Severe hail identification model based on saliency characteristics

Wang Ping; Pan Yue

doi:10.7498/aps.62.069202

Abstract

There are always high false alarm ratios when warning against the severe hail with the severe hail index (SHI) which is supplied by digital weather radar system. To solve this problem, the extraction algorithm with several novel features, such as "overhang", is designed and realized, and these features can describe the severe hail conceptual model from different aspects. Then we take short-time heavy rainfall cells which are easy to be confused with severe hail cells as counter examples to perform statistic analysis for these features and the SHI. Test results show that they have more significant difference between two kinds of samples and hence each of them can reflect one aspect characteristic of severe hail cells. Then a severe hail recognition model that is the Support Vector Machine with radial primary kernel function is learned. Finally, the normalized distance between the sample to be recognized and the optimal separating hyper-plane is determined as a new SHI for warning against the severe hail. Experimental results show that the method proposed in this paper makes severe hail hit ratio higher than the SHI being used and the false alarm ratio is reduced substantially.

Keywords:

Authors and contacts

Wang Ping,
Pan Yue

1.
School of Electrical and Automation Engineering, Tianjin University, Tianjin 300072, China
Funds: Project supported by the Natural Science Foundation of TianJin, China (Grant No. 09JCYBJC07500), and the Special Scientific Research Fund of Meteorological Public Welfare Profession of China (Grant No. GYHY200706004).

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Cited By

[1]	Makitov V 2007 Atmo. Res. 83 380
[2]	Serafin R J, Wilson J W 2000 Bull. Amer. Meteorol. Soc. 81 501
[3]	Holleman I, Wessels H R A, Onvlee J R A, Barlag S J M 2000 Phys. Chem. Earth B-Hydrol. Oceans Atmos. 25 1293
[4]	Lopez L, Sanchez J L 2009 Atmos. Res. 93 358
[5]	Baeck M L, Smith J A 1998 Weather Forecast. 13 416
[6]	Edwards R, Thompson R L 1998 Weather Forecast. 13 277
[7]	Lemon L R 1998 Weather Forecast. 13 327
[8]	Doviak R J, Bringi V, Ryzhkov A, Zahrai A, Zrnic D 2000 J. Atmos. Ocean. Technol. 17 257
[9]	Liang Q Q, Lin L X 2008 Meteorol. Sci. Technol. 2 150 (in Chinese) [梁巧倩, 林良勋 2008 气象科技 2 150]
[10]	Zhang G C 2011 Strong Convection Weather Analysis and Forecasting (1st Ed.) (Beijing: China Meteorological Press) p186 (in Chinese) [章国材 2011 强对流天气分析与预报 (第一版) (北京: 气象出版社) 第186页]
[11]	Zhou Y F, Zhu Y J 2007 J. Anhui Agricult. Sci. 35 9637 (in Chinese) [周叶芳, 朱拥军 2007 安徽农业科学 35 9637]
[12]	Witt A, Eilts M D, Stumpf G J, Johnson J T, Mitchell E D, Thomas K W 1998 Weather Forecast. 13 286
[13]	Lenning E, Fuelberg H E, Watson W I 1998 Weather Forecast. 13 1029
[14]	Zhang J S, Dang J L, Li H C 2007 Acta Phys. Sin. 56 67 (in Chinese) [张家树, 党建亮, 李恒超 2007 56 67]
[15]	Wang F F, Zhang Y R 2012 Acta Phys. Sin. 61 084101 (in Chinese) [王芳芳, 张业荣 2012 61 084101]
[16]	Cai J W, Hu S S, Tao H F 2007 Acta Phys. Sin. 56 6820 (in Chinese) [蔡俊伟, 胡寿松, 陶洪峰 2007 56 6820]
[17]	Cui W Z, Zhu C C, Bao W X, Liu J H 2005 Acta Phys. Sin. 54 3009 (in Chinese) [崔万照, 朱长纯, 保文星, 刘君华 2005 54 3009]

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Catalog

Vol. 62, Issue 6 - 2013-03-20

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