An Algorithm for Automated Identification of Gust Fronts from Doppler Radar Data
- 21 Downloads
Gust fronts are weak narrow-band echoes of increased reflectivity at the background levels in the low-elevation fields of Doppler radar. An automated approach to gust front detection that relies on the image features of radar observations is presented in this paper. The algorithm is not sensitive to the variations in reflectivity values and gust front widths. The approach includes the following steps. First, a novel local binary with dual-template (LBDT) algorithm is designed as the fundamental algorithm to identify the potential areas of narrow-band echoes. Second, based on the disadvantages of the LBDT algorithm, several modifications are made, including splitting the intersecting lines, connecting the fragments, and filtering the edges and radial interference noise. Third, an optical flow method is used to determine whether a weak narrow-band echo is a gust front according to the prior knowledge that a gust front usually propagates in front of the associated generating storm. The results of experiments show that the proposed method can automatically identify gust fronts with a high probability of detection and a low false alarm rate. The automatic identification of gust fronts is potentially useful for accurate short-term weather forecasting, particularly in the forecasting of storm winds.
Key wordsgust fronts weak narrow-band echo automated identification local binary algorithm intersection optical flow method
Unable to display preview. Download preview PDF.
We thank the Meteorological Observation Center of the China Meteorological Administration for providing the radar base data and Bai Li for providing assistance with this work.
- Cao C. Y., Y. Z. Chen, D. H. Liu, et al., 2015: The optical flow method and its application to nowcasting. Acta Meteor. Sinica, 73, 471–480, doi: 10.11676/qxxb2015.034. (in Chinese)Google Scholar
- Delanoy R. L., and S. W. Troxel, 1993: Machine intelligent gust front detection. [Available online at http://citeseerx.ist.psu. edu/viewdoc/summary?doi=10.1.1.230.6211.Google Scholar
- Farnebäck G., 2003: Two-frame motion estimation based on polynomial expansion. Proceedings of the 13th Scandinavian Conference, SCIA 2003, Springer, Halmstad, Sweden, 363–370, doi: 10.1007/3-540-45103-X_50.Google Scholar
- Li G. C., W. H. Guo, L. R. Wang, et al., 2006: Application of gust front to damage wind forecasting. Meteor. Mon., 32, 36–41, doi: 10.3969/j.issn.1000-0526.2006.08.006. (in Chinese)Google Scholar
- Qi L. B., C. H. Chen, and Q. J. Liu, 2006: Application of narrowband echo in severe weather prediction and analysis. Acta Meteor. Sinica, 64, 112–120, doi: 10.3321/j.issn:0577-6619.2006.01.011. (in Chinese)Google Scholar
- Smalley D. J., B. J. Bennett, and R. Frankel, 2005: 8.4 MIGFA: the machine intelligent gust front algorithm for NEXRAD. [Available online at http://citeseerx.ist.psu.edu/viewdoc/summary? doi=10.1.1.371.2090].Google Scholar
- Tao L., Z. H. Yuan, J. H. Dai, et al., 2014: Analysis of the characteristics of a nocturnal bow echo. Acta Meteor. Sinica, 72, 220–236, doi: 10.11676/qxxb2014.027. (in Chinese)Google Scholar
- Xi B. Z., X. D. Yu, L. Sun, et al., 2015: Generating mechanism and type of gust front and its subjective identification methods. Meteor. Mon., 41, 133–142, doi: 10.7519/j.issn.1000-0526.2015.02.001. (in Chinese)Google Scholar
- Xu F., J. Yang, W. M. Xia, et al., 2015: Statistical characteristics and automatic detection of the gust front in radar reflectivity data. Plateau Meteor., 34, 586–595, doi: 10.7522/j.issn.1000-0534.2014.00005. (in Chinese)Google Scholar
- Xu F., J. Yang, H. H. Zheng, et al., 2016: Improvement of the MIGFA technique for identifying gust front and its verification. Meteor. Mon., 42, 44–53, doi: 10.7519/j.issn.1000-0526.2016.01.005. (in Chinese)Google Scholar
- Yu X. D., X. G. Zhou, and X. M. Wang, 2012: The advances in the nowcasting techniques on thunderstorms and severe convection. Acta Meteor. Sinica, 70, 311–337, doi: 10.11676/qxxb2012.030. (in Chinese)Google Scholar
- Zheng J. F., J. Zhang, K. Y. Zhu, et al., 2013: Automatic identification and alert of gust fronts. J. Appl. Meteor. Sci., 24, 117–125, doi: 10.3969/j.issn.1001-7313.2013.01.012. (in Chinese)Google Scholar