IMPROVING VERY-SHORT-TERM STORM PREDICTIONS BY ASSIMILATING RADAR AND

SATELLITE DATA INTO A MESOSCALE NWP MODEL

 

Allen Zhao1, John Cook1, Qin Xu2, and Paul Harasti3

1 Naval Research Laboratory, Monterey, California, USA

2 National Severe Storms Laboratory, Norman. Oklahoma, USA.

3 University Corporation for Atmospheric Research, Boulder, Colorado, USA.

Phone: (831) 656-4700 Fax: (831) 656-4769 zhao@nrlmry.navy.mil

Nowcasting and Data Assimilation

Mesoscale NWP models provide a practical means for nowcasting

• A physical-based approach

• Provide all atmospheric parameters for nowcasting convective storms and other hazardous atmospheric conditions (e.g., low ceiling & visibility)

• Smooth transition from nowcasting (0-6h) to forecasting (6-72h)

0-6 hour represents a hard period for mesoscale NWP models

• Inaccurate initial conditions due to the lack of (or poor) observational data and inadequate data assimilation procedures

• Imperfectness in model dynamics & physical parameterization

Recent developments in high-resolution data assimilation pave the way to use NWP models for nowcasting

• More and more high-resolution data are available from radars, satellites and other sensors

• New techniques, such as variational methods and ensemble-based approaches, have been developed for mesoscale data assimilation

Objective: To study the opportunity and capability of improving 0-6 hour NWP forecasts by assimilation of high-resolution observational data

COAMPS

is a registered trademark of the Naval Research Laboratory

NAVDAS

ConventionalObservations

COAMPS Forecast

T, P, Z, U, V, qv

COAMPS®

Forecast

3D Cloud Analysis

Radarreflectivity

qv, qc, qi, qr, qs, qg

Satellitedata

Blending

3D Wind Analysis

Radar radial velocity

U, V, W, T, P

or

Data Assimilation Procedures

23:08 UTC May 09, 2003 Radar Radius = 150 km

Morehead City, NC(KMHX)

Norfolk, VA(KAKQ)

Raleigh, NC(KRAX)

Model domain (100x100, 6km)

3-D radar reflectivity on COAMPS® grid(Isosurface = 20 dBZ)

1816141210 8 6 4 2

Hei

ght

(km

)

0

20

10.0 15.0 20.0 25.0 30.0 35.0 40.0 45.0 50.0 55.0 60.0

South – North (600 km)

A Convective Storm Case

A strong convective storm system on 9 May 2003 was moving southward along the east coast of the United States

The storm system entered the study area at about 1800 UTC and reached its mature stage at about 2300 UTC

Data from three WSR-88D radars in that area were collected every 5-minutes

GOES-12 IR and vis data were also collected every 30 minutes

COAMPS

is a registered trademark of the Naval Research Laboratory

ForecastCNTL

No DataAssimilation

Forecast from 12 UTC 9 May

1-hourforecast

1-hourforecast

1-hourforecast Forecast

ALL

Satellite IR and vis, Radar reflectivity and radial velocity

Forecast from 12 UTC 9 May

22 UTC21 UTC20 UTC19 UTC

1-hourforecast

1-hourforecast

1-hourforecast Forecast

CLD

Satellite IR and vis data

Forecast from 12 UTC 9 May

22 UTC21 UTC20 UTC19 UTC

1-hourforecast

1-hourforecast

1-hourforecast Forecast

CLD+PR

Satellite IR and vis data, Radar Reflectivity

Forecast from 12 UTC 9 May

22 UTC21 UTC20 UTC19 UTC

1-hourforecast

1-hourforecast

1-hourforecast Forecast

WIND

Radar radial velocity

Forecast from 12 UTC 9 May

22 UTC21 UTC20 UTC19 UTC

Five experiments have been conducted:• CNTL: no radar data assimilation

• CLD: Cloud fields from satellite observations are assimilated hourly

• CLD+PR: Cloud fields from satellite observations and precipitations from radar reflectivity data are assimilated hourly

• WIND: Radar radial velocity data are assimilated hourly

• ALL: All these fields are assimilated hourly

12-hour forecasts were made starting at 22 UTC 9 May 2003 in all five experiments

Experiment Design

4

5

6

0.48 1.49 2.37 3.38 4.26 5.31 6.24 7.47 8.65 9.97 13.9716.6919.46

Radar Elevation Angle (degree)

RM

S E

rro

rs (

m/s

)

CNTL CLDCLD+PR WINDALL

0.79

0.84

0.89

0.48 1.49 2.37 3.38 4.26 5.31 6.24 7.47 8.65 9.97 13.9716.6919.46

Radar Elevation Angles (degree)

Co

rre

lati

on

Sc

ore

s

CNTL CLDCLD+PR WINDALL

Correlation coefficients and RMS errors of 1-hour forecast radial velocity (Vrf) verified

against radar observations of all scans

(Raleigh radar station, 23:00 UTC 9 May 2003)

Wind Forecast Improvements with Forecast Time

0.55

0.65

0.75

0.85

0.95

1 2 3 4 5

CNTL CLDCLD+PR WINDALL

5

7

9

1 2 3 4 5

CNTL CLDCLD+PR WINDALL

Forecast Hour

5

7

9

11

1 2 3 4 5

CNTL CLD

CLD+PR WIND

ALL

Forecast Hour

0.5

0.65

0.8

0.95

1 2 3 4 5

CNTL CLD

CLD+PR WIND

ALL

Ele. Angle

= 2.37o

RMS Error (m1s-1)Correlation Coefficient

Ele. Angle

= 1.49o

The data assimilations affected all dynamical and hydrological fields.

The effects of the implicit latent heat from the assimilated satellite and radar reflectivity data were seen in the temperature changes and affected the wind fields significantly.

The data assimilation impacts remained in the forecasts of winds, temperature and water vapor for several hours, but decreased rapidly in the precipitation fields as the storm system weakened.

Radar radial velocity assimilation led to the biggest improvement in wind forecast, while reflectivity assimilation was the major cause of the improvement in storm location and strength prediction.

The combined data assimilation did not have the best results in each individual field forecast, but was the best in overall improvement.

Conclusions