eurobrisa workshop, paraty 17-19 march 2008, ecmwf system 3 1 the ecmwf seasonal forecast system-3...
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EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 1
The ECMWF Seasonal Forecast
System-3
Magdalena A. BalmasedaFranco Molteni,Tim Stockdale Laura Ferranti,
Paco Doblas-Reyes, Frederic Vitart
European Centre for Medium-Range Weather Forecasts, Reading, U.K.
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 2
Overview
• Introduction to Seasonal Forecasts End to End Seasonal Forecasting System Importance of Ocean Initial Conditions
• ECMWF Seasonal forecasting system 3 Overview Performance Web products
• Calibration of model output
• Multimodel (EUROSIP)
• Calibration + Multimodel
• Summary
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 3
Pro
bab
ilist
ic
fore
cast
calib
ratio
n Rel
iab
le p
rob
abili
ty f
ore
cast
sT
ailo
red
pro
du
cts
End to End
Forecasting System
atmosDA
atmos obs
SST analysis
oceanDA
ocean obs
ocean reanalysis
atmos reanalysis
land,snow…?
sea-ice?
initialconditions
initialconditions
AGCM
OGCM
ensemble
generation
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 4
1997-1998 El-Niño forecast
50OE 100OE 150OE 160OW 110OW 60OW 10OW
Longitude
50OS
0O
50ON
Latit
ude
Contour interval = 1 deg CSea Surface TemperatureECMWF S3 ocean analysis: Anomaly
Interpolated in y1981-2005 climatology
respect to19970716 (31 days mean)
1
1
1
1
2
2
3
-6-4-2.5-2-1.5-1-0.50.511.522.5346
MAGICS 6.11 bee17 - emos Wed Mar 21 13:27:57 2007
Initial Conditions Forecast
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 5
2007 La Niña
50OE 100OE 150OE 160OW 110OW 60OW 10OW
Longitude
50OS
0O
50ON
Latit
ude
Contour interval = 1 deg CSea Surface TemperatureECMWF S3 ocean analysis: Anomaly
Interpolated in y1981-2005 climatology
respect to20070116 (31 days mean)
1
1
1
1
1
-6-4-2.5-2-1.5-1-0.50.511.522.5346
MAGICS 6.11 bee07 - emos Wed Mar 21 13:00:48 2007
50OE 100OE 150OE 160OW 110OW 60OW 10OW
Longitude
300
250
200
150
100
50
0
Dep
th (
met
res)
Contour interval = 1 deg CPotential Temperature along the EquatorECMWF S3 ocean analysis: Anomaly
Interpolated in y1981-2005 climatology
respect to20070116 (31 days mean)
-9.5-8.5-7.5-6.5-5.5-4.5-3.5-2.5-1.5-0.50.51.52.53.54.55.56.57.58.59.5
MAGICS 6.11 bee07 - emos Wed Mar 21 12:58:22 2007
JUL2006
AUG SEP OCT NOV DEC JAN2007
FEB MAR APR MAY JUN JUL AUG SEP
-1
0
1
2
Ano
mal
y (d
eg C
)
-1
0
1
2
Monthly mean anomalies relative to NCEP adjusted OIv2 1971-2000 climatologyECMWF forecast from 1 Jan 2007
NINO3.4 SST anomaly plume
Produced from real-time forecast data
System 3
50OE 100OE 150OE 160OW 110OW 60OW 10OW
Longitude
50OS
0O
50ON
Latit
ude
Contour interval = 1 deg CSea Surface TemperatureECMWF S3 ocean analysis: Anomaly
Interpolated in y1981-2005 climatology
respect to20070816 (31 days mean)
-2
-1
-1
-1
1
1
124
-6-4-2.5-2-1.5-1-0.50.511.522.5346
MAGICS 6.11 bee19 - emos Tue Sep 11 15:33:41 2007
Initial Conditions
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 6
Magdalena A. Balmaseda
Slide 6
Observations used in the S3 ocean analysis
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 7
Impact on ECMWF-S3 Forecast Skill
In ECMWF S3, ocean Data Assimilation improves forecast skill in the Equatorial Pacific, especially in the
Western Part
0 1 2 3 4 5 6 7Forecast time (months)
0.4
0.5
0.6
0.7
0.8
0.9
1
An
om
aly
co
rre
latio
n
wrt NCEP adjusted OIv2 1971-2000 climatology
NINO4 SST anomaly correlation
0 1 2 3 4 5 6 7Forecast time (months)
0
0.2
0.4
0.6
0.8
Rm
s e
rro
r (d
eg
C)
Ensemble sizes are 3 (esj6) and 3 (esj6) 76 start dates from 19870101 to 20051001
NINO4 SST rms errors
Fc esj6/m1 Fc esj6/m0 Persistence Ensemble sd
MAGICS 6.10 hyrokkin - neh Thu Sep 7 19:11:46 2006
S3 Nodata S3 Assim
The impact of ocean initialization in the prediction of SST is comparable to the
impact of atmospheric model cycle
S2 S2ic_S3model S3
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 8
•COUPLED MODEL (IFS + OASIS2 + HOPE)•Recent cycle of atmospheric model (Cy31R1)•Atmospheric resolution TL159 and 62 levels•Time varying greenhouse gasses.•Includes ocean currents in wave model
•INITIALIZATION•Includes bias correction in ocean assimilation.•Includes assimilation of salinity and altimeter data. •ERA-40 data used to initialize ocean and atmosphere in hindcasts•Ocean reanalysis back to 1959, using ENACT/ENSEMBLES ocean data
•ENSEMBLE GENERATION•Extended range of back integrations: 11 members, 1981-2005.•Revised wind and SST perturbations. •Use EPS Singular Vector perturbations in atmospheric initial conditions.
•Forecasts extended to 7 months (to 13 months 4x per year).
The seasonal forecast System-3 (implem. March 07)
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 9
Rms error of forecasts has been systematically reduced (solid lines) ….
Rms error / spread in different ECMWF systems
0 1 2 3 4 5 6Forecast time (months)
0.4
0.5
0.6
0.7
0.8
0.9
1
An
om
aly
co
rre
latio
n
wrt NCEP adjusted OIv2 1971-2000 climatology
NINO3.4 SST anomaly correlation
0 1 2 3 4 5 6Forecast time (months)
0
0.2
0.4
0.6
0.8
1
Rm
s e
rro
r (d
eg
C)
Ensemble sizes are 5 (0001), 5 (0001) and 5 (0001)192 start dates from 19870101 to 20021201
NINO3.4 SST rms errors
Fcast S3 Fcast S2 Fcast S1 Persistence
MAGICS 6.11 cressida - net Tue Apr 17 16:45:18 2007
.. but ensemble spread (dashed lines) is still substantially less than actual forecast error.
0 1 2 3 4 5 6Forecast time (months)
0.4
0.5
0.6
0.7
0.8
0.9
1
An
om
aly
co
rre
latio
n
wrt NCEP adjusted OIv2 1971-2000 climatology
NINO3.4 SST anomaly correlation
0 1 2 3 4 5 6Forecast time (months)
0
0.2
0.4
0.6
0.8
1
Rm
s e
rro
r (d
eg
C)
Ensemble sizes are 5 (0001), 5 (0001) and 5 (0001)192 start dates from 19870101 to 20021201
NINO3.4 SST rms errors
Fcast S3 Fcast S2 Fcast S1 Persistence Ensemble sd
MAGICS 6.11 cressida - net Tue Apr 17 16:41:30 2007
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 10
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18Calendar month
24
25
26
27
28
29
30
Ab
solu
te S
ST
NINO3.4 mean absolute SST
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18Calendar month
-3
-2
-1
0
1
2
3
Dri
ft (
de
g C
)
NINO3.4 mean SST drift
Fcast S3
MAGICS 6.11 cressida - net Mon Feb 5 17:34:33 2007
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Verification month
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
An
om
aly
co
rre
latio
n
wrt NCEP adjusted OIv2 1971-2000 climatology
NINO3.4 SST anomaly correlation at 5 months
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Verification month
0
0.2
0.4
0.6
0.8
1
1.2
Rm
s e
rro
r (d
eg
C)
Ensemble size is 11300 start dates from 19810101 to 20051201
NINO3.4 SST rms errors at 5 months
Fcast S3 Persistence Ensemble sd
MAGICS 6.11 cressida - net Tue Feb 6 09:26:44 2007
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 11
0 1 2 3 4 5 6 7Forecast time (months)
0.4
0.5
0.6
0.7
0.8
0.9
1
An
om
aly
co
rre
latio
n
wrt NCEP adjusted OIv2 1971-2000 climatology
ATL3 SST anomaly correlation
0 1 2 3 4 5 6 7Forecast time (months)
0
0.2
0.4
0.6
0.8
Rm
s e
rro
r (d
eg
C)
Ensemble size is 11300 start dates from 19810101 to 20051201
ATL3 SST rms errors
Fcast S3 Persistence Ensemble sd
MAGICS 6.11 cressida - net Tue Feb 6 09:26:44 2007
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Verification month
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
An
om
aly
co
rre
latio
n
wrt NCEP adjusted OIv2 1971-2000 climatology
ATL3 SST anomaly correlation at 5 months
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Verification month
0
0.2
0.4
0.6
0.8
1
Rm
s e
rro
r (d
eg
C)
Ensemble size is 11300 start dates from 19810101 to 20051201
ATL3 SST rms errors at 5 months
Fcast S3 Persistence Ensemble sd
MAGICS 6.11 cressida - net Tue Feb 6 09:26:44 2007
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18Calendar month
24
25
26
27
28
29
30
Ab
solu
te S
ST
ATL3 mean absolute SST
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18Calendar month
-3
-2
-1
0
1
2
3
Dri
ft (
de
g C
)
ATL3 mean SST drift
Fcast S3
MAGICS 6.11 cressida - net Mon Feb 5 17:34:33 2007
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 12
ACC for seasonal-mean (1981-2005)
2m-T: DJF from 1 Nov 2m-T: JJA from 1 May
Precip: DJF from 1 Nov Precip: JJA from 1 May
Doblas-Reyes
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 13
New products in the web:ocean reanalysis
http://www.ecmwf.int/products/forecasts/d/charts/ocean/reanalysis/
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 14
New products from Sys-3: annual-range Nino indices
S2007
O N D J2008
F M A M J J A S O N D J2009
F M A-2
-1
0
1
2
3A
nom
aly
(deg
C)
-2
-1
0
1
2
3Monthly mean anomalies relative to NCEP adjusted OIv2 1971-2000 climatology
ECMWF forecast from 1 Feb 2008NINO3 SST anomaly plume
Forecast issue date: 15 Feb 2008
System 3
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 15
New products from Sys-3: ’tercile summary’
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 16
New products from Sys-3: climagrams
a) Teleconnection and monsoon
indices with verification
http://www.ecmwf.int/products/forecasts/d/charts/seasonal/forecast/
Feb
ruar
yM
arch
Apr
ilM
ayJu
neJu
lyA
ugus
t
-6
.3
-5.0
-3.8
-2.5
-1.3
-0.0
1.3
2.5
3.8
5.0
En
se
mb
le s
ize
: F
ore
ca
st=
41
Mo
de
l clim
ate
=2
75
An
aly
sis
clim
ate
=2
5 F
ore
ca
st
init
ial d
ate
: 2
00
8 2
01
Eq
ua
tori
al S
ou
the
rn O
sc
illa
tio
n
Feb
ruar
yM
arch
Apr
ilM
ayJu
neJu
lyA
ugus
t
-6
.3
-5.0
-3.8
-2.5
-1.3
-0.0
1.3
2.5
3.8
5.0
En
se
mb
le s
ize
: F
ore
ca
st=
41
Mo
de
l clim
ate
=2
75
An
aly
sis
clim
ate
=2
5 F
ore
ca
st
init
ial d
ate
: 2
00
8 2
01
Eq
ua
tori
al S
ou
the
rn O
sc
illa
tio
n
Feb
ruar
yM
arch
Apr
ilM
ayJu
neJu
lyA
ugus
t
-6
.3
-5.0
-3.8
-2.5
-1.3
-0.0
1.3
2.5
3.8
5.0
En
se
mb
le s
ize
: F
ore
ca
st=
41
Mo
de
l clim
ate
=2
75
An
aly
sis
clim
ate
=2
5 F
ore
ca
st
init
ial d
ate
: 2
00
8 2
01
Eq
ua
tori
al S
ou
the
rn O
sc
illa
tio
n
Feb
ruar
yM
arch
Apr
ilM
ayJu
neJu
lyA
ugus
t
-6
.3
-5.0
-3.8
-2.5
-1.3
-0.0
1.3
2.5
3.8
5.0
En
se
mb
le s
ize
: F
ore
ca
st=
41
Mo
de
l clim
ate
=2
75
An
aly
sis
clim
ate
=2
5 F
ore
ca
st
init
ial d
ate
: 2
00
8 2
01
Eq
ua
tori
al S
ou
the
rn O
sc
illa
tio
n
Feb
ruar
yM
arch
Apr
ilM
ayJu
neJu
lyA
ugus
t
-6
.3
-5.0
-3.8
-2.5
-1.3
-0.0
1.3
2.5
3.8
5.0
En
se
mb
le s
ize
: F
ore
ca
st=
41
Mo
de
l clim
ate
=2
75
An
aly
sis
clim
ate
=2
5 F
ore
ca
st
init
ial d
ate
: 2
00
8 2
01
Eq
ua
tori
al S
ou
the
rn O
sc
illa
tio
n
Feb
ruar
yM
arch
Apr
ilM
ayJu
neJu
lyA
ugus
t
-6
.3
-5.0
-3.8
-2.5
-1.3
-0.0
1.3
2.5
3.8
5.0
En
se
mb
le s
ize
: F
ore
ca
st=
41
Mo
de
l clim
ate
=2
75
An
aly
sis
clim
ate
=2
5 F
ore
ca
st
init
ial d
ate
: 2
00
8 2
01
Eq
ua
tori
al S
ou
the
rn O
sc
illa
tio
n
Feb
ruar
yM
arch
Apr
ilM
ayJu
neJu
lyA
ugus
t
-6
.3
-5.0
-3.8
-2.5
-1.3
-0.0
1.3
2.5
3.8
5.0
En
se
mb
le s
ize
: F
ore
ca
st=
41
Mo
de
l clim
ate
=2
75
An
aly
sis
clim
ate
=2
5 F
ore
ca
st
init
ial d
ate
: 2
00
8 2
01
Eq
ua
tori
al S
ou
the
rn O
sc
illa
tio
n
Feb
ruar
yM
arch
Apr
ilM
ayJu
neJu
lyA
ugus
t
-6
.3
-5.0
-3.8
-2.5
-1.3
-0.0
1.3
2.5
3.8
5.0
En
se
mb
le s
ize
: F
ore
ca
st=
41
Mo
de
l clim
ate
=2
75
An
aly
sis
clim
ate
=2
5 F
ore
ca
st
init
ial d
ate
: 2
00
8 2
01
Eq
ua
tori
al S
ou
the
rn O
sc
illa
tio
n
February March April May June July August -6.3
-5.0
-3.8
-2.5
-1.3
-0.0
1.3
2.5
3.8
5.0
Ensemble size: Forecast=41 Model climate=275 Analysis climate=25 Forecast initial date: 2008 201Equatorial Southern Oscillation
February March April May June July August -6.3
-5.0
-3.8
-2.5
-1.3
-0.0
1.3
2.5
3.8
5.0
Ensemble size: Forecast=41 Model climate=275 Analysis climate=25 Forecast initial date: 2008 201Equatorial Southern Oscillation
February March April May June July August -6.3
-5.0
-3.8
-2.5
-1.3
-0.0
1.3
2.5
3.8
5.0
Ensemble size: Forecast=41 Model climate=275 Analysis climate=25 Forecast initial date: 2008 201Equatorial Southern Oscillation
February March April May June July August -6.3
-5.0
-3.8
-2.5
-1.3
-0.0
1.3
2.5
3.8
5.0
Ensemble size: Forecast=41 Model climate=275 Analysis climate=25 Forecast initial date: 2008 201Equatorial Southern Oscillation
Predictability barrier
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 17
Climagrams : area-averages of 2mT and rainfall
February March April May June July August -1.4
-1.0
-0.7
-0.3
0.0
0.3
0.7
1.0
1.4
1.7
Ensemble size: Forecast=41 Model climate=275 Analysis climate=25 Forecast initial date: 2008 201 2m temp. anomalies (K) latitude= 10.0 to -12.5 longitude= 285.0 to 310.0
February March April May June July August -1.4
-1.0
-0.7
-0.3
0.0
0.3
0.7
1.0
1.4
1.7
Ensemble size: Forecast=41 Model climate=275 Analysis climate=25 Forecast initial date: 2008 201 2m temp. anomalies (K) latitude= 10.0 to -12.5 longitude= 285.0 to 310.0
February March April May June July August -1.4
-1.0
-0.7
-0.3
0.0
0.3
0.7
1.0
1.4
1.7
Ensemble size: Forecast=41 Model climate=275 Analysis climate=25 Forecast initial date: 2008 201 2m temp. anomalies (K) latitude= 10.0 to -12.5 longitude= 285.0 to 310.0
February March April May June July August -1.4
-1.0
-0.7
-0.3
0.0
0.3
0.7
1.0
1.4
1.7
Ensemble size: Forecast=41 Model climate=275 Analysis climate=25 Forecast initial date: 2008 201 2m temp. anomalies (K) latitude= 10.0 to -12.5 longitude= 285.0 to 310.0
2m Temperature Amazones
!"##$% %$#&'( #& #&$#
& )#*#*"
!""#$ $# "%&' "% "%#"
% ()"*("*!)
Anomaly Correlation Temperature
Anomaly Correlation Precipitation
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 18
Climagrams : area-averages of 2mT and rainfall
Anomaly Correlation Temperature
Anomaly Correlation Precipitation
!"##$% %$#&'( #& #&$#
& )#*#*"
!""#$ $# "%&' "% "%#"
% ()"*("*!
North-East
Brasil
Target month is more predictable
Feb/March as a Window of
predictability
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 19
Climagrams : area-averages of 2mT and rainfall
Anomaly Correlation Temperature
Anomaly Correlation Precipitation
South America
Atlantic Coast
! "#$$%&!&%$'()!$'!$'%$
' $*$*#*
!!"##$%!!%$!#&'(!#&!#&$#
& )#*)#*"
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 20
Forecast System is not reliable:
RMS > Spread
To calibrate the model output
To sample model error (multi-model): EUROSIP
Both
A. Can we reduce the error? How much? (Predictability limit)
Is the ensemble spread sufficient? Are the forecast reliable?
B. Can we increase the spread by improving the ensemble generation?
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 21
Anomaly correlation of seasonal-mean rainfall
Franco Molteni
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 22
Can we predict tropical rainfall anomalies?
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 23
Prediction of All India Rainfall: EOF filtered fc. in JAS
CC = .50
Franco Molteni
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 24
Prediction of All India Rainfall
JJASCC = .25
JASCC = .46
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 25
Prediction of East Africa short rains: OND from Aug.
Unfiltered fc. : CC = 0.04 EOF-filt. : CC = 0.42
Franco Molteni
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 26
Persistence
ECMWF
ensemble spread
RMS error of Nino3 SST anomalies
EUROSIP
EUROSIP
ECMWF-UKMO-MeteoFrance
Sampling model error: The Real Time Multimodel
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 27
TROPICAL CYCLONES
80°S80°S
70°S 70°S
60°S60°S
50°S 50°S
40°S40°S
30°S 30°S
20°S20°S
10°S 10°S
0°0°
10°N 10°N
20°N20°N
30°N 30°N
40°N40°N
50°N 50°N
60°N60°N
70°N 70°N
80°N80°N
20°E
20°E 40°E
40°E 60°E
60°E 80°E
80°E 100°E
100°E 120°E
120°E 140°E
140°E 160°E
160°E 180°
180° 160°W
160°W 140°W
140°W 120°W
120°W 100°W
100°W 80°W
80°W 60°W
60°W 40°W
40°W 20°W
20°W
14.3 10.39.8 13.325.1 26.22 2.9
No Significance 90% Significance 95% Significance 99% Significance
Ensemble size = 40,climate size = 70Forecast start reference is 01/06/2005Tropical Storm FrequencyECMWF Seasonal Forecast
Significance level is 90%JASON
FORECAST CLIMATE
80°S80°S
70°S 70°S
60°S60°S
50°S 50°S
40°S40°S
30°S 30°S
20°S20°S
10°S 10°S
0°0°
10°N 10°N
20°N20°N
30°N 30°N
40°N40°N
50°N 50°N
60°N60°N
70°N 70°N
80°N80°N
20°E
20°E 40°E
40°E 60°E
60°E 80°E
80°E 100°E
100°E 120°E
120°E 140°E
140°E 160°E
160°E 180°
180° 160°W
160°W 140°W
140°W 120°W
120°W 100°W
100°W 80°W
80°W 60°W
60°W 40°W
40°W 20°W
20°W
15 10.38.8 13.327.4 26.23 2.9
No Significance 90% Significance 95% Significance 99% Significance
Ensemble size = 41,climate size =225Forecast start reference is 01/06/2005Tropical Storm FrequencyMet Office Seasonal Forecast
Significance level is 90%JASON
FORECAST CLIMATE
Forecasts starting on 1st June 2005: JASON
80°S80°S
70°S 70°S
60°S60°S
50°S 50°S
40°S40°S
30°S 30°S
20°S20°S
10°S 10°S
0°0°
10°N 10°N
20°N20°N
30°N 30°N
40°N40°N
50°N 50°N
60°N60°N
70°N 70°N
80°N80°N
20°E
20°E 40°E
40°E 60°E
60°E 80°E
80°E 100°E
100°E 120°E
120°E 140°E
140°E 160°E
160°E 180°
180° 160°W
160°W 140°W
140°W 120°W
120°W 100°W
100°W 80°W
80°W 60°W
60°W 40°W
40°W 20°W
20°W
20.4 11.67.8 12.516.6 21.22.5 2.5
No Significance 90% Significance 95% Significance 99% Significance
Ensemble size = 41,climate size = 55Forecast start reference is 01/06/2005Tropical Storm FrequencyMétéo-France Seasonal Forecast
Significance level is 90%JASON
FORECAST CLIMATE
ECMWF Met Office
Meteo-France
Obs July-November
AtlW-Pac E-Pac
80°S80°S
70°S 70°S
60°S60°S
50°S 50°S
40°S40°S
30°S 30°S
20°S20°S
10°S 10°S
0°0°
10°N 10°N
20°N20°N
30°N 30°N
40°N40°N
50°N 50°N
60°N60°N
70°N 70°N
80°N80°N
20°E
20°E 40°E
40°E 60°E
60°E 80°E
80°E 100°E
100°E 120°E
120°E 140°E
140°E 160°E
160°E 180°
180° 160°W
160°W 140°W
140°W 120°W
120°W 100°W
100°W 80°W
80°W 60°W
60°W 40°W
40°W 20°W
20°W
17.4 11.68.7 12.520.6 21.22.4 2.5
No Significance Sig at 10% level Sig at 5% level Sig at 1% level
Ensemble size =120,climate size =165Forecast start reference is 01/06/2005Tropical Storm FrequencyEUROSIP multi-model seasonal forecast
Significance level is 10%JASON
ECMWF/Met Office/Météo-France
FORECAST CLIMATE
0
5
10
15
20
25
30
Multi-model
1987-2004
2005
Frederic Vitart
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 28
MULIMODEL: EUROSIP
JUN2006
JUL AUG SEP OCT NOV DEC JAN2007
FEB MAR APR MAY JUN JUL AUG-2
-1
0
1
2
3
Ano
mal
y (d
eg C
)
-2
-1
0
1
2
3Monthly mean anomalies relative to NCEP adjusted OIv2 1971-2000 climatology
ECMWF forecast from 1 Dec 2006NINO3 SST anomaly plume
Produced from real-time forecast data
System 3
JUN2006
JUL AUG SEP OCT NOV DEC JAN2007
FEB MAR APR MAY JUN JUL AUG
-1
0
1
2
3
Ano
mal
y (d
eg C
)
-1
0
1
2
3
Monthly means plotted using NCEP adjusted OIv2 1971-2000 climatologyECMWF, Met Office, Météo-France
EUROSIP multi-model forecast from 1 Dec 2006NINO3 SST anomaly plume
Forecast issue date: 15 Dec 2006
Multi-model anomalies
MAY2007
JUN JUL AUG SEP OCT NOV DEC JAN2008
FEB MAR APR MAY JUN JUL
-4
-3
-2
-1
0
Ano
mal
y (d
eg C
)
-4
-3
-2
-1
0
Monthly means plotted using NCEP adjusted OIv2 1971-2000 climatologyECMWF, Met Office, Météo-France
EUROSIP multi-model forecast from 1 Nov 2007NINO3 SST anomaly plume
Forecast issue date: 15 Nov 2007
Multi-model anomalies
JUL2007
AUG SEP OCT NOV DEC JAN2008
FEB MAR APR MAY JUN JUL AUG SEP
-4
-3
-2
-1
0
Ano
mal
y (d
eg C
)
-4
-3
-2
-1
0
Monthly means plotted using NCEP adjusted OIv2 1971-2000 climatologyECMWF, Met Office, Météo-France
EUROSIP multi-model forecast from 1 Jan 2008NINO3 SST anomaly plume
Forecast issue date: 15 Jan 2008
Multi-model anomalies
But sometimes the spread with EUROSIP is too large!!ECMWF
MULTI-MODEL
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 29
Bayesian Calibration of the Nino Indices:
• Based on the Forecast Assimilation Framework
It will produce a revised mean and variance
• Specific Ingredients:
1. Take into account that error in the models can be correlated (remove correlation from errors, not from the signal, by doing SVD of error covariance matrix)
2. Model for the errors:
3. Given the mean and variance, produce the individual plumes
2 2 2 2
2
2
2
of past performance
spread
i o Ei Si
o
Ei
Si
a b c
const
estimation
ensemble
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 30
EUROSIP: Bayesian Combination
MAY2007
JUN JUL AUG SEP OCT NOV DEC JAN2008
FEB MAR APR MAY JUN JUL
-4
-3
-2
-1
0
Ano
mal
y (d
eg C
)
-4
-3
-2
-1
0
Monthly means plotted using NCEP adjusted OIv2 1971-2000 climatologyECMWF, Met Office, Météo-France
EUROSIP multi-model forecast from 1 Nov 2007NINO3 SST anomaly plume
Forecast issue date: 15 Nov 2007
Multi-model anomalies
MAY2007
JUN JUL AUG SEP OCT NOV DEC JAN2008
FEB MAR APR MAY JUN JUL
-2
-1
0
1
2
Ano
mal
y (d
eg C
)
-2
-1
0
1
2
Monthly means plotted using NCEP adjusted OIv2 1971-2000 climatologyECMWF, Met Office, Météo-France
EUROSIP multi-model forecast from 1 Nov 2007NINO3 SST anomaly plume
Forecast issue date: 15 Nov 2007
Bayesian calibration
JUL2007
AUG SEP OCT NOV DEC JAN2008
FEB MAR APR MAY JUN JUL AUG SEP
-4
-3
-2
-1
0
Ano
mal
y (d
eg C
)
-4
-3
-2
-1
0
Monthly means plotted using NCEP adjusted OIv2 1971-2000 climatologyECMWF, Met Office, Météo-France
EUROSIP multi-model forecast from 1 Jan 2008NINO3 SST anomaly plume
Forecast issue date: 15 Jan 2008
Multi-model anomalies
JUL2007
AUG SEP OCT NOV DEC JAN2008
FEB MAR APR MAY JUN JUL AUG SEP-3
-2
-1
0
1
2
Ano
mal
y (d
eg C
)-3
-2
-1
0
1
2Monthly means plotted using NCEP adjusted OIv2 1971-2000 climatology
ECMWF, Met Office, Météo-FranceEUROSIP multi-model forecast from 1 Jan 2008
NINO3 SST anomaly plume
Forecast issue date: 15 Jan 2008
Bayesian calibration
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 31
Sampling model error: The Real Time Multimodel
Persistence
ECMWF
ensemble spread
RMS error of Nino3 SST anomalies
Bayesian Calibration
EUROSIP
EUROSIP
ECMWF-UKMO-MeteoFrance
EUROBRISA WORKSHOP, Paraty 17-19 March 2008 , ECMWF System 3 32
Conclusions
• The new ECMWF seasonal forecast system-3 gives improved
predictions of tropical/summer variability respect the previous system.
• SST predictions are good in the tropical Pacific and eastern Indian Oc.,
but western Indian Oc. and tropical Atlantic are not better than
persistence in NH summer.
• Difficulty in getting the correct rainfall variability over land. Predictive
skill over land can be improved by exploiting teleconnections
(calibration)
• The Multi-Model (EUROSIP) provides skilful predictions of tropical
storms. In general it improves reliability, but sometimes the spread is
too large
• Bayesian Calibration can improve the products, but attention should be
paid to the estimation of the model error (sensitive to sampling size)
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