Ui -Yong Byun , Song-You Hong, Hyeyum Shin Deparment of Atmospheric Science, Yonsei Univ

WRF-based short-range forecast system of the Korea

Air Force : verification of prediction

skill in 2009 summer

Ui-Yong Byun, Song-You Hong, Hyeyum ShinDeparment of Atmospheric Science, Yonsei Univ.

Ji-Woo Lee, Jae-Ik Song, Sook-Jung Ham, Jwa-Kyum Kim, Hyung-Woo Kim73rd Weather Group, Republic of Korea Air Forece

Numerical Modeling Laboratory, Department of Atmospheric Sciences, Yonsei University

Introduction

Configuration of KAF-WRF

Configuration of verification system

Results

Further study

Summary

Outline


WRF model is designed for both research and operational appli-cations.

Research of extreme weather in Korea peninsula using WRF model Lee et al, 2005 : Orographic effect for a heavy rainfall Lim et al, 2007 : Heavy snowfall over the Ho-Nam province

WRF model operation in forecast institution of Korea Jo et al, 2005 : KWRF construction and test run in KMA The 73rd Weather Group (73WG) of Republic of Korea Air Force (ROKAF) oper-

ates the KAF-WRF model based on Weather Research and Forecasting (WRF) model since 2007.

In this study, KAF-WRF model results in 2009 summer are evalu-ated using quantitative verification system.

Introduction


Configuration of KAF-WRF

250 x 250211 x 211230 x 170Grids

24hr84hr

KAF-WRF V07 (based on WRFv2.2)Model version

31 LayerVertical Layer

None

Noah LSMLSM

RRTM(LW), Dudhia Scheme (SW)Radiation

YSU PBLPBL

Kain-FritcshCumulus

WSM6Microphysics

84hrFCST

2 km6 km18 kmResolution

DM 3DM 2DM 1

250 x 250211 x 211230 x 170Grids

24hr84hr

KAF-WRF V09 (based on WRFv3.1)Model version

31 LayerVertical Layer

None

Noah LSMLSM

RRTM-G(LW), Goddard SW(SW)Radiation

YSU PBLPBL

Kain-FritcshCumulus

WDM6Microphysics

84hrFCST

2 km6 km18 kmResolution

DM 3DM 2DM 1

WSM3

Operation model Experimental model

+ Ocean Mixed Layer+ MODIS Land use data


Domain 1 Domain 2

18 km 6 km12 00 24 36 48 60 72 84

4 times/day84 hour fcst.



Configuration of verification system (domain 1)

00 12 24 36 48

1-day00 UTC :

1-day12 UTC :

Making difference data Monthly mean data

Field figure & score – SLP., 500hPa GPH., Temp., wind

2-day00 UTC :


Configuration of verification system (domain 2)

Extracting precipitation field from model output

Changing the precipitation data from field to point

Extracting 1hr precipitation from AWS

data

Making 6hr precipitation data

Making skill scoreUsing contingency table

Model output process AWS data process


Verification Model : KAF-WRF V07, V09 Period : 2009. JJA Parameter

Domain 1 : SLP., 500hPa GPH, Temperature, Wind

Domain 2 : 6 hour accumulated precipitation Statistics

Domain 1 : RMSE, Bias score Domain 2 : Skill score

Result


Result - domain 1

2009. 07. 24hr fcst

9.438

7.768

500hPa GPH.SLP

KAF-WRF V07

KAF-WRF V09

1.593

1.515


Result - domain 1

2009. 07. 24hr fcst

KAF-WRF V07

KAF-WRF V09

0.725

0.718

U : 2.837V : 2.821

U : 2.781V : 2.744

500hPa Temp. 500hPa Wind


• Bias : Sea level pressure

• RMSE : Sea level pressure

06 12 18 24 30 36 42 480

0.5

1

1.5

2

2.5

3

3.5

4

KW07 JunKW07 JulKW07 AugKW09 JunKW09 JulKW09 Aug

06 12 18 24 30 36 42 48

-1.2

-1

-0.8

-0.6

-0.4

-0.2

0


06 12 18 24 30 36 42 480

1

2

3

4

KW07 JunKW09 Jun

06 12 18 24 30 36 42 480

1

2

3

4

OPR JulEXP Jul

06 12 18 24 30 36 42 480

0.51

1.52

2.53

3.54

OPR AugEXP Aug


06 12 18 24 30 36 42 480

2

4

6

8

10

12

14

16

18


06 12 18 24 30 36 42 480

0.2

0.4

0.6

0.8

1

1.2


06 12 18 24 30 36 42 48

-4

-3

-2

-1

0

1

2

3


06 12 18 24 30 36 42 480

0.05

0.1

0.15

0.2

0.25

0.3

0.35


• Bias : 500hPa Geopotential Height

• RMSE : 500hPa Geopotential Height

• Bias : 500hPa Temperature

• RMSE : 500hPa Temperature


• Bias : 500hPa u-wind

• RMSE : 500hPa u-wind

• Bias : 500hPa v-wind

• RMSE : 500hPa v-wind

06 12 18 24 30 36 42 48

-0.25

-0.2

-0.15

-0.1

-0.05

0

0.05


06 12 18 24 30 36 42 48

-0.3

-0.25

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2


06 12 18 24 30 36 42 480

0.5

1

1.5

2

2.5

3

3.5

4

4.5


06 12 18 24 30 36 42 480

0.51

1.52

2.53

3.54

4.55



Contingency table

POD = H / (M + H) ; Probability of Detection FAR = F / (H + F) ; False Alarm Ratio Bias = (H + F) / (H + M) ; Bias Score ETS = (H – E) / (H + M + F – E)

( E = (H + F) x (H + M) / (H + M + F + C) ); Equitable Threat Score

Result - domain 2

Forecast

Yes No

Observati

on

Yes H M Observation yes

No F C Observation no

Forecast yes Forecast no


Precipitation analysis

Result - domain 2

AWS KAF-WRF V09

2009. 07. 1-month precipitation


’09. June 12hr fcst precipitation (6 hour accumulated)

0.5 1 3 5 7 10 15 20 250

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

KW07KW09

0.5 1 3 5 7 10 15 20 250

0.1

0.2

0.3

0.4

0.5

0.6

KW07KW09

0.5 1 3 5 7 10 15 20 250

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

KW07KW09

0.5 1 3 5 7 10 15 20 250

0.050.1

0.150.2

0.250.3

0.350.4

0.450.5

KW07KW09

• POD

•Bias

• FAR

• ETS

Found a problem with weak precipitation


OBS : TMPA & FNL WSM6 exp. WDM6 exp.

Hong et al., 2010

Int : 2008.02.23 00 UTC, 36hr fcst, 6hr precip.

Nc Nr

A : B :

B

A


Purpose of further study Finding the cause of low accuracy of KAF-WRF V09 on

weak precipitation. Improvement of accuracy of weak precipitation

Possibility 1 : Microphysics Microphysics is changed from V07 to V09

Further Study (1)

Domain 1 Domain 2

KAF-WRF V07 (OPR)

WSM6 WSM6

KAF-WRF V09 (EXP) WSM3 WDM6


Int : 2010.08.24 00 UTC, Valid : 15 UTC, 3hr precip.

KAF-WRF V07WSM6-WSM6

KAF-WRF V09WSM3-WDM6

KAF-WRF V09WDM6-WDM6

KAF-WRF V09WSM6-WDM6

OPR EXP


Possibility 2: Error of YSU PBL

Some error of YSU PBL was corrected in updated WRF model (ver. 3.2.1). Minor bug fixes for PBL Prandtl number calculation in stable and unstable

condition.

WRF model that based on WRF ver. 3.2.1 and that has same physics setting with ‘KAF-WRF V09’ , is defined ‘KAF-WRF V10’.

Select case - 2009. 07. 09. precipitation Initial time : 2009. 07. 08. 12 UTC

: 2009. 07. 09. 00 UTC : 2009. 07. 09. 12 UTC

Compare the verification score; KAF-WRF V07, V09, V10

Further Study (2)


12hr fcst precipitation (6 hour accumulated)

• POD

•Bias

• FAR

• ETS0.5 1 3 5 7 10 15 20 25

00.10.20.30.40.50.60.70.80.9

1

V07V09V10

0.5 1 3 5 7 10 15 20 250

0.05

0.1

0.15

0.2

0.25

0.3

V07V09V10

0.5 1 3 5 7 10 15 20 250

0.2

0.4

0.6

0.8

1

1.2

V07V09V10

0.5 1 3 5 7 10 15 20 250

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

V07V09V10


Summary

Quantitative verification system is constructed

RMSE and Bias score of SLP, 500hPa Geopotential Height, temper-ature and wind of the KAF-WRF V09 shows better performance than V07.

Verification result of precipitation shows different patterns de-pending on precipitation intensity Score of V07 is better than V09 in weak precipitation intensity (less than 3 mm/6hour)

Score of V09 is better than V07 in heavy precipitation intensity (more than 10 mm/6hour)

Accuracy of light-precipitation prediction is possible to increase adapting microphysics change and PBL debug.

ROKAF has plan that is changed EXP model instead of OPR model

Thank you


Minor bug fixes for PBL Prandtl number calculation in stable and unstable condition.

PR = 1 + (PR_0 – 1) x exp(PR_fac)PR_0 = (ph_h/ph_m + prfac)

prfac = conpr / ph_m / (1 + 4 x karman * wstar3 / ust3) prfac = conpr / ph_m / (1 + 4 x karman * wstar3 / ust3)^h1 (h1 = 0.33333335) PR = momentum diffusivity(Km) / heat, moisture diffusivity(Kh)

(0.25 <= PR <= 4.0)

It means ‘prfac’ of new ver. has larger values in same con-dition. Also, ‘PR_0’ and ‘PR’ has larger values. In boundary layer, Km Kh ; Kh ↓ In free atmosphere and stable condition, Kh Km ; Km ↑


KAF-WRF V07 WSM6 KAF-WRF V09 WSM3

KAF-WRF V09 WDM6KAF-WRF V09 WSM6

2010.08.24 00 UTC, 48 hour precip.


KAF-WRF V07 KAF-WRF V09 KAF-WRF test

Int : 2009.07.09 00 UTC, Valid : 12 UTC, 6hr precip.

Documents

Ui -Yong Byun , Song-You Hong, Hyeyum Shin Deparment of Atmospheric Science, Yonsei Univ