Nowcasting techniques in use for severe weather operation in NMC/CMA

Transcription

1 WWRP NMRWG Buenos Aires Aug 2017 Nowcasting techniques in use for severe weather operation in NMC/CMA Jianjie WANG National Meteorological Center, CMA

2 Cascading Weather Forecasting Process --- different levels taking different responsibilities on weather forecasts NMC NWP Systems Development Nation-wide Watch & Guidance Central Government Service 105 VSRF: outlook on the coverages of 3-type SW Provincial MS 31 NWP Application Province Forecast Guidance Province Government Service 822 VSRF: outlook & warning Prefecture & County MS Local Warnings Local Forecasts Advice to Emergency 2529 VSRF: warning

3 Monitoring: heavy rainfall lightning thunder gust hails Convective Weather Forecast at NMC SPC was established in NMC/CMA since 2009 Diagnosis & analysis: time series of surface variables structures of dynamic/ thermal dynamic/moisture derivatives in troposphere convective indexes mesoscale systems Forcasting: 0-24h outlook of 3 types of SW 24-72h outlook of severe convection Warning of 4 types of SW (only issuing to decision makers) Outlook: 0-24h with 6h or 12h interval to 3-types of SW heavy rainfall (>= 20mm/h, 50mm/h) thunder storm / lightning storm gust wind and/or hails ( >=17.2m/s) Warning: 0-2h/6h (rain storm / gale / lightning / hail)

4 Basic strategy High-resolution model with rapid cycle Blending Monitor and Extrapolation Radar-based Satellite-based 0-2hour 2-6hour 6-24hour The better use of observations (extrapolation, DA, verification/evaluation) The better use of NWP products (high resolution/ruc, bias correction, ensemble) Time scale

5 1. Convective Weather Monitoring Hail Monitoring Lightning Comprehensive Monitoring

6 RDC(Rapid Developing Convection) Identification Radar echo Hail Identifying Based on Radar Image Features

7 2. Nowcasting-extrapolation 0-2h Extrapolation using radar data TREC based QPF (0-2h) QPF OBS 1 h rainfall nowcast by CMA nowcasting system SWAN 02:00 to 03:00 BJT on 20 th May 2009, Guangxi

8 MCS identifying, tracking & nowcasting by satellite data Satellite Data Identif y-ing High-resolution multi-spectral TBB of highresolution IR Track -ing Area Overlapping Hungrary algorithm Method CORR RMSE POD FAR CSI nowcast Kalman Filter 0.85~ ~9 0.64~ ~ ~ min 0-2h Extrapo -lation Kalman Filter 1h extrapolation by using FY-2 data Forecast image OBS image

9 h Forecasting Technique Based on High-Resolution NWP 1 Hourly QPF Technique Based on GRAPES-RAFS 2 Neighborhood Technique of Short-duration Heavy Rainfall and Intense Echoes Based on GRAPES-Meso 3 Ingredient-Based Forecasting Technique of Different Types of Severe Convective Weather Based on GRAPES-Meso 4 Multi-model ensemble (GRAPES-Meso and 3 models of regional centers) CMA-NWPC unified model : GRAPES GRAPES =Global/Regional Assimilation PrEdiction System

10 (1) Hourly QPF Technique Based on GRAPES-RAFS Step 1: Time-lagged ensemble Try to reduce the impact of model spin-up Step 2: Rainfall intensity correction based on frequency match between observations and prediction Step 3: Phase adjustment based on correlation between observations and prediction

11 TS during June-August, 2015 (Red: Correction, Blue: Model Prediction) 5-10mm Obs RAFS Rainfall Prediction Corrected Rainfall Prediction

12 (2) Neighborhood Techniques of VSRF on Short-duration Heavy Rainfall & Intense Echoes Based on GRAPES-MESO Step 1: Rainfall intensity correction based on frequency match between observations and prediction Step 2: Determining neighborhood probability Obs Prediction Model rainfall Prediction ( 5mm) Probability of Hourly Rainfall ( 10mm) Obs Hourly Rainfall ( 10mm)

13 (3) Ingredient-Based Forecasting Technique on Different Types of Severe Convective Weather Based on GRAPES-MESO Step 1:Selecting parameters based on the mechanism of convective weather Step 2:Presenting comprehensive probability of convective weather Obs BT BT Prob. of heavy rainfall (>=20mm/h) Prob. of hail Prob. of gust winds

14 (4) Multi model ensemble Models from NWPC and Shanghai, Beijing, Guangzhou

15 GRAPES-RAFS QPF & radar echo multimodel ensemble products Shanghai Model Guangdong Model Beijing Model Same area coverage Same resolution Same map projection Bilinear interpolation to 0.05*0.05 Lon-Lat grids Correction based on probability matching VSRF guidance of heavy rainfall Corrected radar echo & (1h/3h/6h) QPF products of different models Varied weight based on recent forecast score 预警标准 Multi-model radar echo & QPF (1h/3h/6h) ensemble products at 3 hourly update

16 Shanghai Grapes-3km GRAPES-RAFS Multi-model ensemble OBS A missing part is catched by Grapes 3km model

17 Conclusion Cascading nowcasting/vsrf operation has been established in CMA to support weather services of 4 levels (central gov., province, city and county) The scope of nowcast operation in CMA is expanding from SW (traditional focus) to other weather phenomena and meteo-elements Nowcast techniques for SW in operation are mainly radar-based, while satellite-based methods are attracting more attentions recent few years Techniques for VSRF (including 0-2h meteo-element nowcast) are high-resolution nwp-based (RR/RUC, multimodel ensemble) with bias correction to direct model outputs.

18 Acknowledgement: Yongguang ZHENG Xiaoling ZHANG Thanks for your attention!