it is effective in clutter removal process. It is also applied for the both time series and spectrum datasets. The moments estimated using this method are compared with those derived using conventional DC-filtering clutter removal method. The comparisons show that the proposed method effectively removes the clutter and produce reliable moments.