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Global and regional OSEs at JMA
Ko KOIZUMI
Numerical Prediction Division
Japan Meteorological Agency
Contents• Experiments with Global Spectral Model
– Asia-Pacific RARS and EARS– MTSAT-1R Clear-Sky Radiance– BUFR AMV (incl. MTSAT-1R Hourly AMV) instead of
SATOB
• Experiments with Meso-Scale Model– BUFR AMV (incl. MTSAT-1R Hourly AMV) instead of
SATOB– Doppler radar radial wind– Ground-based GPS
Global Experiments Specification
• Model: Global Spectral Model TL319L40• Assimilation:
– 4D-Var method– Inner model resolution: T106L40– Assimilation window: six hours– Six-hourly cycle
• Experiment period: one month each for summer and winter
• Forecasts: 216 hour forecasts once a day at 12 UTC
ATOVS used in Global Analysis
Early Analysis
Cycle Analysis
Data cut-off time : 2h20min.
Data cut-off time :
11h35min.(00 and 12 UTC)
5h35min.(06 and 18 UTC)
Coverage of RARS data
EARS
AP-RARS
2008.5.12
Analysis difference of 20hPa height(Early analysis – Cycle analysis)
06 UTC 25 Sep. 2006
Data from Beijing and Crib Point were provided by AP-RARS
06 UTC 25 Sep. 2006
Data from Beijing and Crib Point were provided by AP-RARS
with AP-RARS
w/o AP-RARS
Comparison of RMSE scores(winning % among 30 forecasts in September 2006)
(forecast hours)
Almost neutral for scores of troposphere
EARS (EUMETSAT Advanced Retransmission Service)
EARS data (AMSU-A)at 12 UTC 17 June 2007
EARS data (AMSU-B)at 12 UTC 17 June 2007
Analysis difference of 500hPa height
w/o EARS with EARS
Comparison of RMSE scores(winning % among 30 forecasts in June 2007)
(forecast hours)
•Positive impacts mainly on early hours of forecasts•Difference of impacts of AP-RARS and EARS might be due to the difference of data amount
MTSAT-1R Clear-Sky Radiance
• Infrared 3 channel (6.5-7.0 μm)• Averaging radiances of cloud-fre
e pixels in a 16 x 16 pixel region (60km x 60km at nadir)
• Thinned to 2 x 2 degree longitude/latitude and to every two hours
• Variational bias correction applied
Weighting Function
0
100
200
300
400
500
600
700
800
900
10000 0.001 0.002 0.003 0.004
dτ / dp
Pre
ssur
e(hP
a)
Comparison of RMSE scores(winning % among 31 forecasts in Aug. 2006 and Jan. 2007)
August 2006
January 2007
Typhoon track forecasts(Typhoon center position errors in August 2006)
RED: w/o MTSAT-1R CSRBLUE: with MTSAT-1R CSR
AMV in BUFR format (instead of SATOB)
• Larger amount of data, including hourly reports of MTSAT-1R AMV, are available
• Data selection using Quality Indicator (contained in the reports) is possible
More strict data selection from larger amount of candidates improves the forecasts
Data selection strategyMSM-DAGSM-DA MSM-DAGSM-DA
175hPa
225hPa
275hPa
400hPa
825hPa
975hPa
IR-NH,SH & WV-NH,SH AMVs
IR-NH,SH AMVs
ALL AMVs
ALL AMVs
ALL AMVs ALL AMVs
ALL AMVs
HL ML LL HL ML LL
I R 94/ 94 94/ 94 86/ 85 84 88 85
VIS -/ - -/ - -/ 88 - - 84
WV 95/ 95 -/ - -/ - 88 - -
I R 94/ 90 90/ 90 80/ 80 82 88 85
VIS -/ - -/ - 82/ 82 - - 82
WV 94/ 94 -/ - -/ - 84 - -
I R 60/ 60 60/ 60 60/ 60 60 60 60
VIS -/ - -/ - 60/ 60 - - 60
WV 60/ 60 -/ - -/ - 60 - -
I R 98/ 96 96/ 94 84/ 84 84 84 85
VIS -/ - -/ - 84/ 84 - - 84
WV 95/ 90 -/ - -/ - 88 - -
MTSAT-1R
Meteosat-9
GOES-11/ 12
extratropics(NH/ SH) tropics
Meteosat-7
Thinning: One datum in a 2 degree x 2 degree box in the assimilation window (6 hours)
Data not used mainly due to irremovable biases of data (or model)
QI threshold
Comparison of RMSE scores(winning % among 30 forecasts in Sep. 2005 and Jan. 2006)
September 2005
January 2006
TEST
CNTL
Num. of Samples
TEST
CNTL
Num. of Samples
Typhoon track forecasts(Typhoon center position errors in Sep. 2005)
RED: with BUFR AMVsBLUE: with SATOB AMVs
Regional Experiments Specification(except for GPS experiment)
• Model: MesoScale Model– Non-hydrostatic grid model with 5km grid distance
• Assimilation:– 4D-Var system based on a hydrostatic spectral model (former op
erational model)– Outer/ Inner resolution: 10km/20km– Assimilation window: six hours– Three-hourly cycle
• Experiment period: one or two weeks in a rainy season• Forecasts: 33 hour forecasts were made six-hourly (03,
09, 15 and 21 UTC initials)
Data selection strategyMSM-DAGSM-DA MSM-DAGSM-DA
175hPa
225hPa
275hPa
400hPa
825hPa
975hPa
IR-NH,SH & WV-NH,SH AMVs
IR-NH,SH AMVs
ALL AMVs
ALL AMVs
ALL AMVs ALL AMVs
ALL AMVs
Thinning: One datum in a 200 km x 200 km box,-in 6-hour assimilation window (test 1)-in every one hour (test 2)
HL ML LL
I R 95 95 86
VIS - - 86
WV 96 - -
MTSAT-1R
QI threshold
Data not used mainly due to irremovable biases of data (or model)
Results of an experiment in 1-15 July 2007
Against Japan Sonde Wind
hP
a
RMSE(m/s)
1000
800
600
400
200
2.8 3.0 4.0 4.2 4.43.2 3.4 3.6 3.8
Against Japan Sonde Wind
hP
a
ME(m/s)
1000
800
600
400
200
-1.2 -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2-1.4
Against Japan Sonde Wind
hP
a
RMSE(m/s)
1000
800
600
400
200
2.8 3.0 4.0 4.2 4.43.2 3.4 3.6 3.8
Against Japan Sonde Wind
hP
a
ME(m/s)
1000
800
600
400
200
-1.2 -1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2-1.4
Against R/A
Th
rea
tS
core
0.1
0.2
0.3
0.4
0.5
0 5 10 15 20 25 30 35 40 45 50
mm/3hour
Against R/A
Bia
sS
core
mm/3hour0 5 10 15 20 25 30 35 40 45 50
0.80
0.90
0.78
0.82
0.84
0.86
0.88
0.92
0.96
0.98
1.00
0.94
Against R/A
Th
rea
tS
core
0.1
0.2
0.3
0.4
0.5
0 5 10 15 20 25 30 35 40 45 50
mm/3hour
Against R/A
Bia
sS
core
mm/3hour0 5 10 15 20 25 30 35 40 45 50
0.80
0.90
0.78
0.82
0.84
0.86
0.88
0.92
0.96
0.98
1.00
0.94
RED: with SATOB AMVsGREEN: with BUFR AMVs (one datum per six hours)BLUE: with BUFR AMVs (one datum per one hour)
Threat scores of 3-hour precipitation forecast against analyzed precipitation
RMSE of wind speed forecasts at ft=3 against radiosonde observation in Japan
Weather Radars of JMA
Kushiro
Sendai
Tokyo
ShizuokaNagano
NagoyaOosaka
Murotomisaki
Sapporo
Akita
Niigata
FukuiMatsue
Hiroshima
Fukuoka
Tanegashima
Naze
OkinawaIshigaki-jima
Hakodate
PINK Doppler radar used in the analysis for MesoScale Model
YELLOW
Doppler radar planned to be used in the analysis for MesoScale Model
CYAN
Not yet Doppler-ized
Preprocessing of the data
Original data3D volume scan(resolution)-500m (radius)-0.7deg.(azimuth)-15 pre-set elevation angles
Averaged data
(resolution)-5km (radius)-5.625 deg.(azimuth)-15 pre-set elevation angles
Thinning &Quality control
Thinning (2D or 3D)
All data 2D thinning 3D thinning
Considering only two-dimensional data distribution on a cone of an elevation angle
Easy to implement but too dense near the radar
Considering three-dimensional distribution of all data
20km horizontally0.5km vertically
Quality ControlFollowing data are rejected• Number of samples in an averaging volume is smaller
than or equal to 10• Range of velocity in an averaging volume is larger
than 10m/s• Departure from first-guess is larger than 10m/s• Velocity is lower than 5m/s
– Coherent MTI algorithm sometimes works wrong with slow-moving particles
• Within 10km from the radar– To avoid backscattering noise
• Elevation angle is larger than 5.9 degree– To avoid contamination from raindrop falling
Statistical scores(8-17 June 2006)
Threshold value (mm/3hour)
Green: with Doppler velocity of Tokyo radar (w. 3D thinning)Red: w/o Doppler velocity of Tokyo radar
Threat scores of 3-hour precipitation RMSE of wind speed of six-hour forecasts against radiosondes
RMSE (m/s)
Hei
ght
(hP
a)
Impact of different thinning method
Threshold value (mm/3hour)
Green: 3D thinningRed: 2D thinning
Threat scores of 3-hour precipitation
Observationw. Tokyo radar Doppler vel.(3D thinning) w/o Tokyo radar Doppler vel.
w/o Tokyo radar Doppler vel.Observation
An example of 3-hour precipitation forecast
FT=9
FT=12
w. Tokyo radar Doppler vel.(3D thinning)
• Over 1,000 GPS receivers are owned by Geographical Survey Institute
• A real-time analysis system of ZTD and PW has been installed in JMA headquarter.
Ground-based GPS observation
GPS real-time analysis shows good agreement with radiosonde observation
(August 2005 and January 2006)
Quality control etc.• PW value is modified
according to model topography
• PW smaller than 1mm or larger than 90mm is rejected
• A datum is rejected when the departure from first guess is larger than 8mm
• A datum is rejected when the departure is larger than 5mm and differs from the averaged departures of surrounding data (within 20km) for 5mm or larger
• No thinning applied
Actual topographyModel topography
A B
C
Statistical scores for 3-hour precipitation(1 to 13 Sep. 2006)
Positive impact at FT=9 and afterPrecipitation is suppressed in early stage
The experiment was performed with the hydrostatic spectral version of MSM and the same 4D-Var as in the other experiments except for 3-hour assimilation window
An example of 3-hour precipitation forecast(FT=6-9 from 00 UTC 6 Sep. 2006)
Observation with GPS PW w/o GPS PW
Seems good, however …
Analysis increments of specific humidity (for positive departure of PW)
-6 -4 -2 0 2 4 6 8 (g/kg)
Hei
ght (
km)
0
2
4
6
8
10
When an integrated value is assimilated, the increment distribution depends on the system
insufficient(?)
mm
Summary• RARS
– Improve the operational forecast– Impact depends on the amount of available data
• CSR of MTSAT-1R– Improve the forecast especially in boreal summer– Improve typhoon track forecast
• BUFR AMV– Advantage to SATOB AMV in data amount and QI– “more strict data selection from larger volume of candidates” is
preferable to the forecast• Doppler velocity
– Impact is sensitive to data thinning• Ground-based GPS
– Positive impact can be acquired even from the near real-time data– Since the vertical distribution of analysis increment from vertically
integrated observation (such as ZTD or PW) depends on the assimilation system, some modifications to the assimilation system might be able to enhance the impacts of the data