Seasonal forecasting: status and plans
David Anderson
Tim Stockdale, Magdalena Balmasda, Arthur Vidard, Alberto Troccoli,
Paco Doblas-Reyes, Kristian Morgensen, Malcolm MacVean,
Laura Ferranti, Frederic Vitart
• ECMWF System-2 is the same as last year.
• System-3 is under development. This involves substantial changes to the coupled system, though the changes should be largely transparent to the user.
• Another major initiative is the development of a real-time, multi-model, multi-analysis system. The UKMO and Meteo France systems are implemented. Other Met Services may join in future: DWD, Spain.
System 2 Recap• Forecast model• TL95L40 atmosphere• L29 ocean (Variable resolution 0.3X1in tropics)• Ocean Analysis• OI analysis of T• Corrections to salinity when T is assimilated.• Corrections to velocity when density is updated.• Ensemble of ocean analyses: 5 analyses perturbed
by wind anomalies.• Ensemble generation• From each ocean analysis, 8 perturbations to SST
are made, creating an ensemble of 40 members.
• Cycle 23r4(24r1) of atmosphere, TL95, L40• Calibration based on 5-member ensemble
from 1987 to 2001.• 40 member ensembles run for November
and May for validation.• Plumes contain forecasts for Nino3,
Nino3.4, Nino4• Various plots on the web e.g. terciles,
15%iles, ensemble means.. Precip, T2m, upper level data
The information on which a seasonal forecast is based lies mainly in the ocean. (Soil moisture, snow cover, sea ice, atmospheric state.. may also add some predictability). Considerable effort is put into analysing the ocean state.
• An ensemble of ocean analyses is created.
• Five ocean analyses are created by perturbing the wind stress with perceived uncertainty. (These analyses are used to create an ensemble of forecasts.) The purpose of creating an ensemble of ocean analyses is to represent some of the uncertainty in knowing the ocean state. These analyses are used in creating the ensemble of forecasts in System-2 (the current ECMWF seasonal forecast system and in the monthly forecast system).
Operating method of
ARGO floats.
• Operating
Data coverage for June 1982
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X B T p r o b e s : 9 3 7 6 p r o f i l e sOBSERVATION MONITORING
Data coverage for March 2002
Build up of ARGO: Data coverage for February 2005
• XBT, MOORINGS, ARGO floats
FEB2004
MAR APR MAY JUN JUL AUG SEP OCT NOV DEC JAN2005
FEB MAR
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Monthly means plotted using NCEP adjusted OIv2 1971-2000 climatologyECMWF forecast from 1 Jul 2004
NINO3 SST anomaly plume
Forecast production date: 14 Jul 2004
System 2
NOV2004
DEC JAN2005
FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC2006
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Monthly means plotted using NCEP adjusted OIv2 1971-2000 climatologyECMWF forecast from 1 May 2005
NINO3 SST anomaly plume
Forecast production date: 14 May 2005
System 2
JUL2004
AUG SEP OCT NOV DEC JAN2005
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Monthly means plotted using NCEP adjusted OIv2 1971-2000 climatologyECMWF forecast from 1 Feb 2005
NINO3 SST anomaly plume
Forecast production date: 14 Feb 2005
System 2
MAY2004
JUN JUL AUG SEP OCT NOV DEC JAN2005
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Monthly means plotted using NCEP adjusted OIv2 1971-2000 climatologyECMWF forecast from 1 Nov 2004
NINO3 SST anomaly plume
Forecast production date: 14 Nov 2004
System 2
System 3
System-3•A new cycle of the atmospheric model - 29r1 with 40 levels or following physics cycle with green house gasses and aerosols and 62 levels.•Extended range and size of back integrations.• Strawman 11member, back to 1982.•Include bias correction in ocean assimilation.•Include salinity assimilation. •Include altimeter assimilation•Revised wind and SST perturbations. •New sea-ice specification algorithm. •Include ocean currents in wave model. •Use EPS Singular Vector perturbations in atmospheric initial conditions. •Forecasts out to 12 months (4X per year) •Will use ENACT/ENSEMBLES ocean data.
• There will be some extra data archived:
• Pressure level data for 100HPa, and 50HPa at 12 hourly intervals.
• A full set for 400 and 300 HPa (currently only T)
• MSLP every 6 hours (currently 12hours)
• Potential temperature on PV=2 surface.
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E C M W F M e a n c u r r e n t selv5_M1: comparison with Oscar
0.3m/s
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Prototype of System 3 currents
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O s c a r M e a n c u r r e n t selv5_M0: comparison with Oscar
0.3m/s
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OSCAR currents
Velocity fields
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C o r r e l a t i o n s i n u ( s e a s o n a l c y c l e r e m o v e d )elv5_M1: comparison with Oscar
0.5 0.70.7
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C o r r e l a t i o n s i n u ( s e a s o n a l c y c l e r e m o v e d )0001_M1: comparison with Oscar
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Zonal velocities: Correlation with OSCAR (NOAA) currents (15m depth)
Period 1993-2004, seasonal cycle removed
System 2
Prototype of System 3
Spring barrier: predictability
potential predictability *) seasonal recharge oscillator
Estimate of predictability with parameters and noise properties from seasonal fit. From Gerrit Burgers KNMI
skill ECMWF operational forecast 1987-2001
ERA15-SOC (1986-1993)
Wind stress perturbationsStandard deviation of zonal wind stress differences (in N/m**2,
multiplied by 100) for JanuaryERA40-CORE (1986-1993)
ERA40-CORE (1958-1979) ERA40-CORE (1980-2000)
Constant GHGCorrelation = 0.52
Anthropogenic effect: T2m predictions
Variable GHGCorrelation = 0.77
1-month lead, summer (JJA) predictions of global T2m
The multi-model
Forecast System is not reliable:
RMS > Spread
A) Can we reduce the error? How much?
(Predictability limit)
B)Or can we only increase the spread?
A) Improve the ensemble generation: Need to sample model error
B) Improve calibration: A posteriori use of all available information
• The Met Office model is very similar to that used in Demeter. The ensemble strategy follows the ECMWF S2 strategy except that it uses ERA-40/Ops rather than ERA-15/Ops and the wind perturbations used in the ensemble ocean analysis are half amplitude. The ocean analyses use the ENACT data set.
• The atmospheric resolution is 2.5 X 3.75 degrees, with 19 vertical levels. The ocean has resolution of 1.25X1.25, increasing to .28220 in the north south direction near the equator. There are 40 vertical levels. The calibration period is 1987-2004, 15 members ensemble.
• The Meteo France atmospheric model has 31 vertical levels, TL63 resolution. The ocean model is ORCA: 2X2 at mid latitudes, increasing to 0.50 near the equator. There are 31 vertical levels. The ocean analyses are produced without in situ data assimilation. Altimeter data are used and a moderate relaxation to observed SST is applied. Forecasts are available from 1993-present. (A 5-member ensemble from 1993 to 2004 inc. The real-time forecast ensemble is 41.)
• Differences can be considerably larger e.g. in Nino4
NOV2004
DEC JAN2005
FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC2006
-1
0
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3A
nom
aly
(deg
C)
-1
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Monthly means plotted using NCEP adjusted OIv2 1971-2000 climatologyMet Office forecast from 1 May 2005
NINO3 SST anomaly plume
Forecast issue date: 15 May 2005
System 2
NOV2004
DEC JAN2005
FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC2006
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eg C
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Monthly means plotted using NCEP adjusted OIv2 1971-2000 climatologyMétéo-France forecast from 1 May 2005
NINO3 SST anomaly plume
Forecast issue date: 15 May 2005
System 1
NOV2004
DEC JAN2005
FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC2006
-1
0
1
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3
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mal
y (d
eg C
)
-1
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3
Monthly means plotted using NCEP adjusted OIv2 1971-2000 climatologyECMWF forecast from 1 May 2005
NINO3 SST anomaly plume
Forecast production date: 14 May 2005
System 2
0 1 2 3 4 5 6Forecast time (months)
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om
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wrt NCEP adjusted OIv2 1971-2000 climatology
NINO3.4 SST anomaly correlation
0 1 2 3 4 5 6Forecast time (months)
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rro
r (d
eg
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Ensemble sizes are 15 (MM ), 10 (MM ) and 5 (0001)141 start dates from 19930201 to 20041001
NINO3.4 SST rms errors
MM MM Fcast S2 Persistence
MAGICS 6.9.1 cumal - net Mon May 9 14:58:43 2005
Results from the real-time multi-model forecast system. Three different models, using three different analysis strategies.
Green is ECMWF, blue ECMWF + MO, red ECMWF+MO+MF.
Ensemble size = 41, climate size = 60Forecast start reference is 01/05/05Prob(upper tercile) - 2m temperatureMétéo-France Seasonal Forecast
No significance test appliedJJA 2005System 2
75°S 75°S
60°S60°S
45°S 45°S
30°S30°S
15°S 15°S
0°0°
15°N 15°N
30°N30°N
45°N 45°N
60°N60°N
75°N 75°N
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150°W 120°W
120°W 90°W
90°W 60°W
60°W 30°W
30°W 0°
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60°E 90°E
90°E 120°E
120°E 150°E
150°E
Forecast issue date: 15/05/2005
0..10% 10..20% 20..40% 40..50% 50..60% 60..70% 70..100%
Ensemble size = 40, climate size = 75Forecast start reference is 01/05/05Prob(upper tercile) - 2m temperatureECMWF Seasonal Forecast
No significance test appliedJJA 2005System 2
75°S 75°S
60°S60°S
45°S 45°S
30°S30°S
15°S 15°S
0°0°
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75°N 75°N
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90°W 60°W
60°W 30°W
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30°E 60°E
60°E 90°E
90°E 120°E
120°E 150°E
150°E
Forecast production date: 14/05/2005
0..10% 10..20% 20..40% 40..50% 50..60% 60..70% 70..100%
Ensemble size = 41, climate size = 225Forecast start reference is 01/05/05Prob(upper tercile) - 2m temperatureUKMO Seasonal Forecast
No significance test appliedJJA 2005System 2
75°S 75°S
60°S60°S
45°S 45°S
30°S30°S
15°S 15°S
0°0°
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60°N60°N
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90°E 120°E
120°E 150°E
150°E
Forecast issue date: 15/05/2005
0..10% 10..20% 20..40% 40..50% 50..60% 60..70% 70..100%
Unweighted meanForecast start reference is 01/05/05Prob(upper tercile) - 2m temperatureMulti-model Seasonal Forecast
No significance test appliedJJA 2005
ECMWF/Météo-France/Met Office
75°S 75°S
60°S60°S
45°S 45°S
30°S30°S
15°S 15°S
0°0°
15°N 15°N
30°N30°N
45°N 45°N
60°N60°N
75°N 75°N
150°W
150°W 120°W
120°W 90°W
90°W 60°W
60°W 30°W
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30°E 60°E
60°E 90°E
90°E 120°E
120°E 150°E
150°E
Forecast issue date: 15/05/2005
0..10% 10..20% 20..40% 40..50% 50..60% 60..70% 70..100%
Ensemble size = 41, climate size = 60Forecast start reference is 01/05/05Prob (precipitation > median)Météo-France Seasonal Forecast
Solid contour at 1% significance levelJJA 2005System 2
75°S 75°S
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60°W 30°W
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30°E 60°E
60°E 90°E
90°E 120°E
120°E 150°E
150°E
Forecast issue date: 15/05/2005
0..10% 10..20% 20..30% 30..40% 40..60% 60..70% 70..80% 80..90% 90..100%
Ensemble size = 41, climate size = 225Forecast start reference is 01/05/05Prob (precipitation > median)UKMO Seasonal Forecast
Solid contour at 1% significance levelJJA 2005System 2
75°S 75°S
60°S60°S
45°S 45°S
30°S30°S
15°S 15°S
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60°E 90°E
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150°E
Forecast issue date: 15/05/2005
0..10% 10..20% 20..30% 30..40% 40..60% 60..70% 70..80% 80..90% 90..100%
Ensemble size = 40, climate size = 75Forecast start reference is 01/05/05Prob (precipitation > median)ECMWF Seasonal Forecast
Solid contour at 1% significance levelJJA 2005System 2
75°S 75°S
60°S60°S
45°S 45°S
30°S30°S
15°S 15°S
0°0°
15°N 15°N
30°N30°N
45°N 45°N
60°N60°N
75°N 75°N
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150°W 120°W
120°W 90°W
90°W 60°W
60°W 30°W
30°W 0°
0° 30°E
30°E 60°E
60°E 90°E
90°E 120°E
120°E 150°E
150°E
Forecast production date: 14/05/2005
0..10% 10..20% 20..30% 30..40% 40..60% 60..70% 70..80% 80..90% 90..100%
Unweighted meanForecast start reference is 01/05/05Prob (precipitation > median)Multi-model Seasonal Forecast
No significance test appliedJJA 2005
ECMWF/Météo-France/Met Office
75°S 75°S
60°S60°S
45°S 45°S
30°S30°S
15°S 15°S
0°0°
15°N 15°N
30°N30°N
45°N 45°N
60°N60°N
75°N 75°N
150°W
150°W 120°W
120°W 90°W
90°W 60°W
60°W 30°W
30°W 0°
0° 30°E
30°E 60°E
60°E 90°E
90°E 120°E
120°E 150°E
150°E
Forecast issue date: 15/05/2005
0..10% 10..20% 20..30% 30..40% 40..60% 60..70% 70..80% 80..90% 90..100%
Predictions from the 3 multi-model components: Sahel precipitation
Met Office Météo France
Ecmwf
Predictions from the 3 multi-model components: Guinea Coast precipitation
Met Office
Ecmwf
Météo France
Results are from DEMETER
ENACT, DEMETER, ENSEMBLES, MERSEA
ENACT
• Enact was an EU framework V project, seeking to advance ocean data assimilation strategies, to generate an ensemble of ocean analyses for climate assessment and to assess the impact of different assimilation strategies on forecast skill.
anom NINO3 Averaged temperature over the top 300m
1965 1970 1975 1980 1985 1990 1995 2000Time
-2
-1
0
1
2
3
4
3DVAR(T)-CERFACS (0.750)
OI(T)-ECMWF (0.749)
OI(T)-INGV(0.715)
OI(T+S)-MetOffice (0.741)
OI(T+S)-ECMWF (0.742)
OI(T+S)-INGV(0.715)
Obj Analysis (0.710)
CTL-OPA (0.629)
CTL-HOPE (0.633)
CTL-UM (0.652)
anom NINO3 Averaged salinity over the top 300m
1965 1970 1975 1980 1985 1990 1995 2000Time
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.15
0.20
3DVAR(T)-CERFACS (0.053)
OI(T)-ECMWF (0.038)
OI(T)-INGV(0.024)
OI(T+S)-MetOffice (0.028)
OI(T+S)-ECMWF (0.031)
OI(T+S)-INGV(0.024)
Obj Analysis (0.020)
CTL-OPA (0.023)
CTL-HOPE (0.021)
CTL-UM (0.021)
anom GLOBAL Averaged temperature over the top 300m
1965 1970 1975 1980 1985 1990 1995 2000Time
-0.3
-0.2
-0.1
0.0
0.1
0.2
3DVAR(T)-CERFACS (0.077)
OI(T)-ECMWF (0.064)
OI(T)-INGV(0.073)
OI(T+S)-MetOffice (0.077)
OI(T+S)-ECMWF (0.067)
OI(T+S)-INGV(0.073)
Obj Analysis (0.069)
CTL-OPA (0.038)
CTL-HOPE (0.040)
CTL-UM (0.039)
anom GLOBAL Averaged salinity over the top 300m
1965 1970 1975 1980 1985 1990 1995 2000Time
-0.04
-0.02
0.00
0.02
0.04
3DVAR(T)-CERFACS (0.011)
OI(T)-ECMWF (0.011)
OI(T)-INGV(0.007)
OI(T+S)-MetOffice (0.007)
OI(T+S)-ECMWF (0.014)
OI(T+S)-INGV(0.007)
Obj Analysis (0.005)
CTL-OPA (0.002)
CTL-HOPE (0.009)
CTL-UM (0.007)
DEMETER and ENSEMBLES
Activities
The DEMETER heritage
• DEMETER ended in September 2003. However, work has been carried out on forecast quality assessment (additional verification of time series), analysis of the benefits of the multi-model, etc.
• Research on model calibration and combination has led to strong collaborations with CPTEC (Brazil) and IRI.
• A special issue of Tellus A has appeared in May 2005.
• Additional work on applications and end-user verification: the case of malaria.
Seasonal predictability, Southern Europe
2-4 (JJA)
PrecipitationT2m
4-6 (ASO)
From Coelho et al. (2005)
Calibrated downscaled predictionsPAGE agricultural extent
PAGE agroclimatic zones
Northern box
Forecast Correlation BSS
Multi-model 0.57 0.12
Forecast Assimilation
0.74 0.32
Calibrated downscaled predictions
From Coelho et al. (2005)
Southern box
Forecast Correlation BSS
Multi-model 0.62 0.16
Forecast Assimilation
0.63 0.28
ENSEMBLES project
• Integrated Project funded by the EC within the VIth FP, 69 partners.
• Start date: 1 September 2004, Duration: 5 years
• Integrated probabilistic prediction system for time scales from seasons to decades, and beyond.
• Seasonal-to-decadal hindcasts will be used to assess the reliability of forecast systems used for scenario runs.
• Comparison of the benefits of the multi-model, perturbed parameters and stochastic physics approaches to assess forecast uncertainty.
• Great diversity of applications: health, crop yield, energy production, river streamflow, etc.
Initial s2d activities (RT1)• Main goal: assess best method to estimate model uncertainty among
multi-model, perturbed parameter and stochastic physics approaches.
• Estimates of model uncertainty using a new multi-model ensemble, a recently developed stochastic physics scheme (ECMWF and Met Office) and the perturbed parameters approach (Met Office with 2 different versions of HadCM3).
• Ocean initial conditions from ENACT and new sets.
• Common output archived at ECMWF in MARS (atmosphere) and ECFS (ocean).
• Pre-production for 1991-2001 with reduced start dates and expected completion for end 2005.
• Additional experiments to test the consistency of the predictions and the impact of the ensemble size.
Three different forecast systems to estimate model uncertainty
• Multi-model, built from ECMWF, Met Office, Météo-France operational activities and DEMETER experience.
• Perturbed parameter approach, from the decadal prediction system (DePreSys) at the Met Office.
• Stochastic physics, from the stochastic physics system developed for medium-range forecasting at ECMWF.
• Design of a set of common experiments to determine the benefits of each approach.
A service that offers immediate and free access to data from:•DEMETER•ERA-40•ERA-15•ENACTwith monthly and daily data, select area and plotting facilities, GRIB or NetCDF formats
Data disseminationDifferent depending on access granted to ECMWF systems:
– access: MARS http://www.ecmwf.int/services/archive/– no access: public data server and OPenDAP (DODS) server
http://www.ecmwf.int/research/EU-projects/ENSEMBLES/news/index.html
Downscaling for s2d predictions
MERSEA
• Will use the 0.25 degree ocean analyses from MERCATOR.
• Will couple the 0.25 degree ocean to an atmosphere of comparable resolution to test the impact on an active ocean on medium range forecasts.
• Will assess the impact of the high resolution ocean analyses on seasonal forecasts.
• INGV, Meteo France, ECMWF, MERCATOR.
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