Nowcasting &amp; Warning Operational System in the Middle Reaches of the Yangtze with Its Implementation

Wan Yufa; Wang Zhibin; Zhang Jiaguo; Wu Cuihong; Wu Tao; Wang Jue

Vol.24, NO.4, 2013

Article Contents

Article Navigation > Journal of Applied Meteorological Science > 2013 > 24(4): 504-512

Wan Yufa, Wang Zhibin, Zhang Jiaguo, et al. Nowcasting & warning operational system in the middle reaches of the Yangtze with its implementation. J Appl Meteor Sci, 2013, 24(4): 504-512.

Citation:

Wan Yufa, Wang Zhibin, Zhang Jiaguo, et al. Nowcasting & warning operational system in the middle reaches of the Yangtze with its implementation. J Appl Meteor Sci, 2013, 24(4): 504-512.

Wan Yufa, Wang Zhibin, Zhang Jiaguo, et al. Nowcasting & warning operational system in the middle reaches of the Yangtze with its implementation. J Appl Meteor Sci, 2013, 24(4): 504-512.

Citation:

Wan Yufa, Wang Zhibin, Zhang Jiaguo, et al. Nowcasting & warning operational system in the middle reaches of the Yangtze with its implementation. J Appl Meteor Sci, 2013, 24(4): 504-512.

PDF( 1385 KB)

Nowcasting & Warning Operational System in the Middle Reaches of the Yangtze with Its Implementation

1.
Wuhan Institute of Heavy Rain, CMA, Wuhan 430074
2.
Wuhan Central Meteorological Observatory, Wuhan 430074

Received Date: 2012-10-09
Rev Recd Date: 2013-06-08
Publish Date: 2013-08-31

Abstract

Abstract

In order to meet the need for modern operational forecasting of severe storm events in the middle reaches of the Yangtze, MYNOS (Nowcasting & warning Operational System in the Middle reaches of theYangtze), an advanced and useful nowcasting system, is originally established in 2007 based on the experiences of the advanced nowcasting systems Auto-Nowcaster and WDSS-II of USA and GANDOLF of UK. MYNOS combines the resources of new generation radar network in China with the data from numerical weather prediction. Several advanced techniques and methods are developed and adopted as follows: Quality control of radar reflectivity field and the precipitation echo classification are achieved by identifying the structures of the vertical gradient and horizontal textures of radar reflectivity echoes. Real time formation technique of vertical reflectivity profile (VPR) is developed and used for vertical calibration of precipitation reflectivity factor. Important concepts of "quasi same-rain-volume sample" and "hourly equivalent reflectivity factor" are proposed, and the synchronously integrated method of radar and rain gauge (RASIM) is established. The cell gravity potential energy, as an important physical component of radar for describing the life span of storms, is proposed. The technique for automatic identification and tracking of severe weather is developed by means of radar derived parameters and the meso-scale output of physical parameters. The multi-scale characteristics of storm echoes through their life courses are analyzed and the echo filtering technique is studied, and the multi-scale precipitation nowcasting confined to the life time of each scale echo is realized. Potential forecasting products for severe convection meteorological phenomena (torrential rain, hail, thunderstorm, etc.) are developed based on numerical models and fuzzy logics. The problem of image registration and animation in ordinary GIS (Geographic Information System) is solved by introducing custom layer, and the nowcasting workstation equipped with the function of GIS along with numerical prediction, radar, satellite, lightning data and various quantitative monitoring, forecasting and warning products is developed from the bottom. MYNOS is put into operational experiments in May 2006 and has been in concentional operation since the flood season of 2007. The real-time generated output of MYNOS, such as valley quantitative precipitation estimation and nowcasting, strong convective weather classified potential diagnosis and identification warning products, provide an important foundation and reference for routine nowcasting operation.
- MYNOS;
- strong convection;
- quantitative detection;
- automatic identification

FullText(HTML)

References(33)

Figures and Tables

Fig. 1 Function structure chart of MYNOS

DownLoad: Full-Size Img PowerPoint

图 2 2008年6月3日19：30 (北京时，下同) 黄冈地区强对流天气识别产品

(椭圆圈表示风暴水平投影面范围，如同时识别出冰雹和大风天气则只显示冰雹符号)

Fig. 2 Identification products of strong convective weather in Huanggang Region at 1930 BT 3 Jun 2008

(ellipse denotes the range of horizontal projection plane of wind storm, if both hail and gale are identified at the same time, only hail symbol is signed)

DownLoad: Full-Size Img PowerPoint

图 3 2003年7月8日07:00武汉天气雷达1 h降水外推预报和小时降水实况

(a) 不分尺度外推预报，(b) 分尺度外推预报

Fig. 3 1-h precipitation extrapolated prediction of Wuhan radar and the observed hourly precipitation at 0700 BT 8 Jul 2003

(a) non-separated scaling extrapolated prediction, (b) multi-scale extrapolated prediction

DownLoad: Full-Size Img PowerPoint

Fig. 4 Fuzzy logic algorithm flowchart of strong convective weather classified potential diagnosis

DownLoad: Full-Size Img PowerPoint

Table 1 Prediction objects, model output physical quantities and their weights

预报对象	模式输出物理量	权重系数
雷暴	对流有效位能	0.66
	K指数	0.41
	对流抑制能量	0.40
	850 hPa涡度ζ₈₅₀	0.31
	850 hPa与700 hPa平均相对湿度F₈₇	0.20
雷暴大风	对流有效位能	0.62
	K指数	0.60
	对流抑制能量	0.30
	850 hPa涡度ζ₈₅₀	0.40
	850 hPa与700 hPa平均相对湿度F₈₇	0.20
	700 hPa与500 hPa平均相对湿度F₇₅	0.40
	500 hPa与200 hPa平均相对湿度F₅₂	0.30
冰雹	对流有效位能	0.60
	K指数	0.60
	对流抑制能量	0.40
	850 hPa涡度ζ₈₅₀	0.30
	850 hPa与700 hPa平均相对湿度F₈₇	0.20
	700 hPa与500 hPa平均相对湿度F₇₅	0.20
	500 hPa与200 hPa平均相对湿度F₅₂	0.40
	0℃温度层高度	0.60
	-20℃温度层高度	0.38
	海拔高度(非模式输出量)	0.20
短时暴雨	K指数	0.50
	850 hPa与700 hPa平均相对湿度F₈₇	0.60
	700 hPa与500 hPa平均相对湿度F₇₅	0.60
	500 hPa与200 hPa平均相对湿度F₅₂	0.50
	850 hPa水汽通量散度	0.60
	850 hPa假相当位温	0.50
	300 hPa与850 hPa涡度差	0.50

DownLoad: Download CSV

References

[1]	Keenan T, Joe P, Wilson J, et al.The Sydney 2000 World Weather Research Programme Forecast Demonstration Project:Overview and current status.Bull Amer Meteor Soc, 2003, 84:1041-1054. doi: 10.1175/BAMS-84-8-1041
[2]	Wang J J, Keenan T, Joe P, et al.Overview of Beijing 2008 Olympics Forecast Demonstration Project:Nowcasting Demonstration.World Meteorological Organization Symposium on Nowcasting and Very Short Term Forecasting, 2009.
[3]	陈明轩, 高峰, 孔荣, 等.自动临近预报系统及其在北京奥运期间的应用.应用气象学报, 2010, 21(4):395-404. doi: 10.11898/1001-7313.20100402
[4]	Mueller C, Saxen T, Roberts R, et al.NCAR Auto-nowcast System.Wea Forecasting, 2003, 18:545-561. doi: 10.1175/1520-0434(2003)018<0545:NAS>2.0.CO;2
[5]	Lakshmanan V, Smith T, Stumpf G, et al.The warning decision support system-integrated information.Wea Forecasting, 2007, 22(3):596-612. doi: 10.1175/WAF1009.1
[6]	Pierce C E, Collier C G, Hardaker P J, et a1.GANDOLF:A system for generating automated nowcasts of convective precipitation.Meteor Appl, 2000, 7:341-360. doi: 10.1017/S135048270000164X
[7]	Wilson J W, Crook N A, Mueller C K, et a1.Nowcasting thunderstorms:A status report.Bull Amer Meteor Soc, 1998, 79:2079-2099. doi: 10.1175/1520-0477(1998)079<2079:NTASR>2.0.CO;2
[8]	俞小鼎, 周小刚, 王秀明.雷暴与强对流临近天气预报技术进展.气象学报, 2012, 70(3):311-337. doi: 10.11676/qxxb2012.030
[9]	郑永光, 张小玲, 周庆亮, 等.强对流天气短时临近预报业务技术进展与挑战.气象, 2010, 36(7):33-42. doi: 10.7519/j.issn.1000-0526.2010.07.008
[10]	Wolfson M M, Dupree W J, Rasmussen R M, et a1.Consolidated Storm Prediction for Aviation (CoSPA).13th Conference on Aviation, Range and Aerospace Meteorology, 2008.
[11]	Bowler N E, Pierce C, Seed A W.STEPS:A probabilistic precipitation forecasting scheme which merges an extrapolation nowcast with downscaled NWP.Q J R Meteor Soc, 2006, 132:2127-2155. doi: 10.1256/qj.04.100
[12]	万玉发, 陈少林, 罗建国.数字化天气雷达联网拼图与卫星云图综合实时处理系统.气象, 1994, 20(8):27-31. http://www.cnki.com.cn/Article/CJFDTOTAL-QXXX199408005.htm
[13]	万玉发, 张家国, 杨洪平, 等.联合雷达网和卫星定量监测与预报长江流域大范围降水.应用气象学报, 1998, 9(1):94-103. http://qikan.camscma.cn/jams/ch/reader/view_abstract.aspx?file_no=19980113&flag=1
[14]	王志斌, 万玉发, 陈波, 等.新一代短时天气预警报系统设计与实现.计算机应用研究, 2007, 24(12):296-299. doi: 10.3969/j.issn.1001-3695.2007.12.096
[15]	万玉发, 吴翠红, 金鸿祥.基于准同雨团样本概念雷达和雨量计的实时同步结合方法.气象学报, 2008, 66(2):262-273. doi: 10.11676/qxxb2008.025
[16]	Smith P L, Joss J.Use of a Fixed Exponent in "Adjustable" Z-R Relationships.Preprints, 28th Conference on Radar Meteorology, 1997:254-255.
[17]	万玉发, 王珏, 金鸿祥.雷达与雨量计同步结合区域型估算降水方程的误差分析.气象学报, 2013, 71(2):332-343. doi: 10.11676/qxxb2013.023
[18]	王佑兵, 万玉发.雷达体扫反射率场的自动质量控制.气象科技, 2006, 34(5):615-619. http://www.cnki.com.cn/Article/CJFDTOTAL-QXKJ200605025.htm
[19]	吴涛, 吴翠红, 万玉发, 等.用雷达反射率作对流性降水和层状云降水自动分类.气象科技, 2006, 34(5):610-614. http://www.cnki.com.cn/Article/CJFDTOTAL-QXKJ200605023.htm
[20]	吴翠红, 万玉发, 吴涛, 等.雷达回波垂直廓线及其生成方法.应用气象学报, 2006, 17(2):232-239. doi: 10.11898/1001-7313.20060215
[21]	肖艳姣, 刘黎平, 杨洪平.基于天气雷达网三维拼图的混合反射率因子生成技术.气象学报, 2008, 66(3):470-473. doi: 10.11676/qxxb2008.043
[22]	Gabella M, Amitai E.Radar rainfall estimates in an Alpine environment using different gage-adjustment techniques.Phys Chem Earth:Series B, 2000, 25(10-12):927-931. doi: 10.1016/S1464-1909(00)00127-1
[23]	Hand W H.An object-oriented technique for nowcasting he-avy showers and thunderstorms.Meteor Appl, 1996, 3:31-41.
[24]	Johnson J T, MacKeen P L, Witt A, et al.The storm cell identification and tracking algorithm:An enhanced WSR-88D algorithm.Wea Forecasting, 1998, 13:263-276. doi: 10.1175/1520-0434(1998)013<0263:TSCIAT>2.0.CO;2
[25]	Dixon M, Wiener G.TITAN:Thunderstorm Identification, Tracking, Analysis and Nowcasting-A radar-based methodology.J Atmos Oceanic Technol, 1993, 10:785-797. doi: 10.1175/1520-0426(1993)010<0785:TTITAA>2.0.CO;2
[26]	Witt A, Eilts M D, Stumpf G J, et al.An enhanced hail detection algorithm for the WSR-88D.Wea Forecasting, 1998, 13:286-303. doi: 10.1175/1520-0434(1998)013<0286:AEHDAF>2.0.CO;2
[27]	郑佳锋, 张杰, 朱克云, 等.阵风锋自动识别与预警.应用气象学报, 2013, 24(1):117-125. doi: 10.11898/1001-7313.20130112
[28]	张家国, 万玉发, 王珏.风暴生命史雷达特征量反演.应用气象学报, 2008, 19(1):101-105. doi: 10.11898/1001-7313.20080116
[29]	Lakshmanan V, Rabin R, DeBrunner V.Multiscale storm identification and forecast.J Atmos Research, 2003, 66:367-380.
[30]	王珏, 张家国, 万玉发.多尺度合成的降水临近预报技术.气象科技, 2008, 36(5):524-528. http://www.cnki.com.cn/Article/CJFDTOTAL-QXKJ200805003.htm
[31]	张家国, 王珏, 王叶红.用中尺度数值模式诊断强风暴潜势研究.气象科技, 2008, 36(2):129-133. http://www.cnki.com.cn/Article/CJFDTOTAL-QXKJ200802001.htm
[32]	王珏, 寿绍文, 张家国, 等.利用中尺度模式建立暴雨落区潜势预报.暴雨灾害, 2010, 29(4):350-355. http://www.cnki.com.cn/Article/CJFDTOTAL-HBQX201004009.htm
[33]	Doswell Ⅲ C A, Brooks H E, Maddox H E.Flash flood forecasting:An ingredients-based methodology.Wea Forecasting, 1996, 11:561-581.