Variational Doppler Radar Assimilation System (VDRAS) for

Ramp Prediction

Juanzhen (Jenny) Sun

MMM/RAL, NCAR

May 12, 2010

Outline

• Challenge of ramp forecast• VDRAS - background and technique• Real-time low-level frequent wind analysis • 0-6 hour convective forecast initialized by

high-resolution data• Summary

May 12, 2010

Challenge of ramp prediction

• Sudden wind change associated with thunderstorms

• Current operational NWP has difficulty in forecasting the pattern and timing of storms

• Require high resolution data (radar, lidar, mesonet, …) and advanced data assimilation techniques

May 12, 2010

Current Skill in Rainfall Prediction

0 1 2 3 4 5 6Forecast Length, hours

.2

.4

.6

.8

1.0

Accuracy of Rainfall Nowcasts>1 mm/h

GRID MESH 20 kmJun-Oct 2002

Courtesy of Shingo Yamada JMA

NWP

Crit

ical

Suc

cess

Inde

x (C

SI)

• VDRAS is an advanced data assimilation system for high-resolution (1-3 km) and rapid updated (12 min) wind analysis

• The main sources of data are radar radial velocity, reflectivity, and high-frequency surface obs.

• The core is a 4-dimensional data assimilation scheme based on a cloud-scale model

• Nowcasting can be produced by the cloud model or providing initial conditions for WRF

• VDRAS has been installed at more than 20 sites for various applications

May 12, 2010

General description of VDRAS

History of VDRAS

May 12, 2010

Development milestones

1991: First version of VDRAS developed and successfully applied to simulated radar data (Sun et al 1991)

1997: Extended to a full troposphere cloud model (Sun and Crook 1997,1998)

2001: Applied to lidar data for convective boundary layer analysis (VLAS)

2005: Added the capability to cover multiple radars (Sun and Ying 2007)

2007: Coupling with mesoscale models (mm5 or WRF)

2008: Began to explore how to use VDRAS analysis to initialize WRF

History of VDRAS cont…

May 12, 2010

Real-time installations

1998: Implemented at Sterling, NWS

2000: Installed at Sydney, Australia for the Olympics

2000-2005: Field Demonstration for FAA aviation weather program

2003-now: Run at various mission agencies

2006-2008: Real-time demonstration for Beijing Olympics 2008

Currently: NWS at Melbourne, FloridaNWS at Dallas, TexasATEC at Dugway, UtahBeijing, ChinaTaipei, Taiwan

Beijing 2008 Olympics

ATEC Dugway Utah

Data Ingest• Rawinsondes• Mesoscale model • Profilers• Mesonet• Doppler radars/lidars

Data Preprocessing• Quality control• Interpolation• Background analysis• First Guess

Output &Display (CIDD)

• Plots and images• Animations• Diagnostics and statistics

4DVAR Assimilation• Cloud-scale model• Adjoint model• Cost function• Weighting specification• Minimization

Major components of VDRAS

May 12, 2010

KVNXKDDCKICTKTLX

0 mintime

12 min 18 min6-min Forward Integration

30 min

Cold startMesoscale analysisas first guess

6-min Forecast as first guess;Mesoscale analysis

4DVar 4DVar

Output of u,v,w,T’,qv,qc,qr

Model dataSounding

VAD profile Surface obs.

Model dataSounding

VAD profile Surface obs.

How VDRAS analysis is produced with time

Output of u,v,w,T’,qv,qc,qr

VDRAS analysis by assimilating 8 NEXRADs

over IHOP domain

Radar radial velocitiesAnalyzed temperatureRed contour: 25 dBZ ref.

High-resolution data assimilation reveals how low-level wind evolves with cold pools

0611 2046 UTC - 0612 1250 UTC; every 24 min

Pert. Temp. (color)Wind vector at 0.1875km(black arrow)Red contour (25 dBZ observed reflectivity)

4DVar analyses with radar data assimilationvia VDRAS

QuickTime™ and aBMP decompressor

are needed to see this picture.

QuickTime™ and aBMP decompressor

are needed to see this picture.

VDRAS wind analysis over complex terrain in Taiwan

SPol

Red contours: observed 25 & 35 dBZ reflectivityblack contour: 100 meter terrain line

VDRAS Verification from previous studies

• ACARS(Sun and Crook 2000)

• Dual-Doppler(Crook and Sun 2004)

• Research aircraft(Sun and Crook 1998)

• Profiler, AWS (Sun et al. 2010)

May 12, 2010

Cpol

Kurnell

rms(udual – uvdras) = 1.4 m/s

rms(vdual – vvdras) = 0.8 m/s

Dual-Doppler verification

VDRAS verification for Olympics 2008 FDP

VDRAS cold pool compared with AWS

0-6 hour forecast is very sensitive to initial conditions

No radar

With radarInitial conditions

Physics

QuickTime™ and aCinepak decompressor

are needed to see this picture.

2-hour forecast of a gust front using VDRAS cloud model

Advantage:Balanced initial Conditions

Disadvantage:The model is Relatively simple

Inserting VDRAS analysis into WRF inner domain

• Interpolated fields of VDRAS analysis (MESO) to RTFDDA_d02– U-wind at the 1st level– Without (left) and with (right) weighting on RTFDDA

RTFDDA_d02

VDRAS

19 UTC 15 June 2002

2-hour WRF forecastNo VDRAS

With VDRAS

OBS

5-hour WRF forecast No VDRAS

With VDRAS

OBS

WRF Radar data assimilation

Front Range Radar data assimilation testbed through NCAR’sShort Term Explicit Prediction (STEP) program

• WRFDA 3DVAR + DDFI• WRFDA 3DVAR + RTFDDA• WRFDA EnKF• HRRR with second-pass DDFI

Obs. No radar With radar

Summary

May 12, 2010

• Accurate nowcasting of thunderstorms and the associated sudden wind change is critical for ramp prediction

• VDRAS produces robust and accurate high temporal and spatial resolution analysis of wind by combining radar, surface, and mesoscale model data and has a good potential for application of ramp prediction

• High-resolution data assimilation systems that aim at the improvement of 0-6 wind and precipitation forecasts are being actively developed and tested at NCAR