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CMIP5 Earth System Models with biogeochemistry: a Ross Sea assessment

Published online by Cambridge University Press:  10 May 2016

Graham Rickard  and
Erik Behrens
Graham Rickard*
Affiliation:
National Institute of Water and Atmospheric Research, PO Box 14-901, Kilbirnie, Wellington, New Zealand
Erik Behrens
Affiliation:
National Institute of Water and Atmospheric Research, PO Box 14-901, Kilbirnie, Wellington, New Zealand
*
[email protected]
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Abstract

An assessment is made of the ability of the Coupled Model Intercomparison Project 5 (CMIP5) models to represent the seasonal cycles of biogeochemistry of the Ross Sea over the late twentieth century. In particular, sea surface temperature, sea ice concentration, surface chlorophyll a, nitrate, phosphate and silicate, and the depth of the seasonal thermocline (measuring vertical mixing) are examined to quantify the physical-biogeochemical capabilities of each model, and to provide for ‘ranked’ model ensembles. This permits critical assessment of modelled Ross Sea biogeochemical cycling, including less well observed variables such as iron and vertically integrated primary production. The assessment enables determination of model output confidence limits; these confidence limits are used to examine future model scenario projections for consideration of potential ecosystem changes. The future scenarios examined are the representative concentration pathways rcp4.5 and rcp8.5. Our study suggests that by the end of the twenty-first century under rcp4.5 and/or rcp8.5 that there will be average increases in sea surface temperature, surface chlorophyll a, integrated primary production and iron, average decreases in surface nitrate, phosphate and silicate, and relatively large decreases in the depth of the seasonal thermocline and percentage coverage by sea ice in the Ross Sea.

Keywords

climate predictionsCMIP5 intercomparisonearth system modellingevaluationmarine ecosystemsSouthern Ocean
Type
Biological Sciences
Information
Antarctic Science , Volume 28 , Issue 5 , October 2016 , pp. 327 - 346
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Copyright
© Antarctic Science Ltd 2016 

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References

Adachi, Y., Yukimoto, S., Deushi, M., Obata, A., Nakano, H., Tanaka, T.Y., Hosaka, M., Sakami, T., Yoshimura, H., Hirabara, M., Shindo, E., Tsujino, H., Mizuta, R., Yabu, S., Koshiro, T., Ose, T. & Kitoh, A. 2013. Basic performance of a new earth system model of the Meteorological Research Institute (MRI-ESM1). Papers in Meteorology and Geophysics, 64, 10.2467/mripapers.64.1.Google Scholar
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. Journal of Climate, 26, 6801–6843.CrossRefGoogle Scholar
Antonov, J.I., Seidov, D., Boyer, T.P., Locarnini, R.A., Mishonov, A.V., Garcia, H.E., Baranova, O.K., Zweng, M.M. & Johnson, D.R. 2010. World Ocean Atlas 2009. Volume 2: Salinity. In Levitus, S., ed. NOAA Atlas NESDIS 69. Washington, DC: US Government Printing Office, 184 pp.Google Scholar
Arrigo, K.R. & van Dijken, G.L. 2004. Annual changes in sea-ice, chlorophyll a, and primary production in the Ross Sea, Antarctica. Deep-Sea Research II - Topical Studies in Oceanography, 51, 117–138.Google Scholar
Arrigo, K.R., van Dijken, G.L. & Bushinsky, S. 2008. Primary production in the Southern Ocean, 1997–2006. Journal of Geophysical Research - Oceans, 113, 10.1029/2007JC004551.Google Scholar
Aumont, O. & Bopp, L. 2006. Globalizing results from ocean in situ iron fertilization studies. Global Biogeochemical Cycles, 20, 10.1029/2005GB002591.Google Scholar
Behrenfeld, M.J. & Falkowski, P.G. 1997. Photosynthetic rates derived from satellite-based chlorophyll concentration. Limnology and Oceanography, 42, 1–20.Google Scholar
Bopp, L., Resplandy, L., Orr, J.C., Doney, S.C., Dunne, J.P., Gehlen, M., Halloran, P., Heinze, C., Ilyina, T., Seferian, R., Tjiputra, J. & Vichi, M. 2013. Multiple stressors of ocean ecosystems in the 21st century: projections with CMIP5 models. Biogeosciences, 10, 10.5194/bg-10-6225-2013.CrossRefGoogle Scholar
Bowden, D.A., Schiaparelli, S., Clark, M.R. & Rickard, G.J. 2011. A lost world? Archaic crinoid-dominated assemblages on an Antarctic seamount. Deep-Sea Research II - Topical Studies in Oceanography, 58, 119–127.Google Scholar
Boyd, P.W., Lennartz, S.T., Glover, D.M. & Doney, S.C. 2015. Biological ramifications of climate-change-mediated oceanic multi-stressors. Nature Climate Change, 5, 71–79.Google Scholar
Brandt, A., Griffiths, H., Gutt, J., Linse, K., Schiaparelli, S., Ballerini, T., Danis, B. & Pfannkuche, O. 2014. Challenges of deep-sea biodiversity assessments in the Southern Ocean. Advances in Polar Science, 25, 204–212.Google Scholar
Cabré, A., Marinov, I. & Leung, S. 2014. Consistent global responses of marine ecosystems to future climate change across the IPCC AR5 earth system models. Climate Dynamics, 45, 10.1007/s00382-014-2374-3.Google Scholar
Christian, J.R., Arora, V.K., Boer, G.J., Curry, C.L., Zahariev, K., Denman, K.L., Flato, G.M., Lee, W.G., Merryfield, W.J., Roulet, N.T. & Scinocca, J.F. 2010. The global carbon cycle in the Canadian earth system model (CanESM1): preindustrial control simulation. Journal of Geophysical Research - Biogeosciences, 115, 10.1029/2008JG000920.Google Scholar
Constable, A.J., Melbourne-Thomas, J., Corney, S.P. et al. 2014. Climate change and Southern Ocean ecosystems I: how changes in physical habitats directly affect marine biota. Global Change Biology, 20, 10.1111/gcb.12623.Google Scholar
Cunningham, S.A., Alderson, S.G., King, B.A. & Brandon, M.A. 2003. Transport and variability of the Antarctic Circumpolar Current in Drake Passage. Journal of Geophysical Research - Oceans, 108, 10.1029/2001JC001147.Google Scholar
De Lavergne, C., Palter, J.B., Galbraith, E.D., Bernardello, R. & Marinov, I. 2014. Cessation of deep convection in the open Southern Ocean under anthropogenic climate change. Nature Climate Change, 4, 278–282.Google Scholar
Dunne, J.P., John, J.G., Shevliakova, E., Stouffer, R.J., Krasting, J.P., Malyshev, S.L., Milly, P.C.D., Sentman, L.T., Adcroft, A.J., Cooke, W., Dunne, K.A., Griffies, S.M., Hallberg, R.W., Harrison, M.J., Levy, H., Wittenberg, A.T., Phillips, P.J. & Zadeh, N. 2013. GFDL’s ESM2 global coupled climate-carbon earth system models. Part II: carbon system formulation and baseline simulation characteristics. Journal of Climate, 26, 2247–2267.Google Scholar
Garcia, H.E., Locarnini, R.A., Boyer, T.P., Antonov, J.I., Zweng, M.M., Baranova, O.K. & Johnson, D.R. 2010. World Ocean Atlas 2009. Volume 4: Nutrients (phosphate, nitrate, silicate). In Levitus, S., ed. NOAA Atlas NESDIS 71. Washington, DC: US Government Printing Office, 398 pp.Google Scholar
Gregg, W.W. 2008. Assimilation of SeaWiFS ocean chlorophyll data into a three-dimensional global ocean model. Journal of Marine Systems, 69, 205–225.Google Scholar
Griesel, A., Mazloff, M.R. & Gille, S.T. 2012. Mean dynamic topography in the Southern Ocean: evaluating Antarctic Circumpolar Current transport. Journal of Geophysical Research - Oceans, 117, 10.1029/2011JC007573.CrossRefGoogle Scholar
Heuzé, C., Heywood, K.J., Stevens, D.P. & Ridley, J.K. 2013. Southern Ocean bottom water characteristics in CMIP5 models. Geophysical Research Letters, 40, 10.1002/grl.50287.Google Scholar
Ilyina, T., Six, K.D., Segschneider, J., Maier-Reimer, E., Li, H. & Nez-Riboni, I. 2013. Global ocean biogeochemistry model HAMOCC: model architecture and performance as component of the MPI-earth system model in different CMIP5 experimental realizations. Journal of Advances in Modeling Earth Systems, 5, 287–315.CrossRefGoogle Scholar
Jolliff, J.K., Kindle, J.C., Shulman, I., Penta, B., Friedrichs, M.A.M., Helber, R. & Arnone, R.A. 2009. Summary diagrams for coupled hydrodynamic-ecosystem model skill assessment. Journal of Marine Systems, 76, 64–82.Google Scholar
Locarnini, R.A., Mishonov, A.V., Antonov, J.I., Boyer, T.P., Garcia, H.E., Baranova, O.K., Zweng, M.M. & Johnson, D.R. 2010. World Ocean Atlas 2009. Volume 1: Temperature. In Levitus, S., ed. NOAA Atlas NESDIS 71. Washington, DC: US Government Printing Office, 184 pp.Google Scholar
Martin, T., Park, W. & Latif, M. 2013. Multi-centennial variability controlled by Southern Ocean convection in the Kiel Climate Model. Climate dynamics, 40, 2005–2022.CrossRefGoogle Scholar
Mazloff, M.R., Heimbach, P. & Wunsch, C. 2010. An eddy-permitting Southern Ocean State Estimate. Journal of Physical Oceanography, 40, 10.1175/2009JPO4236.1.Google Scholar
Meijers, A.J.S., Shuckburgh, E., Bruneau, N., Sallee, J.-B., Bracegirdle, T.J. & Wang, Z. 2012. Representation of the Antarctic Circumpolar Current in the CMIP5 climate models and future changes under warming scenarios. Journal of Geophysical Research - Oceans, 117, 10.1029/2012JC008412.Google Scholar
Moore, J.K., Lindsay, K., Doney, S.C., Long, M.C. & 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. Journal of Climate, 26, 10.1175/JCLI-D-12-00566.1.Google Scholar
Moss, R.H., Edmonds, J.A., Hibbard, K.A., Manning, M.R., Rose, S.K., van Vuuren, D.P., Carter, T.R., Emori, S., Kainuma, M., Kram, T., Meehl, G.A., Mitchell, J.F.B., Nakicenovic, N., Riahi, K., Smith, S.J., Stouffer, R.J., Thomson, A.M., Weyant, J.P. & Wilbanks, T.J. 2010. The next generation of scenarios for climate change research and assessment. Nature, 463, 747–756.Google Scholar
Oschlies, A. 2001. Model-derived estimates of new production: new results point towards lower values. Deep-Sea Research II - Topical Studies in Oceanography, 48, 2173–2197.CrossRefGoogle Scholar
Palmer, J.R. & Totterdell, I.J. 2001. Production and export in a global ocean ecosystem model. Deep-Sea Research I - Oceanographic Research Papers, 48, 1169–1198.Google Scholar
Pierce, D.W., Barnett, T.P. & Mikolajewicz, U. 1995. Competing roles of heat and freshwater flux in forcing thermohaline oscillations. Journal of Physical Oceanography, 25, 2046–2064.Google Scholar
Pinkerton, M.H. & Bradford-Grieve, J. 2010. Phytoplankton: trophic modelling of the Ross Sea. Available at: https://www.ccamlr.org/en/system/files/08_Phytoplankton.pdf.Google Scholar
Pinkerton, M.H. & Bradford-Grieve, J.M. 2014. Characterizing foodweb structure to identify potential ecosystem effects of fishing in the Ross Sea, Antarctica. ICES Journal of Marine Science, 71, 1542–1553.Google Scholar
Pinkerton, M.H., Bradford-Grieve, J.M. & Hanchet, S.M. 2010. A balanced model of the food web of the Ross Sea, Antarctica. CCAMLR Science, 17, 1–31.Google Scholar
Rayner, N.A., Parker, D.E., Horton, E.B., Folland, C.K., Alexander, L.V., Rowell, D.P., Kent, E.C. & Kaplan, A. 2003. Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. Journal of Geophysical Research - Atmospheres, 108, 10.1029/2002JD002670CrossRefGoogle Scholar
Séférian, R., Bopp, L., Gehlen, M., Orr, J.C., Ethé, C., Cadule, P., Aumont, O., Melia, D.S.Y., Voldoire, A. & Madec, G. 2013. Skill assessment of three earth system models with common marine biogeochemistry. Climate Dynamics, 40, 2549–2573.Google Scholar
Shu, Q., Song, Z. & Qiao, F. 2015. Assessment of sea ice simulations in the CMIP5 models. Cryosphere, 9, 399–409.Google Scholar
Smith, W.O. Jr., Sedwick, P.N., Arrigo, K.R., Ainley, D.G. & Orsi, A.H. 2012. The Ross Sea in a sea of change. Oceanography, 25, 90–103.Google Scholar
Smith, W.O. Jr., Ainley, D.G., Arrigo, K.R. & Dinniman, M.S. 2014a. The oceanography and ecology of the Ross Sea. Annual Review of Marine Science, 6, 469–487.Google Scholar
Smith, W.O. Jr., Dinniman, M.S., Hofmann, E.E. & Klinck, J.M. 2014b. The effects of changing winds and temperatures on the oceanography of the Ross Sea in the 21st century. Geophysical Research Letters, 41, 10.1002/2014GL059311.Google Scholar
Stössel, A., Notz, D., Haumann, F.A., Haak, H., Jungclaus, J. & Mikolajewicz, U. 2015. Controlling high-latitude Southern Ocean convection in climate models. Ocean Modelling, 86, 58–75.Google Scholar
Tagliabue, A., Mtshali, T., Aumont, O., Bowie, A.R., Klunder, M.B., Roychoudhury, A.N. & Swart, S. 2012. A global compilation of dissolved iron measurements: focus on distributions and processes in the Southern Ocean. Biogeosciences, 9, 10.5194/bg-9-2333-2012.Google Scholar
Turner, J., Bracegirdle, T.J., Phillips, T., Marshall, G.J. & Hosking, J.S. 2013. An initial assessment of Antarctic sea ice extent in the CMIP5 models. Journal of Climate, 26, 1473–1484.Google Scholar
Van Vuuren, D.P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K., Hurtt, G.C., Kram, T., Krey, V., Lamarque, J.F., Masui, T., Meinshausen, M., Nakicenovic, N., Smith, S.J. & Rose, S.K. 2011. The representative concentration pathways: an overview. Climatic change, 109, 5–31.Google Scholar
Vichi, M., Pinardi, N. & Masina, S. 2007. A generalized model of pelagic biogeochemistry for the global ocean ecosystem. Part I: Theory. Journal of Marine Systems, 64, 89–109.CrossRefGoogle Scholar
Wang, C.Z., Zhang, L.P., Lee, S.K., Wu, L.X. & Mechoso, C.R. 2014. A global perspective on CMIP5 climate model biases. Nature Climate Change, 4, 201–205.Google Scholar
Zahariev, K., Christian, J.R. & Denman, K.L. 2008. Preindustrial, historical, and fertilization simulations using a global ocean carbon model with new parameterizations of iron limitation, calcification, and N2 fixation. Progress in Oceanography, 77, 56–82.Google Scholar