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 Contributors: Wan Qilin 3, Chen Dehui 1, Liu Yan 1, Liu Hongya 1

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

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

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

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

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

Cycle of Hourly Assimilation and Forecast IDFI

Test of Hydrometeors initialization model modelvar qcqr.dat ISI adjustment IDFI nudg model postvar 3DV Radar, Satellite Parameters to be nudged : q c, q r, q i, q s, q h, q g (skipped in this presentation)

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

Main components of SWIFT o Currently available: 1. Identification of SC (storm cell) 2. Potential of intense convection （ tornado, hail, thunderstorm ） 3. TREC wind (estimation of SC movement) 4. SC Tracking and forecasting 5. Quantitative precipitation estimation （ QPE ） 6. Quantitative precipitation forecast (QPF) o To be developed: 1. Potential of lightning 2. Forecasts of storm-genesis and dissipation 3. Urban water logging forecast 4. Debris flow forecast

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

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

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

o TREC winds are used for extrapolation within 1 hour o 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 ) o Forecast of CS with weighting mean of NWP and TREC o Statistical approach with NWP products as predictors 1 hour Weight of TREC Weight of NWP

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

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

case 每隔 10 分钟外推 的 2 小时外推 的 3 小时外推

Quantitative Precipitation Forecast QPF 预报

Radar Mosaic --STS Bilis

1-h QPF

1 小时后的回波

2-h QPF

2 小时后的回波

3-h QPF

3 小时后的回波

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

The end Thank you for attention