Global ocean surface and subsurface temperature forecast skill over subseasonal to seasonal timescales
Grant A. Smith
A * and Claire M. Spillman A
A
Abstract
Subseasonal to seasonal forecasts of ocean temperatures, including extreme events such as marine heatwaves, have demonstrated utility in informing operational decision-making by marine end users and managing climate risk. Verification is critical for effective communication and uptake of forecast information, together with understanding ocean temperature predictability. The forecast skill of surface and subsurface ocean temperature forecasts from the Bureau of Meteorology’s new ACCESS-S2 seasonal prediction system are assessed here over an extended 38-year hindcast period, from 2 weeks to 6 months into the future. Forecasts of sea surface temperature (SST), heat content down to 300 m (HC300), bottom temperatures on continental shelves, and mixed layer depth are compared to both satellite observations and ocean reanalyses for the globe and the Australian region, using a variety of skill metrics. ACCESS-S2 demonstrates increased SST skill over its predecessor ACCESS-S1 at subseasonal timescales for all variables assessed. Heat content skill is particularly high in the tropics but reduced in subtropical regions especially when compared to persistence. Forecast skill for ocean temperature is higher in the austral summer months than winter at lead times up to 2 months in the Western Pacific region. Mixed layer depth is poorly predicted at all lead times, with only limited areas of skill around Australia and in the south-west Pacific region. Probability of exceedance forecasts for the 90th percentile as an indicator for marine heatwave conditions, shows adequate skill for SST, HC300 and bottom temperatures, especially near shelf regions at shorter lead times. This work will underpin the future development of an operational marine heatwave forecast service, which will provide early warning of these events and thus valuable preparation windows for marine stakeholders.
Keywords: ACCESS-S, heat content, marine heatwave, mixed layer depth, model skill, sea surface temperature, seasonal prediction, validation.
References
Alexander MA, Scott JD, Friedland KD, Mills KE, Nye JA, Pershing AJ, et al. (2018) Projected sea surface temperatures over the 21st century: changes in the mean, variability and extremes for large marine ecosystem regions of Northern Oceans. Elementa: Science of the Anthropocene 6, 9.
| Crossref | Google Scholar |
Amaya DJ, Jacox MG, Alexander MA, Scott JD, Deser C, Capotondi A, Phillips AS (2023) Bottom marine heatwaves along the continental shelves of North America. Nature Communications 14, 1038.
| Crossref | Google Scholar | PubMed |
Babcock RC, Bustamante RH, Fulton EA, Fulton DJ, Haywood MDE, Hobday AJ, Kenyon R, Matear RJ, Laganyi E, Richardson AJ, Vanderklift M (2019) Severe continental-scale impacts of climate change are happening now: extreme climate events impact marine habitat forming communities along 45% of Australia’s coast. Frontiers in Marine Science 6, 411.
| Crossref | Google Scholar |
Banzon V, Smith TM, Chin TM, Liu C, Hankins W (2016) A long-term record of blended satellite and in situ sea-surface temperature for climate monitoring, modeling and environmental studies. Earth System Science Data 8, 165-176.
| Crossref | Google Scholar |
Benthuysen JA, Smith GA, Spillman CM, Steinberg CR (2021) Subseasonal prediction of the 2020 Great Barrier Reef and Coral Sea marine heatwave. Environmental Research Letters 16(12), 124050.
| Crossref | Google Scholar |
Brodie S, Hobday AJ, Smith JA, Spillman CM, Hartog JR, Everett JD, Taylor MD, Gray CA, Suthers IM (2017) Seasonal forecasting of dolphinfish distribution in eastern Australia to aid recreational fishers and managers. Deep-Sea Research – II. Topical Studies in Oceanography 140, 222-229.
| Crossref | Google Scholar |
Calvert D, Nurser G, Bell MJ, Fox-Kemper B (2020) The impact of a parameterisation of submesoscale mixed layer eddies on mixed layer depths in the NEMO ocean model. Ocean Modelling 154, 101678.
| Crossref | Google Scholar |
Caputi N, Kangas M, Chandrapavan A, Hart A, Feng M, Marin M, de Lestang S (2019) Factors affecting the recovery of invertebrate stocks from the 2011 Western Australian extreme marine heatwave. Frontiers in Marine Science 6, 484.
| Crossref | Google Scholar |
de Burgh-Day CO, Spillman CM, Stevens C, Alves O, Rickard G (2019) Predicting seasonal ocean variability around New Zealand using a coupled ocean–atmosphere model. New Zealand Journal of Marine and Freshwater Research 53(2), 201-221.
| Crossref | Google Scholar |
de Burgh-Day CO, Spillman CM, Smith G, Stevens CL (2022) Forecasting extreme marine heat events in key aquaculture regions around New Zealand. Journal of Southern Hemisphere Earth Systems Science 72(1), 58-72.
| Crossref | Google Scholar |
Ershova EA, Hopcroft RR, Kosobokova KN (2015) Inter-annual variability of summer mesozooplankton communities of the western Chukchi Sea: 2004–2012. Polar Biology 38, 1461-1481.
| Crossref | Google Scholar |
Eveson JP, Hobday AJ, Hartog JR, Spillman CM, Rough KM (2015) Seasonal forecasting of tuna habitat in the Great Australian Bight. Fisheries Research 170, 39-49.
| Crossref | Google Scholar |
Garric G, Parent L, Greiner E, Drévillon M, Hamon M, Lellouche JM, et al. (2018) Performance and quality assessment of the global ocean eddy-permitting physical reanalysis GLORYS2V4 operational oceanography serving sustainable marine development. In ‘Proceedings 8th EuroGOOS International Conference’, 3–5 October 2017, Bergen, Norway. (Eds E Buch, V Fernandez, G Nolan, D Eparkhina) p. 516. (EuroGOOS: Brussels, Belgium)
Gwyther DE, Kerry C, Roughan M, Keating SR (2022) Observing system simulation experiments reveal that subsurface temperature observations improve estimates of circulation and heat content in a dynamic western boundary current. Geoscientific Model Development 15(17), 6541-6565.
| Crossref | Google Scholar |
Hallberg R (2013) Using a resolution function to regulate parameterizations of oceanic mesoscale eddy effects. Ocean Modelling 72, 92-103.
| Crossref | Google Scholar |
Hartog JR, Spillman CM, Smith G, Hobday AJ (2023) Forecasts of marine heatwaves for marine industries: reducing risk, building resilience and enhancing management responses. Deep-Sea Research – II. Topical Studies in Oceanography 209, 105276.
| Crossref | Google Scholar |
Hobday AJ, Hartog JR, Spillman CM, Alves O (2011) Seasonal forecasting of tuna habitat for dynamic spatial management. Canadian Journal of Fisheries and Aquatic Sciences 68(5), 898-911.
| Crossref | Google Scholar |
Hobday AJ, Oliver ECJ, Gupta AS, Benthuysen JA, Burrows MT, Donat MG, Holbrook NJ, Moore PJ, Thomsen MS, Wernberg T, Smale DA (2018) Categorizing and naming marine heatwaves. Oceanography 31(2), 162-173.
| Crossref | Google Scholar |
Holbrook NJ, Sen Gupta A, Oliver ECJ, et al. (2020) Keeping pace with marine heatwaves. Nature Reviews Earth & Environment 1, 482-493.
| Crossref | Google Scholar |
Huang B, Liu C, Banzon V, Freeman E, Graham G, Hankins B, Smith T, Zhang H-M (2021) Improvements of the Daily Optimum Interpolation Sea Surface Temperature (DOISST) version 2.1. Journal of Climate 34(8), 2923-2939.
| Crossref | Google Scholar |
Hudson D, Alves O, Hendon HH, Lim EP, Liu G, Luo J-J, MacLachlan C, Marshall AG, Shi L, Wang G, Wedd R, Young G, Zhao M, Zhou X (2017) ACCESS-S1: the new Bureau of Meteorology multi-week to seasonal prediction system. Journal of Southern Hemisphere Earth Systems Science 67(3), 132-159.
| Crossref | Google Scholar |
Hughes TP, Kerry JT, Connolly SR, Álvarez-Romero JG, Eakin CM, Heron SF, Gonzalez MA, Moneghetti J (2021) Emergent properties in the responses of tropical corals to recurrent climate extremes. Current Biology 31(23), 5393-5399.
| Crossref | Google Scholar | PubMed |
Masson-Delmotte V, Zhai P, Pirani A, Connors SL, Péan C, Berger S, Caud N, Chen Y, Goldfarb L, Gomis MI, Huang M, Leitzell K, Lonnoy E, Matthews JBR, Maycock TK, Waterfield T, Yelekçi O, Yu R, Zhou B (Eds) (2021) Summary for policymakers. In ‘Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change’. pp. 3–32. (Cambridge University Press: Cambridge, UK, and New York, NY, USA)
Jacox MG, Alexander MA, Amaya D, Becker E, Bograd SJ, Brodie S, Hazen EL, Pozo Buil M, Tommasi D (2022) Global seasonal forecasts of marine heatwaves. Nature 604, 486-490.
| Crossref | Google Scholar | PubMed |
Jin EK, Kinter JL, Wang B, et al. (2008) Current status of ENSO prediction skill in coupled ocean–atmosphere models. Climate Dynamics 31, 647-664.
| Crossref | Google Scholar |
Johnson GC, Moore DW (1997) The Pacific subsurface countercurrents and an inertial model. Journal of Physical Oceanography 27(11), 2448-2459.
| Crossref | Google Scholar |
Lellouche JM, Le Galloudec O, Drévillon M, Régnier C, Greiner E, Garric G, Ferry N, Desportes C, Testut CE, Bricaud C, et al. (2013) Evaluation of global monitoring and forecasting systems at Mercator Océan. Ocean Science 9, 57-81.
| Crossref | Google Scholar |
Liu G, Eakin CM, Chen M, Kumar A, De La Cour JL, Heron SF, Geiger EF, Skirving WJ, Tirak KV, Strong AE (2018) Predicting heat stress to inform reef management: NOAA Coral Reef Watch’s 4-month coral bleaching outlook. Frontiers in Marine Science 5, 57.
| Crossref | Google Scholar |
MacLachlan C, Arribas A, Peterson KA, et al. (2015) Global seasonal forecast system version 5 (GloSea5): a high-resolution seasonal forecast system. Quarterly Journal of the Royal Meteorological Society 141(698), 1072-1084.
| Crossref | Google Scholar |
Manzanas R (2020) Assessment of model drifts in seasonal forecasting: sensitivity to ensemble size and implications for bias correction. Journal of Advances in Modeling Earth Systems 12, e2019MS001751.
| Crossref | Google Scholar |
Marsh R, de Cuevas BA, Coward AC, Jacquin J, Hirschi JJM, Aksenov Y, et al. (2009) Recent changes in the North Atlantic circulation simulated with eddy-permitting and eddy-resolving ocean models. Ocean Modelling 28, 226-239.
| Crossref | Google Scholar |
Mason I (1982) A model for assessment of weather forecasts. Australian Meteorological Magazine 30, 291-303.
| Google Scholar |
McAdam R, Masina S, Balmaseda M, et al. (2022) Seasonal forecast skill of upper-ocean heat content in coupled high-resolution systems. Climate Dynamics 58, 3335-3350.
| Crossref | Google Scholar |
McAdam R, Masina S, Gualdi S (2023) Seasonal forecasting of subsurface marine heatwaves. Communications Earth & Environment 4, 225.
| Crossref | Google Scholar |
Megann A, Storkey D, Aksenov Y, Alderson S, Calvert D, Graham T, Hyder P, Siddorn J, Sinha B (2014) GO5.0: the joint NERC–Met Office NEMO global ocean model for use in coupled and forced applications. Geoscientific Model Development 7, 1069-1092.
| Crossref | Google Scholar |
Oke PR, Sakov P, Cahill ML, Dunn JR, Fiedler R, Griffin DA, Mansbridge JV, Ridgway KR, Schiller A (2013) Towards a dynamically balanced eddy-resolving ocean reanalysis: BRAN3. Ocean Modelling 67, 52-70.
| Crossref | Google Scholar |
Powers M, Begg Z, Smith G, Miles E (2019) Lessons from the Pacific Ocean portal: building pacific island capacity to interpret, apply, and communicate ocean information. Frontiers in Marine Science 6, 476.
| Crossref | Google Scholar |
Rae JGL, Hewitt HT, Keen AB, Ridley JK, West AE, Harris CM, Hunke EC, Walters DN (2015) Development of the Global Sea Ice 6.0 CICE configuration for the Met Office Global Coupled Model. Geoscientific Model Development 8, 2221-2230.
| Crossref | Google Scholar |
Reynolds RW, Smith TM, Liu C, Chelton DB, Casey KS, Schlax MG (2007) Daily high-resolution-blended analyses for sea surface temperature. Journal of Climate 20(22), 5473-5496.
| Crossref | Google Scholar |
Sakov P (2014) EnKF-C user guide. arXiv: Computer Science 2014(10), 1410.1233, v1.
| Crossref | Google Scholar |
Scales KL, Moore TS II, Sloyan B, Spillman CM, Eveson JP, Patterson TA, Williams AJ, Hobday AJ, Hartog JR (2023) Forecast-ready models to support fisheries’ adaptation to global variability and change. Fisheries Oceanography 32(4), 405-417.
| Crossref | Google Scholar |
Scannell HA, Johnson GC, Thompson L, Lyman JM, Riser SC (2020) Subsurface evolution and persistence of marine heatwaves in the northeast Pacific. Geophysical Research Letters 47(13), e2020GL090548.
| Crossref | Google Scholar |
Smale DA, Wernberg T, Oliver ECJ, Thomsen M, Harvey BP, Straub SC, Burrows MT, Alexander LV, Benthuysen JA, Donat MG, Feng M, Hobday AJ, Holbrook NJ, Perkins-Kirkpatrick SE, Scannell HA, Sen Gupta A, Payne BL, Moore PJ (2019) Marine heatwaves threaten global biodiversity and the provision of ecosystem services. Nature Climate Change 9, 306-312.
| Crossref | Google Scholar |
Smith G, Spillman C (2019) New high-resolution sea surface temperature forecasts for coral reef management on the Great Barrier Reef. Coral Reefs 38, 1039-1056.
| Crossref | Google Scholar |
Smith KE, Burrows MT, Hobday AJ, Sen Gupta A, Moore PJ, Thomsen M, Wernberg T, Smale DA (2021) Socioeconomic impacts of marine heatwaves: global issues and opportunities. Science 374(6566), eabj3593.
| Crossref | Google Scholar | PubMed |
Spillman CM (2011) Operational real-time seasonal forecasts for coral reef management. Journal of Operational Oceanography 4(1), 13-22.
| Crossref | Google Scholar |
Spillman CM, Hobday AJ (2014) Dynamical seasonal ocean forecasts to aid salmon farm management in a climate hotspot. Climate Risk Management 1, 25-38.
| Crossref | Google Scholar |
Spillman CM, Smith GA (2021) A new operational seasonal thermal stress prediction tool for coral reefs around Australia. Frontiers in Marine Science 8, 687833.
| Crossref | Google Scholar |
Spillman CM, Smith GA, Hobday AJ, Hartog JR (2021) Onset and decline rates of marine heatwaves: global trends, seasonal forecasts and marine management. Frontiers in Climate 3, 801217.
| Crossref | Google Scholar |
Storto A, Masina S, Navarra A (2015) Evaluation of the CMCC eddy-permitting global ocean physical reanalysis system (C-GLORS, 1982–2012) and its assimilation components. Quarterly Journal of the Royal Meteorological Society 142(695), 738-758.
| Crossref | Google Scholar |
Tommasi D, Stock CA, Hobday AJ, Methot R, Kaplan IC, Eveson JP, Holsman K, Miller TJ, Gaichas S, Gehlen M, et al. (2017) Managing living marine resources in a dynamic environment: the role of seasonal to decadal climate forecasts. Progress in Oceanography 152, 15-49.
| Crossref | Google Scholar |
Treguier AM, de Boyer Montégut C, Bozec A, Chassignet EP, Fox-Kemper B, Hogg A, Iovino D, Kiss AE, Le Sommer J, Li Y, Lin P, Lique C, Liu H, Serazin G, Sidorenko D, Wang Q, Xu X, Yeager S (2023) The mixed-layer depth in the Ocean Model Intercomparison Project (OMIP): impact of resolving mesoscale eddies. Geoscience Model Development 16, 3849-3872.
| Crossref | Google Scholar |
Vidard A, Anderson DLT, Balmaseda M (2007) Impact of ocean observation systems on ocean analysis and seasonal forecasts. Monthly Weather Review 135(2), 409-429.
| Crossref | Google Scholar |
Walters D, Boutle I, Brooks M, et al. (2017) The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations. Geoscientific Model Development 10, 1487-1520.
| Crossref | Google Scholar |
Wedd R, Alves O, de Burgh-Day C, Down C, Griffiths M, Hendon HH, Hudson D, Li S, Lim E-P, Marshall AG, Shi L, Smith P, Smith G, Spillman CM, Wang G, Wheeler MC, Yan H, Yin Y, Young G, Zhao M, Zhou X (2022) ACCESS-S2: the upgraded Bureau of Meteorology multi-week to seasonal prediction system. Journal of Southern Hemisphere Earth Systems Science 72(3), 218-242.
| Crossref | Google Scholar |
Widlansky MJ, Long X, Balmaseda MA, Spillman CM, Smith G, Zuo H, Yin Y, Alves O, Kumar A (2023) Quantifying the benefits of altimetry assimilation in seasonal forecasts of the upper ocean. Journal of Geophysical Research: Oceans 128(5),.
| Crossref | Google Scholar |
Williams KD, Harris CM, Bodas-Salcedo A, Camp J, Comer RE, Copsey D, Fereday D, et al. (2015) The Met Office Global Coupled model 2.0 (GC2) configuration. Geoscientific Model Development 88, 1509-1524.
| Crossref | Google Scholar |
Zuo H, Balmaseda MA, Tietsche S, Mogensen K, Mayer M (2019) The ECMWF operational ensemble reanalysis–analysis system for ocean and sea ice: a description of the system and assessment. Ocean Science 15(3), 779-808.
| Crossref | Google Scholar |
