CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 1 Contents: Sensitivity studies: fluxes versus ocean model ERA-Interim fluxes CORE-II simulations.

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Presentation transcript:

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 1 Contents: Sensitivity studies: fluxes versus ocean model ERA-Interim fluxes CORE-II simulations and initialization of decadal forecasts Input from the Pacific Panel regarding CORE-II ocean model integrations.

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 2 Uncertainties: Model versus forcing 2 models: HOPE and NEMO  Similar horizontal resolution (~1 deg + eq refinement)  Different grids, different vertical discretization, different numerics, different physics 2 sets of forcing fluxes: ERA-40/OPS and ERA-Interim Integrations:   Daily fluxes  Strong relaxation to SST

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 3 Heat flux corrections: In The Eastern Pacific the solution depends mainly on the ocean model In the Equatorial Indian the solution depends mainly on the forcing fluxes

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 4 Total sea level Differences due to models Differences due to forcing fluxes

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 5 Surface Salinity Differences due to models Differences due to forcing fluxes

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 6 Solar Heat flux: Era Interim – Era 40

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 7 Flux correction term (~ SST error) ERA-40 ERA-INTERIM

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 8 Wind Stress

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 9 Meridional wind stress time series ERA-40/OPS ERA-INTERIM

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 10 T300

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 11 Correlation with Altimeter date ERA-40 ERA-INTERIM

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 12 EXPLOITATION OF THE ENSEMBLES DATA SET In preparation for the CMIP5 integrations… There is a good set of MULTI-MODEL decadal integrations. Data on a OpenDap server (common grid, CF compliant):   Output from Ocean and Atmosphere predictions and Ocean Initial Conditions (ocean reanalysis) Opportunity to investigate Pacific Decadal Predictability/Prediction?..ENSO behaviour…

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 13 Example: forecast anomalies of ocean temperature HadGEM2 (3 members) DePreSys_PP (9 members)  Ocean-point (70°N-60°S) SST anomaly (2-year running mean applied) from ENSEMBLES hindcasts. REFERENCE is ERA40/OPS.  Results from 2 of these models have been published in Nature/Science. Spot which ones ECHAM5/OM1 (3 members) ARPEGE4/OPA (3 members) IFS/HOPE (3 members) Results produced by F. Doblas -Reyes

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 14 IFS/HOPE: impact of ocean observations Global mean near-surface air temperature anomaly (2-year running mean applied) from the ECMWF re-forecasts. ERA40/OPS is used as a reference. The mean systematic error has been removed over the period IFS/HOPE (3 members) IFS/HOPE NoObs

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 15 Estimation of the Atlantic MOC Assimilation No-Data Bryden etal 2005 Cunningham etal 2007 From Balmaseda etal 2007

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 16 Zonally integrated across the Atlantic meridional water velocity (10 3 m 2 /s) from the ECMWF ocean re-analysis (left) and the mean of the ten ECMWF re-forecasts Assim (centre) and NoObs (right). 27°N 36°N Profiles below 150m IFS/HOPE: impact of ocean observations

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 17 Perceived Paradigm for initialization of coupled forecasts Real worldModel attractor Medium range Being close to the real world is perceived as advantageous. Model retains information for these time scales. Model attractor and real world are close? Decadal or longer Need to initialize the model attractor on the relevant time and spatial scales. Model attractor different from real world. Experiments: Uncoupled SST + Wind Stress + Ocean Observations (ALL) Uncoupled SST + Wind Stress (NO-OCOBS) Coupled SST (SST-ONLY) (Keenlyside et al 2008, Luo et al 2005) Seasonal? Somewhere in the middle? At first sight, this paradigm would not allow a seamless prediction system.

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 18 Impact of “real world” information on skill: NINO3.4 RMS ERROR ALL NO-OCOBS SST-ONLY Adding information about the real world improves ENSO forecasts From Balmaseda and Anderson 2009

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 19 NINO-W EQATL EQ3 STIO WTIO Reduction (%) in SST forecast error Range 1-3 months In Central/Western Pacific, up to 50% of forecast skill is due to atmos+ocean observations. Sinergy: > Additive contribution Ocean~20% Atmos ~25% OC+ATM~55% Impact of “real world” information on skill:

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 20 Relation between drift and Amplitude of Interannual variability. Upwelling area penetrating too far west leads to stronger IV than desired. Western Pacific Relation between drift and Amplitude of Interannual variability. Possible non linearity: is the warm drift interacting with the amplitude of ENSO? Impact of Initialization Drift and Variability depend on Initialization !! More information corrects for model error, and the information is retained during the fc. Need “more balanced” initialization methods to prevent initialization shock hitting non linearities Eastern Pacific ALL NO-OCOBS SST-ONLY DRIFT VARIABILITY

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 21 Initialization Shock and non linearities Forecast lead time phase space Model Attractor (MA) non-linear interactions important Real World (RW) Initialization shock a b c

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 22 Initialization shock and non linearities Forecast lead time phase space Model Attractor (MA) non-linear interactions important Real World (RW) Empirical Flux Corrections

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 23 Pacific Panel Input: General proposal  0. Scientific Questions  1. Process oriented metrics (with/without observations)  2. Generic (blanket) metrics (with/without observations) METRICS and/or DIAGNOSTICS? Ongoing work on ENSO metrics to evaluate climate models (Pacific Panel, Eric Guilyardi).

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 24 CORE-II draft proposal from Pacific Panel (summary I) Relevant scientific questions  Which processes control the SST off the South American coast, and why models are not able to represent it correctly? Link to VOCALS  Which are the determining factors for ocean models to represent the depth and slope in equatorial thermocline?  What controls the intensity and extension of the cold tongue?  What is the heat budget of the warm pool?  What determines the Equatorial heat content? What are the ocean heat and fresh water transports at the equator?  Which is the origin of the water masses in the Indonesian Troughflow (ITF), which will determine the ITF heat and fresh water transports.?  Which is the heat transport done by Tropical Instability Waves?  SPICE science questions?  Equatorial currents. Tsuchiya jets.  Barrier Layer.

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 25 1 Relevant metrics for process studies  1.1 Observed  Depth of the 20D isotherm along the Equator: Mean, SVD, RMS/RMSE, and ACC (TAO/TRITON observations).  Structure of the Tropical Instability Waves (TWI): Power spectra as a function of latitude (Altimeter data and SST)  Indonesian Throughflow (IT): Volume transport, Water mass properties of the waters in that region. (Verifying observations?)  Barrier Layer (Maes et al,…)  South American Upwelling: VOCALS area SST, upwelling, meridional velocity…Verifying observations: Stratus BUOY, Stratus cruise.  SPICE Region: U,V,T,S. There will be verifying observations CORE-II draft proposal from Pacific Panel (summary II)

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 26 1 Relevant metrics for process studies  1.2 Non Observed  Heat and volume transports by TWIs  Heat budget in the warm pool region  Indonesian Throughflow: heat and fresh water mass transport.  Origin of waters in the IT?  Trends in the Equatorial Circulation?  ….. CORE-II draft proposal from Pacific Panel (summary II)

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda Generic metrics  2.1 Observed  Temperature and Salinity profiles in prescribed areas (to include attachment with Pacific_areas), compared with observations. Mean, SDV, mean difference/error and RMS/RMSE. oT/S Observations are from WOA05 or from the Hadley Centre EN3. oT/S and Currents profiles at TAO/TRITON mooring location. Mean, SDV, mean difference/error, RMS/RMSE and ACCTAO/TRITON observations.  2.2 Non observed: (comparable with reanalysis and obs-only analysis)  Zonal sections along the Equator of T,S,U,V,W: Mean, SDV, mean difference, RMS.  Meridional sections or T,S,U,V,W: Mean, SDV, mean difference, RMS. Longitudes: 137E, 165E, 180,140W, 110W, 95W  Others... CORE-II draft proposal from Pacific Panel (summary III)

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 28 EXPLOITATION OF THE ENSEMBLES DATA SET In preparation for the CMIP5 integrations… There is a good set of MULTI-MODEL decadal integrations. Data on a OpenDap server (common grid, CF compliant):   Output from Ocean and Atmosphere predictions and Ocean Initial Conditions (ocean reanalysis) Opportunity to investigate Pacific Decadal Predictability/Prediction?..ENSO behaviour…

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 29 Example: forecast anomalies of ocean temperature HadGEM2 (3 members) DePreSys_PP (9 members)  Ocean-point (70°N-60°S) SST anomaly (2-year running mean applied) from ENSEMBLES hindcasts. REFERENCE is ERA40/OPS.  Results from 2 of these models have been published in Nature/Science. Spot which ones ECHAM5/OM1 (3 members) ARPEGE4/OPA (3 members) IFS/HOPE (3 members) Results produced by F. Doblas -Reyes

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 30 IFS/HOPE: impact of ocean observations Global mean near-surface air temperature anomaly (2-year running mean applied) from the ECMWF re-forecasts. ERA40/OPS is used as a reference. The mean systematic error has been removed over the period IFS/HOPE (3 members) IFS/HOPE NoObs

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 31 Estimation of the Atlantic MOC Assimilation No-Data Bryden etal 2005 Cunningham etal 2007 From Balmaseda etal 2007

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 32 Zonally integrated across the Atlantic meridional water velocity (10 3 m 2 /s) from the ECMWF ocean re-analysis (left) and the mean of the ten ECMWF re-forecasts Assim (centre) and NoObs (right). 27°N 36°N Profiles below 150m IFS/HOPE: impact of ocean observations

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 33 Perceived Paradigm for initialization of coupled forecasts Real worldModel attractor Medium range Being close to the real world is perceived as advantageous. Model retains information for these time scales. Model attractor and real world are close? Decadal or longer Need to initialize the model attractor on the relevant time and spatial scales. Model attractor different from real world. Experiments: Uncoupled SST + Wind Stress + Ocean Observations (ALL) Uncoupled SST + Wind Stress (NO-OCOBS) Coupled SST (SST-ONLY) (Keenlyside et al 2008, Luo et al 2005) Seasonal? Somewhere in the middle? At first sight, this paradigm would not allow a seamless prediction system.

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 34 Impact of “real world” information on skill: NINO3.4 RMS ERROR ALL NO-OCOBS SST-ONLY Adding information about the real world improves ENSO forecasts From Balmaseda and Anderson 2009

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 35 NINO-W EQATL EQ3 STIO WTIO Reduction (%) in SST forecast error Range 1-3 months In Central/Western Pacific, up to 50% of forecast skill is due to atmos+ocean observations. Sinergy: > Additive contribution Ocean~20% Atmos ~25% OC+ATM~55% Impact of “real world” information on skill:

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 36 Relation between drift and Amplitude of Interannual variability. Upwelling area penetrating too far west leads to stronger IV than desired. Western Pacific Relation between drift and Amplitude of Interannual variability. Possible non linearity: is the warm drift interacting with the amplitude of ENSO? Impact of Initialization Drift and Variability depend on Initialization !! More information corrects for model error, and the information is retained during the fc. Need “more balanced” initialization methods to prevent initialization shock hitting non linearities Eastern Pacific ALL NO-OCOBS SST-ONLY DRIFT VARIABILITY

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 37 Initialization Shock and non linearities Forecast lead time phase space Model Attractor (MA) non-linear interactions important Real World (RW) Initialization shock a b c

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 38 Initialization shock and non linearities Forecast lead time phase space Model Attractor (MA) non-linear interactions important Real World (RW) Empirical Flux Corrections

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 39 Pacific Panel Input: General proposal  0. Scientific Questions  1. Process oriented metrics (with/without observations)  2. Generic (blanket) metrics (with/without observations) METRICS and/or DIAGNOSTICS? Ongoing work on ENSO metrics to evaluate climate models (Pacific Panel, Eric Guilyardi).

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 40 CORE-II draft proposal from Pacific Panel (summary I) Relevant scientific questions  Which processes control the SST off the South American coast, and why models are not able to represent it correctly? Link to VOCALS  Which are the determining factors for ocean models to represent the depth and slope in equatorial thermocline?  What controls the intensity and extension of the cold tongue?  What is the heat budget of the warm pool?  What determines the Equatorial heat content? What are the ocean heat and fresh water transports at the equator?  Which is the origin of the water masses in the Indonesian Troughflow (ITF), which will determine the ITF heat and fresh water transports.?  Which is the heat transport done by Tropical Instability Waves?  SPICE science questions?  Equatorial currents. Tsuchiya jets.  Barrier Layer.

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 41 1 Relevant metrics for process studies  1.1 Observed  Depth of the 20D isotherm along the Equator: Mean, SVD, RMS/RMSE, and ACC (TAO/TRITON observations).  Structure of the Tropical Instability Waves (TWI): Power spectra as a function of latitude (Altimeter data and SST)  Indonesian Throughflow (IT): Volume transport, Water mass properties of the waters in that region. (Verifying observations?)  Barrier Layer (Maes et al,…)  South American Upwelling: VOCALS area SST, upwelling, meridional velocity…Verifying observations: Stratus BUOY, Stratus cruise.  SPICE Region: U,V,T,S. There will be verifying observations CORE-II draft proposal from Pacific Panel (summary II)

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda 42 1 Relevant metrics for process studies  1.2 Non Observed  Heat and volume transports by TWIs  Heat budget in the warm pool region  Indonesian Throughflow: heat and fresh water mass transport.  Origin of waters in the IT?  Trends in the Equatorial Circulation?  ….. CORE-II draft proposal from Pacific Panel (summary II)

CLIVAR WGOMD, Exeter April 2009 Magdalena Alonso Balmaseda Generic metrics  2.1 Observed  Temperature and Salinity profiles in prescribed areas (to include attachment with Pacific_areas), compared with observations. Mean, SDV, mean difference/error and RMS/RMSE. oT/S Observations are from WOA05 or from the Hadley Centre EN3. oT/S and Currents profiles at TAO/TRITON mooring location. Mean, SDV, mean difference/error, RMS/RMSE and ACCTAO/TRITON observations.  2.2 Non observed: (comparable with reanalysis and obs-only analysis)  Zonal sections along the Equator of T,S,U,V,W: Mean, SDV, mean difference, RMS.  Meridional sections or T,S,U,V,W: Mean, SDV, mean difference, RMS. Longitudes: 137E, 165E, 180,140W, 110W, 95W  Others... CORE-II draft proposal from Pacific Panel (summary III)