INTRODUCTIONINTRODUCTION

The BSISO influences the life cycle of the Asian summer monsoon systems; The BSISO modulates the summertime sub-seasonal precipitation variability over North America; There exists clear evidence that a proper representation of tropical intraseasonal convective forcing helps enhance extended-range weather forecast skill in the extratropics; Therefore it is essential to assess the ability of global climate models in simulating and forecasting the intraseasonal variations; The proper simulation of the BSISO is one of the rigorous benchmark tests for climate models since models should produce the following factors: (a) northward propagating wave activity over the Indian and western Pacific Oceans, (b) eastward moving component along the equator, (c) seasonal changes in the mean state, and (d) appropriate air-sea interaction.

The Boreal Summer Intraseasonal OscillationThe Boreal Summer Intraseasonal Oscillation Simulated in the NCEP GFS and CFS modelsSimulated in the NCEP GFS and CFS models

Kyong-Hwan Seo, Jae-Kyung E. Schemm, Wanqiu Wang and Arun KumarClimate Prediction Center/NCEP/NOAA, Kyong-Hwan.Seo@noaa.gov

Figure Group 1: Life Cycle of Observed BSISO Convection AnomalyFigure Group 1: Life Cycle of Observed BSISO Convection Anomaly

MODELS

• Atmospheric Model (Global Forecast System: GFS2003): T62 L64

• Oceanic Model (MOM3): GFDL Modular Ocean Model V.3 1/3°X1° in tropics; 1°X1° in extratropics; 40 layers Quasi-global domain (74°S to 64°N)

• Coupled Model (Climate Forecast System: CFS) : GFS2003+MOM3 Once-a-day coupling No flux adjustment Sea ice extent taken as observed climatology

The first EEOF mode of CMAP precipitation for 1982-2002 JJAS: the BSISO is manifested as the northward propagation of convection and circulation anomalies over the Indian and western Pacific Oceans and the eastward propagation of equatorial Kelvin mode in boreal summer.

2005 CDPW30

SIMULATIONS

• GFS: AMIP run with monthly-SSTs for 1982-2002 (21-yr)

• CFS: CMIP run with 21-year coupled free run

• CFSA: CFS run with flux adjustments

Figure Group 2: Northward Propagation and Phase RelationshipsFigure Group 2: Northward Propagation and Phase Relationships

Figure Group 5: CFSA (Coupled Run with Flux Adjustments)Figure Group 5: CFSA (Coupled Run with Flux Adjustments)

Time evolution of intraseasonally filtered (a) 1000-hPa zonal wind, (b) surface latent heat flux (down is positive), (c) downward solar radiation flux, (d) surface temperature, (e) 1000-hPa vorticity, and (f) 1000-hPa moisture convergence relative to precipitation (shading). All variables are averaged over 65O-95OE. The CFS model realistically simulates the characteristic northward propagation and phase relationships.

CONCLUSIONS

• The CFS model simulates realistic intraseasonal variation associated with the characteristic northward propagation over the Indian Ocean in terms of peak period (~40 days) and intensity, whereas the GFS model shows erroneous standing oscillations.

• On coupling, phase relationships between precipitation and surface dynamic and thermodynamic variables for the northward propagation are very consistent with the observations.

• The surface meridional moisture flux convergence is regarded the most contributing factor for the propagation of the BSISO.

• Both GFS and CFS runs do not realistically simulate the eastward propagating equatorial mode due to errors in mean state SST and vertical shear of zonal wind.

• The NCEP GFS model tends to simulate Rossby wave better than the eastward propagating Kelvin wave in relation to the ISO (Seo et al. 2005); thus the CFS seems to have the similar problem.

• This study suggests that the proper representation of both mean state SST and intraseasonal SST fluctuation may be prerequisite for the development and maintenance of the BSISO along with direct air-sea interaction.

Seo K.-H., J.-K. E. Schemm, C. Jones and S. Moorthi 2005: Forecast skill of the tropical intraseasonal oscillation in the NCEP GFS dynamical extended range forecasts. Climate Dynamics, Vol. 25, 265-284.

Figure Group 4: Eastward Propagating Equatorial ModeFigure Group 4: Eastward Propagating Equatorial Mode

Eastward propagating Kelvin wave along the equator (5°S-5°N):

Frictional wave-CISK mechanism in the observation: the surface moisture convergence propagates eastward slightly ahead of the convection anomaly.

Both GFS and CFS models have difficulties in simulating the eastward propagating equatorial mode.

Cold bias near the Indonesia Island region vanishes.

The flux-corrected run (CFSA) produces more realistic eastward propagation mode over the eastern Indian Ocean and Indonesia Island region.

The propagation into the west Pacific has been failed due to:

(a) errors in high- and low-level basic winds, and

(b) physical parameterization problems.

Figure Group 3: Moisture Convergence and Space-Time Power SpectraFigure Group 3: Moisture Convergence and Space-Time Power Spectra

Zonal and Meridional Moisture Convergence

OBS

OBSERVATIONS

• Reanalysis 2, 1982-2002, daily

• CMAP precipitation, 1982-2002, pentad to daily

GFS CFS

Space-Time Power Spectra

Vertical easterly shear of basic zonal wind along the equator is improved