Skip to main content

Advertisement

Log in

Impact of chlorophyll bias on the tropical Pacific mean climate in an earth system model

  • Published:
Climate Dynamics Aims and scope Submit manuscript

Abstract

Climate modeling groups nowadays develop earth system models (ESMs) by incorporating biogeochemical processes in their climate models. The ESMs, however, often show substantial bias in simulated marine biogeochemistry which can potentially introduce an undesirable bias in physical ocean fields through biogeophysical interactions. This study examines how and how much the chlorophyll bias in a state-of-the-art ESM affects the mean and seasonal cycle of tropical Pacific sea-surface temperature (SST). The ESM used in the present study shows a sizeable positive bias in the simulated tropical chlorophyll. We found that the correction of the chlorophyll bias can reduce the ESM’s intrinsic cold SST mean bias in the equatorial Pacific. The biologically-induced cold SST bias is strongly affected by seasonally-dependent air–sea coupling strength. In addition, the correction of chlorophyll bias can improve the annual cycle of SST by up to 25%. This result suggests a possible modeling approach in understanding the two-way interactions between physical and chlorophyll biases by biogeophysical effects.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  • Anav A, Friedlingstein P, Kidston M, Bopp L, Ciais P, Cox P, Jones C, Jung M, Myneni R, Zhu Z (2013) Evaluating the land and ocean components of the global carbon cycle in the CMIP5 earth system models. J Clim 26:6801–6843

    Article  Google Scholar 

  • Anderson JL, Balaji V, Broccoli AJ, Cooke WF (2004) The new GFDL global atmosphere and land model AM2-LM2: evaluation with prescribed SST simulations. J Clim 17:4641

    Article  Google Scholar 

  • Anderson W, Gnanadesikan A, Wittenberg A (2009) Regional impacts of ocean color on tropical Pacific variability. Ocean Sci 5:313

    Article  Google Scholar 

  • Aumont O, Bopp L (2006) Globalizing results from ocean in situ iron fertilization studies. Glob Biogeochem Cycles. https://doi.org/10.1029/2005GB002591

    Article  Google Scholar 

  • Azhar MA, Canfield DE, Fennel K, Thamdrup B, Bjerrum CJ (2014) A model-based insight into the coupling of nitrogen and sulfur cycles in a coastal upwelling system. J Geophys Res Biogeosci 119:264–285. https://doi.org/10.1002/2012JG002271

    Article  Google Scholar 

  • Bjerknes J (1968) Atmospheric teleconnections from the equatorial Pacific. Mon Weather Rev 97:163–172

    Article  Google Scholar 

  • Buitenhuis ET, Hashioka T, Quéré CL (2013) Combined constraints on global ocean primary production using observations and models. Glob Biogeochem Cycles 27:847–858. https://doi.org/10.1002/gbc.20074

    Article  Google Scholar 

  • Chavez F, Strutton P, Friederich G, Feely R, Feldman G, Foley D, McPhaden M (1999) Biological and chemical response of the equatorial Pacific Ocean to the 1997–98 El Niño. Science 286:2126–2131

    Article  Google Scholar 

  • Collins WJ, Bellouin N, Doutriaux-Boucher M, Gedney N, Halloran P, Hinton T, Hughes J, Jones CD, Joshi M, Liddicoat S, Martin G, O’Connor F, Rae J, Senior C, Sitch S, Totterdell I, Wiltshire A, Woodward S (2011) Development and evaluation of an earth-system model—HadGEM2. Geosci Model Dev 4:1051–1075. https://doi.org/10.5194/gmd-4-1051-2011

    Article  Google Scholar 

  • Delworth TL, Broccoli AJ, Rosati A, Stouffer RJ, Balaji V, Beesley JA, Cooke WF, Dixon KW, Dunne J, Dunne KA, Durachta JW, Findell KL, Ginoux P, Gnanadesikan A, Gordon CT, Griffies SM, Gudgel R, Harrison MJ, Held IM, Hemler RS, Horowitz LW, Klein SA, Knutson TR, Kushner PJ, Langenhorst AR, Lee H-C, Lin S-J, Lu J, Malyshev SL, Milly PCD, Ramaswamy V, Russell J, Schwarzkopf MD, Shevliakova E, Sirutis JJ, Spelman MJ, Stern WF, Winton M, Wittenberg AT, Wyman B, Zeng F, Zhang R (2006) GFDL’s CM2 global coupled climate models. Part I: formulation and simulation characteristics. J Clim 19:643–674. https://doi.org/10.1175/JCLI3629.1

    Article  Google Scholar 

  • Dufresne J-L, Foujols M-A, Denvil S, Caubel A, Marti O, Aumont O, Balkanski Y, Bekki S, Bellenger H, Benshila R, Bony S, Bopp L, Braconnot P, Brockmann P, Cadule P, Cheruy F, Codron F, Cozic A, Cugnet D, de Noblet N, Duvel J-P, Ethé C, Fairhead L, Fichefet T, Flavoni S, Friedlingstein P, Grandpeix J-Y, Guez L, Guilyardi E, Hauglustaine D, Hourdin F, Idelkadi A, Ghattas J, Joussaume S, Kageyama M, Krinner G, Labetoulle S, Lahellec A, Lefebvre M-P, Lefevre F, Levy C, Li ZX, Lloyd J, Lott F, Madec G, Mancip M, Marchand M, Masson S, Meurdesoif Y, Mignot J, Musat I, Parouty S, Polcher J, Rio C, Schulz M, Swingedouw D, Szopa S, Talandier C, Terray P, Viovy N, Vuichard N (2013) Climate change projections using the IPSL-CM5 earth system model: from CMIP3 to CMIP5. Clim Dyn 40:2123–2165. https://doi.org/10.1007/s00382-012-1636-1

    Article  Google Scholar 

  • Dunne JP, Armstrong RA, Gnanadesikan A, Sarmiento JL (2005) Empirical and mechanistic models for the particle export ratio. Glob Biogeochem Cycles. https://doi.org/10.1029/2004gb002390

    Article  Google Scholar 

  • Dunne JP, Sarmiento JL, Gnanadesikan A (2007) A synthesis of global particle export from the surface ocean and cycling through the ocean interior and on the seafloor. Glob Biogeochem Cycles. https://doi.org/10.1029/2006gb002907

    Article  Google Scholar 

  • Dunne JP, John JG, Adcroft AJ, Griffies SM, Hallberg RW, Shevliakova E, Stouffer RJ, Cooke W, Dunne KA, Harrison MJ, Krasting JP, Malyshev SL, Milly PCD, Phillipps PJ, Sentman LT, Samuels BL, Spelman MJ, Winton M, Wittenberg AT, Zadeh N (2012) GFDL’s ESM2 global coupled climate–carbon earth system models. Part I: physical formulation and baseline simulation characteristics. J Clim 25:6646–6665. https://doi.org/10.1175/jcli-d-11-00560.1

    Article  Google Scholar 

  • Dunne JP, John JG, Shevliakova E, Stouffer RJ, Krasting JP, Malyshev SL, Milly PCD, Sentman LT, Adcroft AJ, Cooke W, Dunne KA, Griffies SM, Hallberg RW, Harrison MJ, Levy H, Wittenberg AT, Phillips PJ, Zadeh N (2013) GFDL’s ESM2 global coupled climate–carbon earth system models. Part II: carbon system formulation and baseline simulation characteristics. J Clim 26:2247–2267. https://doi.org/10.1175/jcli-d-12-00150.1

    Article  Google Scholar 

  • Esaias WE, Abbott MR, Barton I, Brown OB, Campbell JW, Carder KL, Clark DK, Evans RH, Hoge FE, Gordon HR (1998) An overview of MODIS capabilities for ocean science observations. IEEE Trans Geosci Remote Sens 36:1250–1265

    Article  Google Scholar 

  • Fan S-M, Moxim WJ, Levy H (2006) Aeolian input of bioavailable iron to the ocean. Geophys Res Lett. https://doi.org/10.1029/2005GL024852

    Article  Google Scholar 

  • Garcia HE, Locarnini RA, Boyer TP, Antonov JI, Baranova OK, Zweng MM, Reagan J, Johnson DR (2014) World Ocean Atlas 2013, Volume 4: Dissolved Inorganic Nutrients (Phosphate, Nitrate, Silicate). In: Levitus S (ed) NOAA Atlas NESDIS, vol 76. U.S. Government Printing Office, Washington, DC, p 25

    Google Scholar 

  • Geider R, MacIntyre H, Kana T (1997) Dynamic model of phytoplankton growth and acclimation: responses of the balanced growth rate and the chlorophyll a: carbon ratio to light, nutrient-limitation and temperature. Mar Ecol Prog Ser 148:187–200. https://doi.org/10.3354/meps148187

    Article  Google Scholar 

  • Gnanadesikan A, Anderson WG (2009) Ocean water clarity and the ocean general circulation in a coupled climate model. J Phys Oceanogr 39:314–332

    Article  Google Scholar 

  • Green PA, Vörösmarty CJ, Meybeck M, Galloway JN, Peterson BJ, Boyer EW (2004) Pre-industrial and contemporary fluxes of nitrogen through rivers: a global assessment based on typology. Biogeochemistry 68:71–105. https://doi.org/10.1023/b:biog.0000025742.82155.92

    Article  Google Scholar 

  • Griffies SM (2012) Elements of the modular ocean model (MOM). NOAA Geophysical Fluid Dynamics Laboratory, Princeton

    Google Scholar 

  • Griffies SM, Winton M, Anderson WG, Benson R, Delworth TL, Dufour CO, Dunne JP, Goddard P, Morrison AK, Rosati A, Wittenberg AT, Yin J, Zhang R (2015) Impacts on ocean heat from transient mesoscale eddies in a hierarchy of climate models. J Clim 28:952–977. https://doi.org/10.1175/jcli-d-14-00353.1

    Article  Google Scholar 

  • Ham Y-G, Kug J-S (2011) How well do current climate models simulate two types of El Nino? Clim Dyn 39:383–398. https://doi.org/10.1007/s00382-011-1157-3

    Article  Google Scholar 

  • Horowitz LW, Walters S, Mauzerall DL, Emmons LK, Rasch PJ, Granier C, Tie X, Lamarque J-F, Schultz MG, Tyndall GS, Orlando JJ, Brasseur GP (2003) A global simulation of tropospheric ozone and related tracers: description and evaluation of MOZART, version 2. J Geophys Res Atmos. https://doi.org/10.1029/2002JD002853

    Article  Google Scholar 

  • Hourdin F, Mauritsen T, Gettelman A, Golaz J-C, Balaji V, Duan Q, Folini D, Ji D, Klocke D, Qian Y, Rauser F, Rio C, Tomassini L, Watanabe M, Williamson D (2017) The art and science of climate model tuning. Bull Am Meteorol Soc 98:589–602. https://doi.org/10.1175/bams-d-15-00135.1

    Article  Google Scholar 

  • Jochum M, Yeager S, Lindsay K, Moore K, Murtugudde R (2010) Quantification of the feedback between phytoplankton and ENSO in the community climate system model. J Clim 23:2916–2925

    Article  Google Scholar 

  • Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437–471

    Article  Google Scholar 

  • Kim D, Jang Y-S, Kim D-H, Kim Y-H, Watanabe M, Jin F-F, Kug J-S (2011) El Niño–Southern Oscillation sensitivity to cumulus entrainment in a coupled general circulation model. J Geophys Res Atmos. https://doi.org/10.1029/2011jd016526

    Article  Google Scholar 

  • Large W, Yeager S (2004) Diurnal to decadal global forcing for ocean and seaice models: the data sets and climatologies. Technical Report TN-460+STR, NCAR, p 105

  • Laufkötter C, Vogt M, Gruber N, Aita-Noguchi M, Aumont O, Bopp L, Buitenhuis E, Doney SC, Dunne J, Hashioka T, Hauck J, Hirata T, John J, Le Quéré C, Lima ID, Nakano H, Seferian R, Totterdell I, Vichi M, Völker C (2015) Drivers and uncertainties of future global marine primary production in marine ecosystem models. Biogeosciences 12:6955–6984. https://doi.org/10.5194/bg-12-6955-2015

    Article  Google Scholar 

  • Lengaigne M, Menkes C, Aumont O, Gorgues T, Bopp L, André J-M, Madec G (2007) Influence of the oceanic biology on the tropical Pacific climate in a coupled general circulation model. Clim Dyn 28:503–516. https://doi.org/10.1007/s00382-006-0200-2

    Article  Google Scholar 

  • Lin S-J (2004) A “vertically Lagrangian” finite-volume dynamical core for global models. Mon Weather Rev 132:2293–2307

    Article  Google Scholar 

  • Lin P, Liu H, Zhang X (2007) Sensitivity of the upper ocean temperature and circulation in the equatorial Pacific to solar radiation penetration due to phytoplankton. Adv Atmos Sci 24:765–780

    Article  Google Scholar 

  • Lin P, Liu H, Yu Y, Zhang X (2011) Response of sea surface temperature to chlorophyll-a concentration in the tropical Pacific: annual mean, seasonal cycle, and interannual variability. Adv Atmos Sci 28:492–510

    Article  Google Scholar 

  • Löptien U, Eden C, Timmermann A, Dietze H (2009) Effects of biologically induced differential heating in an eddy-permitting coupled ocean-ecosystem model. J Geophys Res. https://doi.org/10.1029/2008jc004936

    Article  Google Scholar 

  • Manizza M, Le Quéré 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:L05603. https://doi.org/10.1029/2004GL020778

    Article  Google Scholar 

  • Marzeion B, Timmermann A, Murtugudde R, Jin F-F (2005) Biophysical feedbacks in the tropical Pacific. J Clim 18:58–70

    Article  Google Scholar 

  • McClain CR (1998) Science quality SeaWiFS data for global biosphere research. Sea Technol 39:10–16

    Google Scholar 

  • Mignot J, Swingedouw D, Deshayes J, Marti O, Talandier C, Séférian R, Lengaigne M, Madec G (2013) On the evolution of the oceanic component of the IPSL climate models from CMIP3 to CMIP5: a mean state comparison. Ocean Model 72:167–184

    Article  Google Scholar 

  • Mitchell TP, Wallace JM (1992) The annual cycle in equatorial convection and sea surface temperature. J Clim 5:1140–1156. https://doi.org/10.1175/1520-0442(1992)005<1140:TACIEC>2.0.CO;2

    Article  Google Scholar 

  • Moore JK, Lindsay K, Doney SC, Long MC, Misumi K (2013) Marine ecosystem dynamics and biogeochemical cycling in the community earth system model [CESM1(BGC)]: comparison of the 1990s with the 2090s under the RCP4.5 and RCP8.5 scenarios. J Clim 26:9291–9312. https://doi.org/10.1175/jcli-d-12-00566.1

    Article  Google Scholar 

  • Morel A (1988) Optical modeling of the upper ocean in relation to its biogenous matter content (case I waters). J Geophys Res 93:749–710

    Article  Google Scholar 

  • Morel A, Antoine D (1994) Heating rate within the upper ocean in relation to its bio-optical state. J Phys Oceanogr 24:1652–1665

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Murtugudde R, Beauchamp J, McClain CR, Lewis M, Busalacchi AJ (2002) Effects of penetrative radiation on the upper tropical ocean circulation. J Clim 15:470–486

    Article  Google Scholar 

  • Nakamoto S, Kumar SP, 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 

  • Oka A, Hasumi H, Obata H, Gamo T, Yamanaka Y (2009) Study on vertical profiles of rare earth elements by using an ocean general circulation model. Glob Biogeochem Cycles. https://doi.org/10.1029/2008GB003353

    Article  Google Scholar 

  • Park J-Y, Kug J-S, Park Y-G (2014a) An exploratory modeling study on bio-physical processes associated with ENSO. Prog Oceanogr 124:28–41. https://doi.org/10.1016/j.pocean.2014.03.013

    Article  Google Scholar 

  • Park J-Y, Kug J-S, Seo H, Bader J (2014b) Impact of bio-physical feedbacks on the tropical climate in coupled and uncoupled GCMs. Clim Dyn 43:1811–1827. https://doi.org/10.1007/s00382-013-2009-0

    Article  Google Scholar 

  • Patara L, Vichi M, Masina S, Fogli PG, Manzini E (2012) Global response to solar radiation absorbed by phytoplankton in a coupled climate model. Clim Dyn 39:1951–1968. https://doi.org/10.1007/s00382-012-1300-9

    Article  Google Scholar 

  • Popova EE, Yool A, Coward AC, Dupont F, Deal C, Elliott S, Hunke E, Jin M, Steele M, Zhang J (2012) What controls primary production in the Arctic Ocean? Results from an intercomparison of five general circulation models with biogeochemistry. J Geophys Res Oceans 117:C00D12. https://doi.org/10.1029/2011JC007112

    Article  Google Scholar 

  • Sallée JB, Shuckburgh E, Bruneau N, Meijers A, Bracegirdle T, Wang Z (2013) Assessment of Southern Ocean mixed-layer depths in CMIP5 models: historical bias and forcing response. J Geophys Res Oceans 118:1845–1862

    Article  Google Scholar 

  • Séférian R, Bopp L, Gehlen M, Orr JC, Ethé C, Cadule P, Aumont O, Salas y Mélia D, Voldoire A, Madec G (2013) Skill assessment of three earth system models with common marine biogeochemistry. Clim Dyn 40:2549–2573. https://doi.org/10.1007/s00382-012-1362-8

    Article  Google Scholar 

  • Séférian R, Gehlen M, Bopp L, Resplandy L, Orr JC, Marti O, Dunne JP, Christian JR, Doney SC, Ilyina T, Lindsay K, Halloran PR, Heinze C, Segschneider J, Tjiputra J, Aumont O, Romanou A (2016) Inconsistent strategies to spin up models in CMIP5: implications for ocean biogeochemical model performance assessment. Geosci Model Dev 9:1827–1851. https://doi.org/10.5194/gmd-9-1827-2016

    Article  Google Scholar 

  • Smith TM, Reynolds RW, Peterson TC, Lawrimore J (2008) Improvements to NOAA’s historical merged land-ocean surface temperature analysis (1880–2006). J Clim 21:2283–2296

    Article  Google Scholar 

  • Stock CA, Dunne JP, John JG (2014) Global-scale carbon and energy flows through the marine planktonic food web: an analysis with a coupled physical–biological model. Progr Oceanogr 120:1–28. https://doi.org/10.1016/j.pocean.2013.07.001

    Article  Google Scholar 

  • Strutton PG, Evans W, Chavez FP (2008) Equatorial Pacific chemical and biological variability, 1997–2003. Glob Biogeochem Cycles. https://doi.org/10.1029/2007GB003045

    Article  Google Scholar 

  • Sweeney C, Gnanadesikan A, Griffies SM, Harrison MJ, Rosati AJ, Samuels BL (2005) Impacts of shortwave penetration depth on large-scale ocean circulation and heat transport. J Phys Oceanogr 35:1103–1119

    Article  Google Scholar 

  • Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design. Bull Am Meteorol Soc 93:485–498

    Article  Google Scholar 

  • Timmermann A, Jin F-F (2002) Phytoplankton influences on tropical climate. Geophys Res Lett 29:19-11–19-14. https://doi.org/10.1029/2002gl015434

    Article  Google Scholar 

  • Vancoppenolle M, Bopp L, Madec G, Dunne J, Ilyina T, Halloran PR, Steiner N (2013) Future Arctic Ocean primary productivity from CMIP5 simulations: uncertain outcome, but consistent mechanisms. Glob Biogeochem Cycles 27:605–619. https://doi.org/10.1002/gbc.20055

    Article  Google Scholar 

  • Vichi M, Pinardi N, Masina S (2007) A generalized model of pelagic biogeochemistry for the global ocean ecosystem. Part I: theory. J Mar Syst 64:89–109

    Article  Google Scholar 

  • Watanabe S, Hajima T, Sudo K, Nagashima T, Takcmura T, Okajima H, Nozawa T, Kawase H, Abe M, Yokohata T (2011) MIROC-ESM 2010: model description and basic results of CMIP 5–20c3m experiments. Geosci Model Dev 4:845–872

    Article  Google Scholar 

  • 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 

  • Winton M (2000) A reformulated three-layer sea ice model. J Atmos Ocean Technol 17:525–531

    Article  Google Scholar 

  • Wittenberg AT, Rosati A, Lau N-C, Ploshay JJ (2006) GFDL’s CM2 global coupled climate models. Part III: tropical Pacific climate and ENSO. J Clim 19:698–722. https://doi.org/10.1175/JCLI3631.1

    Article  Google Scholar 

  • Xie S-P, Philander SGH (1994) A coupled ocean–atmosphere model of relevance to the ITCZ in the eastern Pacific. Tellus A 46:340–350. https://doi.org/10.1034/j.1600-0870.1994.t01-1-00001.x

    Article  Google Scholar 

  • Yeh S-W, Kug J-S, An S-I (2014) Recent progress on two types of El Nino: observations, dynamics, and future changes. Asia-Pac J Atmos Sci 50(1):69–81. https://doi.org/10.1007/s13143-014-0028-3

    Article  Google Scholar 

Download references

Acknowledgements

This study was supported by the Korea Meteorological Administration Research and Development Program under Grant KMIPA 2015-1041 and National Research Foundation of Korea (NRF-2017R1A2B3011511). H.-G. Lim is supported by Hyundai Motor Chung Mong-Koo Foundation.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Jong-Yeon Park or Jong-Seong Kug.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lim, HG., Park, JY. & Kug, JS. Impact of chlorophyll bias on the tropical Pacific mean climate in an earth system model. Clim Dyn 51, 2681–2694 (2018). https://doi.org/10.1007/s00382-017-4036-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00382-017-4036-8

Keywords

Navigation