Coupled Initialization Experiments in the COLA Anomaly Coupled Model

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Presentation transcript:

Coupled Initialization Experiments in the COLA Anomaly Coupled Model Ben Kirtman George Mason University and Center for Ocean-Land-Atmosphere Studies Missing Elements: (i) relating interactive ensemble (ic uncertainty), (ii) clarity regarding analogue approach, (iii) why would one want to do coupled initialization, (iv) more emphasis on why we need to nudge once the coupled modes are identified, (v)

Why Do Coupled Assimilation? Better State Estimation (Air-Sea Fluxes For Example) Assessing Observing Systems Improve Coupled Model Improve Coupled Predictions (Coupled Assimilation != Coupled Initialization)

COLA Perspective Emphasis Needs to be on Prediction The Forecast Initialization Procedure Should Account for Two Problems: Coupled Model Climate Does Not Agree with Observed Climate Coupled Modes of the Coupled Model are Significantly Different From the Coupled Modes of Nature Approaches: (i) Anomaly Initialization (ii) Anomaly Coupling (iii) Assimilate “Coupled Modes” Maybe these two assertions are obvious. First assertion leads to an initialization shock which we will show. The way I view the second assertion is that the slow manifold of the coupled model is different from observations and the trick to initializing forecasts is to initialization the model slow manifold. Some progress is possible regarding both these issues without coupled initialization. However, seems easier to deal with these problems within the framework of coupled initialization.

Outline Motivation: Identifying Coupled Modes Experimental Prediction: Where do we Stand? Results From ARCS Project Results From COLA Anomaly Coupled Model Initialization Shock and Aliasing Coupled Modes Identifying Coupled Modes Mapping Observed Modes onto Model Modes Coupled Initialization (Nudging) Model Coupled Modes

Is the Best Fit Best For Forecasting? Give More Weight to the Model? Ji et al. (1998) NCEP

Atmos Initialization No Atmos Initialization Persistence Coupled forecast results suggest that some equilibrium between atmosphere and SST required. Schneider et al., 1998; COLA Coupled Model Two points: (i) Anomaly Initialization and (ii) initialization of the atmosphere Lead Time (months)

ODA SST Winds and SST Rosati et al., 1997; GFDL

Chen et al., 1995, 1997; LDEO Wind Nudging within the Coupled System Standard Zebiak-Cane Ocean: FSU Forcing Wind Nudging within the Coupled System Chen et al., 1995, 1997; LDEO

COLA-IRI-GFDL-NCAR Collaboration on Global Coupled Prediction OGCM: MOM3 with Agreed Upon Physics, High Res. 1.0x1.0x40 ÿ 1/3x1.0x40 Medium Res. 1.5x1.5x25 ÿ 1/2x1.5x25 AGCM: T42L18: ECHAM4.5 (IRI), COLA, CCM3 ICs: Ocean: GFDL ODA, 40 Cases: Jan. and Jul. 1980-1999; Atmosphere: Open but taken from long simulation with observed SST. Coupling: No Flux Corrections or Anomaly Coupling

Problem: Coupled Model Climate Does Not Agree with Observed (ODA) Climate Initialization Shock May Degrade Forecast Skill

Analysis 80-99 Consensus COLA (High) COLA (Med) ECHAM (high) ECHAM (Med) CCM (Med) Figure 13. Longitude-time sections of the evolution of the standard deviation of SST anomalies (C) in the equatorial Pacific as a function of month of year for analysis and retrospective forecasts: (a) Analysis 1980-1999, (b) Consensus, (c) COLA high, (d) COLA medium, (e) ECHAM high, (f) ECHAM medium, (g) CCM medium. Model results in left hand column are averaged over cases with January initial conditions, and in right hand column the averages are over the cases with July initial conditions. Time increases upwards in each panel

Analysis 80-99 Consensus COLA (High) COLA (Med) ECHAM (High) ECHAM (Med) CCM (Med)

COLA ECHAM CCM Figure 15. Longitude-time sections of the annual cycle of the standard deviation of SST anomalies (C; left column) and heat content anomalies (C; right column) in the equatorial Pacific from long simulations with the coupled models: (a) COLA medium, (b) ECHAM medium, (c) CCM medium. Time increases upwards in each panel

Initialization Shock Problem: Coupled Model Climate Does Not Agree with ODA Climate Fix the Coupled Model Anomaly Initialization Empirical Corrections (Anomaly Coupling)

+2 -9 Atmos Initialization No Atmos Initialization Persistence Two points: (i) Anomaly Initialization and (ii) initialization of the atmosphere Lead Time (months)

Empirically Correcting the Model System Error 3-D OGCM Flux Correction Coupled Forecasts

OGCM Systematic error corrections

COLA Anomaly Coupled Model OGCM GFDL MOM3 1.5x1.5x25 0.5x1.5x25 AGCM COLA T42L18 ICs: Ocean: GFDL ODA Interpolated to Above Resolution. 80 Cases: Jan, Apr, Jul, Oct. 1980-1999 Atmosphere: Generated by Running with Observed SSTs. Six Atmospheric Perturbations Generated by Resetting the Calendar and Running for One Week ÿ 6 x 80 Cases = 480 Hindcasts

Even With Anomaly Coupling the Forecast Do Not Have the Right Variability Problem: Coupled Modes of the Coupled Model are Significantly Different From the Coupled Modes of Nature

Initializing the Model Coupled Modes Identify Model Coupled Modes Mapping Between Model Modes and Observed Modes Inserting Mapped Modes into Coupled Model (Coupled Nudging) Experimental Forecasts

Sub-Surface Temperature Nudging Procedure Where time scale of the damping (a) is 10 days-1 at the surface and 50 days-1 at 250 meters. Linearly decreasing from the surface to 250 meters and constant below 250 meters. Does Nudging Work? - Compare Different Data Assimilation Systems.

This shows that the “assimilation of the ODA” works, but that there are differences.

Forecasts from nudged data same as assimilation.

Note that this is the January 1997 Forecast Note that this is the January 1997 Forecast. This result shows that the nudged assimilation produces similar forecasts as the original data.

Initializing the Model Coupled Modes Identify Model Coupled Modes Mapping Between Model Modes and Observed Modes Inserting Mapped Modes into Coupled Model (Coupled Nudging) Experimental Forecasts

Identifying Coupled Modes Analogue Approach Heat Content Analogues Don’t Work Coupled Modes of Coupled Model are Not the Same as the Observations Use Long Simulation to Identify “Best Fit” SST Evolution (12 Months) Relate Analogue “Initial State” to Observed Initial State

Simulated Heat Content Does Not Match Observations Well GFDL ODA Anomaly Coupled Simulation RMSE Best Fit Show that heat content analogues directly are not good-more evidence that model coupled modes are different from observed coupled models Simulated Heat Content Does Not Match Observations Well

And Then Leads to a Relatively Poor Forecast This figure demonstrates that a heat content best fit does not give good forecasts. Forecast Initialized with GFDL ODA Jan1982

Best Fit Initial Heat Content Does Not Make A Good Analogue. Model Modes are Different From Obs What Do The Modes That Fit The Forecast Look Like? Fit SST Evolution to Observations What is Initial Heat Content?

However, show that we can find “best fit” coupled modes from the SST evolution

Show that these “best fit” modes are robust, but also provide some estimate of the uncertainty in the initial conditions.

Simulated Heat Content Does Not Match Observations Well GFDL ODA Anomaly Coupled Simulation RMSE Best Fit Show that heat content analogues directly are not good-more evidence that model coupled modes are different from observed coupled models Simulated Heat Content Does Not Match Observations Well

Initializing the Model Coupled Modes Identify Model Coupled Modes Mapping Between Model Modes and Observed Modes Inserting Mapped Modes into Coupled Model (Coupled Nudging) Experimental Forecasts

What do the Coupled Modes Look like.

Initializing the Model Coupled Modes Identify Model Coupled Modes Mapping Between Model Modes and Observed Modes Inserting Mapped Modes into Coupled Model (Coupled Nudging) Experimental Forecasts

Do actual coupled initialization/forecasts: need to talk about why.

Initializing the Model Coupled Modes Identify Model Coupled Modes Mapping Between Model Modes and Observed Modes Inserting Mapped Modes into Coupled Model (Coupled Nudging) Experimental Forecasts

Concluding Remarks Emphasized Coupled Initialization for Prediction Recognize that Best Fit State May Not be Best for Prediction Initialization Shock Ad-Hoc Procedures for Identifying Model Coupled Modes, Mapping Observations Inserting them into Coupled Model Coupled Modes Different From Observed Modes