On the evolution of the oceanic component of the ipsl climate models

Download 84.39 Kb.
Size84.39 Kb.
On the evolution of the oceanic component of the IPSL climate models
Possible contributors (alphabetical order):

Rashid Benshila

Julie Deshayes

Gurvan Madec

Olivier Marti

Juliette Mignot

Didier Swingedouw

Claude Talandier

Sebastien Masson

Pascal Terray

1. Introduction

The aim of this paper is to detail the formulation of the oceanic component of the climate model developed at IPSL, and in particular to give insight on its evolution from the IPSLCM4 version [Marti et al., 2009] to IPSL_CM5A ([Dufresne, in prep.]).

Regarding the atmospheric component, several features have significantly evolved from IPSLCM4_v2 to IPSL_CM5A. These are described in detail in [Hourdin F., et al., submitted]. Note that increasing the vertical resolution (from 19 to 39 levels) has been prioritized with respect to increasing the horizontal resolution. Furthermore, preliminary studies using a low vertical resolution have shown that increasing the resolution in latitude leads to a poleward shift of the jet (e.g. [Guemas et Codron, 2011], thereby correcting a major bias of the IPSL_CM4 model version (e.g. [Marti et al., 2009]). Although the poleward shift is not as strong with the higher vertical resolution ([Hourdin F., et al., submitted] ), the atmospheric horizontal resolution has thus been changed from 96x71 grid points to 96x96 grid points in IPSL_CM5A-LR and 144x142 in IPSL_CM5A-MR.
Both versions of the coupled model use the global Océan Parallèlisé (OPA) ocean general circulation models (OGCM, [Madec et al., 1999]. OPA solves the primitive equations on the Arakawa C grid, with a second order finite difference scheme. It assumes the Boussinesq and hydrostatic approximations, the incompressibility hypothesis, and uses a free-surface formulation [Roullet et Madec, 2000]. The density is computed from potential temperature, salinity and pressure using the [Jacket et McDougall, 1995] equation of state. In its global configuration ORCA2, used in both version of the coupled climate model, the horizontal mesh is based on a 2°x2° Mercator grid and, following [Murray, 1996], two numerical inland poles have been introduced in order to remove the North Pole singularity from the computational domain. The departure from the Mercator starts at 20°N, and is constructed using a series of embedded ellipses based on the semi-analytical method of [Madec et Imbard, 1996]. The model uses realistic bottom topography and coastlines, derived from [Smith et Sandwell, 1997] up to 60° of latitude and ETOPO5 elsewhere. The maximum depth of 5000m is spanned by 31 z-levels ranging from 10m in thickness in the upper 120m to 500m at the bottom in absence of partial steps.

In spite of these similarities, IPSLCM4 and IPSLCM5A ocean components have evolved from OPA8 [Madec et al., 1999] in the former to NEMO ([Madec, 2008] in the latter. This implies the implementation of several additional parameterizations. Section 1 below describes these evolutions, and illustrates their effects with a series of sensitivity tests with ocean-only simulations.

2. Description of the main evolutions of the oceanic model

We present here a series of experiments ran in forced mode describing the main evolutions of the oceanic model from the IPSLCM4 version to IPSLCM5A. Table 1 summarizes the five configurations (labeled AR4_01, AR4_05, AR4_06, AR4_12 and AR5 respectively) under investigation here and their major characteristics in terms of oceanic circulation.

The first major evolution was to introduce a partial step representation of bottom topography instead of a full step one [Barnier et al., 2006][Le Sommer et al., 2009], [Penduff et al., 2007]. Indeed, as discussed in [Pacanowski et Gnanadesikan, 1998], discretizing the bottom topography by steps often leads to a misrepresentation of a gradually sloping bottom and to large localized depth gradients associated with large localized vertical velocities. The second major change, introduced in AR4_06, is the treatment of tidal mixing. First, additional vertical diffusivity resulting from internal tide breaking is introduced. The resulting tidal mixing parameterization is intensified at the bottom, following the formulation proposed by [St Laurent et al., 2001] and first introduced in an OGCM by [Simmons, 2004]. Furthermore, when the Indonesian ThroughFlow (ITF) area is included in the model domain, a specific treatment of tidal induced mixing in this area improves the representation of water masses in this area ([Koch-Larrouy et al., 2007][Koch-Larrouy et al., 2008]) and has a significant impact on the behavior of global coupled GCMs [Koch-Larrouy et al., 2009]. The third level of major changes concerns the Turbulent Kinetic Energy (TKE) scheme: in AR_12, it includes a Langmuir cell parameterization [[Axell, 2002] [Mellor et Blumberg, 2004]] surface wave breaking parameterization, and has a time discretization which is energetically consistent with the ocean model equations [[Burchard, 2002] [Marsaleix et al., 2008]]. In addition, in AR_12, a penetration of tke below the mixed layer (ML) due to internal & inertial waves is allowed through the high frequency variations of the wind stress. *** Note that this last development was finally not taken into account in the final AR5 version, for reasons developed below. Finally, the last step of evolution from the oceanic configuration in AR4 to AR5 is the coupling to the PISCES module [Aumont et Bopp, 2006]. ** Note that in the final configuration presented here (AR_13, see table 1), this module is implemented but not the penetration of the turbulent kinetic energy below the mixed layer.
The table 1 illustrates how each of these new features successively induces an intensification of the large-scale oceanic circulation. In fact, some of the evolutions have a specific influence on individual features of the circulation, inducing a step-wise increase. Implementation of partial steps in particular is seen to have a significant influence on the MOC intensity, inducing by itself an increase of 2.17Sv (Comment Gurvan, Claude, Olivier?). It also induces an intensification of the Antarctic Circumpolar Current by about 10% of its intensity. This could be related to a direct effect of the partial steps on the barotropic circulation. It could also be linked to the intensification of NADW formation, which helps to increase the density gradient across the ACC in the South Atlantic and thus to increase the ACC transport (check in coupled mode?). Improved tidal mixing, probably more specifically its intensification at the bottom in the ocean, favors rather an intensification of the circulation of Antarctic Bottom Water (AABW) and its formation. It also helps to further intensify the Antarctic Circumpolar Current, again by roughly by 10% of its intensity. Again, this can be directly linked to an intensification of the density gradient across the southern ocean (not that obvious from Fig 1, to check).

As described above, AR4_12 is a bit peculiar in this model hierarchy as it contains more developments than what was finally kept for the AR5 version. In AR4_13, the AABW is slightly reduced after the modifications of the tke scheme while the other measures of the large scale oceanic circulation are also enhanced.

Fig. 1 shows the zonally averaged temperature profiles in the five forced oceanic configurations described in Table 1. Fig. 2 illustrates the zonal mean mixed layer depth. Fig. 3 finally shows the globally averaged temperature and salinity profiles. A commenter: Claude/Gurvan?


Evolution of the physics

MOC (Sv)




AABW formation (Sv)

AR4_01 (Ref)







+ partial steps






+ kz tides






+ etau=3 and Langmuir Cells





AR4_13=AR5 (etau=0)







Table 1: add definition of etau, length of simulations, etc

3. Evolution of the oceanic component in coupled mode

a. Description of the simulations

In order to test the robustness of these evolutions in coupled mode, we ran two sensitivity simulations. Both use rigorously the same atmospheric and land surface configurations as the latest IPSL climate model, namely IPSL-CM5A-LR ([Dufresne, in prep.]), under pre-industrial conditions. Regarding the oceanic model, piStart uses the same configuration as “AR5” described above, which is rigorously the same configuration as in the coupled model IPSLCM5A-LR. The only difference between piStart and the pre-industrial control simulation of the coupled model (piControl, see [Dufresne, in prep.]) lies in the initial conditions. In piStart, it is taken as an ocean at rest using the January temperature and salinity fields from the Levitus World Ocean Atlas [Levitus et Boyer, 1994]. piControl results from several hundreds oy years of adjustment in coupled and decoupled mode (see [Dufresne, in prep.] for details). In the second sensitivity experiment performed in coupled mode for the present study, the ocean model was set back to the configuration used in IPSLCM4 ([Marti et al., 2009]), that is the configuration AR4_01 in the previous section. This simulation is named RETRO hereafter. As detailed in the introduction, the coupled simulation RETRO thus differs from IPSL_CM4 configuration because of evolutions of the atmospheric component, most notably its horizontal and vertical resolutions. This set-up was thus designed to test the effect of the evolution of the oceanic model on the evolution of the coupled IPSL model.

Both simulations start from Levitus at rest and were run for 491 years.

b. Oceanic circulation

Fig. 4 shows the time series of the global heat content in the upper 300m (top panel), the total transport integrated over the water column at the Drake Passage (middle panel), and the AMOC maximum (bottom panel). Although it is clear that the oceanic adjustment requires several hundreds of years, this figure illustrates that the upper 300m heat content have reached approximately an equilibrium state after 300 years. piStart equilibrates globally to a colder state for the upper ocean than RETRO, but to a stronger intensity for the ACC at Drake Passage and a similar intensity of the Atlantic (and global, not shown) meridional overturning circulation. Given that the two simulations start from the same initial conditions, comparing the climate state even after these relatively short simulations gives insight in the evolution of each model and the influence of the evolutions of the oceanic model.

Fig. 5 shows the total net mass transport across selected sections both for piStart (top) and RETRO (bottom) and averaged over the years [2200-2291], that is after [400-491] years of simulation. Fig. 5 shows that the net mass transport is generally weaker in RETRO than in piStart. At the Drake passage, in particular, the total transport at the amounts about 109Sv in piStart, which is 23% more than what is simulated in the RETRO configuration, but still weaker than the value inferred from observations (136.7 ± 7.8 Sv [Cunningham et al., 2003]). Note that such increase of ACC intensity at the Drake Passage from RETRO to piStart is very close to the 21% increase diagnosed in the forced configurations described above. This suggests an important role of the oceanic component in this evolution. Nevertheless, the weak ACC intensity was a known deficiency of the IPSL_CM4 climate model (e.g. [Marti et al., 2009] [Marini et al., 2010]). The latter was enhanced from 50 to 98Sv from IPSL_CM4 to IPSL_CM5-LR (Fig. 4), thus an increase of roughly 50%, twice as much as what is found from RETRO to piStart. This indicates that the change in atmospheric horizontal resolution also plays an important role, as explained in [Hourdin F., et al., submitted]. Note also that these numbers highlight the fact that piStart is not in full equilibrium, as the intensity of the flow through the Drake Passage largely differs from what is found in piControl.

Downstream of the Drake Passage, this transport of mass is fed by a weak input from the South Atlantic and a stronger one from the Indian Ocean, consistent with inversions from [Ganachaud et Wunsch, 2000]. In both simulations, it thus slightly increases from the Drake Passage to the Cape of Good Hope and Cape Leewin sections. In the Pacific, the net mass transport is northward at all latitudes, while it is southward in the Atlantic and in the Indian basin (except for the Arabian Sea). This is again consistent with [Ganachaud et Wunsch, 2000]. Their inversion yield an throughflow of 16Sv, and the latest long-term simultaneous measurements within both inflow and outflow passages (INSTANT 2004–2006) estimated a total transport of 14 ± 3 Sv ([Sprintall et al., 2009]). The intensity of the Indonesian Throughflow in terms of net mass transport is similar in piStart and in RETRO (12.71 Sv and 12.27Sv respectively Fig. 5). This is lower than the most recent estimates inferred from observations, but close to the value proposed by [Ganachaud et Wunsch, 2000]. Note that this is relatively surprising as the ITF parametrisation developed by [Koch-Larrouy et al., 2009] was set in piStart but not in RETRO. (Gurvan?)

As indicated above, all transports are generally stronger in piStart than in RETRO Exceptions concern the southward transport of mass at the southern end of the Bay of Bengal and the exchange of mass in the northern North Atlantic. In the Bay of Bengal, this is associated with a strong reduction of the outflow of the Gange River in piStart. Given that the runoff is rigorously similar in the two simulations, this must com from a difference in atmospheric circulation.

Fig. 6 (left panels) compares the global mean meridional circulation for the years [2200-2290] of each simulation. The major difference lies in an intensification by roughly 12 Sv of the AABW circulation at the bottom ocean of the southern hemisphere in piStart as compared to RETRO. This increase is roughly portioned among the oceanic basins according to their width, as this cell increases by 4Sv at the southern bottom of the Indian Ocean, 5Sv in the Pacific and only 3Sv in the Atlantic. As seen above for the forced simulations, this intensification is consistent with the evolution of the oceanic component, and in particular the implementation of the kz-tide parameterization, as discussed in section 1. The shallow subtropical cells are very similar in the two simulations, consistent with a similar wind stress field and wind stress curl (not shown). Regarding the upper cell of inter-hemispheric transport, the weak intensification of the global cell (Fig. 6, left panels) is due to the North Atlantic contribution (Fig. 6 right panels). The maximum of the NADW overturning cell is very similar in both simulation (between 8.5 and 8.7 Sv, when accounting for to eulerian currents only, Fig. 4 bottom panel), and it is located around 26°N in piStart and slightly further north in RETRO. At 26°N, the intensity of the overturning component of mass transport is much weaker both in RETRO (7.32 Sv) and in piStart (8.7 Sv ) than what is suggested by observations (e.g. 18.7 ± 5.6 Sv [Cunningham et al., 2007]). At this location, intensification from RETRO to piStart configuration amounts 37%. Further north, at 45°N, the overturning component of mass transport amounts about 8.03 Sv in RETRO and 8.4 Sv in piStart. Both these values are again weaker than values inferred from observations [Ganachaud et Wunsch, 2000; Talley et al., 2003], as already commented in several references concerning the IPSL coupled model [Dufresne, in prep.; Marti et al., 2009; Swingedouw et al., 2006]. Nevertheless, it increases by 17% from RETRO to piStart (in forced simulations, increase of roughly 20%. Check how the max is computed (fixed latitude?))

Another general view of the oceanic circulation is given by the barotropic streamfunction (Fig. 7). This figure confirms that the Antarctic Circumpolar Current (ACC) is weaker in RETRO than in piStart after 400 years of simulation. Beyond the Southern Ocean, major changes are found in the North Pacific, with a basinwide positive anomaly in RETRO. Note that the intensity of both gyres is stronger in RETRO (59Sv vs 55Sv for the subtropical gyre, 27Sv vs 21Sv for the subpolar gyre). Given the lack of significant differences in the wind stress curl structure and intensity in both simulations, these differences are probably due to partial steps (ideas ? (ps: nothing obvious on f/h contours)). In the North Atlantic, the oceanic circulation is generally relatively weak in IPSLCM5A-LR (see Escudier et al. in rev for references) and it is also the case in piStart: the North Atlantic subpolar gyre maximum amounts 18 Sv (16Sv in RETRO) and the subtropical gyre 40Sv (similar value in RETRO). Observations-based estimates are around 40 Sv for the subpolar gyre ([Hakkinen et Rhines, 2004]) and around 60 Sv for the subtropical one ([Greatbatch et al., 1991],[Johns et al., 1995]). Fig. 7b shows that this bias is even stronger in RETRO, but the anomalies are not as marked as in the North Pacific. This might be due to a compensating effect from the intensification of the AMOC upper branch.

c. heat and freshwater transports

Fig. 8 shows the global ocean heat transport respectively in piStart01 and in RETRO averaged over the same period. Fig. 8 shows that in piStart, the direction of the heat transport is generally consistent with [Greatbatch et al., 1991; Johns et al., 1990] but its intensity is much weaker. In the North Atlantic and at the Drake Passage, this is probably strongly linked to the weak net mass transport commented above. At the Indian and Pacific southern entrances, we note a contradiction between estimations of [Ganachaud et Wunsch, 2000] and of [Talley, 2003]: as indicated above, the inversion of [Ganachaud et Wunsch, 2000] yield a flow through the Indonesian archipelago (Indonesian Throughflow or ITF) of 16Sv and consequently, in order to feed this intense flow of warm water towards the indian ocean, heat transport at 30°S in the South Pacific is northward (0.6 PW) and the heat export at the southern boundary of the Indian ocean is quite intense (1.5 PW). On the contrary, using an estimation of the throughflow of 8Sv, [Talley, 2003] diagnoses a southward heat transport in the South Pacific (0.39PW) and a much weaker export of heat at the southern boundary of the Indian Ocean (0.76PW). In piStart, the situation is closer to the picture drawn by Ganachaud et Wunsch, 2000, although again weaker (0.26 PW entering the SouthPacific and 1.07 PW exiting the South Indian).

The colors in Fig. 8 (upper panel) show the net total atmospheric flux into the ocean in piStart. They highlight the link between the heat received by the ocean from the atmosphere, and the convergence or divergence of heat carried by the ocean. In the Equatorial Pacific for example, the ocean gains heat from the atmosphere, and transports it poleward across the sections at 10°N and 10°S. Between 26°N and 45°N, on the other hand, the ocean looses heat in the western boundary current in both basins, and there is a net convergence of the oceanic heat transport between these two latitudes.

Fig. 8 (lower panel) shows the major differences between RETRO and piStart both in terms of heat transport (arrows) and of atmospheric heat flux (colors). In terms of heat transport, major differences are found again in the southern basins. Firstly, as opposed to the net zonal mass transport, the zonal heat transport in the austral ocean is stronger (by 2 to 10%) in RETRO than in piStart. This might be linked to the generally stronger atmospheric heat input at these latitudes. (?) There might also be a contribution of the southward heat transport in the South Atlantic in RETRO, feeding the net eastward heat transport. This feature is strongly unrealistic [Ganachaud et Wunsch, 2000; Talley, 2003]. It is difficult to pin down to the exact causes for this inversion. The strong anomalous atmospheric heat input into the western southern tropical Atlantic in RETRO (e.g. [Breugem et al., 2008]) might be a contributor.

In the South Pacific the northward heat transport is intensified in RETRO. This intensification essentially feeds the ITF, which itself feeds the northward heat flux into the Arabian Sea. The excess of heat is then directed back to the atmosphere. (poule et oeuf entre intensified mass transport et heat transport?)

Finally, Fig. 9 shows the annual mean transport of freshwater (in mSv) across the same selected sections. This figure can be compared to estimates by [Talley et al., 2003]. The sign of these transports generally agrees with the observations: The ACC transport freshwater eastward, which enters at the southern edge of each oceanic basin. In the North Atlantic and North Pacific, on the other hand, the net transport is southward, and convergences are found in the subtropics, where evaporation is maximum. Comparing RETRO and piStart, we notice generally a qualitative compensation in terms of density between the anomalous heat and freshwater transports. In the tropics, anomalies of the total atmospheric freshwater flux out of the ocean are generally strong, and consistent with a southward shift of the ITCZ in RETRO in the Atlantic and the Indian ocean, and a stronger SPCZ (or double ITCZ) in the Pacific. Finally, as indicated above, strong changes are also found in the northern Indian basin, associated with a strong reduction of the Gange river outflow.

d. tracers distribution

Fig. 10 investigates the annual mean surface temperature and salinity anomalies in the ocean. The upper left panel shows that in piStart the oceanic surface is generally colder than the observations. This bias is generally even stronger in the control simulation of IPSL_CM5A-LR by 0.5 to 2°C, depending on locations. Notable exceptions are around 50°N in the Atlantic and the Pacific: at these locations, where the cold bias in piStart is maximum (and maximum in summer), it exceeds the one found in piControl by about 0.5°C. Note that this cold bias in also stronger in piStart than in RETRO (Fig. 10 bottom) around 50°N, while it is reduced in both the Atlantic and the Pacific around 40°N. Similarly, in the austral ocean, piStart is generally too cold around 50°S and too warm south of 60°S. This is associated with an anomalously weak ACC and a weak meridional density gradient. Both these biases (weak meridional density gradient and weak ACC° are stronger in RETRO.

At low latitudes, a warm bias is detected in the coastal upwelling areas in piStart. Again, similar bias was found in IPSLCM4 and IPSL_CM5A-LR. It is a typical bias in coupled ocean–atmosphere models (IPCC, Fig. S8.1). It is associated with insufficient resolution, which leads to a poor representation of the local wind stress and the oceanic upwelling ([Braconnot et al., 2011], [Braconnot et al., 2007]). In RETRO, this bias was generally weaker, while the cold bias seen in piStart in the centre and west of the tropical basins was weaker (Fig. 10 bottom right). Explain?

The annual means in Fig. 10 hide in fact seasonal differences: Fig. 11 (left panel) shows that summer SSTs are much warmer in piStart than in RETRO, in particular in the northern hemisphere. As detailed above for the forced simulations, this can be explained quite directly by the new tke parameterization in piStart. This effect is probably partly too strong, as consequently, the amplitude of the seasonal cycle at midlatitudes exceeds the one that is observed (Fig. 11, right panel).

Fig. 10 (bottom) also shows that surface water masses are warmer by up to 1°C and fresher by more than 1.5 psu in RETRO as compared to piStart in the southern part of the Indonesian Archipelago (IA). This is consistent with simulations from [Koch-Larrouy et al., 2009] showing the effect of implementing tidal mixing in the Indonesian Archipelago in a coupled climate model. (Remarque: anomalie de sel autour de l’asie du sud-est?). The total integrated heat and freshwater transports are nevertheless unchanged, as shown in Fig. 6 and 7.

Finally, Fig. 12 shows the zonal mean temperature and salinity as a function of latitude and depth. Fig. 12 (top left panel) shows that surface cold bias in piStart extends down to more than 500m, and even more in the austral ocean. Fig. 12 (bottom left panel) compares the cold bias from piStart and RETRO. This figure can be compared to Fig. 1 middle left panel, which shows the same variable in a forced mode. In both forced and coupled modes, the AR5 configuration is colder than the AR4 configuration above the tropical thermocline and down to about 1000m between 30° and 50° of latitude north and south. On the other hand, the anomalous warming that was seen in forced mode over the whole water depth in the southern ocean and at depth in all basins is not present anymore in the coupled mode. It is overwhelmed by the general cold anomaly. At tropical and mid-latitudes a warm bias around 500m in RETRO as compared to piStart reflects a weakened stratification and thickening of the permanent thermocline. It is largely accompanied with a salty anomaly in RETRO (Fig. 12 bottom right). Along the Antarctic continent, on the other hand, water masses are fresher in RETRO than in piStart, while they are saltier north of 50°S. Fig 13 shows that these salinity changes in the southern hemisphere are essentially responsible for potential density changes: in RETRO, the density gradient across the southern ocean (80°S-50°S) was reduced by roughly 15% as compared to piStart in surface. This is both due to the presence of denser (saltier) water masses along the shelf in piStart and flatter isopcynals above 100m and poleward of the polar front in RETRO associated to much fresher and slightly colder surface waters. Just below, warmer and more saline waters contribute to create a stronger thermocline. Bottom waters long the continental shelf are warmer (less dense) in RETRO. All these characteristics are consistent with intensified ACC and AABW formation described above in piStart. (could be better described)

4. Focus on the tropics?

(needed? Add something on ENSO (-> Pascal Terray)? But it would take us to seasonality etc… )
Fig. 14: Thermocline is deeper in RETRO. Associated to a thicker Equatorial UnderCurrent.

5. Influence of the interactive biological module

(not sure to add this section yet, because results are opposite to Lengaigne et al as we understand it at the moment….)

One specific difference between ocean configurations in piStart and RETRO is the use of a state-of-the-art biological model representing space- and-time varying chlorophyll concentrations, namely the PISCES 24 compartments ecosystem model of [Talley et al., 2003]. The simulated chlorophyll concentrations can feedback onto the ocean by modifying the vertical distribution of radiant heating. (Aumont & Bopp 2006) showed that introducing an interactive biology acts to warm the surface eastern equatorial Pacific by about 0.5°C and slightly increase ENSO amplitudes. [Lengaigne et al., 2006] further showed that in the polar regions, the resulting surface warming triggers a reduction of sea-ice thickness and concentration.

6. Conclusions


Aumont, O., et L. Bopp (2006), Globalizing results from ocean in situ iron fertilization studies, Global Biogeochemical Cycles, 20, doi:10.1029/2005GB002591. [en ligne] Available from: http://www.agu.org/pubs/crossref/2006/2005GB002591.shtml (Consulté 26 septembre 2011)

Axell, L. B. (2002), Wind-driven internal waves and Langmuir circulations in a numerical ocean model of the southern Baltic Sea, Journal of Geophysical Research, 107, doi:10.1029/2001JC000922. [en ligne] Available from: http://www.agu.org/pubs/crossref/2002/2001JC000922.shtml (Consulté 10 octobre 2011)

Barnier, B. et al. (2006), Impact of partial steps and momentum advection schemes in a global ocean circulation model at eddy-permitting resolution, Ocean Dynamics, 56, 543-567, doi:10.1007/s10236-006-0082-1.

Braconnot, P., B. Otto-Bliesner, et S. Harrison (2007), Results of PMIP2 coupled simulations of the Mid- Holocene and last glacial maximum. Part 1. Experiments and large-scale features.,

Braconnot, P., F. Hourdin, S. Bony, J.-L. Dufresne, J.-Y. Grandpeix, et O. Marti (2011), Impact of different convective cloud schemes on the simulation of the tropical seasonal cycle in a coupled ocean– atmosphere model., , 501-520.

Breugem, W.-P., P. Chang, C. J. Jang, J. Mignot, et W. Hazeleger (2008), Barrier layers and tropical Atlantic SST biases in coupled GCMs, Tellus A, 60(5), 885-897, doi:10.1111/j.1600-0870.2008.00343.x.

Burchard, H. (2002), Energy-conserving discretisation of turbulent shear and buoyancy production, Ocean Modelling, 4, 347-361, doi:10.1016/S1463-5003(02)00009-4.

Cunningham, A. S. et al. (2007), Temporal Variability of the Atlantic Meridional Overturning Circulation at 26.5°N, S, 317, 935 Р938, DOI: 10.1126/science.1141304.

Cunningham, S. A., S. G. Alderson, B. A. King, et M. A. Brandon (2003), Transport and variability of the Antarctic Circumpolar Current in Drake Passage, J. Geophys. Res., 108(C5), 8084, doi:10.1029/2001JC001147.

Dufresne, J.-L. (in prep.), Overview of the IPLS-CM5 Earth System Model with an emphasis on model and forcing changes between CMIP3 and CMIP5, Clim. Dyn.

Ganachaud, A., et C. Wunsch (2000), Improved estimates of global ocean circulation, heat transport and mixing from hydrographic data, Nature, 408, 453–456.

Greatbatch, R. J., A. F. Fanning, A. D. Goulding, et S. Levitus (1991), A Diagnosis of Interpentadal Circulation Changes in the North Atlantic, Journal of Geophysical Research, 96(C12), 22009-22023, doi:10.1029/91JC02423.

Guemas, V., et F. Codron (2011), Differing impacts of resolution changes in latitude and longitude on the mid-latitudes in the LMDZ Atmospheric GCM, Journal of Climate, 110516122137059, doi:10.1175/2011JCLI4093.1.

Hakkinen, S., et P. B. Rhines (2004), Surface salinity variability in the northern North Atlantic during recent decades, Science, 304 (5670) , pp. 555 - 559, 555–559, doi:10.1126/science.1094917.

Hourdin F., et al. (submitted), From LMDZ4 to LMDZ5 : impact of the atmospheric model grid resolution on the climatology and climate sensitivity in the IPSL coupled model, Clim. Dyn. [en ligne] Available from: http://forge.ipsl.jussieu.fr/igcmg/wiki/IPSLCM5/SpecialIssue (Consulté 26 septembre 2011)

Jacket, D. R., et T. J. McDougall (1995), Minimal adjustment of hydrographic data to achieve static stability, J. Atmos. Oceanic Technol, 12, 381–389.

Johns, W. E., T. N. Lee, F. Schott, R. J. Zantopp, et R. H. Evans (1990), The North Brazil Current Retroflection: seasonal structure and eddy variability, JGR, 95, 22103–22120.

Johns, W. E., T. J. Shay, J. M. Bane, et D. R. Watts (1995), Gulf Stream structure, transport, and recirculation near 68°W, Journal of Geophysical Research, 100(C1), 817-838, doi:10.1029/94JC02497.

Koch-Larrouy, A., G. Madec, P. Bouruet-Aubertot, T. Gerkema, L. Bessières, et R. Molcard (2007), On the transformation of Pacific Water into Indonesian Throughflow Water by internal tidal mixing, Geophysical Research Letters, 34, doi:10.1029/2006GL028405. [en ligne] Available from: http://www.agu.org/pubs/crossref/2007/2006GL028405.shtml (Consulté 10 octobre 2011)

Koch-Larrouy, A., G. Madec, B. Blanke, et R. Molcard (2008), Water mass transformation along the Indonesian throughflow in an OGCM, Ocean Dynamics, 58, 289-309, doi:10.1007/s10236-008-0155-4.

Koch-Larrouy, A., M. Lengaigne, P. Terray, G. Madec, et S. Masson (2009), Tidal mixing in the Indonesian Seas and its effect on the tropical climate system, Climate Dynamics, 34(6), 891-904, doi:10.1007/s00382-009-0642-4.

Lengaigne, M., C. Menkes, O. Aumont, T. Gorgues, L. Bopp, J.-M. André, et G. Madec (2006), Influence of the oceanic biology on the tropical Pacific climate in a coupled general circulation model, Climate Dynamics, 28, 503-516, doi:10.1007/s00382-006-0200-2.

Levitus, S., et T. Boyer (1994), World Ocean Atlas, Volume 4: Temperature., NOAA Atlas NESDIS 4, Washington D.C.

Madec, G. (2008), NEMO ocean engine, Note du pole de modelisation, NEMO ocean engine, Institut Pierre-Simon Laplace, France. [en ligne] Available from: http://www.nemo-ocean.eu/About-NEMO/Reference-manuals (Consulté 5 octobre 2011)

Madec, G., et M. Imbard (1996), A global ocean mesh to overcome the North Pole singularity, CD, 12(6), 381–388.

Madec, G., P. Delecluse, M. Imbart, et C. Levy (1999), OPA8.1 Ocean General Circulation Model reference manual, Institut Pierre-Simon Laplace (IPSL), France.

Marini, C., C. Frankignoul, et J. Mignot (2010), Links between the Southern Annular Mode and the Atlantic Meridional Overturning Circulation in a Climate Model, J. Climate, 24(3), 624-640, doi:10.1175/2010JCLI3576.1.

Marsaleix, P., F. Auclair, J. W. Floor, M. J. Herrmann, C. Estournel, I. Pairaud, et C. Ulses (2008), Energy conservation issues in sigma-coordinate free-surface ocean models, Ocean Modelling, 20, 61-89, doi:10.1016/j.ocemod.2007.07.005.

Marti, O. et al. (2009), Key features of the IPSL ocean atmosphere model and its sensitivity to atmospheric resolution, Climate Dynamics, 34, 1-26, doi:10.1007/s00382-009-0640-6.

Mellor, G., et A. Blumberg (2004), Wave Breaking and Ocean Surface Layer Thermal Response, Journal of Physical Oceanography, 34, 693-698, doi:10.1175/2517.1.

Murray, R. J. (1996), Explicit generation of orthogonal grids for ocean models, J. Comput. Phys., 126, 251–273.

Pacanowski, R. C., et A. Gnanadesikan (1998), Transient response in a z-level ocean model that resolves topography with partial cells, Monthly Weather review, 3248-3270.

Penduff, T., J. Le Sommer, B. Barnier, A.-M. Treguier, J.-M. Molines, et G. Madec (2007), Influence of numerical schemes on current-topography interactions in 1/4 degrees global ocean simulations, Ocean Science, 3(4), 509-524.

Roullet, G., et G. Madec (2000), Salt conservation, free surface and varying volume: A new formulation for ocean GCMs., JGR, 105, 23 927–23 942.

Simmons, H. (2004), Tidally driven mixing in a numerical model of the ocean general circulation, Ocean Modelling, 6, 245-263, doi:10.1016/S1463-5003(03)00011-8.

Smith, W., et D. T. Sandwell (1997), Global sea-floor topography from satellite altimetry and ship depth souding, Science, 277, 1952-1956.

Le Sommer, J., T. Penduff, S. Theetten, G. Madec, et B. Barnier (2009), How momentum advection schemes influence current-topography interactions at eddy permitting resolution, Ocean Modelling, 29, 1-14, doi:10.1016/j.ocemod.2008.11.007.

Sprintall, J., S. E. Wijffels, R. Molcard, et I. Jaya (2009), Direct estimates of the Indonesian Throughflow entering the Indian Ocean: 2004–2006, Journal of Geophysical Research, 114(C7), doi:10.1029/2008JC005257. [en ligne] Available from: http://www.agu.org/pubs/crossref/2009/2008JC005257.shtml (Consulté 10 avril 2012)

St Laurent, L., J. M. Toole, et R. W. Schmitt (2001), Buoyancy forcing by turbulence above rough topography in the abyssal Brazil Basin, JPO, 31, 3476–3495.

Swingedouw, D., P. Braconnot, P. Delecluse, E. Guilyardi, et O. Marti (2006), Impact of global freshwater forcing on the thermohaline circulation: adjustment of the North Atlantic convection sites in a CGCM, CD, in revision.

Talley, L. D. (2003), Shallow, intermediate, and deep overturning components of the global heat budget, Journal of Physical Oceanography, 33(3), 530–560.

Talley, L. D., J. L. Reid, et P. E. Robbins (2003), Data-based Meridional Overturning streamfunctions for the global oceans, JC, 16, 3213–3226.
Download 84.39 Kb.

Share with your friends:

The database is protected by copyright ©ininet.org 2020
send message

    Main page