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30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 11
Observing system experiments using the operational NWP system of JMA
with T-PARC 2008 special observations targeted for Typhoon Sinlaku
Koji Yamashita*1, Yoichiro Ohta*1, Kiyotomi Sato*1 and Tetsuo Nakazawa*2
1 : Japan Meteorological Agency
2 : Meteorological Research Institute
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 2
Outline• Objectives
• Global Experiments Specification
• Results of OSEs– Mean Track Forecast Errors– Mean Central Pressure Errors– Case study at 12UTC 11th September
• Verification of sensitivity analysis system– Two case studies
• Trial of OSEs using RS-MTSAT-2-AMV
• Summary
2
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 33
Objectives
Observational dataEvaluation
• To investigate effectiveness of next generation forecast technology, "Interactive forecast system“
• To evaluate targeted observational data for typhoon track forecasts using the JMA operational NWP system Observatio
n System
Sensitivity Analysis
Numerical Prediction
Assimilation
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 44
Global Experiments Specification• Model
– Global Spectral Model : TL959L60 ( 20km )(Reduced Gaussian Grid; top 0.1hPa)
• Assimilation
– 4D-Var method• Forecasts
– 84 hours for statistical evaluation and longer hours for case studies
• Target Typhoon ( September, 2008 )
– SINLAKU
• From 00UTC 09/09/2008 to 18UTC 18/09/2008
– JANGMI
• From 00UTC 25/09/2008 to 18UTC 30/09/2008Presentation of Mr. Ohta
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 5
Experimental Design• TEST – Special Observations are assimilated ( With Drop ).
• CNTL – No Special Observations are assimilated ( Without Drop ).
• BOGUS - TC bogus data are assimilated (with BOGUS : instead of special observation)
Utilization of special observations TEST CNTL BOGUS
Dropsonde ○ (use) × ×
Special upper sounding(3-hourly)
○ × ×
TC BOGUS × ( no use) × ○
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 6
Typhoon Track and Special Observations Distribution Map
●: Dropsonde ▲: Ship ★:Observatory
Before recurvature
After recurvature
Blue : Before recurvature ( to 06UTC 14th Sep. )Green : After recurvature ( from 00UTC 16th Sep. )
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 7
Results of OSEs (TEST vs CNTL / BOGUS vs CNTL)
– Mean Track Forecast Errors – Mean Central Pressure Errors– Case study at 12UTC 11th September
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 8
0
100
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0 12 24 36 48 60 72 84Forecast time(hours)
Posi
tional
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or
(km
)0
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0 12 24 36 48 60 72 84Forecast time(hours)
Posi
tional
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or
(km
)
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Count
Results of OSEs : TEST ~ Mean Track
Forecast Error for SINLAKU ~before-recurvature stage after-recurvature stagesignificant improvement (95% conf. lev.)
10% Improvement for 66- to 84-hour forecasts
23-30% Improvementfor 12-h forecasts
0
100
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0 12 24 36 48 60 72 840
5
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データ数
TESTCNTL
Number of data
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0 12 24 36 48 60 72 840
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データ数
TESTCNTL
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 9
Results of OSEs : BOGUS ~ Mean Track Forecast Error for SINLAKU ~
before-recurvature stage after-recurvature stage
0
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0 12 24 36 48 60 72 84Forecast time(hours)
Posi
tional
err
or
(km
)
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Count
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0 12 24 36 48 60 72 84Forecast time(hours)
Posi
tional
err
or
(km
)0
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Count
Number of data
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0 12 24 36 48 60 72 840
5
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データ数
BOGUSCNTL
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0 12 24 36 48 60 72 840
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データ数
BOGUSCNTL
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0 12 24 36 48 60 72 840
5
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データ数
10-23% Worse for 6- to 30-h forecasts
15% Improvementfor 60- to 72-h forecasts
No significant difference
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 10
Results of OSEs : TEST ~ Mean Central Pressure Error for SINLAKU ~
before-recurvature stage after-recurvature stage
- 10
0
10
20
30
40
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0 12 24 36 48 60 72 84
Forecast time(hours)
ME o
f C
entr
al P
ress
ure
err
or
(hPa)
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10
15
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25
30
Count
0
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0 12 24 36 48 60 72 840
5
10
15
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データ数
TESTCNTL
- 10
0
10
20
30
40
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0 6 12182430364248546066727884
Forecast time(hours)
ME o
f C
entr
al P
ress
ure
err
or
(hPa)
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0
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0 12 24 36 48 60 72 840
5
10
15
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データ数
TESTCNTL
Number of data
significant improvement (95% conf. lev.)
Over 10hPa reduction of intensity bias for 36-hour forecasts
Little significant difference
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 11
Results of OSEs : BOGUS ~ Mean Central Pressure Error for
SINLAKU ~before-recurvature stage after-recurvature stage
- 10
0
10
20
30
40
50
0 12 24 36 48 60 72 84
Forecast time(hours)
ME o
f C
entr
al P
ress
ure
err
or
(hPa)
0
5
10
15
20
25
30
Count
- 10
- 8
- 6
- 4
- 2
0
2
4
6
8
10
0 6 12182430364248546066727884
Forecast time(hours)
ME o
f C
entr
al P
ress
ure
err
or
(hPa)
0
5
10
15
Count
significant improvement (95% conf. lev.)
0
100
200
300
0 12 24 36 48 60 72 840
5
10
15
20
25
30
データ数
BOGUSCNTL
0
100
200
300
0 12 24 36 48 60 72 840
5
10
15
20
25
30
データ数
0
100
200
300
0 12 24 36 48 60 72 840
5
10
15
20
25
30
データ数
BOGUSCNTL
0
100
200
300
0 12 24 36 48 60 72 840
5
10
15
20
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30
データ数
Number of data
Over 10hPa reduction of intensity bias for 24-hour forecasts
Slightly stronger intensity bias for 18- to 84-h forecasts
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 12
Case study at 12UTC 11th September12
Core
SINLAKU environmental field
11Z
13Z12Z
14Z
C-130 targeted observation data and observed time
TC center
Case study using C-130 aircraft data
Typhoon Forecast Track
○: using observations × : using no observations
C-130 Others Drop BOGUS
With Drop ○ ○ ×
Without C-130 × ○ ×
With BOGUS × × ○
12
1314
15 1617
18
1213
14
16 17
18
19
2019
15 Rapid recurvature
and fast moving
Test (with Drop): Increased track forecast errors by using all C-130 data
Without C-130 (almost same as CNTL): Better track forecasts at the beginning With BOGUS: Better track forecasts at the
beginning. Recurvature didn’t occur.
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 13
Why was the worse typhoon track forecast brought for “With Drop”?
(m)
850-1000 hPa
Difference of average analysis (Z and Wind) at 12UTC 11th September
400-700 hPa
m/s
Test ( With Drop ) – Cntl ( Without C-130 )
Deepened Z and strengthened circulation in the south or east side of TC center
Moving the typhoon to the south, and next moving to the north-east TC track forecast of
Test from FT0 to FT12
FT0
FT6
FT12
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 14
What brought the worse typhoon track forecast ?
14
1000hPa
700hPa900hPa
S
N
EW
300km
200km
Dropsonde average wind observations around the center of SINLAKU at 12UTC 11th September 2008
Assimilated dropsonde observations in the SINLAKU core fields within 200km
Different from observed typhoon center
Biased and warpedvortex to the south
Moving the typhoon to the south Next moving to the north-east
Probably the worse forecast is caused by assimilating the dropsonde data in the core.
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 15
First Summary
• Special observations contributed to improve the track and intensity forecasts especially during the before-recurvature stage.
• The typhoon track errors increased by using special observations .
General results for SINLAKU
From case Study at 12UTC 11th September
• It's better not to assimilate dropsonde observations in vicinity of the TC center.
• TC bogus data instead of special observation were generally efficient to improve the TC track and intensity forecasts.
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 16
Outline• Objectives
• Global Experiments Specification
• Results of OSEs– Mean Track Forecast Errors– Mean Central Pressure Errors– Case study at 12UTC 11th September
• Verification of sensitivity analysis system– Two case studies
• Trial of OSEs using RS-MTSAT-2-AMV
• Summary
16
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 17
Verification of sensitivity analysis system
First case study of 9/11 from 00 to 12 UTC
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 18
0
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0 6 12 18 24 30 36 42 48 54 60 66 72 78 84
Forecast time (hour)
Posi
tional
err
or
(km
)
CNTLCase ACase B
TEST with special observations – 9/11 from 00 to 12 UTC -
High sensitive area
Forecasted field T+24h
Case ACase B
Init. 00 UTC 10/09/2008 Sensitivity area
using SV method at 00 UTC 11/09/2008
(First SV)
Case A : Using special observations in the N-E area of typhoon center
Case B : Using special observations in the S-W area of typhoon center
CNTL : No special observations are assimilated
Case A : decreased
Case B : increased
Track forecast errors
Mean Track Forecast Error
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 19
TEST with special observations of Case A for humidity – 9/11 from 00 to 12 UTC -
Init. 00 UTC 10/09/2008 Sensitivity area
using SV method at 00 UTC 11/09/2008
(First SV)
Targeted area
EXP. Wind Temperature humidity
ALL ○ ○ ○NOVAPOR ○ ○ ×
CNTL × × ×
ALL : av. 16% Improvement
NOVAPOR : av. 10% Improvement
Case A =
ALL : av. 32 - 45% Improvement
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 20
Why the errors were reduced in Case A ?
N N
E E
Wind Wind
Q :N
Q :NE
Q :E
Q :N
Q :NE
Q :E
The mean departure of 3D dropsonde wind and mixing ratio observations
from the first-guess (O-B) from the analysis (O-A)
Red vector : greater than 10 m/s Blue vector : greater than 5 m/s
The analysis was close to the observations.
The special observations in the north-east sensitivity area of TC center contributed to
reduce the track errors.
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 21
Why the errors increased in Case B?
0
50
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250
0 6 12 18 24 30 36 42 48 54 60 66 72 78 84
Forecast time (hour)
Posi
tional
err
or
(km
)
CNTLCase ACase B
Mean Track Forecast Error
High sensitive area
Forecasted field T+24h
Case ACase B
Worse forecasts
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 22
Why the errors increased in Case B?
Case A
Case BCNTL (no use) O-A in Case B
O-B in Case BN
N
E
E
W
W
blue 5m/s≧ red 10m/s≧
TC track forecast
BST: Observed TC position at JMA
The observations were not reflected in the analysis..
The departure of 3D dropsonde wind
The number of observations in Case B was much less than in Case A.
We are considering the reason.
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 23
Second SummaryVerification of sensitivity analysis system
• Case study of 11th September– Special observations in high sensitive area in the N-E
quadrant of SINLAKU environmental field were effective.
– Possibility as the tool of “ Interactive forecast system”
• The improvement of TC track forecasts was found in the early hour and after FT=60.
• The humidity observations contributed to improve TC track forecast errors after FT=60. However, they brought almost no impact of forecasts in the early hour.
( All OBS : av. 16% Improvement , without humidity: av. 10% Improvement )
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 24
Second SummaryVerification of sensitivity analysis system
• Case study of 11th September – Special observations in high sensitive area in the S-W side of
SINLAKU environmental field brought worse TC track forecasts.
• The observations were not fitting to the analysis.• The number of observations was much less than in the N-E side of
TC center.• We are considering the reason..
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 25
Verification of sensitivity analysis system
Second case study of 00 UTC 10th September
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 26
TEST with special observations – 9/10 00 UTC -
Area A
Area B
Special Observations
Init. 00 UTC 09/09/2008 Sensitivity area
using SV method at 00 UTC 10/09/2008
(First SV) 0
50
100
150
200
250
0 12 24 36 48 60 72 84
Forecast time (hour)
Pos
itio
nal er
ror
(km
)
NODATAALL(A+B)Area AArea B
Exp. SP.OBS: Area A
SP.OBS: Area B
Result of forecasts
NODATA × × CNTL
ALL(A+B) ○ ○ Neutral
Area A ○ × Worse
Area B × ○ Better
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 27
Cause of result in case of 00 UTC 10 September
Area A
NO DATA
Area BALL(A+B)
TC track forecast
BST: Observed TC position at JMA
Modification of circulation in the N-E area of TC center ( Area A )
O-B in ALL
O-A in ALL
blue 5m/s≧ red 10m/s≧
Moving the typhoon to the northward especially in Area A
N
E
W
N
E
W
S
SBetter
Better
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 28
Third SummaryVerification of sensitivity analysis system• Case study of 10th September
– Special observations in high sensitive area in the N-E side of TC were not effective.
– Special observations in low sensitive area in the S-W side of TC were effective.
• Modifying of counterclockwise circulation in the N-E area of TC center, and moving the typhoon to the northward
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 29
Trial of OSEs using RS-MTSAT-2-AMV
at 18 UTC 17th September
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 30
Experimental Design ( TEST and CNTL)• Same as global experiments specification for special
observations– TL959L60 ( 20km ), 4D-Var method
• Without the TC bogus data and special observations
• Usage of two kinds of MTSAT-2 rapid scan AMV ( only TEST )– Cloud images of the intervals of 4 or 7 minutes
• All winds are thinned by 1°in horizontal and 100 hPa in vertical. A minimum horizontal distance is 100km.
• Only one wind selected per box in the hourly time window • Added to other AMVs of satellite data
– The intervals of 15 minutes (same as usage of the others GS wind ) • All winds are thinned by 2°in horizontal and 100 hPa in vertical. A minimum
horizontal distance is 200km.• Only one wind selected per box in the 6 hour time window • Other AMVs are assimilated together.
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 31
Example of AMV after QC at 18 ~ 19UTC 11th September
≒100 km thinning
Others 200 km thinning
Red color ≦ 400hPa level
Blue color ≧ 850hPa level
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 32
Result of OSE
Slightly improvement of slow bias speed for TC track forecasts
TC track forecast
18
19
20
19
Mean Positional Error For SINLAKU
(00 UTC 9 September 2008 ~18 UTC 14 September 2008)
0
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200
300
0 12 24 36 48 60 72 84Forecast time(hours)
Posi
tiona
l err
or
(km
)
0
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Coun
t
データ数
TESTCNTL
Mean Positional Error For SINLAKU
(00 UTC 9 September 2008 ~18 UTC 14 September 2008)
0
100
200
300
0 12 24 36 48 60 72 84Forecast time(hours)
Posi
tiona
l err
or
(km
)
0
5
10
15
20
25
30
Coun
t
データ数
TESTCNTL
Track Forecast Error
Possibility of improvement for TC track forecasts using RS-MTSAT-2-AMV data
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 33
Thank you for your attention
33
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 34
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique
TC bogus ( Outline )35
• Tropical Cyclone generated on the Northwest Pacific ocean
• Wind speed is greater than 28 knots.
• Setup• Horizontal
• Psea • Wind except TC center • Four bogus data are located every 200 km from
TC center. • Vertical
• Wind except TC center• Located on the standard isobaric surface
(1000,925,850, 700,500,400 and 300 hPa )
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 36
Case study at 12UTC 11th September36
Core
SINLAKU environmental field
11Z
13Z12Z
14Z
C-130 targeted observation data and observed time
TC center
11Z 12Z 13Z 14Z Result
With Drop ○ ○ ○ ○ Worse (Rapid recurvature and moving)
Without C-130 × × × × Better track forecast at the beginning
With 11/12UTC ○ ○ × × Better; Recurvature did not occur
With 13UTC × × ○ × Better track forecast at the beginning; Nearly BST
With 14UTC × × × ○ Better track forecast at the beginning
Without 13UTC ○ ○ × ○ Nearly BST ( good track forecast )
With 13/14UTC × × ○ ○ Nearly BST ( good track forecast )
17
18
1615
141312
19
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19
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1213
14
19 2017
18
1615
141312
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1716
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1213
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19 20
18
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171615
1413
131415 16
17
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1212
19
19
18
19
171615
1413
131415 16
17
18
1212
19
19
Case study using C-130 aircraft data
Typhoon Forecast Track
Increased track forecast errors by using all C-130 data
Better track forecasts at the beginning
○: using observations × : using no observations
Sensitive in the TC center core fields
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 3737
Core
SINLAKU environmental field
11Z
13Z12Z
14Z14Z
C-130 targeted observation data and observed time
TC center
30 November 2009 - 2 December
International Workshop on Advancement of Typhoon Track Forecast Technique 38