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Influence of the oceanic biology on the tropical Pacific climate in a coupled general circulation model

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Abstract

The influence of chlorophyll spatial patterns and variability on the tropical Pacific climate is investigated by using a fully coupled general circulation model (HadOPA) coupled to a state-of-the-art biogeochemical model (PISCES). The simulated chlorophyll concentrations can feedback onto the ocean by modifying the vertical distribution of radiant heating. This fully interactive biological-ocean-atmosphere experiment is compared to a reference experiment that uses a constant chlorophyll concentration (0.06 mg m−3). It is shown that introducing an interactive biology acts to warm the surface eastern equatorial Pacific by about 0.5°C. Two competing processes are involved in generating this warming: (a) a direct 1-D biological warming process in the top layers (0–30 m) resulting from strong chlorophyll concentrations in the upwelling region and enhanced by positive dynamical feedbacks (weaker trade winds, surface currents and upwelling) and (b) a 2-D meridional cooling process which brings cold off-equatorial anomalies from the subsurface into the equatorial mixed layer through the meridional cells. Sensitivity experiments show that the climatological horizontal structure of the chlorophyll field in the upper layers is crucial to maintain the eastern Pacific warming. Concerning the variability, introducing an interactive biology slightly reduces the strength of the seasonal cycle, with stronger SST warming and chlorophyll concentrations during the upwelling season. In addition, ENSO amplitude is slightly increased. Similar experiments performed with another coupled general circulation model (IPSL-CM4) exhibit the same behaviour as in HadOPA, hence showing the robustness of the results.

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References

  • AchutaRao K, Sperber KR, in collaboration with the CMIP modelling groups (2002) Simulation of the El Niño southern oscillation: results from the coupled model intercomparison project. Climate Dyn 19:191–209

    Google Scholar 

  • Aumont O, Bopp L (2006) Globalizing ocean in-situ iron fertilization experiments. Global Biogeochem Cycles 20:GB2017. DOI 10.1029/2005GB002591

  • Aumont O, Maier-Reimer E, Blain S, Monfray P (2003) An ecosystem model of the global ocean including Fe, Si, P colimitations. Global Biogeochem Cycles 17:1060. DOI 10.1029/2001GB001745

    Google Scholar 

  • Barber RT, Sanderson MP, Lindley ST, Chai F, Newton J, Trees CC, Foley DG, Chavez FP (1996) Primary productivity and its regulation in the equatorial Pacific during and following the 1991–1992 El Niño. Deep Sea Res 43B:933–969

    Google Scholar 

  • Bjerknes J (1969) Atmospheric teleconnections from the equatorial Pacific. Mon Wea Rev 97:163–172

    Google Scholar 

  • Blanke B. Delecluse P (1993) Variability of the tropical Atlantic ocean simulated by a general circulation model with two different mixed layer physics. J Phys Oceanogr 23:1363–1388

    Article  Google Scholar 

  • Bony S, Emmanuel KA (2001) A parameterization of the cloudiness associated with cumulus convection, evaluation using TOGA COARE data. J Atmos Sci 58:3158–3183

    Article  Google Scholar 

  • Chavez FP, Strutton PG, Friedrich GE, Feely RA, Feldman GC, Foley DG, McPhaden MJ (1999) Biological and chemical response of the equatorial Pacific ocean to the 1997–98 El Niño. Science 286:2126–2131

    Article  Google Scholar 

  • Emanuel KA, (1991) A scheme for representing cumulus convection in large-scale models. J Atmos Sci 48:2313–2335

    Article  Google Scholar 

  • Fedorov AV, Philander SG (2001) A stability analysis of tropical ocean–atmosphere interactions: bridging measurements and theory for El Niño. J Clim 14:3086–3101

    Article  Google Scholar 

  • Fichefet T, Morales Maqueda MA (1999) Modelling the influence of snow accumulation and snow-ice formation on the seasonal cycle of the Antarctic sea-ice cover. Clim Dyn 15:251–268

    Article  Google Scholar 

  • Grandpeix JY, Phillips V, Tailleux R (2004) Improved mixing representation in Emanuel’s convection scheme. Q J R Meteorol Soc 604:3207–3222

    Article  Google Scholar 

  • Gregory D, Rowntree PR (1990) A mass flux convection scheme with the representation of cloud ensemble characteristics and stability dependent closure. Mon Wea Rev 118:1483–1506

    Article  Google Scholar 

  • Gregory D, Kershaw R, Inness PM (1997) Parametrisation of momentum transport by convection. II: Tests in single column and general circulation models. Q J Roy Meteor Soc 123:1153–1183

    Google Scholar 

  • Guilyardi E (2006) El Niño–mean state–seasonal cycle interactions in a multi-model ensemble. Climate Dyn 26:329–348. DOI 10.1007/s00382-005-0084-6

    Google Scholar 

  • Hourdin F, Musat I, Bony S, Braconnot P, Codron F, Dufresne JL, Fairhead L, Filiberti MA, Friedlingstein P, Grandpeix JY, Krinner G, LeVan P, Li ZX, Lott F (2005) The LMDZ4 general circulation model: climate performance and sensitivity to parametrized physics with emphasis on tropical convection. Climate Dyn DOI 10.1007/s00382-006-0158-0

  • Jerlov NG (1968) Optical oceanography. Elsevier, London

    Google Scholar 

  • Krinner G, Viovy N, de Noblet-Ducoudré N, Ogée J, Polcher J, Friedlingstein P, Ciais P, Sitch S, Prentice IC (2005) A dynamic global vegetation model for studies of the coupled atmosphere-biosphere system. Global Biogeochem Cycles 19. DOI 10.1029/2003GB002199

  • Lengaigne M, Madec G, Menkes C, Alory G (2003) The Impact of Isopycnal mixing on the tropical ocean circulation. J Geophys Res 108. DOI 10.1029/2002JC001704

  • Lengaigne M, Guilyardi E, Boulanger JP, Menkes C, Delecluse P, Inness P, Cole J, Slingo J (2004) Triggering of El Niño by Westerly wind events in a coupled general circulation model. Climate Dyn 23:601–620. DOI 10.1007/s00382-004-0457-2

    Google Scholar 

  • Lengaigne M, Boulanger JP, Menkes C, Spencer H (2006) Influence of the seasonal cycle on the termination of El Nino events in a coupled general circulation model. J Clim 19:1850–1868. DOI 10.1175/JCLI3706.1

    Google Scholar 

  • Lewis MR, Carr ME, Feldman GC, Esias W, McClain C (1990) Influence of penetrating solar radiation on the heat budget of the Equatorial Pacific. Nature 347:543–546

    Article  Google Scholar 

  • Liu Z (2002) A simple model study of the forced response of ENSO to an external periodic forcing. J Clim 15:1088–1098

    Article  Google Scholar 

  • Ludwig W, Probst JL, Kempe S (1996) Predicting the oceanic input of organic carbon by continental erosion. Global Biogeochem Cycles 10:23–41

    Article  Google Scholar 

  • Madec G, Delecluse P, Imbard M, Lévy C (1998) OPA 8.1 Ocean General Circulation Model reference manual. Note du Pôle de modélisation, Institut Pierre-Simon Laplace, No. 11, 91pp

  • Manizza M, Le Quere C, Watson AJ, Buitenhuis ET (2005) Bio-optical feedbacks among phytoplankton, upper ocean physics and sea-ice in a global model. Geophys Res Lett 32. DOI 10.1029/2004GL020778

  • Marzeion B, Timmermann A, Murtuggude R, Jin FF (2005) Biophysical feedbacks in the Tropical Pacific. J Clim 18:58–70

    Article  Google Scholar 

  • McClain CR, Cleave ML, Feldman GC, Gregg WW, Hooker SB, Kuring N (1998) Science quality SeaWiFS data for global biosphere research. Sea Technol 39:10–16

    Google Scholar 

  • Murtugudde RJ Beauchamp, Busalacchi A (2002) Effects of penetrative radiation in the upper ocean tropical ocean circulation. J Clim 15:470–486

    Article  Google Scholar 

  • Moore JK, Doney SC, Lindsay K (2004) Upper ocean ecosystem dynamics and iron cycling in a global three-dimensional model. Global Biogeochem Cycles 18:GB4028. DOI 10.1029/2004GB002220

    Google Scholar 

  • Morel A (1988) Optical modeling of the upper ocean in relation to its biogenous matter content (Case I waters). J Geophys Res 93:10749–10768

    Article  Google Scholar 

  • Morel A, Maritorena S (2001) Bio-optical properties of oceanic waters: a reappraisal. J Geophys Res 106:7163–7180

    Article  Google Scholar 

  • Nakamoto S, Prasanna Kumar S, Oberhuber J, Ishizaka J., Muneyama K, Frouin R (2001) Response of the equatorial Pacific to chlorophyll pigment in a mixed-layer isopycnal ocean general circulation model. Geophys Res Lett 28:2021–2024

    Article  Google Scholar 

  • Paulson CA, Simpson JJ (1977) Irradiance measurements in the upper ocean. J Phys Oceanogr 7:952–956

    Article  Google Scholar 

  • Pope VD, Gallani ML, Rowntree PR, Stratton RA (2000) The impact of new physical parametrisations in the Hadley Centre climate model-HadAM3. Climate Dyn 16:123–146

    Article  Google Scholar 

  • Roullet G, Madec G (2000) Salt conservation, free surface and varying volume: a new formulation for Ocean GCMs. J Geophys Res 105:23927–23942

    Article  Google Scholar 

  • Sathyendranath S, Platt T, Horne EPW, Harrison WG, Ulloa O, Outerbridge R, Hoepffner N (1991) Estimation of new production in the ocean by compound remote sensing. Nature 353:129–133

    Article  Google Scholar 

  • Spencer H, Slingo JM (2003) The simulation of peak and delayed ENSO teleconnections. J Clim 16:1757–1774

    Article  Google Scholar 

  • Stoens A, Menkes C, Radenac MH, Dandonneau Y, Grima N, Eldin G, Memery L, Navarette C, Andre JM, Moutin T, Raimbault P (1999) The coupled physical-new production system in the equatorial Pacific during the 1992–1995 El NIno. J Geophys Res 104:3323–3329

    Article  Google Scholar 

  • Strutton PG, Chavez FP (2004) Radiant heating in the equatorial Pacific: observed variability and potential for real-time calculation. J Clim 17:1097–1109

    Article  Google Scholar 

  • Tegen I, Fung I (1995) Contribution to the atmospheric mineral aerosol load from land surface modification. J Geophys Res100:18707–18726

    Article  Google Scholar 

  • Timmermann A, Jin FF (2002) Phytoplankton influences on tropical climate. Geophys Res Lett 29. DOI 10.1029/2002GL015434

  • Vialard J, Menkes C, Boulanger JP, Delecluse P, Guilyardi E, McPhaden MJ, Madec G (2001) Oceanic mechanisms driving the SST during the 1997–1998 El Niño. J Phys Oceanogr 31:1649–1675

    Article  Google Scholar 

  • Valcke S, Terray L, Piacentini A (2000) The OASIS coupler user guide version 2.4, Technical report TR/CMGC/00-10, available at Cerfacs, Toulouse, France

  • Valcke S, Caubel A, Vogelsang R, Declat D (2004) OASIS3 ocean atmosphere sea ice soil user’s guide technical report TR/CMGC/04/68, CERFACS, Toulouse, France

  • Wetzel P, Maier-Reimer E, Botzet M, Jungclaus J, Keenlyside N, Latif M (2006) Effects of ocean biology on the penetrative radiation in a coupled climate model. J Clim 19:3973–3987

    Article  Google Scholar 

Download references

Acknowledgments

The authors gratefully acknowledge comments of E. Maier-Raimer and an anonymous reviewer that led to significant improvements in an earlier version of the manuscript. They further acknowledge IRD for support, the developers team of the HadOPA and IPSL-CM4 models and the IDRIS centre where computations were carried out. ML also likes to thank J. Slingo, A. Timmermann and F.-F. Jin for invaluable discussion on this work. ML was founded by the Marie Curie Intra-European fellowship MEIF-CT-2003-501143.

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Correspondence to Matthieu Lengaigne.

Appendix: Description of the IPSL-CM4 coupled general circulation model

Appendix: Description of the IPSL-CM4 coupled general circulation model

The IPSL-CM4 model presently couples four components of the Earth system. LMDZ is the component for atmospheric dynamics and physics. OPA-ORCA2 is the component for ocean dynamics (same as in HadOPA and already described in Sect. 2.1). ORCHIDEE handles the land surface and LIM is the component for sea-ice dynamics and thermodynamics.

The atmospheric component of IPSL-CM4 is LMDZ-4 and has been developed at the Laboratoire de Meteorologie Dynamique (LMD). The model has a horizontal resolution of 3.75°longitude × 2.5°latitude, with 19 levels in the vertical. The dynamical part of the code is based on a finite-difference formulation of the primitive equations. In this model, the cloud cover and in-cloud water are deduced from the large scale total water and moisture at saturation, using a Probability Distribution Function (PDF) for the subgrid-scale total water, following Bony and Emmanuel (2001). The PDF moments are diagnosed interactively from the condensated water predicted by the convection scheme at the subgrid scale and from the large-scale degree of saturation of the atmosphere. Condensation is parameterized separately for convective and non-convective clouds. Moist convection is treated using a modified version of the Emanuel (1991) scheme (Grandpeix et al. 2004). A more detailed description of this atmospheric model and its climate performance can be found in Hourdin et al. (2005). This model is coupled to a land surface model (ORCHIDEE) described in Krinner et al. (2005).

The ocean component in this IPSL-CM4 CGCM is the OPA model (Madec et al. 1998, see documentation at http://www.lodyc.jussieu.fr/opa/) in its ORCA2 configuration. This model has already been described in Sect. 2.1. Contrary to HadOPA model, an interactive sea-ice model (LIM) with explicit thermodynamics and prognostically computed sea-ice cover is included in the IPSL-CM4 model. A detailed description of this sea-ice model in Fichefet and Morales Maqueda (1999).

These components have been coupled through OASIS 3 (Valcke et al. 2004). Air–sea, air–ice fluxes and SST are exchanged every day. Ocean–sea-ice are coupled every oceanic time step. Atmosphere and land surface are coupled every atmospheric time step. A full documentation of this coupled model can be found on http://dods.ipsl.jussieu.fr/omamce/IPSLCM4/DocIPSLCM4/FILES/DocIPSLCM4.pdf

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Lengaigne, M., Menkes, C., Aumont, O. et al. Influence of the oceanic biology on the tropical Pacific climate in a coupled general circulation model. Clim Dyn 28, 503–516 (2007). https://doi.org/10.1007/s00382-006-0200-2

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