SWAN The Operational System for Nowcasting and Very-short Range Forecast in CMA
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1 SWAN The Operational System for Nowcasting and Very-short Range Forecast in CMA National Meteorological Center (NMC) China Meteorological Administration (CMA) Mao Dongyan, Zheng Yuanyuan, Zhou Kanghui Feng Yerong, Yang Bo, Han Feng, Xue Feng, et al
2 OUTLINE INTRODUCTION MAIN FUNCTIONS in SWAN
3 INTRODUCTION SWAN - Severe Weather Automatic Nowcasting System SWAN was developed by the cooperation among NMC, Guangdong Meteorological Bureau, Wuhan Storm Office and other local meteorological departments and research institutions. SWAN was first proposed in 2008, and updated to V2.0 in June 2016.
4 SWAN-Severe Weather Auto-Nowcasting Version 0(2009): preliminary finished the framework construction and basic algorithms development Version 1.0(2010): improved the algorithms, embeded the client to Micaps 3.1 Version 1.5(2012): developed the Flash floods integrated platform of geological disasters, upgraded the client to Micaps 3.2 Version 2.0 (2016): integrated new algorithms, updated the client to Micaps4.0
5 SWAN interface
6 SWAN DATA FLOW RADAR PUP UPPER WARNINGS RADAR BASE DATA AWS LIGHTNING WARNINGS RADAR 3-D WIND AWS RAINS HAIL IDENTIFICATION QPE SOUNDINGS DATA SOURCE WARNINGS MONITORING FORCAST
7 MAIN FUNCTIONS in SWAN Working model Monitoring and auto-alarm Nowcasting and very-short range forecast Warning issuance
8 Working model 2 models: real-time model and analyzing model Real-time model: updated automatically without any operating Analyzing model: forecasters can operate by using the time-axis and analyzing
9 Monitoring and auto-alarm Products Frequency Basic data/technique Radar 3-D mosic 6min Radar base data by QC Com. Reflectivity 6min Radar base data by QC 3-DVAR wind 6min Radar base data by QC ET 6min Radar 3-D mosic VIL 6min Radar 3-D mosic 1-h QPE 6min Radar 3-D mosic QPE for heavy rain 1hour Radar 3-D mosic Cotrec wind 6min Radar 3-D mosic AWS 5/10 min AWS observation Lightning Real time Lightning observation AWS warning 5/10 min AWS observation PUP warning Real time PUP products Hail warning 6min Radar 3-D mosic
10 Radar Monitoring SWAN2.0 客户端 3DVar Wind RESO= D Ref Mosic QPE+COTREC
11 CROSS SECTION B C D A A B C D SET THRESHOLD SET THRESH DISPLAY MORE INFO
12 AWS Monitoring RAIN: Different period from 10min to 24h RH WIND: different threshold Variation of T and P: different period
13 TIME-SERIAL 3h ΔP 1h RAIN WIND STATISTIC of a specified area
14 Auto-Alarm Based on Radar and AWS Alarm Regions: Administrative region Circle (radius defined by user) user-defined Alarm Form: Flash Sound
15 ALARM INTERFACE Alarm list Not-read alarm Alarm icon Alarm info
16 Nowcasting and very-short range forecast Products Frequency Basic data/technique Radar Ref. Fcst 6min Cotrec wind QPF 6min Cotrec wind SCIT 6min Radar 3-D mosic TITAN 6min Radar 3-D mosic
17 QPF SWAN2.0 客户端 TITAN TITAN : Thunderstorm Identification, Tracking, Analysis and Nowcasting CTREC : Current implementation of Tracking Radar Echoes by Correlation
18 Radar Echo Nowcasting Radar OBS 11:42 5 Apr,2014 1h Radar Ref Nowcasting
19 OBJECTIVE FORECAST Ingredients-Based Methodology -Charles Doswell (1996) P = Eqw D P: total rainfall E: rainfall efficiency D: duration W: ascending velocity q: mixing ratio for ascending air The Ingredients-Based Methodology (IM) Charles Doswell provides a framework for a systematic assessment of the fundamental physical ingredients that influence the duration, intensity, and type of a given weather phenomenon. (Wetzel and Martin 2001)
20 Physical Parameters Unstability SI (Showalter Index) LI (Lifting Index) /BLI (Best Lifting Index) T850-T500 (Temperature difference between 850hPa and 500hPa) CAPE (Convective Available Potential Energy) DCAPE (Downdraft CAPE) K (K Index) Water Vapour RH (Relative Humidity) PWAT (Precipitable Water) Td (Dew point Temperature)
21 Convergence DIV (Divergence) CON(Convergence) Vertical Wind Shear Shr0-6 (0-6km shear) Shr0-3 (0-3km shear) Others T (Temperature) H0 (Height of 0 ) H20 (Height of -20 ) WI (Windex) TT (Total Totals) SWEAT (Severe WEAther Threat)
22 Short-Term Heavy Rain Forecast Short-Term Heavy Rain: PWAT, T850-T500, BLI, RH, Low-level DIV
23 Warning issue 3 ways of warning producing: Draw warning areas Select administrative regions All the area Warning issued by one button. Draw warning areas Select different areas
24 THANKS FOR YOUR ATTENTION!
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