CINRAD /SA CIN- RAD /SC 7 S CINRAD CR 1 CR a CR 1 CR

33 5 2014 10 PLATEAU METEOROLOGY Vol. 33 No. 5 October 2014. J. 2014 33 5 1426-1439 doi 10. 7522 /j. issn. 1000-0534. 2013. 00139. 1-3 1 2 4 5 3 1. 210044 2. 100081 3. 330046 4. 100089 5. 337000 6 SCIT > 77% < 26% < 22% SCIT 1000-0534 2014 05-1426-14 doi 10. 7522 /j. issn. 1000-0534. 2013. 00139 P456. 1 A 1 4 5 SCIT 6 SCIT 1-12 1 13 Johnson et al 2 SCIT Storm Cell SCIT Identification and Tracking Algorithm 6561 90% Witt et al 3 SCIT 2013-04-23 2013-10-08 973 2012CB417202 41175038 1979 -. E-mail duan_yiping1979@ 163. com

2 5 1427 2. 1 2011 6 11 12 30-18 00 2012 6 13 12 30-18 00 2013 3 19 18 33-20 06 49 CINRAD /SA CIN- RAD /SC 7 S CINRAD 3. 1. 2 CR 1 CR 2. 2 1a CR 1 CR 3 Table 1 The experience of CR threshold throughout the hail suppression at different station in China X 1 /dbz X 2 /dbz 15 50 16 55 44 17 45 18 SCIT 19 20 VIL 21 22 23 CR 45 30 35 55 60 50 50 55 25 MET ET VIL VIL VIL 3. 1 CR 3. 1. 1 40 dbz 13 14 X 1 = 37 dbz X 2 = 48 dbz 0 1 24 35 50 X 1 X 2 CR 3. 2 ET 3. 2. 1 ET 18 dbz

1428 33 26 32 3. 3. 2 34 ET MET 3 ET MET 3. 2. 2 X 1 = 4 km X 2 = 7 km 0 1 ET 2 1c MET 3 MET ET Table 3 The experience of MET threshold throughout the X 1 = 9 km X 2 = 12 km hail suppression at different station in China ET 0 1 1b ET Table 2 2 ET The experience of ET threshold throughout the hail suppression at different station in China X 1 /km X 2 /km 25 6. 5 8 10 11 26 8 12 15 11 18 12 23 8 16 24 10 11 19 9 12. 5 20 9 11 27 5 10 22 9 X 1 X 2 ET 3. 3 MET 3. 3. 1 7-10 14-17 19-20 28-40 X 1 /km X 2 /km 25 6. 5 26 5 6. 837 26 31 6 8 17 6 8 18 8. 5 23 4 5. 3 19 2 8. 3 28 4 7 X 1 X 2 MET 3. 4 VIL 3. 4. 1 VIL 29 30 VIL 29-30 ET VIL 3. 4. 2 26 32 VIL 4 8 MET > 45 dbz VIL 6837 m VIL 1 min MET > 45 dbz X 1 = 22 kg m - 2 X 2 = 35 kg 300 m m - 2 0 1

5 1429 Table 4 4 VIL The experience of VIL threshold throughout the hail suppression at different station in China X 1 X 2 5. 0 VILD Table 5 5 VILD The experience of VILD threshold throughout the hail suppression at different station in China X 1 X 2 30 7. 0 8. 9 15 44 50 33 42 21 37 34 25 50 23 5 40 24 40 19 30 35 20 40 22 30 50 X 1 X 2 VIL kg m - 2 1d VIL VIL GVIL = VIL j - VIL j-1 1 3. 5 VIL VILD VIL j VIL j - 1 VIL 3. 5. 1 42 GVIL VIL 23 VIL VIL VIL VIL VIL VIL 24 VIL VIL VILD 24 Amburn et al 36 VILD VIL 15 ~ 35 kg m - 2 VIL VIL VILD = VIL /ET VIL 41 VILD 4 g m - 3 2 cm 16 10 ~ 15 min VIL 2006 2 cm VIL 3. 0 ~ 4. 0 g 35 3. 5 Amburn 36 4 16 3 4 17 1 3 20 3. 5 X 1 X 2 VILD g m - 3 3. 6 VIL GVIL 3. 6. 1 VIL GVIL kg m - 2 VIL VIL 10 ~ 20 min VIL VIL 50 kg m - 2 m - 3 3. 5. 2 3. 6. 2 VILD 5 VILD GVIL 6 GVIL X 1 = 1 g m - 3 X 2 = 3. 5 g m - 3 X 1 = 12 kg m - 2 VILD X 2 = 25 kg m - 2 0 GVIL 1 1e 0 1

1430 33 Fig. 1 1 6 CR a ET b MET c VIL d VILD e GVIL f Membership functions of CR a ET b MET c VIL d VILD e and GVIL f Table 6 6 GVIL The experience of the VIL step increment threshold throughout the hail suppression at different station in China X 1 X 2 5. 0 30 7. 0 8. 9 15 44 50 33 40 21 37 34 25 50 23 5 40 24 40 19 30 35 20 40 X 1 X 2 GVIL kg m - 2 1f GVIL 35 SCIT 2-3 6 0. 01 o 0. 01 6 min 1 km 7 SCIT CR ET MET VIL 4. 2 Zadeh 43 Kessinger 44 45 4 4. 1 0 ~ 1 > 0. 5 6

T X X 1 X 2 = 0 X 2 - X X 2 - X 1 {1 P = n j = 1 X X 1 X 1 X X 2 ω j p j 3 j n ω j 4 84. 62% j p j j 15. 38% 26. 67% P n 16 00 14 54 15 18 ω j = 1 4 j = 1 3 ω CR = ω ET = ω MET = ω VIL = ω VILD = ω GVIL = 1 /6. 5 P 0. 5 14 54 3a 4 SCIT 1571 SCIT 1571 14 54 5 5 1431 0. 62 7 39. 58 N 115. 72 E 15 05-15 08 2 cm 39. 65 N 115. 85 E 15 10-15 11 1 cm 3a PPI 5. 1 2011 6 11 5. 1. 1 2011 6 11 4 5 12 30-18 00 11 1571 9 39. 68 N 115. 82 E 1573 39. 97 N 12 30 116. 22 E SCIT SCIT X > X 2 2 2 1 ~ 6 2c SCIT 15 2b c 10 3 8 11 2 12 30-12 45 14 30-14 35 5. 1. 2 3 15 05-64 dbz 12 km VIL 38 kg m - 2 VILD 3. 17 g m - 3 14 58-15 11 5 1 cm 18 00 3b 13 1571 39. 88 N 116. 45 E 0. 59 3 CINRAD / 15 11-16 00 39. 92 N 116. 64 E SA 15 18-15 26 39. 87 N 116. 40

1432 33 2 2011 6 11 12 30-18 00 a b c Fig. 2 Distribution of the surface hail a the simulated hail b and the measured and simulated hail storm c from 12 30 to 18 00 on 11 June 2011. Red triangle area is the ground hail data blue triangle area is simulated operational area the blue circles respectively corresponding to the storm can be worked the conditional probability values can be worked 3 2011 6 11 14 54 a 15 18 b Fig. 3 The simulation operation area and surface hail distribution at 14 54 a and 15 18 b on 11 June 2011 7 2011 6 11 14 54 Table 7 Recognition result of hail weather in Beijing at 14 54 on 11 June 2011 CR /dbz ET /km MET /km VIL / kg m - 2 VILD / g m - 3 GVIL / kg m - 2 1570 67 10 8. 5 44 4. 40-2 0. 61 1571 64 12 11 38 3. 17 4 0. 62 1572 62 10 8 35 3. 50 6 0. 56 1573 61 9 3 35 3. 89 6 0. 50 1574 59 9 4 25 2. 78 1 0. 34 1575 55 7 4 17 2. 43-7 0. 26

E 5 1433 15 20-16 00 39. 96 N 116. 51 E 1 cm 1571 1 1570 40. 07 N 116. 99 E 117. 09 E 0. 6 7 2011 6 11 14 54 40. 13 N 117. 10 E 20 18-20 19 40. 11 N 117. 10 E 20 24-1570 ~ 1573 4 20 25 20 24 40. 22 N 0. 5 1574 1575 117. 23 E 0. 61 0. 5 0. 5 1570 ~ 1573 40. 15 N 117. 12 E 20 35-20 40 1574 1575 1571 1573 4b 5 5. 2 2012 6 13 VIL 18 54 5. 2. 1 24 2012 6 13 42 19 25-20 40 VIL SCIT 4c VILD VIL 1570 VILD 8 4 8 1570 8 SCIT 1570 38. 41 N 114. 63 E 19 42 20 12 40. 16 N 8 2012 6 13 1570 Table 8 No. 1570 storm part time indicator parameters changes in Beijing on 13 June 2012 / E CR / N /dbz Y1 ET /km Y2 MET /km Y3 VIL / kg m - 2 Y4 VILD / g m - 3 Y5 GVIL / kg m - 2 Y6 Y 11 12 117. 68 40. 16 55 1 12 1 3 0. 0 29 0. 27 2. 42 0. 57-1 0. 0 0. 47 11 18 117. 76 40. 17 58 1 13 1 3 0. 0 24 0. 0 1. 85 0. 34-5 0. 0 0. 39 11 24 114. 38 38. 38 53 1 17 1 3 0. 0 24 0. 0 1. 41 0. 16 0. 0 0. 0 0. 36 11 30 114. 46 38. 39 53 1 15 1 3 0. 0 29 0. 27 1. 93 0. 37 5 0. 0 0. 44 11 36 114. 54 38. 39 56 1 13 1 2 0. 0 27 0. 13 2. 08 0. 43-2 0. 0 0. 43 11 42 114. 63 38. 41 57 1 15 1 2 0. 0 46 0. 99 3. 07 0. 83 19 0. 0 0. 64 11 48 117. 31 40. 31 57 1 17 1 3 0. 0 44 0. 98 2. 59 0. 64-2 0. 0 0. 61 11 54 117. 37 40. 32 56 1 17 1 3 0. 0 36 0. 73 2. 12 0. 45-8 0. 0 0. 53 12 00 117. 42 40. 31 57 1 13 1 3 0. 0 33 0. 53 2. 54 0. 62-3 0. 0 0. 52 12 06 117. 04 40. 14 56 1 12 1 6 0. 8 45 0. 99 3. 75 1 12 0. 0 0. 80 12 12 117. 09 40. 16 58 1 10 0. 67 3 0. 0 39 0. 93 3. 90 1-6 0. 0 0. 60 12 18 117. 15 40. 20 60 1 12 1 2 0. 0 42 1 3. 5 1 3 0. 0 0. 67 12 24 117. 23 40. 22 59 1 13 1 1 0. 0 38 0. 87 2. 92 0. 77-4 0. 0 0. 61 Y1 ~ Y6 Y

1434 33 Fig. 4 4 1570 a CR b VIL c VILD The change of hail suppression indicators and membership function for No. 1570 storm. a the CR value and membership function b the VIL value and membership function c the VILD value and membership function 9 2012 6 13 19 25-20 40 Table 9 The measured point and the corresponding recently body scanning of the hail contrast storm track simulation operational areas in Beijing at 19 25-20 40 on 13 June 2012 /mm 19 25-19 26 19 30-19 32 117. 10 E 40. 13 N 8 117. 02 E 40. 18 N 7 19 39-19 40 116. 65 E 40. 74 N 8 11 24 1572 116. 54 E 40. 66 N 3 0. 50 19 40-19 44 117. 09 E 40. 20 N 8 19 45-19 52 117. 13 E 40. 19 N 8 11 42 1571 117. 23 E 40. 32 N 2 0. 55 19 46-19 51 117. 12 E 40. 15 N 8 11 42 1571 117. 23 E 40. 32 N 2 0. 55 20 18-20 19 117. 10 E 40. 13 N 8 12 12 1570 117. 09 E 40. 16 N 6 0. 60 20 24-20 25 117. 98 E 28. 45 N 7 12 12 1570 117. 09 E 40. 16 N 6 0. 60 19 25-19 26 117. 12 E 40. 15 N 7 12 24 1570 117. 23 E 40. 22 N 0. 61 5. 2. 2 11 15 05-15 08 117. 98 E 28. 45 N 9 6 7 mm SCIT 1570 66. 7% 3 9 59 dbz 20 24 1570 117. 23 E 40. 22 N 1 13 km VIL 38 kg m - 2 VILD

5 1435 5 2012 6 13 a b 20 12 c 20 12 Fig. 5 Distribution images of the surface hail and simulated hail storm in Beijing on 13 June 2012. a the surface hail and simulated at all times b all simulated storm track distribution hail storm at 20 12 c simulation operational storm distribution and parallel time surface hail data at 20 12 Fig. 6 6 2013 3 20 a 00 18 b Distribution images of the surface hail and simulated hail storm in Jiangxi at all times a and distribution of simulation operational storm and parallel time surface hail data at 00 18 b on 20 March 2013

1436 33 10 2012 6 13 20 24 Table 10 The hail recognition results in Beijing at 20 24 on 13 June 2012 CR /dbz ET /km MET /km VIL / kg m - 2 VILD / g m - 3 GVIL / kg m - 2 1570 59 13 12 38 2. 92-4 0. 61 1571 55 12 9 28 2. 33-1 0. 46 1572 53 9 8 13 1. 44 1 0. 25 1588 46 7 6 3 0. 43-1 0. 26 2. 92 g m - 3 0. 61 10 40. 16 N 117. 09 E 8 10 1570 0. 6 20 24-20 25 40. 11 N < 0. 5 0. 5 117. 10 E 20 18-20 19 40. 13 N 1570 117. 10 E 1571 1572 1588 20 24 1570 5. 3 2013 3 19-20 1 2013 3 19 18 33-20 06 49 2012 6 13 5a CINRAD /SA 15 13 20 12 5b 22 26 6a 12 2 5c 3 80% 20% 1570 8 11 2013 3 19 18 33-20 06 49 Table 11 The hail the measured point and the corresponding recently body scanning contrast storm track simulation operational areas in Jiangxi from 18 33 on 19 to 06 49 on 20 March 2013 /mm 19 18 33 115. 98 E 29. 58 N 9 19 20 30 113. 80 E 27. 88 N 5 1572 113. 84 E 27. 91 N 0. 69 2 19 21 31 114. 91 E 28. 23 N 6 1572 114. 93 E 28. 12 N 0. 70 3 19 22 27 115. 55 E 28. 06 N 3 19 22 50 116. 68 E 28. 70 N 1 1572 117. 45 E 28. 89 N 0. 61 2 20 00 12 117. 43 E 28. 40 N 2 1573 117. 45 E 28. 22 N 0. 56 1 20 00 19 118. 25 E 28. 68 N 3 1577 118. 31 E 28. 74 N 0. 53 6 20 00 23 117. 98 E 28. 45 N 17 1573 117. 97 E 28. 48 N 0. 75 6 20 00 38 118. 20 E 28. 43 N 3 1573 118. 20 E 28. 44 N 0. 71 4 20 01 13 115. 41 E 27. 33 N 5 1570 115. 50 E 27. 41 N 0. 77 4 20 03 24 114. 16 E 26. 58 N 4 1571 114. 23 E 26. 59 N 0. 79 4 20 05 53 115. 35 E 26. 35 N 25 1571 115. 55 E 26. 34 N 0. 67 2 20 05 59 114. 55 E 25. 80 N 15 20 06 06 116. 01 E 26. 48 N 5 1570 116. 13 E 26. 59 N 0. 69 2 20 06 49 116. 35 E 26. 35 N 4 1570 116. 22 E 26. 35 N 0. 79 2

6b 3 20 00 18 6 2 5 2 20 00 19 20 00 23 11 6b 2013 3 20 20 18 SCIT 6 6b 1577 118. 31 E 28. 74 N 0. 53 20 00 19 118. 25 E 28. 68 N 1573 117. 97 E 28. 48 N 20 00 23 117. 98 E 28. 45 N 6 5 1437 1 13 286-303. CR ET 4 MET VIL D. VILD GVIL 6 2 6 2012 70 6 1347-1355. SCIT 7 J SCIT 1. J. 1991 10 3 317-324. 2 Johnson J T MacKeen P L Witt A. The storm cell identification and tracking algorithm An enhanced WSR - 88D algorithm J. Wea Forecasting 1998 13 263-276. 3 Witt A Eilts M D Stumpf G J et al. An enhanced hail detection algorithm for the WSR - 88D J. Wea Forecasting 1998. 1998. 5. J. 2002 30 2 127-128 117-118.. J... 2012 31 3 836-846. 8. J. 2011 30 1 252-257. 3 9 J. 2012 31 1 269-276. 22 26 10 17 5 6 J. 77. 27% 26. 09% 11 22. 73% 2011 30 4 1108-1118. 4 12 15 38 J. issn. 1000-0534. 2012. 00053. 11 4 26 13 80% 20% J. 14. D. 2006. 2013 3 19 18 33-20 06 49 15 J. 16 S J - 1349. 17... 2011 30 4 1119-1131.. J.. 2013 32 2 556-563 doi 10. 7522 /j.. 2005 31 9 39-43.. 2011 33 11 132-135... 2008 27 6 1343 2011 5 J.

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5 1439 Application of CINRAD Mosaic Products on Artificial Hail Suppression DUAN Yiping 1-3 LIU Shoudong 1 LIU Liping 2 MA Jianli 4 YE Xiaofeng 5 WANG Guanhua 3 1. Yale - NUIST Center on Atmospheric Environment of Nanjing University of Information Science & Technology Nanjing 210044 China 2. State Key Laboratory of Severe Weather Chinese Academy of Meteorological Sciences Beijing 100081 China 3. Jiangxi Meteorological Service Center Nanchang 330046 China 4. Beijing Weather Modification Office Beijing 100089 China 5. Pingxiang in Jiangxi Province Meteorological Bureau Pingxiang 337000 China Abstract On basis of the distribution characteristics of reflectivity mosaic of China new generation weather radar CINRAD six indexes are suggested to identify hail cloud during hail suppression by artificial means which include composite reflectivity CR echo top ET maximum reflectivity of ET MET vertical integrated liquid VIL density of VIL VILD and gradient of VIL GVIL respectively. Some indexes are calculated depending on storm cell identification and tracking SCIT form the fuzzy logical method to identify the suppression area. The results indicate that the method of three-dimensional hail recognition experiment are applied multiple hail fall alone in Beijing and Jiangxi. To contrast the hail observation data calculation of the accuracy are greater than 77% the false ratio is below 26% empty ratio below 22% through multiple example. Consider the portfolio reflectance characteristics of three-dimensional shape distribution of fuzzy logic method can w ell i- dentify most workable hail cloud tracking simulation effect is good is conducive to effective application in figure hail proof operation. The hail clouds w hich need to be suppressed by artificial means can mostly be identified according to the characteristics of reflectivity mosaic and fuzzy logical method. The method has a better tracking effect and a promising application in hail suppression. Key words Radar mosaic Fuzzy-logical discrimination The Storm Cell Identification and Tracking SCIT Index of suppresion Hail suppression