Upload
bell
View
60
Download
0
Embed Size (px)
DESCRIPTION
Ongoing developments at ECMWF. Magdalena A. Balmaseda ECMWF, Reading, U.K. Overview. Progress in Seasonal Forecasting in past 10 years End to End Seasonal Forecasting System Progress in ENSO Prediction: model and initialization To do: - PowerPoint PPT Presentation
Citation preview
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 1
Ongoing developments at ECMWF
Magdalena A. Balmaseda
ECMWF, Reading, U.K.
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 2
Overview
• Progress in Seasonal Forecasting in past 10 years End to End Seasonal Forecasting System Progress in ENSO Prediction: model and initialization To do:
o Can we measure progress on precipitation due to calibration….?o Can users give feedback to the observation community? Which are the needs?
• Ongoing developments at ECMWF NEMO/NEMOVAR: big investment in infrastructure. ERA-Interim: impact on Atlantic SST. Look at precipitation? Exploring limits on forecast horizons: 1yr and beyond Atmospheric model: Convection, WWB, resolution. Time line for implementation
• La Nina and impacts. Time for a Review focused on SA?
• Calibration: Some ideas on what to do next
• Summary
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 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
InitializationGCM integration
Ensemble Gen FC calibration
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 4
Evolution of the ECMWF SF
•Steady progress: ~1 month/decade skill gain
•Dramatic change in coupled behaviour between S1 & S2: bias and variability
•Improvement in S3, but still
• Warm(est) bias in eastern Pacific
•Underestimation of interannual variability
S1 S2 S3
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 5
Contribution of Initialization and Model
Relative Reduction in SST Forecast ErrorECMWF Seasonal Forecasting Systems
-20
-10
0
10
20
30
40
NINO3 NINO4
%
S1 to S2 TOTAL OC INI MODEL
S2 to S3 TOTAL OC INI MODEL
S1 to S3 TOTAL OC INI MODEL
•For the prediction of ENSO-SST, it is possible to measure progress and to attribute improvements.
•Is it possible with other variables? Should it be tried with the EUROBRISA System?
•Is it possible to measure the impact of model/initialization and calibration?
•In particular, it is important to determine the relevance of the calibration period.
•It is important to give feedback to the wider community about the observational/reanalysis needs of forecast calibration.
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 6
Impact of observations (ocean and atmos)
Impact on 1-7 month SF of SST
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 8
Example from the Medium Range
Impact of Increased ensemble size versus longer calibration period
(Continuous Rank Probability Skill Score, T-2m Europe)
The longer calibration period has larger impact than increasing the ensemble size. From Hagerdorn 2008
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 9
On going developments at ECMWF
Preparations for S4
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 10
•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, Dartmoor 21-24 July 2009 , ECMWF developments 11
•COUPLED MODEL (IFS + OASIS3+ NEMO (ORCA1))•Recent cycle of atmospheric model (Cy35R3 and beyond)•Atmospheric resolution TL159 (TL255?) and 62-(90?) levels•Time varying greenhouse gasses.
•INITIALIZATION with NEMOVAR•Includes bias correction in ocean assimilation.•Includes assimilation of salinity and altimeter data. •ERA-40/ ERA-Interim data used to initialize ocean and atmosphere in hindcasts•Ocean reanalysis back to 1959, using EN3-XBt corrected ocean data
•ENSEMBLE GENERATION•Wind, SST and Freshwater perturbations. •Perturbations to the sea-ice concentration during forecast.
•Forecasts extended to 7 months (to 13 months 4x per year).
The seasonal forecast System-4 (2010?)
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 12
Impact of ERA-INTERIM
• Era Interim is from 1989, continuously updated about 2 months behind real time
• More up-to-date atmospheric model, increased resolution (from T159 in ERA-40 to T255), variational bias correction, 4D-var… See Uppala et al 2008, ECMWF Newsletter 115)
• Large impact on hydrological cycle, winds, solar radiation…
• Impact in the ocean is noticeable. It also affects the seasonal forecast skill
• Should be used for verification (shortcoming: does not go back for a long enough period).
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 13
ERA-40 versus ERA-InterimCorrelation with Altimeter data
correl
0.0
0.2
0.4
0.6
0.8
EQ1 EQ3 EQATL EQIND NSTRPAC SSTRPAC NSTRATL SSTRATL
ERA-40 ERA-INTERIM
EastPacWestPac EqAtlEqInd
NsTrPac
SsTrPac
NsTrAtl
SsTrAtl
Total Flux Correction
-10 0 10 20EastPac
WestPac
EqAtl
EqInd
NsTrPac
SsTrPac
NsTrAtl
SsTrAtl
Seasonal Flux Correction
0 2 4 6 8 10EastPac
WestPac
EqAtl
EqInd
NsTrPac
SsTrPac
NsTrAtl
SsTrAtl
Interannual Flux Correction
0 5 10 15 20EastPac
WestPac
EqAtl
EqInd
NsTrPac
SsTrPac
NsTrAtl
SsTrAtlEra-Interim improves the interannual variability of the ocean initial conditions, especially in the Equatorial and South-Tropical Atlantic
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 14
ERA-40 versus ERA-Interim: Forecast Skill
0 1 2 3 4 5 6 7Forecast time (months)
0.4
0.5
0.6
0.7
0.8
0.9
1
Anom
aly
corre
latio
n
wrt NCEP adjusted OIv2 1971-2000 climatology
EQATL SST anomaly correlation
0 1 2 3 4 5 6 7Forecast time (months)
0
0.2
0.4
0.6
Rm
s er
ror (
deg
C)
Ensemble sizes are 5 (esj6) and 5 (f1v1) 71 start dates from 19900101 to 20061001
EQATL SST rms errors
Fc esj6/m0 Fc f1v1/m0 Persistence Ensemble sd
MAGICS 6.11 verhandi - neh Mon Jun 29 19:07:57 2009
ERA-40ERA-Interim
Ocean Initial conditions prepared with ERA-Interim fluxes improve the forecast skill in the Equatorial Atlantic.
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 15
Onset of ENSO and MJO:
All the SF systems failed to predict the amplification of El Nino 1997 from spring starts (April/May 1997).
The reason: failure to generate a powerful WWB associated to an MJO event (already present in the initial conditions at the start of the integrations).
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 16
60OE 110OE 160OE 150OW 100OW 50OW 0O
Longitude
0
20
40
60
80
Tim
e (
days
)
0
20
40
60
80
Plot resolution is 2.8125 in x and 12 in yTime-longitude plot at 0.00 deg NSea level contoured every 0.05 mAnalysis
No interpolation
I.C. 19970501
-0.6-0.55-0.5-0.45-0.4-0.35-0.3-0.25-0.2-0.15-0.1-0.050.050.10.150.20.250.30.350.40.450.50.550.6
MAGICS 6.2 tamlane - neh Tue Apr 2 19:16:24 2002
60OE 110OE 160OE 150OW 100OW 50OW 0O
Longitude
0
20
40
60
80
Tim
e (
days
)
0
20
40
60
80
Plot resolution is 2.8125 in x and 12 in yTime-longitude plot at 0.00 deg N and 10.0 metres depthPotential temperature contoured every 0.5 deg CAnalysis
No interpolation
I.C. 19970501
0. 5
2
22.5
4
-6-5.5-5-4.5-4-3.5-3-2.5-2-1.5-1-0.50.511.522.533.544.555.56
MAGICS 6.2 tamlane - neh Tue Apr 2 19:16:26 2002
Analysis (hovmollers May-July 1997)
SST anom (c.i. 0.5 deg)
Sea Level anom (c.i. 5cm)Taux anom (c.i. 0.02 N/m2)
1st May 1997
1st May 1997
1st May 1997
•WWB in July associated to an MJO event (alrady present at initial time) reach peak values ~0.2N/m2 around dateline.
•They trigger a downwelling Kelvin wave. Peak values of SL anomalies in the Eastern Pacific reach 25 cm by mid June..
•SST anomalies reach maximum values of 4 deg in the Eastern Pacific by end of June-beg July
60OE 110OE 160OE 150OW 100OW 50OW 0O
Longitude
0
20
40
60
80
Tim
e (
days
)
0
20
40
60
80
Plot resolution is 2.8125 in x and 120 in yTime-longitude plot at 0.00 deg NSurface stress (tau-x) contoured every 0.02 PaAnalysis
Interpolated in y
I.C. 19970501
0.06
-0.24-0.22-0.2-0.18-0.16-0.14-0.12-0.1-0.08-0.06-0.04-0.020.020.040.060.080.10.120.140.160.180.20.220.24
MAGICS 6.2 tamlane - neh Tue Apr 2 19:16:37 2002
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 17
Coupled FC (hovmollers May-July 1997) (S3)
SST anom (c.i. 0.5 deg)
Sea Level anom (c.i. 5cm)Taux anom (c.i. 0.02 N/m2)
1st May 1997
1st May 1997
1st May 1997
•In the Coupled forecasts the surface signature of the MJO dies after 20 days, there is not any propagation to the Pacific, and there is not any WWB.
•As a consequence, the SL and SST anomalies of the coupled forecasts are those associated with the ocean initial conditions.
•The El Nino fails to amplify. Peak SST values ~2 deg
50OE 100OE 150OE 160OW 110OW 60OW 10OW
Longitude
JUN
JUL
Tim
e
Plot resolution is 1.4063 in x and 120 in yTime-longitude plot at 0.00 deg NX-Surface stress contoured every 0.02 N/m2HOPE gcm: 0001
Interpolated in y19960501 + 91 days
difference from19970501 + 91 days
0.02
-0.24
-0.2
-0.16
-0.12
-0.08
-0.04
0.02
0.06
0.1
0.14
0.18
0.22
MAGICS 6.11 verhandi - neh Tue Nov 4 14:28:36 2008
50OE 100OE 150OE 160OW 110OW 60OW 10OW
Longitude
JUN
JUL
Tim
e
Plot resolution is 1.4063 in x and 24 in yTime-longitude plot at 0.00 deg NSea level contoured every 0.05 mHOPE gcm: 0001
No interpolation19960501 + 91 days
difference from19970501 + 91 days
-0.05
-0.6
-0.5
-0.4
-0.3
-0.2
-0.1
0.05
0.15
0.25
0.35
0.45
0.55
MAGICS 6.11 verhandi - neh Tue Nov 4 14:28:34 2008
50OE 100OE 150OE 160OW 110OW 60OW 10OW
Longitude
JUN
JUL
Tim
e
Plot resolution is 1.4063 in x and 24 in yTime-longitude plot at 0.00 deg N and 5.0 metres depthPotential temperature contoured every 0.5 deg CHOPE gcm: 0001
No interpolation19960501 + 91 days
difference from19970501 + 91 days
-2 -1
-1
-0.5
-0.5
1.5
2
-6
-5
-4
-3
-2
-1
0.5
1.5
2.5
3.5
4.5
5.5
MAGICS 6.11 verhandi - neh Tue Nov 4 14:28:35 2008
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 19
New Atmospheric Cycles:
S3 in red
Changes in the parameterization of deep convection improve the representation of the MJO and he Onset of El Nino 1997.
But this is not all the story, some other aspects get worse: too strong easterlies in the Eastern Pacific.
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 20
New Atmos cycles (33r1 versus S3)
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18Calendar month
25
26
27
28
29
30
31
Abs
olu
te S
ST
NINO4 mean absolute SST
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18Calendar month
-2
-1
0
1
2
Dri
ft (
deg
C)
NINO4 mean SST drift
Fcast S3 Fcast f05p
MAGICS 6.12n verhandi - neh Tue Jul 21 14:30:33 2009
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 (0001) and 3 (f05p) 68 start dates from 19890201 to 20051101
NINO4 SST rms errors
Fcast S3 Fcast f05p Persistence Ensemble sd
MAGICS 6.12n verhandi - neh Tue Jul 21 14:30:31 2009
33r1
S3
•The new cycles have colder bias (resulting from stronger easterlies)
•There is too much variability in the Western Pacific, larger RMS error
•The anomaly correlation is also degraded.
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 21
NEMO-CONTROL
NEMO-ASSIM
HOPE-ASSIM
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 0
34
a
NINO4 mean absolute 034a
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
NINO4 mean 034a drift
Fcast f4wj Fcast f6ji Fcast f05p
MAGICS 6.12n verhandi - neh Wed May 20 11:55:34 2009
•NEMO has colder bias than HOPE in the Pacific, and larger variability => larger RMS error
•NEMOVAR has impact on the drift
•NEMOVAR improves correlation 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 034a anomaly correlation
0 1 2 3 4 5 6 7Forecast time (months)
0
0.2
0.4
0.6
0.8
1
Rm
s e
rro
r
Ensemble sizes are 3 (f4wj), 3 (f6ji) and 3 (f05p) 68 start dates from 19890201 to 20051101
NINO4 034a rms errors
Fcast f4wj Fcast f6ji Fcast f05p Persistence Ensemble sd
MAGICS 6.12n verhandi - neh Wed May 20 11:55:32 2009
Impact of ocean model NEMO/NEMOVAR
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 22
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
EQATL 034a anomaly correlation
0 1 2 3 4 5 6 7Forecast time (months)
0
0.2
0.4
0.6
0.8
1
Rm
s e
rro
r
Ensemble sizes are 3 (f4wj), 3 (f6ji) and 3 (f05p) 68 start dates from 19890201 to 20051101
EQATL 034a rms errors
Fcast f4wj Fcast f6ji Fcast f05p Persistence Ensemble sd
MAGICS 6.12n verhandi - neh Wed May 20 11:55:32 2009
Impact on Equatorial Atlantic
NEMOVAR improves correlation in the Atlantic.
Better than NEMO-CONTROL and HOPE-ASSIM
It is the first time that Assimilation has a positive impact on the Atlantic Skill !!
NEMO-CONTROL
NEMO-ASSIM
HOPE-ASSIM
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 23
• Seasonal integrations for winters 1990/91-2005/06
• Atmosphere only with prescribed SST/sea ice
• Resolutions: TL159, TL255 and TL511 (all 91 levels in the vertical)
Impact of Atmospheric Resolution
Courtesy of Thomas Joung
Experimental Setup
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 27
Mean Precipitation
Precipitation GPCP (12-3 1990-2005)
1
3
5
7
9
11
13
15
Precipitation f127-GPCP (12-3 1990-2005)
-10
-4
-2
-0.5
0.5
2
4
10
Precipitation GPCP (12-3 1990-2005)
1
3
5
7
9
11
13
15
Precipitation f0cm-GPCP (12-3 1990-2005)
-10
-4
-2
-0.5
0.5
2
4
10
Total Precipitation f127 (12-3 1990-2005)
1
3
5
7
9
11
13
15
Total Precipitation f0cm-f127 (12-3 1990-2005)
-10
-4
-2
-0.5
0.5
2
4
10
GPCP
T159-GPCP
T511-GPCP
T511-T159
Courtesy of Thomas Joung
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 28
Winds @ 850 hPa
20.0m/sMean Wind 850hPa er40 (12-3 1990-2005)
5.0m/sWind Difference 850hPa f127-er40 (12-3 1990-2005)20.0m/sMean Wind 850hPa er40 (12-3 1990-2005)
5.0m/sWind Difference 850hPa f0cm-er40 (12-3 1990-2005)
20.0m/sMean Wind 850hPa er40 (12-3 1990-2005)
5.0m/sWind Difference 850hPa f3oa-er40 (12-3 1990-2005)T159-ERA40 T255-ERA40
T511-ERA40
•Increasing horizontal resolution beneficial for surface winds in the tropical Pacific.
•TL255 might be enough to reduce the surface wind bias
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 29
EUROBRISA: some ideas
• Paper on La Nina effects on SA
• Work of optimality of historical hindcasts record. Also useful for decadal forecasting.
• Can EUROBRISA detect the impact of the ocean observing system?.
• How to get rid of the “negative” correlation in the calibrated product. See next slide.
1) less weight to the statistical 2) linear combination of “uncalibrated” + calibrated. [Penalty to
account for the error in the calibration coefficients]
• Work on temporal properties of the predictability: show when the calibration works best.
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 30
La Nina 2007-2008
2006 2007 2008 2009
-3
-2
-1
0
1
2
3
Ano
mal
y (d
eg C
)
-3
-2
-1
0
1
2
3
Ensemble sizes are 40 (0001), 40 (0001) and 40 (0001) SST obs: NCEP OIv2ECMWF forecasts at month 5
NINO3.4 SST forecast anomalies
Obs. anom. ECMWF S3 Met Office S3 Météo-France S3
MAGICS 6.12n verhandi - neh Tue Jul 21 11:36:25 2009
The EUROSIP multimodel captured well the onset, amplitude and long duration of La Nina conditions.
No individual model capture it correctely.
How was the impact in precip over South America?
How did EUROBRISA performed?
Scope for a paper?
Others: in Nino3 there were some misses.
The calibrated plumes are slightly better: not misses, reduced spread
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 31
2006 2007 2008 2009-4
-3
-2
-1
0
1
2
Ano
mal
y (d
eg C
)
-4
-3
-2
-1
0
1
2
Ensemble sizes are 33 (MM ) and 33 (MMB ) SST obs: NCEP OIv2ECMWF forecasts at month 5
NINO3 SST forecast anomalies
Obs. anom. EUROSIP10 EUROSIP11
MAGICS 6.12n verhandi - neh Tue Jul 21 14:39:00 2009
Multimodel: Raw versus calibrated
Raw
Bayesian
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 32
Curiosity: calibration versus multi-model
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
NINO4 SST anomaly correlation
0 1 2 3 4 5 6Forecast time (months)
0
0.2
0.4
0.6
0.8
Rm
s e
rro
r (d
eg
C)
Ensemble sizes are 33 (MMB ) and 11 (0001)252 start dates from 19870101 to 20071201
NINO4 SST rms errors
EUROSIP10 C000 ecm1 C001 Persistence Ensemble sd
MAGICS 6.12n verhandi - neh Tue Jul 21 12:07:15 2009
EUROSIP
ECWMF only (calibrated)
For ENSO, ECMWF calibrated can beat the multi-model.
This is not the case for the Atlantic.
The calibration of the ECMWF is only a scaling factor of the interannual variance
(as to match the observed variability)
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 33
Problems with Negative correlation
ECMWF UKMO CPTEC Meteo France
EMPIRICAL CALIBRATED
•None of the GCMs show large areas nor values of –ve correlation
•The empirical shows large areas of –ve correlation
•The calibrated shows large areas and large values of –ve correlation
Why? No robust calibration?
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 34
Temporal properties of Predictability
2m Temperature Amazones
!"##$% %$#&'( #& #&$#
& )#*#*"
!""#$ $# "%&' "% "%#"
% ()"*("*!)
Anomaly Correlation Temperature
Anomaly Correlation Precipitation
Predictability as a function of target month
Predictability as a function of initial conditions
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 35
How the time-properties change in EUROBRISA?
Anomaly Correlation Temperature
Anomaly Correlation Precipitation
!"##$% %$#&'( #& #&$#
& )#*#*"
!""#$ $# "%&' "% "%#"
% ()"*("*!
North-East
Brasil
Target month is more predictable
Feb/March as a Window of
predictability
EUROBRISA WORKSHOP, Dartmoor 21-24 July 2009 , ECMWF developments 37
Summary
• Evidence that ENSO forecast is improving in time. Evidence of improved initialization.
Can the improvements be seen in the EUROBRISA system? Need to assess the value of long hindcast calibrating records.
• The ECMWF S4 will be ready in 2010. It will be based on NEMOVAR It will use ERA-Interim from 1989-onwards. Improvement in the Equatorial
Atlantic Probably improved Intraseasonal variability. It is early times to assess performace
• How to go on with EUROBRISA Outstanding issue of no robust calibration (-ve skill in x-validation) Explore/exploit the temporal features of prediction skill Document performance of La Nina 2007-2008?