Articles | Volume 2, issue 3
https://doi.org/10.5194/wcd-2-739-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wcd-2-739-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Aug 2021
Research article |
| 06 Aug 2021
| 06 Aug 2021
Subtle influence of the Atlantic Meridional Overturning Circulation (AMOC) on seasonal sea surface temperature (SST) hindcast skill in the North Atlantic
Julianna Carvalho-Oliveira
CORRESPONDING AUTHOR
School of Ocean and Earth Science, University of Southampton, Southampton, United Kingdom
Helmholtz-Zentrum Hereon, Geesthacht, Germany
present address: International Max Planck Research School on Earth System Modelling, Max Planck Institute for Meteorology, Hamburg, Germany
Leonard Friedrich Borchert
LOCEAN Laboratory, Institut Pierre Simon Laplace (IPSL), Sorbonne Universités (SU/CNRS/IRD/MNHN), Paris, France
Institute of Oceanography, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Hamburg, Germany
present address: LMD Laboratory, IPSL, École Normale Supérieure, Paris, France
Aurélie Duchez
ESAIP La Salle, Aix-en-Provence, France
National Oceanography Centre, Southampton, United Kingdom
Mikhail Dobrynin
Institute of Oceanography, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Hamburg, Germany
Deutscher Wetterdienst (DWD), Hamburg, Germany
Johanna Baehr
Institute of Oceanography, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Hamburg, Germany
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Cited articles
Alessandri, A., Borrelli, A., Masina, S., Cherchi, A., Gualdi, S., Navarra, A., Di Pietro, P., and Carril, A. F.: The INGV–CMCC seasonal prediction system: improved ocean initial conditions, Mon. Weather Rev., 138, 2930–2952, 2010. a
Arora, K. and Dash, P.: Towards dependence of tropical cyclone intensity on sea surface temperature and its response in a warming world, Climate, 4, 30, https://doi.org/10.3390/cli4020030, 2016. a, b
Arribas, A., Glover, M., Maidens, A., Peterson, K., Gordon, M., MacLachlan, C., Graham, R., Fereday, D., Camp, J., Scaife, A. A., Xavier, P., McLean, P., Colman, A., and Cusack, S.: The GloSea4 ensemble prediction system for seasonal forecasting, Mon. Weather Rev., 139, 1891–1910, 2011. a
Ba, J., Keenlyside, N. S., Latif, M., Park, W., Ding, H., Lohmann, K., Mignot, J., Menary, M., Otterå, O. H., Wouters, B., Salas y Melia, D., Oka, A., Bellucci, A., and Volodin, E.: A multi-model comparison of Atlantic multidecadal variability, Clim. Dynam., 43, 2333, https://doi.org/10.1007/s00382-014-2056-1, 2014. a
Baehr, J. and Piontek, R.: Ensemble initialization of the oceanic component of a coupled model through bred vectors at seasonal-to-interannual timescales, Geosci. Model Dev., 7, 453–461, https://doi.org/10.5194/gmd-7-453-2014, 2014. a
Baehr, J., Fröhlich, K., Botzet, M., Domeisen, V., Kornblueh, L., Notz, D., Piontek, R., Pohlmann, H., Tietsche, S., and Müller, W. A.: The prediction of surface temperature in the new seasonal prediction system based on the MPI-ESM coupled climate model, Clim. Dynam., 44, 2723, https://doi.org/10.1007/s00382-014-2399-7, 2015. a
Bingham, R. J., Hughes, C. W., Roussenov, V., and Williams, R. G.: Meridional
coherence of the North Atlantic meridional overturning circulation, Geophys. Res. Lett., 34, L23606, https://doi.org/10.1029/2007GL031731, 2007. a
Bjerknes, J.: Atlantic air-sea interaction, Adv. Geophys., 10, 1–82, 1964. a
Bryden, H., King, B., McCarthy, G., and McDonagh, E.: Impact of a 30 %
reduction in Atlantic meridional overturning during 2009–2010, Ocean Science, 10, 683–691, 2014. a
Cassou, C., Deser, C., Terray, L., Hurrell, J. W., and Drévillon, M.:
Summer sea surface temperature conditions in the North Atlantic and their
impact upon the atmospheric circulation in early winter, J. Climate, 17, 3349–3363, 2004. a
Cayan, D. R.: Latent and sensible heat flux anomalies over the northern oceans: Driving the sea surface temperature, J. Phys. Oceanogr., 22, 859–881, 1992. a
Collins, M.: Climate predictability on interannual to decadal time scales: the initial value problem, Clim. Dynam., 19, 671–692, 2002. a
Comiso, J. C.: SSM/I sea ice concentrations using the bootstrap algorithm, in: vol. 1380, National Aeronautics and Space Administration, NASA Ref. Publ., Goddard Space Flight Center, 1995. a
Coumou, D. and Rahmstorf, S.: A decade of weather extremes, Nat. Clim. Change, 2, 491–496, 2012. a
Cunningham, S. A., Kanzow, T., Rayner, D., Baringer, M. O., Johns, W. E.,
Marotzke, J., Longworth, H. R., Grant, E. M., Hirschi, J. J.-M., Beal, L. M.,
Meinen, C. S., and Bryden, H. L.: Temporal variability of the Atlantic meridional overturning circulation at 26.5∘ N, Science, 317, 935–938, 2007. a, b, c, d
Cunningham, S. A., Roberts, C. D., Frajka-Williams, E., Johns, W. E., Hobbs,
W., Palmer, M. D., Rayner, D., Smeed, D. A., and McCarthy, G.: Atlantic
Meridional Overturning Circulation slowdown cooled the subtropical ocean,
Geophys. Res. Lett., 40, 6202–6207, 2013. a
Dee, D., Uppala, S., Simmons, A., Berrisford, P., Poli, P., Kobayashi, S.,
Andrae, U., Balmaseda, M., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system, Q. J. Roy. Meteorol. Soc., 137, 553–597, 2011. a, b, c
Dobrynin, M., Müller, W. A., Brune, S., Bunzel, F., Düsterhus, A., Fröhlich, K., Pohlmann, H., and Baehr, J.: MPI-ESM-MR-30: Seasonal hindcasts with MPI-ESM1.0-MR, World Data Center for Climate (WDCC) at DKRZ, [data], available at: http://cera-www.dkrz.de/WDCC/ui/Compact.jsp?acronym=DKRZ_LTA_1075_ds00005, last access: 6 August 2021. a
Duchez, A., Courtois, P., Harris, E., Josey, S. A., Kanzow, T., Marsh, R.,
Smeed, D., and Hirschi, J. J.: Potential for seasonal prediction of Atlantic
sea surface temperatures using the RAPID array at 26 [deg] N, Clim. Dynam., 46, 3351, https://doi.org/10.1007/s00382-015-2918-1, 2016a. a, b, c
Duchez, A., Frajka-Williams, E., Josey, S. A., Evans, D. G., Grist, J. P.,
Marsh, R., McCarthy, G. D., Sinha, B., Berry, D. I., and Hirschi, J. J.:
Drivers of exceptionally cold North Atlantic Ocean temperatures and their
link to the 2015 European heat wave, Environ. Res. Lett., 11, 074004, https://doi.org/10.1088/1748-9326/11/7/074004, 2016b. a
Ferrari, R. and Ferreira, D.: What processes drive the ocean heat transport?,
Ocean Model., 38, 171–186, 2011. a
Frankignoul, C.: Sea surface temperature anomalies, planetary waves, and
air-sea feedback in the middle latitudes, Rev. Geophys., 23, 357–390, 1985. a
García-Serrano, J., Cassou, C., Douville, H., Giannini, A., and
Doblas-Reyes, F. J.: Revisiting the ENSO teleconnection to the tropical North
Atlantic, J. Climate, 30, 6945–6957, 2017. a
Giorgetta, M. A., Jungclaus, J., Reick, C. H., Legutke, S., Bader, J.,
Böttinger, M., Brovkin, V., Crueger, T., Esch, M., Fieg, K., Glushak, K., Gayler, V., Haak, H., Hollweg, H.-D., Ilyina, T., Kinne, S., Kornblueh, L., Matei, D., Mauritsen, T., Mikolajewicz, U., Mueller, W., Notz, D., Pithan, F., Raddatz, T., Rast, S., Redler, R., Roeckner, E., Schmidt, H., Schnur, R., Segschneider, J., Six, K. D., Stockhause, M., Timmreck, C., Wegner, J., Widmann, H., Wieners, K.-H., Claussen, M., Marotzke, J., and Stevens, B.: Climate and carbon cycle changes from 1850 to 2100 in MPI-ESM simulations for the Coupled Model Intercomparison Project phase 5, J. Adv. Model. Earth Syst., 5, 572–597, 2013. a
Guemas, V., Salas-Mélia, D., Kageyama, M., Giordani, H., Voldoire, A., and Sanchez-Gomez, E.: Summer interactions between weather regimes and surface ocean in the North-Atlantic region, Clim. Dynam., 34, 527–546, 2010. a
Hirschi, J. J., Killworth, P. D., and Blundell, J. R.: Subannual, seasonal, and interannual variability of the North Atlantic meridional overturning
circulation, J. Phys. Oceanogr., 37, 1246–1265, 2007. a
Jayne, S. R. and Marotzke, J.: The dynamics of ocean heat transport
variability, Rev. Geophys., 39, 385–411, 2001. a
Johns, W. E., Baringer, M. O., Beal, L. M., Cunningham, S. A., Kanzow, T., Bryden, H. L., Hirschi, J. J.-M., Marotzke, J., Meinen, C. S., Shaw, B., and Curry, R.: Continuous, array-based estimates of Atlantic Ocean heat transport at 26.5∘ N, J. Climate, 24, 2429–2449, 2011. a
Jungclaus, J., Fischer, N., Haak, H., Lohmann, K., Marotzke, J., Matei, D.,
Mikolajewicz, U., Notz, D., and Storch, J.: Characteristics of the ocean
simulations in the Max Planck Institute Ocean Model (MPIOM) the ocean component of the MPI-Earth system model, J. Adv. Model. Earth Syst., 5, 422–446, 2013. a
Knight, J. R., Allan, R. J., Folland, C. K., Vellinga, M., and Mann, M. E.: A
signature of persistent natural thermohaline circulation cycles in observed
climate, Geophys. Res. Lett., 32, L20708, https://doi.org/10.1029/2005GL024233, 2005. a
Lozier, M., Li, F., Bacon, S., Bahr, F., Bower, A., Cunningham, S., De Jong,
M., De Steur, L., Deyoung, B., Fischer, J., Gary, S. F., Greenan, B. J. W., Holliday, N. P., Houk, A., Houpert, L., Inall, M. E., Johns, W. E., Johnson, H. L., Johnson, C., Karstensen, J., Koman, G., Le Bras, I. A., Lin, X., Mackay, N., Marshall, D. P., Mercier, H., Oltmanns, M., Pickart, R. S., Ramsey, A. L., Rayner, D., Straneo, F., Thierry, V., Torres, D. J., Williams, R. G., Wilson, C., Yang, J., Yashayaev, I., and Zhao, J.: A sea change in our view of overturning in the subpolar North Atlantic, Science, 363, 516–521, 2019. a
Lozier, S., Bacon, S., Bower, A. S., Cunningham, S. A., Femke de Jong, M., de Steur, L., deYoung, B., Fischer, J., Gary, S. F., Greenan, B. J. W., Heimbach, P., Holliday, N. P., Houpert, L., Inall, M. E., Johns, W. E., Johnson, H. L., Karstensen, J., Li, F., Lin, X., Mackay, N., Marshall, D. P., Mercier, H., Myers, P. G., Pickart, R. S., Pillar, H. R., Straneo, F., Thierry, V., Weller, R. A., Williams, R. G., Wilson, C., Yang, J., Zhao, J., and Zika, J. D.: Overturning in the Subpolar North Atlantic Program: a new international ocean observing system, B. Am. Meteorol. Soc., 98, 737–752, 2017. a
Muir, L. and Fedorov, A.: How the AMOC affects ocean temperatures on decadal to centennial timescales: the North Atlantic versus an interhemispheric seesaw, Clim. Dynam., 45, 151–160, 2015. a
NCAR: NCAR/ncl [code], Github, https://github.com/NCAR/ncl, last access: 27 July 2021. a
Neddermann, N.-C., Müller, W. A., Dobrynin, M., Düsterhus, A., and
Baehr, J.: Seasonal predictability of European summer climate re-assessed, Clim. Dynam., 53, 3039–3056, https://doi.org/10.1007/s00382-019-04678-4, 2019. a
Oelsmann, J., Borchert, L., Hand, R., Baehr, J., and Jungclaus, J. H.: Linking Ocean Forcing and Atmospheric Interactions to Atlantic Multidecadal Variability in MPI-ESM1.2, Geophys. Res. Lett., 47, e2020GL087259, https://doi.org/10.1029/2020GL087259, 2020. a
Rayner, D., Mack, S., Foden, P., Charcos-Llorens, M., and Campbell, J.:
Development of the RAPID MK III telemetry system – a report on the NOC
tank-testing and shallow and deep-water field trials, National Oceanography Centre Internal Document No. 18, National Oceanography Centre, Southampton, 54 pp., 2016. a
Saunders, M. A. and Lea, A. S.: Large contribution of sea surface warming to
recent increase in Atlantic hurricane activity, Nature, 451, 557, https://doi.org/10.1038/nature06422 , 2008. a
Smeed, D., Josey, S., Beaulieu, C., Johns, W., Moat, B., Frajka-Williams, E.,
Rayner, D., Meinen, C., Baringer, M., Bryden, H., and McCarthy, G.: The North Atlantic Ocean is in a state of reduced overturning, Geophys. Res. Lett., 45, 1527–1533, 2018. a
Smeed, D. A., McCarthy, G. D., Cunningham, S. A., Frajka-Williams, E., Rayner, D., Johns, W. E., Meinen, C. S., Baringer, M. O., Moat, B. I., Duchez, A., and Bryden, H. L.: Observed decline of the Atlantic meridional overturning circulation 2004–2012, Ocean Sci., 10, 29–38, https://doi.org/10.5194/os-10-29-2014, 2014. a
Stevens, B., Giorgetta, M., Esch, M., Mauritsen, T., Crueger, T., Rast, S.,
Salzmann, M., Schmidt, H., Bader, J., Block, K., Brokopf, R., Fast, I., Kinne, S., Kornblueh, L., Lohmann, U., Pincus, R., Reichler, T., and Roeckner, E.: Atmospheric component of the MPI-M Earth System Model: ECHAM6, J. Adv. Model. Earth Syst., 5, 146–172, 2013. a
Stock, C. A., Pegion, K., Vecchi, G. A., Alexander, M. A., Tommasi, D., Bond,
N. A., Fratantoni, P. S., Gudgel, R. G., Kristiansen, T., O'Brien, T. D.,
Xue, Y., and Yang, X.: Seasonal sea surface temperature anomaly prediction for coastal ecosystems, Prog. Oceanogr., 137, 219–236, 2015. a
Stockdale, T. N., Anderson, D. L., Balmaseda, M. A., Doblas-Reyes, F.,
Ferranti, L., Mogensen, K., Palmer, T. N., Molteni, F., and Vitart, F.: ECMWF
seasonal forecast system 3 and its prediction of sea surface temperature,
Clim. Dynam., 37, 455–471, 2011. a
Stocker, T.: Climate change 2013: the physical science basis: Working Group I
contribution to the Fifth assessment report of the Intergovernmental Panel on
Climate Change, Cambridge University Press, Cambridge, 2014. a
Sutton, R. T. and Hodson, D. L.: Atlantic Ocean forcing of North American and
European summer climate, Science, 309, 115–118, 2005. a
Zhang, R.: Anticorrelated multidecadal variations between surface and
subsurface tropical North Atlantic, Geophys. Res. Lett., 34, L12713, https://doi.org/10.1029/2007GL030225, 2007. a
Zhang, R.: Coherent surface-subsurface fingerprint of the Atlantic meridional
overturning circulation, Geophys. Res. Lett., 35, L20705, https://doi.org/10.1029/2008GL035463, 2008. a, b
Zhang, R., Sutton, R., Danabasoglu, G., Kwon, Y.-O., Marsh, R., Yeager, S. G., Amrhein, D. E., and Little, C. M.: A review of the role of the Atlantic
meridional overturning circulation in Atlantic multidecadal variability and
associated climate impacts, Rev. Geophys., 57, 316–375, 2019. a
Short summary
This work questions the influence of the Atlantic Meridional Overturning Circulation, an important component of the climate system, on the variability in North Atlantic sea surface temperature (SST) a season ahead, particularly how this influence affects SST prediction credibility 2–4 months into the future. While we find this relationship is relevant for assessing SST predictions, it strongly depends on the time period and season we analyse and is more subtle than what is found in observations.
This work questions the influence of the Atlantic Meridional Overturning Circulation, an...
