基于探空资料因子组合分析方法的冰雹预报

刘晓璐; 刘建西; 张世林; 刘平

基于探空资料因子组合分析方法的冰雹预报

四川省人工影响天气办公室，成都 610072

资助项目:

中国气象局气象新技术面上推广项目 CMATG2010M21

详细信息

通信作者:
刘晓璐, email: suoyingchuang@163.com

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出版历程
- 收稿日期: 2013-05-07
- 修回日期: 2013-11-20
- 刊出日期: 2014-03-31

Hail Forecast Based on Factor Combination Analysis Method and Sounding Data

Sichuan Weather Modification Office, Chengdu 610072

摘要

摘要: 以1978—2007年四川省宜宾探空站200 km范围内共45例降雹事件与非降雹事件作为时间样本，将利用T-lnp探空资料计算表征热力、动力、水汽条件、温度、高度等物理参数作为预报因子，采用因子组合分析方法对3244个预报因子进行筛选，找出影响宜宾探空站附近降雹的预报因子，并计算得到它们的阈值及组合关系，建立了冰雹预报指标判别式。两个主要因子为400 hPa饱和湿静力温度与850 hPa湿静力温度之差 (T_σ400^*-T_σ850) 和400 hPa与地面垂直气压梯度之差 (G_z400-G_zsurface)，两个条件因子为700 hPa水汽压与饱和水汽压之差 (e₇₀₀-e_s700) 和700 hPa露点温度与饱和湿静力温度之差 (T_d700-T_σ700^*)。将2008年全年732例时次的T-lnp探空资料代入判别式进行试报，探测率为84%，空报率为67.7%，成功指数为30.4%，试报结果表明：基于探空资料因子组合分析方法得到的冰雹预报指标判别方法可行，具有一定准确性。
- 因子组合分析方法;
- 探空指标;
- 冰雹预报
Abstract: The emergence of the small probability of severe weather events is attributed to specific factor combinations of some early meteorological elements. The nonlinear and complicated characteristics of factor combinations can be used to find the relationship between forecast object and forecast factors. Based on this method, the relationship between hail events in the south of Sichuan Basin and some meteorological elements calculated by the sounding data is investigated, and a hail forecast index discriminant is established. The discriminant is physically significant and applied in daily operation.Hailstorm is a meso-scale weather system with the temporal scale of several to dozens of hours, and the horizontal scale of several hundred kilometers. In real business, the T-lnp sounding data are observed at 0800 BT and 2000 BT every day, and the hail forecasting is carried out every 12 hours. A sample sets of 7 hail events and 38 non-hail events near Yibin Station is established. Using the T-lnp sounding data, 3422 meteorological elements are calculated as forecast factors, including temperature, height, moisture, saturation vapor pressure, potential pseudo-equivalent temperature, K index and so on. Based on factors combination analysis method, 2 main factors and 2 conditional factors are selected from 3422 meteorological elements and their critical values are calculated. The main factors are T_σ400^*-T_σ850 and G_z400-G_zsurface, and the conditional factors are e₇₀₀-e_s700 and T_d700-T_σ700^*, T_σ400^* stands for saturated wet static temperature at 400 hPa, and T_σ850 stands for wet static temperature at 850 hPa; G_z400 and G_zsurface stand for vertical pressure gradient at 400 hPa and the surface level; e₇₀₀ and e_s700 stand for vapour pressure and saturated vapour pressure at 700 hPa; T_d700 and T_σ700^* stand for dew point temperature and saturated wet static temperature at 700 hPa. The hail forecast indexes discriminant nearby Yibin Station is established using these data.The environmental state of hailstorm generation and the unstable mechanism of severe convective weather can be explained by the hail forecast indexes discriminant, which is evaluated using historical records of the year of 2008. Among 65 warnings, the real hail events never miss but the false alarm ratio reaches 67.7%, which should be further distinguished using radar observations. The overall probability of detection is 84%, and the critical success index is 30.4%. The result shows that factor combination analysis method is feasible to some extent.
- factor combination analysis method;
- sounding index;
- hail forecasting

HTML全文

表 1 降雹事件样本

Table 1 Hail event samples

序号	探空资料时间	降雹时间	降雹地点	降雹地与探空站距离/km	降雹地海拔/m	冰雹直径/mm
1	1983-04-10T20：00	22:47	宜宾	0	341	5
2	1985-08-06T08：00	17:57	荣县	72	382	20
3	1994-07-18T08：00	16:45	隆昌	88	374	9
4	1994-07-27T08：00	15:12	井研	106	419	8
5	1998-04-28T08：00	18:42	珙县	48	368	14
6	2000-07-20T08：00	17:18	井研	106	419	20
7	2002-04-04T08：00	18:50	自贡	61	357	8

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表 2 Y序列与前10个主要因子序列

Table 2 Sequence Y and sequence of top 10 major factors

样本	Y	X′₁	X′₂	X′₃	X′₄	X′₅	X′₆	X′₇	X′₈	X′₉	X′₁₀
1	1	1	1	1	1	1	1	1	1	1	1
2	1	1	1	1	1	1	1	1	1	1	1
3	1	1	1	1	1	1	1	1	1	1	1
4	1	1	1	1	1	1	1	1	1	1	1
5	1	1	1	1	1	1	1	1	1	1	1
6	1	1	1	1	1	1	1	1	1	1	1
7	1	1	1	1	1	1	1	1	1	1	1
8	0	1	0	1	1	1	1	1	1	1	1
9	0	1	1	1	1	1	1	1	1	1	1
10	0	0	0	0	0	0	0	0	0	0	0
11	0	0	0	0	0	0	0	0	0	0	0
12	0	0	0	0	0	0	0	0	0	0	0
13	0	0	0	0	0	0	0	0	0	0	0
14	0	0	0	0	0	0	0	0	0	0	0
15	0	0	0	0	0	0	0	0	0	0	0
16	0	1	1	1	1	1	1	1	1	1	1
17	0	0	0	1	1	0	0	1	1	1	1
18	0	0	0	0	0	0	0	0	0	0	0
19	0	0	0	0	0	0	0	0	0	0	0
20	0	0	0	0	0	0	0	0	0	0	0
21	0	0	0	0	0	0	0	0	0	0	0
22	0	0	0	0	0	0	0	0	0	0	0
23	0	0	0	0	0	0	0	0	0	0	0
24	0	0	0	0	0	0	0	0	0	0	0
25	0	0	0	0	1	0	0	1	1	1	1
26	0	1	1	1	1	1	1	1	1	1	1
27	0	1	1	0	0	1	1	0	0	0	0
28	0	0	0	0	0	0	0	0	0	0	0
29	0	0	0	0	0	0	0	0	0	0	0
30	0	0	0	0	0	0	0	0	0	0	0
31	0	0	0	0	0	0	0	0	0	0	0
32	0	0	0	0	0	0	0	0	0	0	0
33	0	0	0	0	0	0	0	0	0	0	0
34	0	0	0	0	0	0	0	0	0	0	0
35	0	0	1	1	1	1	1	1	1	1	1
36	0	0	1	1	1	1	1	1	1	1	1
37	0	0	0	0	0	0	0	1	1	1	1
38	0	0	0	0	0	0	0	0	0	0	0
39	0	0	0	0	0	0	0	0	0	0	0
40	0	0	0	1	0	1	1	0	0	0	0
41	0	1	0	1	1	1	1	1	1	1	1
42	0	1	1	1	1	1	1	1	1	1	1
43	0	0	1	0	1	1	1	1	1	1	1
44	0	0	1	1	0	0	0	0	0	0	0
45	0	0	1	0	1	1	1	1	1	1	1

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表 3 主要因子组合序列及其前8个条件因子序列

Table 3 Sequence of major factor combination and its top 8 condition factors

样本	Y	V′_1∧2	Y′	Y″	X″₁	X″₂	X″₃	X″₄	X″₅	X″₆	X″₇	X″₈
1	1	1	0	1	1	1	1	1	1	1	1	0
2	1	1	0	1	1	0	0	0	0	0	0	0
3	1	1	0	1	1	1	1	1	1	1	1	1
4	1	1	0	1	1	1	1	1	1	1	0	0
5	1	1	0	1	1	1	1	1	1	1	1	1
6	1	1	0	1	1	1	1	0	0	0	0	1
7	1	1	0	1	0	1	1	1	1	1	1	1
8	0	0	0	1	0	0	1	0	1	0	1	0
9	0	1	1	0	0	0	0	0	0	0	0	0
10	0	0	0	1	1	1	1	1	1	1	1	0
11	0	0	0	1	1	1	1	1	1	1	1	1
12	0	0	0	1	1	1	1	1	1	1	1	1
13	0	0	0	1	1	1	1	1	1	1	1	1
14	0	0	0	1	1	1	1	1	1	1	1	1
15	0	0	0	1	1	1	1	1	1	1	1	1
16	0	1	1	0	0	0	0	0	0	0	0	0
17	0	0	0	1	1	1	1	1	1	1	0	1
18	0	0	0	1	1	1	1	0	1	1	1	0
19	0	0	0	1	1	1	1	1	1	1	1	0
20	0	0	0	1	1	1	1	1	1	1	1	1
21	0	0	0	1	1	1	1	1	1	1	1	0
22	0	0	0	1	1	1	1	1	1	1	1	0
23	0	0	0	1	1	1	1	1	1	1	1	1
24	0	0	0	1	1	1	1	1	1	1	1	1
25	0	0	0	1	0	0	0	0	1	0	1	1
26	0	1	1	0	0	0	0	0	0	0	0	0
27	0	1	1	0	0	0	0	0	0	0	0	0
28	0	0	0	1	1	1	1	1	1	1	1	1
29	0	0	0	1	1	1	1	0	1	1	0	1
30	0	0	0	1	1	1	1	1	1	1	1	1
31	0	0	0	1	1	1	1	1	1	1	1	1
32	0	0	0	1	0	1	1	1	1	1	1	1
33	0	0	0	1	0	0	0	1	1	1	1	0
34	0	0	0	1	0	0	0	0	0	0	0	1
35	0	0	0	1	1	1	1	1	1	1	0	1
36	0	0	0	1	1	1	1	0	0	1	0	1
37	0	0	0	1	1	1	1	1	1	1	0	1
38	0	0	0	1	1	1	1	1	1	1	1	1
39	0	0	0	1	0	0	0	0	0	1	0	1
40	0	0	0	1	0	0	0	1	1	1	1	1
41	0	0	0	1	0	0	0	0	0	0	0	0
42	0	1	1	0	0	0	0	0	0	0	0	0
43	0	0	0	1	1	1	1	1	1	1	0	1
44	0	0	0	1	1	1	1	1	1	1	1	0
45	0	0	0	1	0	1	1	1	0	1	0	0

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参考文献(26)

[1]	何立富, 周庆亮, 谌芸, 等.国家级强对流潜势预报业务进展与检验评估.气象, 2011, 37(7):777-784. doi: 10.7519/j.issn.1000-0526.2011.07.001
[2]	彭治班, 刘健文, 郭虎, 等.国外强对流天气的应用研究.北京:气象出版社, 2001.
[3]	王笑芳, 丁一汇.北京地区强对流天气短时预报方法的研究.大气科学, 1994, 18(2):173-183. http://www.cnki.com.cn/Article/CJFDTOTAL-DQXK199402004.htm
[4]	李耀东, 高守亭, 刘健文.对流能量计算及强对流天气落区预报技术研究.应用气象学报, 2004, 15(1):10-20. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20040102&flag=1
[5]	李耀东, 刘健文, 高守亭.动力和能量参数在强对流天气预报中的应用研究.气象学报, 2004, 62(4):401-409. doi: 10.11676/qxxb2004.041
[6]	廖晓农, 俞小鼎, 于波.北京盛夏一次罕见的大雹事件分析.气象, 2008, 34(2):10-17. doi: 10.7519/j.issn.1000-0526.2008.02.002
[7]	雷蕾, 孙继松, 魏东.利用探空资料判别北京地区夏季强对流的天气类别.气象, 2011, 37(2):136-141. doi: 10.7519/j.issn.1000-0526.2011.02.002
[8]	高宾永, 杨仕贤, 吴海涛, 等.运用能量学方法分析大冰雹的落区.气象与环境科学, 2010, 33(2):68-71. http://www.cnki.com.cn/Article/CJFDTOTAL-HNQX201002014.htm
[9]	陈晓红, 郝莹, 周后福, 等.一次罕见冰雹天气过程的对流参数分析.气象科学, 2007, 27(3):335-341. http://www.cnki.com.cn/Article/CJFDTOTAL-QXKX200703017.htm
[10]	刘玉玲.对流参数在强对流天气潜势预测中的作用.气象科技, 2003, 31(3):147-151. http://www.cnki.com.cn/Article/CJFDTOTAL-QXKJ200303003.htm
[11]	周洪祥.灾害性天气的预测方法.北京:气象出版社, 2002.
[12]	Orlanski I.A rational subdivision of scales for atmospheric processes.Bull Amer Meteor Soc, 1975, 56:527-530. http://ci.nii.ac.jp/naid/10003560833/ja/
[13]	叶爱芬, 伍志方, 肖伟军, 等.对流有效位能在强对流预报中的应用研究.热带气象学报, 2006, 22(5):484-490. http://www.cnki.com.cn/Article/CJFDTOTAL-RDQX200605011.htm
[14]	雷雨顺.能量天气学.北京:气象出版社, 1986.
[15]	陆汉城.中尺度天气原理和预报.北京:气象出版社, 2000.
[16]	盛裴轩, 毛节泰, 李建国, 等.大气物理学.北京:北京大学出版社, 2003.
[17]	张杰.中小尺度天气学.北京:气象出版社, 2006.
[18]	孙继松, 陶祖钰.强对流天气分析与预报中的若干基本问题.气象, 2012, 38(2):164-173. http://www.cnki.com.cn/Article/CJFDTOTAL-QXXX201202007.htm
[19]	罗阳, 赵伟, 翟景秋.两类天气预报评分问题研究及一种新评分方法.应用气象学报, 2009, 20(2):129-136. doi: 10.11898/1001-7313.20090201
[20]	Donaldson R J, Dyer R M, Krauss M J.An Objective Evaluator of Techniques for Predicting Severe Weather Events.9th Conf Severe Local Storms, Amer Meteor Soc, 1975:321-326.
[21]	王丽荣, 卞韬, 苏运涛, 等.晴空回波在强对流天气临近预报中的应用.应用气象学报, 2010, 21(5):606-613. doi: 10.11898/1001-7313.20100510
[22]	邓国, 龚建东, 邓莲堂, 等.国家级区域集合预报系统研发和性能检验.应用气象学报, 2010, 21(5):513-523. doi: 10.11898/1001-7313.20100501
[23]	王瑾, 刘黎平.WSR-88D冰雹探测算法在贵州地区的评估检验.应用气象学报, 2011, 22(1):96-106. doi: 10.11898/1001-7313.20110110
[24]	刘春文, 林永辉, 曹艳察.局地分析预报系统在GRAPES模式中的应用.应用气象学报, 2013, 24(2):162-170. doi: 10.11898/1001-7313.20130204
[25]	陈明轩, 俞小鼎, 谭晓光, 等.对流天气临近预报技术的发展与研究进展.应用气象学报, 2004, 15(6):754-766. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=20040693&flag=1
[26]	廖晓农, 俞小鼎, 谭一洲.14时探空在改进北京地区对流天气潜势预报中的作用.气象, 2007, 33(3):28-32. doi: 10.7519/j.issn.1000-0526.2007.03.004