my ocean wp18, athens 29-30 september 2009 1 medium range weather/ monthly and seasonal forecasts...
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My Ocean WP18 , Athens 29-30 September 2009 1
Medium Range Weather/
Monthly and Seasonal forecasts
Magdalena A. Balmaseda ECMWF (UK)
Climate & Seasonal Forecasts
My Ocean WP18 , Athens 29-30 September 2009 2
WP18: Task on Climate Seasonal Forecast
• Participants: Met Office Meteo France CMCC ECMWF MetNo (?)
• First suggestion: generalize a and split the task to
1. Seamless weather to seasonal forecasting2. Climate Impacts
My Ocean WP18 , Athens 29-30 September 2009 3
Overview
• Forecasts at different time scales: SEAMLESS prediction
• Seasonal Forecasts needs Why do we want forecast at seasonal time scales? End To End Seasonal Forecasting Systems Initialization Calibration
• Monthly Forecasts needs
• Weather Forecasts needs
• Climate Reanalysis (atmosphere/ocean/ice) needs
My Ocean WP18 , Athens 29-30 September 2009 4
• There is a clear demand for reliable seasonal forecasts: Forecasts of anomalous rainfall and temperature at 3-6 months ahead
• For a range of societal, governmental, economic applications:
Agriculture Heath (malaria, dengue,…) Energy management Markets, insurance Water resource management,
• Huge progress in the last decade: Operational seasonal forecasts in several centres Pilot/Research progress for demonstrating applicability
(DEMETER,IRI,EUROBRISA,…) Build-up of community infrastructure (at WMO level)
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The basis for extended range forecasts
•Forcing by boundary conditions changes the atmospheric circulation, modifying the large scale patterns of temperature and rainfall, so that the probability of occurrence of certain events deviates significantly from climatology.
Important to bear in mind the probabilistic nature of climate forecasts
How long in advance?: from seasons to decades
The possibility of seasonal forecasting has clearly been demonstrated
Decadal forecasting activities are now starting.
•The boundary conditions have longer memory, thus contributing to the predictability. Important boundary forcing:
SST: ENSO, Indian Ocean Dipole, Atlantic SST Land: snow depth, soil moisture Atmospheric composition: green house gases, aerosols,… Ice?
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End-To-End Seasonal forecasting System
EN
SEM
BL
E G
EN
ER
AT
ION
COUPLED MODEL Forecast PRODUCTS
Initialization Forward Integration Forecast Calibration
OCEAN
PR
OB
AB
ILIS
TIC
CA
LIB
RA
TE
D F
OR
EC
AS
T
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 380°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
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Importance of Initialization
•Atmospheric point of view: Boundary condition problem Forcing by lower boundary conditions changes the atmospheric
circulation.“Loaded dice”
•Oceanic point of view: Initial value problem Prediction of tropical SST: need to initialize the ocean subsurface.
o Emphasis on the thermal structure of the upper oceano Predictability is due to higher heat capacity and predictable dynamics
A simple way: ocean model + surface fluxes.o But uncertainty in the fluxes is too large to constrain the solution.
Alternative : ocean model + surface fluxes + ocean observations o Using a data assimilation system. o The challenge is to initialize the thermal structure
– without disrupting the dynamical balances (wave propagation is important)– While preserving the water-mass characteristics
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Real Time Ocean Observations
ARGO floatsXBT (eXpandable BathiThermograph)
Moorings
Satellite
SST
Sea Level
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Coupled Hindcasts, needed to estimate model climatological PDF, require a historical ocean reanalysis
Real time Probabilistic Coupled Forecast
time
Ocean reanalysis
•Quality of reanalysis affects the climatological PDF, and therefore the real-time forecast
•Consistency between historical and real-time initial conditions is required
Re-forecasting needs an ocean re-analysis
Models have errors and direct model output needs calibration
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Ocean data assimilation improves the forecast skill
(Alves et al 2003)
Data Assimilation
Data Assimilation
No
Da
ta A
ss
imil
ati
on
No
Da
t a A
ss
imi l
at i
on
Impact of Data Assimilation
Forecast Skill
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A decade of progress on ENSO prediction
•Steady progress: ~1 month/decade skill gain
•How much is due to the initialization, how much to model development?
S1 S2 S3
Relative Reduction in SST Forecast ErrorECMWF Seasonal Forecasting Systems
TOTAL GAIN
OC INI
MODEL
0
5
10
15
20
25
30
35
40
1
%TOTAL GAIN OC INI MODEL
Half of the gain on forecast skill is due to improved ocean initialization
0 1 2 3 4 5 6Forecast time (months)
0.4
0.5
0.6
0.7
0.8
0.9
1
Anom
aly
corr
ela
tion
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 err
or
(deg C
)
Ensemble sizes are 5 (0001), 5 (0001) and 5 (0001) 64 start dates from 19870401 to 20021201
NINO3.4 SST rms errors
Fcast S3 Fcast S2 Fcast S1 Persistence
MAGICS 6.11 windmill - neh Mon Sep 14 11:48:01 2009
My Ocean WP18 , Athens 29-30 September 2009 12
Ocean Observation & Reliable forecast products
Calibration and multi-model can increase the skill and reliability of forecasts.
In a general case, even the multi-model needs calibration.
Long records are needed for robust calibration and downscaling
RMS Error Ensemble Spread
A. Can we reduce the error? How much? (Predictability limit)
B. Can we increase the spread by improving the ensemble generation and calibration?
Forecast Systems are generally not reliable (RMS > Spread)
My Ocean WP18 , Athens 29-30 September 2009 13
Requirements for Seasonal
• Data for initialization In situ QC data (historical and real time) SST, high resolution (historical and real time) Sea Level Anomalies (historical and real time) MDT Bottom pressure (?) Sea ice (in the future)
• Independent data for validation/ comparison Sea level data (gauges) Ocean currents (blended product) Ocean reanalysis from other centres (including those without model)
• Direct 3D ocean states: depending on centre Met-Office, INGV (OK), since they produce MyOcean reanalysis with their
own systems Meteo-France will try the ORCA2 product from Mercator ECMWF needs ORCA1 resolution
o Can not use the ¼ degree product directly
The longer the record, the better
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ECMWF and 3D ocean reanalysis from My Ocean
• The time scales of the project precludes the direct output of the ¼ ocean re-analysis for seasonal forecasts
Quite expensive assessment.
• Alternative Interpolate ¼ into 1 deg Use the interpolated data. Directly: not very interesting experiment (?) Anomaly initialization.
• Other alternatives: Use My Ocean re-analysis of sea ice.
Consider other time scales (weather /monthly forecasting).
Start work on the implementation of the ¼ of degree model from MyOcean to be ready for future use of My Ocean products.
My Ocean WP18 , Athens 29-30 September 2009 15
Delayed Ocean Analysis ~12 days
Real Time Ocean Analysis ~Real time
ECMWF:
Weather and Climate Dynamical Forecasts
ECMWF:
Weather and Climate Dynamical Forecasts
10-Day Medium-Range
Forecasts
10-Day Medium-Range
Forecasts
Seasonal Forecasts
Seasonal Forecasts
Monthly Forecasts
Monthly Forecasts
Ocean model
Atmospheric model
Wave model
Atmospheric model
Ocean model
Wave model
My Ocean WP18 , Athens 29-30 September 2009 16
Monthly forecasts
• Mixed layer processes are important
• Currently, monthly forecasts use the same ocean model configuration that seasonal
• Ideally, one would use a dynamical ocean model with Higher horizontal/vertical resolution
• Alternative, an ocean mixed layer model can be used: High horizontal/vertical resolution but not dynamics High resolution initial conditions for this ML model will be needed
My Ocean WP18 , Athens 29-30 September 2009 17
Requirements for Monthly Forecast
• High resolution 3D ocean re-analysis to initialize ML model Temperature and Salinity. Velocities Long Reanalysis and timely real-timi (within 12-24 h)
• Possibility 1: Get data for a long term reanalysis. Exact period to be discussed. (1993-2005) is a
possibility) Use it to initialize the ML model and conduct a series of monthly hindcasts. Assess skill respect initial conditions from a low resolution ocean model. Problem: human resources are scarce
• Possibility 2: Start work on the implementation of the ¼ of degree model from
MyOcean to be ready for future use of My Ocean products.
My Ocean WP18 , Athens 29-30 September 2009 18
Medium Range Weather forecasts
• They will benefit from better representation of air-sea interaction:
Currents coupled to the wave model High resolution SST with diurnal cycle. Sea-ice
• Currently, persisted SST anomalies are used
• Interest in testing coupling to currents. Or at least, initialization of currents
And use persisted currents during the forecast
• Ideally, one would use a dynamical ocean/sea-ice model with
Higher horizontal resolution Higher vertical resolution But software does not exist yet
• Alternative, ML model as in monthly.
My Ocean WP18 , Athens 29-30 September 2009 19
Requirements for Medium Range
• Possibility 1: Use ocean currents. It involves other groups at ECMWF. Need for skill assessment of the product.
• Possibility 2: Start work on the implementation of the ¼ of degree
model from MyOcean to be ready for future use of My Ocean products.
My Ocean WP18 , Athens 29-30 September 2009 20
Summary
• Extend the name of the task to seamless prediction, to include
medium range and seasonal. Separate task on climate impacts.
• Direct products from TACS will be used by the different partners.
Ready to provide assessment for different time scales
• URD From ECMWF can include Atmospheric Re-analysis, Medium Range
weather forecast, monthly and seasonal
• Use of 3D reanalysis Not prescriptive. Depending of group. Assessment of seasonal from CMCC, MetOffice and Meteo-France ECMWF may not provide assessment of 3D products for seasonal. It could
(needs further discussion/iterations. Resource dependent)o Use Sea-ice in seasonal o Initialization of ML model for monthly (resources)o Use of velocity data for the wave model in medium range.o Start implementing MyOcean software (1/4 degree ocean model/sea ice)
My Ocean WP18 , Athens 29-30 September 2009 21
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