Diagnosing ENSO and MJO signal in the new NCEP coupled model

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Diagnosing ENSO and MJO signal in the new NCEP
coupled model

• Wanqiu Wang, Suranjana Saha, Hua-Lu Pan
• Sudhir Nadiga, and Glenn White

Acknowledgements Dave Behringer, Scott Harper,
Qin Zhang, Shrinivas Moorthi and all of the EMC
Climate and Weather Modeling Branch.
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Background
Current NCEP operational coupled model (M. Ji, A.
Kumar, A. Leetmaa, 1994)

• Old version of NCEP MRF model
• Old version of GFDL MOM
• Coupling over tropical Pacific
• Flux correction at air-sea interface

New NCEP Coupled Forecast System Model (CFS03)

• NCEP Global Forecast System 2003
• Global GFDL MOM3
• No flux adjustment

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Objective

• Assess ENSO and MJO simulation by the new NCEP
  coupled model

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Outline

• The model
• The simulation
• Diagnoses
• Conclusions

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The coupled model (CFS03)

• 1. Atmospheric component

• Global Forecast System 2003 (GFS03)
• T62 in horizontal 64 layers in vertical
• Recent upgrades in model physics
• Solar radiation (Hou, 1996)
• cumulus convection (Hong and Pan, 1998)
• gravity wave drag (Kim and Arakawa, 1995)
• cloud water/ice (Zhao and Carr,1997)

2. Oceanic component

• GFDL MOM3 (Pacanowski and Griffies, 1998)
• 1/31 in tropics 11 in extratropics 40
  layers
• Quasi-global domain (74S to 64N)
• Free surface

3. Coupled model

• Once-a-day coupling
• Sea ice extent taken as observed climatology

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Simulation

• Free integration of 32 years
• Initial date 1 January 2002
• Initial conditions
• Atmosphere NCEP GDAS
• Ocean NCEP GODAS

Observations

• ERSST Extended reconstructed SST (Smith and
  Reynolds, 2003)
• R2 NCEP/DOE reanalysis 2 (Kanamitsu et al.,
  2002)
• GODAS NCEP global ocean data assimilation
  (Behringer, personal communication)

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Diagnoses
ENSO variability

• Nino3.4 SST
• EOF modes of SSH
• Composites of Tau, SST, SSH for El Nino events

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Nino3.4 SST anomalies (K)
Composite
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Diagnoses
MJO variability
The runs

• Coupled simulation by CFS03 (21 years)
• AMIP simulation by GFS03 for 1982-2002

• Wavenumber-frequency spectra
• EOF modes of Precipitation, U850, and U200

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Conclusions
ENSO Simulation

• CFS03 simulates an ENSO with amplitude and
  periodicity comparable to that observed. But the
  simulated ENSO appears to be too regular.
• CFS03 reproduces the observed seasonality of ENSO
  variability, although the initial warming from
  January to May of the simulated El Nino events is
  somewhat too strong.
• Diagnoses of the simulated ENSO suggest that
  different mechanisms (delayed oscillator, western
  Pacific oscillator, recharge oscillator, and
  advective-reflective oscillator) may all
  contribute to the ENSO variability.

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Conclusions
MJO Simulation

• Compared with GFS03, CFS03 simulates a more
  realistic MJO
• frequency range more narrow and closer to the
  observed
• convection and circulation more coherent
• propagation better organized
• The MJO in CFS03 is too strong and a little too
  slow.
• Precipitation, solar radiation, and SST in CFS03
  are not as well organized as in the analyses
• Latent heat flux associated with the MJO in CFS03
  is not consistent with that in the reanalysis,
  possibly due to that the mean surface westerly in
  the Indian ocean and western Pacific is too weak

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PC1 leads PC2
PC2leads PC1
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Diagnoses
Climatology

• Sea surface temperature (SST)
• Surface momentum flux (Tau)
• Sea surface height (SSH)

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SSH and Nino3.4 SST in phase
SSH lags Nino3.4 SST by one quarter of the period
Consistent with Hasegawa and Hanawa (2003)