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Nowcasting-Oriented Data Assimilation in GRAPES Briefing of GRAPES-SWIFT

Nowcasting-Oriented Data Assimilation in GRAPES Briefing of GRAPES-SWIFT Jishan Xue 1 Feng Yerong 2 Zitong Chen 3 1, State key Laboratory of Sever Weather, CAMS, CMA 2, Guangdong Provincial Observatory , GRMC, CMA 3, Guangzhou Institute of Tropical and Oceanic meteorology, CMA

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Nowcasting-Oriented Data Assimilation in GRAPES Briefing of GRAPES-SWIFT

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  1. Nowcasting-Oriented Data Assimilation in GRAPES Briefing of GRAPES-SWIFT Jishan Xue1 Feng Yerong2Zitong Chen3 1, State key Laboratory of Sever Weather, CAMS, CMA 2, Guangdong Provincial Observatory , GRMC, CMA 3, Guangzhou Institute of Tropical and Oceanic meteorology, CMA Contributors: Wan Qilin3, Chen Dehui1, Liu Yan1, Liu Hongya1

  2. Outline • Motivation • System structure • GRAPES and its High Resolution assimi.-pred. cycle • Severe weather integrated forecast tools • Some tests and real time running • Unsolved issues and plan for further development

  3. Motivation • Combine the high resolution NWP products ( GRAPES) and nowcasting technologies (SWIFT) to improve severe weather forecasts within 6 hours • Provide a new tool for the weather services for Olympic Games 2008 Beijing • Promote the further development of meso NWP technologies driven by expanded application of NWP

  4. Global-Regional Assimilation and PrEdiction System Schematic description of GRAPES • Chinese new generation NWP systems • Variational data assimilation: 3DVar-available, 4DVar-being developed; • Non-hydrostatic model with options of global and regional configurations • Used in various applications ranging from severe weather events, general circulation modeling, environmental issues,……

  5. System composition GRAPES Cycleof HourlyAssi. Fcst. 6 hour NWP Id. of Conv Storm ( QPE ) Extrapolation and Forecasting Data input TREC Wind ( Movement Esti.) Display and Validation Sever weather integrated forecast tool (SWIFT)

  6. GRAPES cycle of hourly assimi.-fcst. and Prediction • Non-hydrostatic model with spatial res. 13km (1km finally) • 3DVar for analysis • Digital filter controlling noisy oscillation • 1 hour time window • Data ingested: Temp Synop Doppler Radar AWS AIRep Wind profiler Two test beds: Beijing area (for BO2008) Pearl river delta

  7. Cycle of Hourly Assimilation and Forecast IDFI

  8. Test of Hydrometeors initialization Parameters to be nudged : qc , qr, qi, qs, qh, qg (skipped in this presentation) postvar 3DV modelvar ISI IDFI qcqr.dat adjustment nudg model model Radar, Satellite

  9. Severe Weather Integrated Forecast Tool • Radar based approaches • Automatically monitoring data inflow and quick response • High res. (1:5000) GIS coupled • Meso scale precipitation systems as the essential objective to detect and predict • Main components: Storm cell (SC) identification and QPE Estimation of movement of the cells (TREC wind) Extrapolation of SC, QPF

  10. Main components of SWIFT • Currently available: • Identification of SC (storm cell) • Potential of intense convection（tornado , hail, thunderstorm） • TREC wind (estimation of SC movement) • SC Tracking and forecasting • Quantitative precipitation estimation（QPE） • Quantitative precipitation forecast (QPF) • To be developed: • Potential of lightning • Forecasts of storm-genesis and dissipation • Urban water logging forecast • Debris flow forecast

  11. monitoring control Display Rapid Update VS Rapid Response Triggered upon data arrival DataSource Radar Data Mosaic Processor Mosaic Output 数据流 １．触发机制 ２．统一调度 TREC QPE QPF TREC QPE QPF output

  12. Nowcasting Algorithms SC identification: • SC defined by a radar echo with reflectivity reaching specified thresholds • Correlation between storm cell and observed severe weather events. Estimation of movement • Spatial consistency check • Special treatment for missing data area • Adjustment based on continuity hypothesis • Tracking radar echo by correlation

  13. Extrapolation and forecasting algorithms Redarreflectivity TREC Wind Adjust. Based on cons. Of mass Z-R relation Data of AWS Corrected TREC OI QPE GRAPES output Adv. extrapolation of echo Corre. Of TREC and model fcst. FY2C 1h QPF Genes. Disp. Adjust. 2 and 3h QPF

  14. Extrapolation and forecasting algorithms • TREC winds are used for extrapolation within 1 hour • TREC winds are also used to find the model levels on which the NWP wind fits the movement of CS ( 500hpa or higher in most cases ) • Forecast of CS with weighting mean of NWP and TREC • Statistical approach with NWP products as predictors Weight of TREC Weight of NWP 1 hour

  15. 广 东 省 气 象 局 Guangdong Meteorological Bureau 梅州 韶关 Pearl River Delta Trials Radar 阳江 汕头 广州 深圳

  16. Auto weather stations 韶关 汕头 广州 湛江 Distribution of auto weather stations(>=700)

  17. 200608130710 case 200608130710每隔10分钟外推 200608130710的2小时外推 200608130710的3小时外推

  18. Quantitative Precipitation Forecast QPF200608130710 预报

  19. Radar Mosaic --STS Bilis

  20. 1-h QPF

  21. 1小时后的回波

  22. 2-h QPF

  23. 2小时后的回波

  24. 3-h QPF

  25. 3小时后的回波

  26. Further development • Radar and satellite data ingested in real time system • Data quality control • Combine well NWP products with nowcasting technologies

  27. The end Thank you for attention

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