0-12H VSR forecasting and nowcasting review and plan in CMA - - PowerPoint PPT Presentation

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0-12H VSR forecasting and nowcasting review and plan in CMA - - PowerPoint PPT Presentation

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0-12H VSR forecasting and nowcasting review and plan in CMA Xiaoling Zhang, Bo Yang, Yongguang Zheng, Jie Sheng, Yinjing Lin, Wenyuan Tang, Kanghui Zhou National Meteorological Center, China Meteorological Administration Page 1 Synoptic

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0-12H VSR forecasting and nowcasting review and plan in CMA

Xiaoling Zhang, Bo Yang, Yongguang Zheng, Jie Sheng, Yinjing Lin, Wenyuan Tang, Kanghui Zhou National Meteorological Center, China Meteorological Administration

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Australia High

Subtropical High

South-east trade wind Tropical conv. Clouds Typhoon

Mascarene High

Somali Jet

Low pressure of Monsoon

plateau enforce

MJO propagate eastward

D D

D

Cold air

Meiyu Front

Monsoon trough

Synoptic Systems over East Asia

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Weather and Climate Systems

Global Change

Minute Minute Hour Hour day day week week Month Month Year Year Ten Ten Years Years Hundred Hundred Years Years

1km 10km 100km 1000km 100000km 10000km Dust storm Tornado Thunderstorm Typhoon Fronts Torrential rain Monsoo n EI Nino Squall line Pressure

Shor Short-range for nge forecast cast Medi Medium um-range ange fo forecas ecast Shor Short-ter term clim limate p te pred redictio ction Deca Decadal dal clim climate ate pred predict iction

  • n

Clim Climate ate chan change p ge proje rojecti ction

Small Small scale scale（＜2km 2km） Mesoscale Mesoscale（2-200km 200km） Synoptic Scale Synoptic Scale（200 200-10000km 10000km） Global scale Global scale（＞10000km 10000km）

Climate Weather

Nowcasting/ Very-short range forecast

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– Hail >5 mm – Thunderstorm gale> 17m/s – Tornado – Short-time rainstorm>20mm/h

Severe Convective Weather

Beijing Jul.21 Haerbin Hail in Jun.12 Gauntry crane collapse in Guangdong Apr.13 Funing EF4 tornado in Jun.23 North China in Jul.19-20 138.5mm/h（2300BJT Jul.19) Jun.1 in Northeast China

Squall-line Hail Tornado Short-time Rainstorm

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 Severe convective weather characteristics and its operational forecasting in CMA  0-2h Nowcasting  2-12h Very-short-range forecast  Future Prospects

Contents

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 Severe convective weather characteristics and operational forecasting in CMA  0-2h Nowcasting  2-12h Very-short-range forecast  Future Prospects

Contents

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1981-2010 annual frequency of severe convective weather

Thunderstorm ST heavy rainfall >20mm/h Hail Thunderstorm gale

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Jan.1-Jun.24 2016

The high wind in 2016 vs 1981-2010

Jan.1-Jun.24 1981-2010

High frequency

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From Wenjie Fan and Xiaoding Yu ，2015）

Distribution and variation trend of EF2 tornados and above in 1961-2010

Distribution Variation trend

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0 h 2 h 12 h SWPC /NMC

PROVINCE CITY AND COUNTY

MONITOR MONITOR MONITOR WARNING WARNING WATCH WATCH

Operational responsibility in CMA

WATCH WARNING

National level Local level

Lightning Rainstorm Hail Gale

Warning signals

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NMC 12h Forecast NMC 0-6h Watch Local Office 0-2h Warning SCW location and intensity

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 Severe convective weather characteristics and its operational forecasting in CMA  0-2h Nowcasting  2-12h Very-short-range forecast  Future Prospects

Contents

  • In SWPC/NMC, the monitoring and Extrapolation techniques

mainly based on satellite and lightning data

  • In local office mainly based on the radar data
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Severe Convective Weather monitor in NMC

Lightning Hail High Wind Short-time heavy rainfall

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Radar mosaic imagine Radar echo extracting

30dBz 30dBz 45dBz 45dBz 50dBz 50dBz 60dBz 60dBz

MCS identification and track with satellite data Lightning intensity Ｐ\θse\V Objective analysis based on AWS data Lightning monitor

Multiple data applied in a severe convective weather events in South China

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MCS recognition, track and extrapolation based on the FY satellites data

①

t t+1

① ② ③

t t+2

recognition track extrapolation

t+1

① ② ③

t t+2 t+3

Mar ch in g-Sq u ar e 等值线追踪算法 多阈值 等值线识别

指定最低识别亮温值及亮温 变化间隔（如以-92℃为起 点，以2℃为间隔进行识别）

红外1 亮温资料

较“经典等值线追 踪算法”高效

MCS边界 归并

从最低识别亮温开始对逐级亮 温识别得到的等值线判断包含 关系，实现MCS边界的归并

计算MCS特征 并输出

边界阈值、边界点、特征阈值 的面积、平均亮温、椭圆率等

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Recognition, track and extrapolation of the MCS based

  • n the FY satellites data
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60 minutes forecast

  • Obs. at 1900BJT

beginning at 1800BJT Jul.21 2012

120 minutes forecast 180 minutes forecast

  • Obs. at 2000BJT
  • Obs. at 2100BJT

MCSrec ecognition

  • gnition and extra

and extrapolation n +hour +hourly preci y precipitation monit n monitor

0-3h QPF based on the MCS extrapolation

Hourly precipitation monitor MCS extrapolation 0-3h QPF

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temporal evolution of averaged IR BT VS the timing of the gale

Thunderstorm gale likely

  • ccurred as the IR BT

sharply dropped rather than to its minus

Quantity characteristics of Large –zone thunderstorm-gale-produced clouds

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  • Cell recognition by

cluster analysis

  • Track and extrapolation

by Calman filter

  • The algorithm not only

recognizes and tracks thunderstorm cell, but also distinguishes the split and merge of thunderstorm.

Thunderstorm cell recognition, track and Extrapolation based on the lightning data

Cell-1 Cell-3 Cell-2

Cell-2 Cell-3 Cell-1

Cluster analysis Split Merge

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Case in Mar.20 2013

Integrated in SWPC operation platform

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Improved the Mesocyclone recognition algorithm Used in WSR-98D radar Decreased FAR by diagnosing the intensity, bottom height and wind shear of a mesocyclone Decreased FAR by pattern recognition

Tornado recognition and automatic warning in Jiangsu

TVS MC HIT 38% 61% FAR 16 PUP 24 / Total Num. by improved algorithm 40 71

  • Num. by PUP

47 168

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Tornado recognition and automatic warning in Jiangsu

  • Integrated in SWATCH which is the operation platform of Jiangsu province bureau
  • Valid tornado-detected distance associated with typhoon and westerlies is 60km

and 100km

  • A weak tornado was recognized from the mixed echo nearby Nantong at 1653BJT

Aug.7 2014

  • Funing EF4 Tornado was recognized ahead of ~15 min. in Jun.23 2016
  • -- Yuanyuan Zheng 2016
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 Used only in the area within 100km from the radar station  Automatic warning used to value the risk of the electric power system

High wind recognition by radar radial velocity at 0.5 elevation angles

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SWAN2.0客户端

VIL SCIT

Blue: 30min before Red: current Green: 1 hour later

Severe Weather Automatic System(SWAN)  The main operation platform in CMA, used in many local offices  Some updating in 2015

  • Version2.0 replaced Version 1.6
  • significant change in the aspects of algorithm, data resource and

function  3DVAR wind retrieval from Doppler radar  rain cluster recognition by QPE  enhanced very-short-range forecasting capability by integrated the SCW probability forecast based on NWP output

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 Severe convective weather characteristics and its operational forecasting in CMA  0-2h Nowcasting  2-12h Very-short-range forecast  Future Prospects

Contents

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 GRAPES-RAFS (10KM, 3h update, 30h valid time),and GRAPES-CR(3KM,12h update,48h valid time) in NPC/CMA  RMAPS(9/3KM, 3h update) in Beijing Bureau  SMB-WARMS(9/3KM,3h update) in Shanghai Bureau  GRAPES-RAFS(9/3KM,3h update) in Guangdong Bureau

High resolution models

GRAPES-CR SMB-WARMS

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Evaluated the high resolution model in warm season testbed during 2013-2014  High resolution models would be useful in SCW forecast  SWPC began to develop 2-12h forecast techniques based on high resolution models in 2015 and test the 2-6h operational watch in warm season of 2015 and 2016

6h QPF TS in 18hours valid time beginning at 1200UTC during Jun.9-Jul.31 2014

HR Models

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SWPC experimental watch in 2015-2016 warm season SWPC watch and local office warning in Jul.14 2016

Thunderstorm gale and hail watch ST rainstorm watch

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Time-lagged hourly QPF ensemble prediction Based on GRAPES-RAFS

②intensity correction by frequency matching ①Weight decided by T Scores

sw

SWPS 0-12h prediction techniques

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GRAPES-RAFS prediction correction

QPF TS in June to August 2015

(red: after, blue: before) 5-10mm 10-15 15-20 20-25 25-30

Obs.

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Neighborhood calibration of the short-time rainstorm and strong echo forecast（Upscaling）

Fist：intensity correction by frequency matching，Finding the probability forecast threshold of ST rainstorm events (>20mm/h) Second：Averaged the space and temporal grids

Obs. Fore.

calibration Model forecast Color dot; obs. SWPS 0-12h prediction techniques

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Super ensemble based on the deterministic HR models Models：GRAPES-RAFS and GRAPES-CR from NPC/CMA，WRF from

Shanghai bureau, Beijing Bureau and Nanjing University, GRAPES-MESO from Guangdong

First：Uniform resolution and interpolate to 0.05x0.05 1h Second：intensity correction by frequency matching and 5-days sliding

correction

Third：various weighting for the six models Output：

  • 1/3/6h accumulated QPF every 3h
  • Every 3h updating ST rainstorm events prediction during 0-12h

SWPS 0-12h prediction techniques

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Super ensemble ST rainstorm forecast has been integrated in SWPC operational platform Criterion of the ST rainstorm warning

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  • 2-12h SCW monitoring and VSR forecasting based on Obs. and

high resolution and rapid updating models in SWPC/NMC From past to future，Efforts to achieve seamless monitoring and forecasting

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 Severe convective weather characteristics and its operational forecasting in CMA  0-2h Nowcasting  2-12h Very-short-range forecast  Future Prospects

Contents

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Chall lleng enges es fo for r nowcast asting ing and V VSR forecast casting ing

How to comprehensively use the multiple data source (radar, satellite, lightning, AWS, NWP outputs and so

  • n)to enhance the extrapolating capability and extend

the valid time of forecast

How to resolve the convective initiation

How to extend the valid warning time by optimizing the

  • perational process and cooperating between SWPC and

the local offices

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Roadmap of NWP development for 2015-2025

  • CR EPS
  • Focus on convective initiation, location and

intensity of the high wind and heavy rainfall, large scale forcing and so on

NWP plays the key and irreplaceable role

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  • To issue the 0-12h objective SCW products with 1h resolution
  • To issue the 2-6h subjective watch products to guide local office warning
  • To effort the seamless forecasting in 3days by cooperation between SWPC

and local offices

SWPC PC o

  • pera

erational t targ rget ets t to 2018 2018

SWPC 2-6h Local office 0-2h

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SWPC 2-6h watch Local offices：0-2h warning

2016：products communication between SWPC and local office 2018：products inter-work

data exchange SWPC Local office

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监测技术和多源资料融合分析技术 对流尺度天气分析技术 综合多源资料临近预报技术 基于高分辨率模式的短时预报技术

Techniques developing plan

Ensemble ,Upscaling Blending, integrated extrapolation algorithms based on radar, satellite data and so on Warn-on Forecast: to apply the convective recognition and track techniques into the HR models output HR obs. Data applied into convective analysis Comprehensive monitor Assimilation of multiple data, especialy radar and satellite data Cooperation between the

  • perational

branches and the research units

2016 2017 2018

Convection monitor and multiple data blending and analysis techniques Convective-scale analysis techniques Multiple data comprehensively nowcasting VSR Forecast techniques based on HR models

 New data and comprehensively monitor and analysis techniques  Comprehensively extrapolation techniques  HR models output Correction blending  Techniques enhanced further  Pre-warning techniques of convection initiation,deveoping and decay  To buid a SCW monitoring, nowcasting and VSR forecasting systems

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Tha Thank nk you

  • u