Sensitivity of the modeled Dynamics and Biochemistry of the Equatorial Pacific Ocean to Wind Forcing during the 1997-1999 ENSO. S. Cravatte 1 , C. Menkès 2 , T. Gorgues 2 , O. Aumont 2 1. LEGOS , Toulouse, France, 2. LOCEAN, Paris, France contact : [email protected]
Sensitivity of the modeled Dynamics and Biochemistry of the Equatorial Pacific Ocean to Wind Forcing during the 1997-1999 ENSO
S. Cravatte1, C. Menkès2, T. Gorgues2, O. Aumont2
1. LEGOS, Toulouse, France, 2. LOCEAN, Paris, France contact : [email protected]
2. Dynamics and TIWs (Tropical Instability Waves)
Figure 2.1: Equatorial zonal current 1993-2000.
1. The 5 simulations
(Aumont et al., 2002)
Figure 2.2: Surface zonal currents 1993-2000 (cm/s).
The forcing of the instabilities is complex. TIWs at 20 days and 30-40 days are not generated by the same instabilities (Lyman et al., 2005). Therefore, the differences in spectra argue for different generation mechanisms (Fig 2.4). Preliminary analyses indicates that baroclinic, barotropic and frontal contributions vary. In SSMI, the shear between the EUC and the SEC, north and south of the equator, are the main sources of TIWs energy, whereas in ERA, the main source is between SEC and NECC.
Further energetic budgets are necessary.
Figure 1.1: Zonal wind stress (colors) and curl (contours)
Figure 2.3:Turbulent kinetic energy (20-35 days)
Mean zonal wind stress patterns are similar, but the mean strength of trades is different Moreover, the strip of positive curl in the eastern Pacific is not well resolved in reanalysis products.
40 30 20 10 days 40 30 20 10
3. Heat budget in the cold tongue
The processes affecting the mixed layer temperature T in the cold tongue region (160°W-90°W, 2°S-2°N) over 1997-1999 are studied in the 5 simulations.
The mixed layer (h) heat budget can be written as follows:
Figure 2.4: Variance-preserving spectra of meridional currents
Cumulative tT (°C)
4. Biochemistry: 1998 blooms
E-Entrainement + turbulent mixing at the base of the mixed layer
C-advection by eddies
Averaged over 1993-2000, cooling by exchanges with subsurface, warming by atmospheric forcing and by eddy advection, the 3 main contributors to the heat budget, and cooling by mean advection, are very close qualitatively but are strongly varying from one simulation to the other quantitatively (Fig 3.1).
Figure 3.1: mean 93-00 tendencies in the mixed layer)
(left:°C/month and right:% of total heat exchanges)
Figure 4.1: Surface equatorial chlorophylle concentration (mg/m3).
Figure 3.2: T (a) and depth (b) of the mixed layer
We focus on the abrupt cooling in 1998 and transition from El Nino to La Nina (Fig 3.2). Fig 3.3 shows that qualitatively, the contributions of the different terms can be different at a particular time, but are similar most of the time. Quantitatively, all terms are different (sometimes two times larger in SSMI than in NCEP, for ex.).
In May 1998, exchanges with subsurface represents about 80% of the total heat exchanges for all simulations. As this term is smaller in NCEP, the abrupt cooling is badly represented in this simulation.
Figure 3.3: tendencies in the mixed layer Left: °C/month; right: % of total heat exchanges
Figure 4.2: a-[Fe] in the euphotic zone (Nmol)
b-depth of 23°C isotherm at 140°W,0
This poster presents preliminary results on the sensitivity of ocean model to wind forcing. Apart from NCEP forcing that present obvious biases, each wind product show qualities and weaknesses, and it is difficult to isolate the “best forcing field”. Qualitatively, the modeled thermo-dynamical mechanisms are close in the different simulations, and it gives us confidence in using models to analyze the Pacific Ocean and ENSO events.
Quantitatively, TIWs energetics and heat budget terms can be more than two times larger from one simulation to the other. Moreover, the modeled phytoplancton blooms exhibit completely different patterns.
This study points out the sensitivity of OGCM to wind forcing, the difficulty to present quantitative budgets, and the importance of choosing an adequate wind product to study the generation and characteristics of TIWs, heat budgets or biological impacts of ENSO.
Aumont O. et al. 2005: An ecosystem model of the global ocean including Fe, Si, P colimitations, Global Biogeochemical Cycles, Volume 17, DOI 10.1029/2001GB001745.
Cravatte, S., et al., 2005: Improving the Pacific Equatorial Undercurrent simulation in a climate ocean model, submitted to Ocean Modelling.
Madec G., P. Delecluse, M. Imbard and C. Levy, 1998: OPA 8.1 Ocean general circulation model reference manual (http://www.lodyc.jussieu.fr/opa)
Hackert, et al. 2001: A wind comparison study using an ocean general circulation model for the 1997-1998 El Nino, J. Geoph.. Res., 106, 2345-2362
Ryan, J. et al., 2002: Unusual large-scale phytoplancton blooms in the equatorial Pacific, Prog. in Ocean., 55 3-4.
Wang et al.,2005: Ecosystem dynamics and export production in the central and eastern equatorial Pacific: A modeling study of impact of ENSO, GRL, vol. 32, l02608, doi:10.1029/2004gl021538.