Insights into projected changes in marine heatwaves from a high-resolution ocean circulation model.
Journal
Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555
Informations de publication
Date de publication:
28 08 2020
28 08 2020
Historique:
received:
27
11
2019
accepted:
03
08
2020
entrez:
30
8
2020
pubmed:
30
8
2020
medline:
30
8
2020
Statut:
epublish
Résumé
Global climate models project the intensification of marine heatwaves in coming decades due to global warming. However, the spatial resolution of these models is inadequate to resolve mesoscale processes that dominate variability in boundary current regions where societal and economic impacts of marine heatwaves are substantial. Here we compare the historical and projected changes in marine heatwaves in a 0.1° ocean model with 23 coarser-resolution climate models. Western boundary currents are the regions where the models disagree the most with observations and among themselves in simulating marine heatwaves of the past and the future. The lack of eddy-driven variability in the coarse-resolution models results in less intense marine heatwaves over the historical period and greater intensification in the coming decades. Although the projected changes agree well at the global scale, the greater spatial details around western boundary currents provided by the high-resolution model may be valuable for effective adaptation planning.
Identifiants
pubmed: 32859903
doi: 10.1038/s41467-020-18241-x
pii: 10.1038/s41467-020-18241-x
pmc: PMC7455734
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
4352Références
Oliver, E. C. J. et al. Longer and more frequent marine heatwaves over the past century. Nat. Commun. 9, 1324 (2018).
doi: 10.1038/s41467-018-03732-9
Thomsen, M. S. et al. Local extinction of Bull Kelp (Durvillaea spp.) due to a marine heatwave. Front. Mar. Sci. 6, 1–10 (2019).
Feng, M., McPhaden, M. J., Xie, S.-P. & Hafner, J. La Niña forces unprecedented Leeuwin Current warming in 2011. Sci. Rep. 3, 1277 (2013).
doi: 10.1038/srep01277
Nohaïc, M. L. et al. Marine heatwave causes unprecedented regional mass bleaching of thermally resistant corals in northwestern Australia. Sci. Rep. 7, 14999 (2017).
doi: 10.1038/s41598-017-14794-y
Xu, J., Lowe, R. J., Ivey, G. N., Jones, N. L. & Zhang, Z. Contrasting heat budget dynamics during two la niña marine heat wave events along Northwestern Australia. J. Geophys. Res. Oceans 123, 1563–1581 (2018).
doi: 10.1002/2017JC013426
Caputi, N. et al. Management adaptation of invertebrate fisheries to an extreme marine heat wave event at a global warming hot spot. Ecol. Evol. 6, 3583–3593 (2016).
doi: 10.1002/ece3.2137
Jones, T. et al. Massive mortality of a Planktivorous seabird in response to a marine heatwave. Geophys. Res. Lett. 45, 3193–3202 (2018).
doi: 10.1002/2017GL076164
Hobday, A. et al. Categorizing and naming marine heatwaves. Oceanography. 31, 162–173 (2018).
Smale, D. A. et al. Marine heatwaves threaten global biodiversity and the provision of ecosystem services. Nat. Clim. Change. https://doi.org/10.1038/s41558-019-0412-1 (2019).
Frölicher, T. L., Fischer, E. M. & Gruber, N. Marine heatwaves under global warming. Nature 560, 360 (2018).
doi: 10.1038/s41586-018-0383-9
Oliver, E. C. J. et al. Projected marine heatwaves in the 21st century and the potential for ecological impact. Front. Mar. Sci. https://doi.org/10.3389/fmars.2019.00734 (2019).
Hallberg, R. Using a resolution function to regulate parameterizations of oceanic mesoscale eddy effects. Ocean Model. 72, 92–103 (2013).
doi: 10.1016/j.ocemod.2013.08.007
Kiss, A. E. et al. ACCESS-OM2 v1.0: a global ocean–sea ice model at three resolutions. Geosci. Model Dev. 13, 401–442 (2020).
doi: 10.5194/gmd-13-401-2020
Pilo, G. S., Holbrook, N. J., Kiss, A. E. & Hogg, M. A. Sensitivity of marine heatwave metrics to ocean model resolution. Geophys. Res. Lett. 46, 14604–14612 (2019).
doi: 10.1029/2019GL084928
Oke, P. R. et al. Evaluation of a near-global eddy-resolving ocean model. Geosci. Model Dev. 6, 591–615 (2013).
doi: 10.5194/gmd-6-591-2013
Zhang, X. et al. A near-global eddy-resolving OGCM for climate studies. Geosci. Model Dev. Discuss. https://doi.org/10.5194/gmd-2016-17 (2016).
Zhang, X., Church, J. A., Monselesan, D. & McInnes, K. L. Sea level projections for the Australian region in the 21st century. Geophys. Res. Lett. 44, 8481–8491 (2017).
doi: 10.1002/2017GL074176
CSIRO & Bureau of Meteorology. Climate Change in Australia Information for Australia’s Natural Resource Management Regions: Technical Report. (2015).
Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An overview of CMIP5 and the experiment design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012).
doi: 10.1175/BAMS-D-11-00094.1
Matear, R. J., Chamberlain, M. A., Sun, C. & Feng, M. Climate change projection of the Tasman Sea from an Eddy-resolving Ocean Model: climate change projection. J. Geophys. Res. Oceans 118, 2961–2976 (2013).
doi: 10.1002/jgrc.20202
Hobday, A. J. & Lough, J. M. Projected climate change in Australian marine and freshwater environments. Mar. Freshw. Res. 62, 1000–1014 (2011).
doi: 10.1071/MF10302
Kurihara, Y., Sakurai, T. & Kuragano, T. Global daily sea surface temperature analysis using data from satellite microwave radiometer, satellite infrared radiometer and in-situ observations. Weather Bull. 73, 1–18 (2006).
Hogg, A. Mc. C. et al. Recent trends in the Southern Ocean eddy field. J. Geophys. Res. Oceans 120, 257–267 (2015).
doi: 10.1002/2014JC010470
Chambers, D. P. Using kinetic energy measurements from altimetry to detect shifts in the positions of fronts in the Southern Ocean. Ocean Sci. 14, 105–116 (2018).
doi: 10.5194/os-14-105-2018
van Vuuren, D. P. et al. The representative concentration pathways: an overview. Clim. Change 109, 5–31 (2011).
doi: 10.1007/s10584-011-0148-z
Harford, W. J., Karnauskas, M., Walter, J. F. & Liu, H. Non-parametric modeling reveals environmental effects on bluefin tuna recruitment in Atlantic, Pacific, and Southern Oceans. Fish. Oceanogr. 26, 396–412 (2017).
doi: 10.1111/fog.12205
Green, T. J. et al. Simulated marine heat wave alters abundance and structure of vibrio populations associated with the pacific oyster resulting in a mass mortality event. Microb. Ecol. 77, 736–747 (2019).
doi: 10.1007/s00248-018-1242-9
Holbrook, N. J. et al. A global assessment of marine heatwaves and their drivers. Nat. Commun. 10, 2624 (2019).
doi: 10.1038/s41467-019-10206-z
Oliver, E. C. J. Mean warming not variability drives marine heatwave trends. Clim. Dyn. https://doi.org/10.1007/s00382-019-04707-2 (2019).
Kataoka, T., Masson, S., Izumo, T., Tozuka, T. & Yamagata, T. Can Ningaloo Niño/Niña Develop Without El Niño–Southern Oscillation? Geophys. Res. Lett. 45, 7040–7048 (2018).
doi: 10.1029/2018GL078188
Kataoka, T., Tozuka, T., Behera, S. & Yamagata, T. On the Ningaloo Niño/Niña. Clim. Dyn. 43, 1463–1482 (2014).
doi: 10.1007/s00382-013-1961-z
Yeh, S.-W. et al. El Niño in a changing climate. Nature 461, 511–514 (2009).
doi: 10.1038/nature08316
Cai, W. et al. ENSO and greenhouse warming. Nat. Clim. Change 5, 849–859 (2015).
doi: 10.1038/nclimate2743
Knutson, T. R. et al. Tropical cyclones and climate change. Nat. Geosci. 3, 157–163 (2010).
doi: 10.1038/ngeo779
Jacox, M. G. Marine heatwaves in a changing climate. Nature 571, 485–487 (2019).
doi: 10.1038/d41586-019-02196-1
Darmaraki, S. et al. Future evolution of marine heatwaves in the Mediterranean Sea. Clim. Dyn. https://doi.org/10.1007/s00382-019-04661-z . (2019).
Griffies, S. M. et al. Impacts on ocean heat from transient mesoscale eddies in a hierarchy of climate models. J. Clim. 28, 952–977 (2015).
doi: 10.1175/JCLI-D-14-00353.1
Roberts, M. J. et al. The benefits of global high resolution for climate simulation: process understanding and the enabling of stakeholder decisions at the regional scale. Bull. Am. Meteorol. Soc. 99, 2341–2359 (2018).
doi: 10.1175/BAMS-D-15-00320.1
Griffies, S. M. GFDL ocean group. Elements of MOM4P1. 444 (2010).
Ridgway, K. R., Dunn, J. R. & Wilkin, J. L. Ocean interpolation by four-dimensional weighted least squares—application to the waters around Australasia. J. Atmos. Ocean. Technol. 19, 1357–1375 (2002).
doi: 10.1175/1520-0426(2002)019<1357:OIBFDW>2.0.CO;2
Kobayashi, S. et al. The JRA-55 reanalysis: general specifications and basic characteristics. J. Meteorol. Soc. Jpn. Ser. II 93, 5–48 (2015).
doi: 10.2151/jmsj.2015-001
Schurer, A. P., Mann, M. E., Hawkins, E., Tett, S. F. B. & Hegerl, G. C. Importance of the pre-industrial baseline for likelihood of exceeding Paris goals. Nat. Clim. Change 7, 563–567 (2017).
doi: 10.1038/nclimate3345
Hobday, A. J. et al. A hierarchical approach to defining marine heatwaves. Prog. Oceanogr. 141, 227–238 (2016).
doi: 10.1016/j.pocean.2015.12.014
Wernberg, T. et al. An extreme climatic event alters marine ecosystem structure in a global biodiversity hotspot. Nat. Clim. Change 3, 78–82 (2013).
doi: 10.1038/nclimate1627
Fiedler, E. K. et al. Intercomparison of long-term sea surface temperature analyses using the GHRSST Multi-Product Ensemble (GMPE) system. Remote Sens. Environ. 222, 18–33 (2019).
doi: 10.1016/j.rse.2018.12.015
Kawai, Y. & Wada, A. Diurnal sea surface temperature variation and its impact on the atmosphere and ocean: a review. J. Oceanogr. 63, 721–744 (2007).
doi: 10.1007/s10872-007-0063-0
Reynolds, R. W. et al. Daily high-resolution-blended analyses for sea surface temperature. J. Clim. 20, 5473–5496 (2007).
doi: 10.1175/2007JCLI1824.1