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Cited by 2,379Oceanographic and Atmospheric ProcessesMarine and fisheries researchCoral and Marine Ecosystems Studies

A hierarchical approach to defining marine heatwaves

Open access
Hobday, Alistair J., Alexander, Lisa V., Perkins, Sarah E., Smale, Dan A., Straub, Sandra C., Oliver, Eric C.J., Benthuysen, Jessica A., Burrows, Michael T. +7 more·2016·Progress in Oceanography
DOI 10.1016/j.pocean.2015.12.014
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AI snapshot

Written from the paper’s full text.

TL;DR

The paper proposes a hierarchical framework for defining marine heatwaves (MHWs), with a general qualitative definition and a specific quantitative definition: anomalously warm events lasting ≥5 days above the 90th percentile of a 30-year baseline. It illustrates the metrics on three 21st-century MHWs and recommends consistent metrics for global comparisons.

Key findings

  • A MHW is generally defined as a prolonged discrete anomalously warm water event described by duration, intensity, rate of evolution, and spatial extent; specifically, it lasts five or more days with temperatures warmer than the 90th percentile based on a 30-year historical baseline, with gaps of ≤2 days treated as continuous.
  • The hierarchical metrics are primary (duration, maximum/mean/cumulative intensity), secondary (rate of onset/decline, spatial extent), and tertiary (preconditioning factors); the definition was implemented in a free Python package, marineHeatWaves.
  • For Western Australia, 59 MHW events were identified between 1982 and 2014; the 2011 Ningaloo Niño was the largest by maximum intensity (6.50°C) and mean intensity (3.21°C), lasting 60 days with cumulative intensity of 192°C days, while the longest event lasted 95 days in 1999.
  • For the northern Mediterranean, 70 events were identified; the 2003 MHW was largest by mean intensity (4.06°C), lasting 30 days with maximum intensity 5.02°C. For the northwest Atlantic, 67 events were identified; the longest lasted 187 days (31 July 2012–2 February 2013) with maximum intensity 4.00°C, mean intensity 2.37°C, and cumulative intensity 443°C days.

Methods

  • The paper synthesizes lessons from atmospheric heatwave definitions, especially Perkins and Alexander (2013), to propose qualitative and quantitative MHW definitions; a sensitivity analysis for the five-day minimum duration used high-resolution (1/4°), global, daily SSTs from AVHRR satellite data (NOAA OI SST V2).
  • Three case-study regions—Western Australia 2011, northern Mediterranean 2003, and northwest Atlantic 2012—were analyzed using 1/4° daily NOAA OI SST time series, with metrics calculated via the marineHeatWaves Python code.
  • A dataset comparison for the 2011 Ningaloo Niño used monthly and weekly Reynolds SST, daily satellite NOAA OISST, and an hourly in situ logger from Jurien Bay; Table 3 qualitatively scores different data sources for their ability to provide primary, secondary, and tertiary MHW metrics.

Limitations

  • The paper states that the qualitative definition may have limited application in intertidal zones, where ecological responses to high sea temperatures are mediated by air temperature, precipitation, and atmospheric conditions.
  • The paper states that limitations in baseline length, quality, consistency, resolution, and availability may restrict the method; remotely sensed data begin in the 1980s–1990s, so the climatological period may need to be shorter, and different datasets can provide substantially different MHW information despite using the same metrics.
  • The paper states that certain indices may not be derivable from some data sources—for example, in situ data cannot provide spatial extent, and paleo proxies and traditional ecological data can at best provide quantitative information on long-lived MHWs. Evident from the text: the three case studies are illustrative rather than a global validation, and the tertiary preconditioning metric is left as a placeholder without formal definition.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1016/j.pocean.2015.12.014

Cites

78 of 78 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

15 of 27 cited sources checked · 5 supported · 0 flagged · accuracy not yet measured

  • Premisecitation
    § A hierarchical approach to defining marine heatwaves · p. 2

    A consistent definition of marine heatwaves does not exist.

    “yet a consistent definition of MHWs does not exist.”
    • Also stated in: § 1.1. Defining extreme temperatures in marine systems · p. 5 · plain
      “Beyond coral reef research there is limited consistency regarding how MHW metrics are applied or how useful they are in ecological applications.”
    Quote in the paperSubstantial claim1 of 3 sources checked
    • cites Sorte et al. (2010) source
    • cites Selig et al. (2010) source
    • cites Marba et al. (2015) source

      In “Warming Rates in the Mediterranean: Observations and Model Hindcast” (page unavailable), the paper specifies how it characterizes heat waves, but does not discuss whether a consistent definition of marine heatwaves exists across studies. Searches for a consistent definition and for differing standards found no passage addressing that claim. (LLM, conf=0.74)

      Experimental — accuracy not yet measured
  • Premisecitation
    § 2.2. Datasets matter in defining heatwaves · p. 13

    Paleo proxies and traditional ecological data can, at best, only provide quantitative information on long-lived MHWs.

    “While useful for other purposes, paleo proxies and traditional ecological data can, at best, only provide quantitative information on long-lived MHWs (e.g. Zinke et al. 2014).”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Zinke et al. 2014 source

      The Results (‘Coral paleoclimatic records’) and Methods (‘Proxy data treatment’; page unavailable) describe coral proxies used to quantify annually resolved sea-surface-temperature variability, including warm anomalies. The paper does not establish that paleo proxies can quantify only long-lived marine heatwaves, and it does not assess the limits of traditional ecological data. (LLM, conf=0.83)

      Experimental — accuracy not yet measured
  • Interpretationcitation
    § 2.1. Measurement of marine heatwaves · p. 11

    The 56-day event in 2012 is the 2012 northwest Atlantic event discussed in the literature.

    “This latter event is the 2012 northwest Atlantic event discussed in the literature (Mills et al. 2013; Chen et al. 2014).”
    Quote in the paperNot a substantial claim2 of 2 sources checked
    • cites Mills et al. 2013 source
    • cites Chen et al. 2014 source
  • Premisecitation
    § 2.2. Datasets matter in defining heatwaves · p. 12

    Datasets with high spatial and temporal resolution have more variability than those aggregating across larger areas or based on smoother longer time means.

    “Datasets with a high spatial and temporal resolution have more variability than those aggregating across larger areas or based on (smoother) longer time means (Smale and Wernberg 2009).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Smale and Wernberg 2009 source

      The ‘Satellite-derived vs. logger-derived data’ section says satellite SST data miss small-scale temperature fluctuations across time and space, supporting the point that coarse data can conceal variation. But it also reports greater spatial variability in the satellite SST measurements than in the logger measurements. The paper therefore does not support the claim as a general rule that higher-resolution datasets have more variability. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
  • Interpretationcitation
    § 2. A hierarchical definition of marine heatwaves · p. 8

    A marine heatwave in a cold season could lead to suppressed or failed recruitment of habitat-forming seaweeds.

    “In this case, a MHW in a cold season could lead to suppressed or failed recruitment of habitat-forming seaweeds.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Andrews et al. (2014) source

      The Abstract reports that this habitat-forming seaweed reproduces in winter and that elevated temperatures delay settlement and increase germling mortality. The ‘Latitudinal distribution of recruits’ section suggests that a summer heatwave may have contributed to recruitment failure in the following winter. The paper does not assess a heatwave occurring during the cold season itself, so that specific scenario is an extrapolation. (LLM, conf=0.82)

      Experimental — accuracy not yet measured
  • Classified as probably not a substantial claim. 60
  • May combine two claims. 26

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation
    § A hierarchical approach to defining marine heatwaves · p. 2

    A variety of impacts have been associated with marine heatwaves, including shifts in species ranges, local extinctions and economic impacts on seafood industries through declines in important fishery species and impacts on aquaculture.

    “A variety of impacts 4 have been associated with these anomalous events, including shifts in species ranges, local 5 extinctions and economic impacts on seafood industries through declines in important fishery 6 species and impacts on aquaculture.”
    Quote in the paperNot a substantial claim1 of 3 sources checked
    • cites Garrabou et al. 2009 source
    • cites Wernberg et al. 2013 source
    • cites Mills et al. 2013 source

      The “Ecological and Economic Impacts” section describes species range shifts, lobster mortality and substantial economic effects on fisheries. It does not document local extinctions or aquaculture impacts, and the economic harm it describes is not specifically attributed to declines in fishery species; lobster prices fell amid an influx of catch. No page number is available in our copy. (LLM, conf=0.86)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Findingcitation
    § 2.2. Datasets matter in defining heatwaves · p. 12

    The in situ logger data reveal higher temporal SST variability but a lower peak intensity than the daily satellite dataset, consistent with previous analysis in this region.

    “The high temporal resolution provided by the in situ logger data reveals higher temporal SST variability, but a lower peak intensity than the daily satellite dataset, consistent with previous analysis of sub-surface in situ and daily satellite data in this region (Smale and Wernberg 2009).”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites Smale and Wernberg 2009 source

      The ‘Satellite-derived vs. logger-derived data’ section (page not available) says in situ recorders capture short-term temperature fluctuations that satellite data cannot resolve. It also reports that daily AVHRR temperatures were generally higher than logger temperatures, but gives this comparison for annual and seasonal means, not peak intensity. The claimed lower logger peak intensity is therefore not established by the cited analysis. (LLM, conf=0.82)

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation
    § 1.2. Parallels with atmospheric heatwave definitions · p. 5

    The general definition of atmospheric heatwaves is a prolonged period where temperatures are substantially hotter than normal.

    “The general definition of atmospheric heatwaves is a prolonged period where temperatures are substantially hotter than normal (Perkins and Alexander 2013).”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Perkins and Alexander 2013 source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation
    § 2. A hierarchical definition of marine heatwaves · p. 7

    The atmosphere, land surface and ocean all may have important driving roles in how and where prolonged heat events play out.

    “From examples such as the 2003 MHW in the northern Mediterranean Sea (Garrabou et al. 2009), the 2011 Ningaloo Niño in Western Australia (Feng et al. 2013) and the 2012 MHW in the northwest Atlantic (Mills et al. 2013; Chen et al. 2014), it is clear that the atmosphere, land surface and ocean all may have important driving roles in how and where these prolonged heat events play out.”
    Quote in the paperNot a substantial claim2 of 3 sources checked
    • cites Garrabou et al. 2009 source
    • cites Feng et al. 2013 source
    • cites Mills et al. 2013 source

      The Northwest Atlantic temperature discussion says atmospheric blocking brought warm air into the region and contributed to the 2012 ocean heat wave; it also refers to atmosphere–ocean interactions. It does not identify the land surface as a driver of that event: Greenland melting is described as another likely consequence of the atmospheric conditions. No page number is available in our copy. (LLM, conf=0.84)

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation
    § 1.2. Parallels with atmospheric heatwave definitions · p. 6

    Perkins and Alexander (2013) define an atmospheric heatwave when at least three consecutive days exceed a calendar day threshold defined as the 90th percentile value for temperature.

    “Based on these criteria, Perkins and Alexander (2013) define an atmospheric 138 heatwave when at least three consecutive days exceed a calendar day threshold defined as the 139 90 th percentile value for temperature.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Perkins and Alexander (2013) source

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Premisecitation
    § 3. Monitoring and forecasting marine heatwaves · p. 15

    Protecting high diversity coral reef areas with a high probability of catastrophic disturbances in the near future, including MHWs, may be less favourable in comparison with protecting an area with less biodiversity but a low probability for disturbance.

    “protecting high diversity coral reef areas with a high probability of catastrophic disturbances in the near future, including MHWs, may be less favourable in comparison with protecting an area with less biodiversity but a low probability for disturbance (Game et al. 2008).”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites Game et al. 2008 source

      The Discussion (page not available) says that, all else equal, protecting reefs at lower risk of catastrophic bleaching is preferable, and that improving persistence can require trade-offs with biodiversity coverage. It does not establish the specific comparison between a high-diversity, high-risk reef and a less-diverse, low-risk reef. The study models bleaching risk through 2100 but does not explicitly assess marine heatwaves as a broader category of disturbance. (LLM, conf=0.84)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Premisecitation
    § 4. Recommendations and conclusions · p. 17

    A recent atmospherically driven marine heatwave in the northeast Pacific during the boreal winters of 2013-2015 had significant downstream effects on North American weather, and also disrupted northeast Pacific fisheries and coastal ecosystems.

    “A recent atmospherically driven marine heatwave in the northeast Pacific during the boreal winters of 2013-2015 had significant downstream effects on North American weather, and also disrupted northeast Pacific fisheries and coastal ecosystems (Bond et al. 2015; Hartman, 2015; Whitney 2015).”
    Quote in the paperNot a substantial claim2 of 3 sources checked
    • cites Bond et al. 2015 source

      Split into 2 atoms — 1 confirmed, 1 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

      Experimental — accuracy not yet measured
    • cites Hartman, 2015

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

    • cites Whitney 2015 source

      Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data
    § 2.1. Measurement of marine heatwaves · p. 11

    The 21-day event had a lower maximum intensity (imax=4.24°C) than a 56-day event in 2012 (10 April - 4 June) where the imax was 4.89°C.

    “but a lower maximum intensity (imax=4.24°C) than a 56 day event in 2012 (10 April - 4 June) where the imax was 4.89°C”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § 2.1. Measurement of marine heatwaves · p. 11

    The most intense Mediterranean event was in 2008 (maximum intensity = 5.05°C) lasting only 9 days (26 June to 4 July) with a mean intensity of 3.87°C.

    “The most intense event was in 2008 (imax = 5.05) lasting only 9 days (26 June to 4 July) with an imean of 3.87°C.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § 2.1. Measurement of marine heatwaves · p. 11

    The longest Mediterranean event was still ongoing at the time of analysis, with 110 days (13 September - 31 December 2014), with a lower maximum intensity (3.31°C) and mean intensity (2.51°C), but the highest cumulative intensity (276°C days).

    “The longest event was still ongoing at the time of analysis, with 110 days (13 September - 31 December 2014 - the end of the dataset), with a lower imax (3.31°C) and imean (2.51°C), but the highest icum (276°C days).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data
    § 2.1. Measurement of marine heatwaves · p. 11

    The 56-day and 187-day events in 2012 are considered distinct because the temperature dropped below the threshold for at least 3 days (5 days) between them.

    “Note that the 56 and 187 day events in 2012 are considered distinct, as the temperature dropped below the threshold for at least 3 days (5 days) between the two events.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingreasoning
    § 2.2. Datasets matter in defining heatwaves · p. 12

    The variability in SST magnitude clearly differs between the four datasets and would result in different metrics of heatwave intensity.

    “However, the variability in SST magnitude clearly differs between the four datasets, and would result in different metrics of heatwave intensity.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data
    § 2.1. Measurement of marine heatwaves · p. 10

    The longest marine heatwave off Western Australia lasted for 95 days (13 May 1999 - 15 August 1999) with a maximum intensity of 3.60°C, mean intensity of 2.50°C and cumulative intensity of 237°C days above the climatological mean.

    “with the longest MHW lasting for 95 days (13 May 1999 - 15 August 1999) with a maximum (imax), mean (imean) and cumulative intensity (icum) of 3.60°C, 2.50 °C and 237°C days above the climatological mean, respectively.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data
    § 2.1. Measurement of marine heatwaves · p. 11

    The 56-day event had imean 2.59°C and icum 145°C days.

    “The corresponding imean and icum for this 56 day event was 2.59°C and 145 °C days, respectively.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data
    § 2.1. Measurement of marine heatwaves · p. 11

    The 2003 marine heatwave in the Mediterranean was the largest event based on mean intensity (4.06°C) and lasted 30 days (2 June - 1 July) with a maximum intensity of 5.02°C.

    “The 2003 MHW was the largest event based on the imean (4.06°C; not shown in Figure 3b) and lasted 30 days by our definition (2 June - 1 July) with an imax of 5.02°C.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingnone given
    § 2.2. Datasets matter in defining heatwaves · p. 12

    The daily satellite data have finer spatial (0.25° grid) and temporal (daily) resolution than the reconstructed SST products.

    “This is followed by the daily satellite data, which are finer in spatial (0.25° degree grid) and temporal (daily) resolution.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Findingown data
    § 4. Recommendations and conclusions · p. 16

    Sensitivity testing on daily data suggests that a 30-day moving window is appropriate for smoothing climatology from daily data.

    “Sensitivity testing on daily data suggests that a 30-day 'moving window' is appropriate for smoothing climatology from daily data.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data
    § Figure Legends · p. 32

    The Western Australia and northwest Atlantic marine heat waves are the largest by maximum intensity.

    “The WA and northwest Atlantic MHWs are the largest by maximum intensity, such that the red and yellow bars are the same.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingnone given
    § References · p. 30

    In situ temperature loggers provide high resolution primary and secondary marine heat wave metrics but only low spatial area resolution unless multiple loggers are used.

    “In situ temperatures (e.g. loggers) | 4 | 4 | 4 | 4 | 1 (if multiple loggers), else N/A | 2 | High | High | Low | Low/ Med”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Findingown data
    § Figure Legends · p. 32

    The northwest Atlantic marine heat wave event is not the largest according to duration or cumulative intensity.

    “The northwest Atlantic event is not the largest according to duration or cumulative intensity, but the red bar obscures the yellow bar since they are so close in time.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

    Interpretationreasoning
    § A hierarchical approach to defining marine heatwaves · p. 2

    A clear definition will facilitate retrospective comparisons between marine heatwaves, enabling the synthesis and a mechanistic understanding of the role of marine heatwaves in marine ecosystems.

    “A clear 8 definition will facilitate retrospective comparisons between MHWs, enabling the synthesis 9 and a mechanistic understanding of the role of MHWs in marine ecosystems.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation
    § A hierarchical approach to defining marine heatwaves · p. 2

    Marine heatwaves have been observed around the world and are expected to increase in intensity and frequency under anthropogenic climate change.

    “Marine heatwaves (MHWs) have been observed around the world and are expected to 3 increase in intensity and frequency under anthropogenic climate change.”
    • Also stated in: § 1. Introduction - Marine heatwaves and their ecological impact · p. 4 · hedged
      “which may increase in frequency and magnitude as a result of anthropogenic climate change (IPCC 2012)”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites IPCC 2012

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

    Premisenone given
    § 3. Monitoring and forecasting marine heatwaves · p. 14

    Extreme temperature events can affect species distributions and alter ecosystem structure.

    “extreme temperature events can affect species distributions and alter ecosystem structure”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

    Interpretationnone given
    § 3. Monitoring and forecasting marine heatwaves · p. 14

    Monitoring heatwaves can lead to a better understanding of their development, characteristics and impacts.

    “Furthermore, monitoring heatwaves can lead to a better understanding of their development, characteristics and impacts.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationnone given
    § 2. A hierarchical definition of marine heatwaves · p. 7

    Under the qualitative definition, a marine heatwave can be caused by a combination of atmospheric forcing and oceanic conditions.

    “Under this definition, a MHW can be caused by a combination of atmospheric forcing (e.g. heating) and oceanic conditions (e.g. faster advection or advection of unusually warm water).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationnone given
    § 2.2. Datasets matter in defining heatwaves · p. 13

    Many of the MHW metrics can be calculated from gridded products, such as SST datasets, reconstructed observational data, and model/reanalysis data.

    “Many of the MHW metrics can be calculated from gridded products, such as SST datasets, reconstructed observational data, and model/reanalysis data.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationnone given
    § 2. A hierarchical definition of marine heatwaves · p. 7

    The qualitative definition of a marine heatwave applies to ocean regions, including subsurface waters, estuarine, or enclosed seas such as the Mediterranean Sea or Baltic Sea.

    “The qualitative definition of a MHW applies to ocean regions (including subsurface waters, estuarine, or enclosed seas such as the Mediterranean Sea or Baltic Sea)”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationreasoning
    § 3. Monitoring and forecasting marine heatwaves · p. 15

    These metrics can be useful at different time scales in forecasting for the following days to weeks and for long-term projections.

    “These metrics can be useful at different time scales in forecasting for the following days to weeks and for long-term projections.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation
    § 3. Monitoring and forecasting marine heatwaves · p. 15

    Australia's Bureau of Meteorology OceanMAPS system predicts daily SSTs with a one-week lead time.

    “Australia's Bureau of Meteorology OceanMAPS system predicts daily SSTs with a one-week lead time (www.csiro.au/bluelink/)”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites www.csiro.au/bluelink/

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.

    Interpretationnone given
    § 3. Monitoring and forecasting marine heatwaves · p. 14

    Deployment of submerged data loggers close to the coastline and the use of oceanographic arrays for the open sea could provide information about heat penetration depths and durations.

    “deployment of submerged data loggers close to the coastline and the use of oceanographic arrays for the open sea could provide information about heat penetration depths and durations”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning
    § 2.2. Datasets matter in defining heatwaves · p. 12

    Differences in heatwave information between datasets are generally due to the resolution of the data, but can also relate to other issues of quality, consistency and instrumentation.

    “This is generally due to the resolution of the data, but can also relate to other issues of quality, consistency and instrumentation.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Interpretationreasoning
    § 2.2. Datasets matter in defining heatwaves · p. 13

    Lower spatial resolution data results in reduced intensity because neighbouring non-heatwave areas are included in mean values.

    “Lower spatial resolution data results in reduced intensity because neighbouring non-heatwave areas are included in mean values.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation
    § 3. Monitoring and forecasting marine heatwaves · p. 14

    Coral Reef Watch is based on near real-time monitoring during the warmest months of the year and is used to identify areas where conditions may be approaching those conducive to coral bleaching.

    “For example, Coral Reef Watch is based on near real-time monitoring during the warmest months of the year and is used to identify areas where conditions may be approaching those conducive to coral inform management actions (to reduce additional stressors for example) which can be implemented quickly (e.g. Beeden et al. 2012).”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Beeden et al. 2012 source

  • Classified as probably not a substantial claim.

    Interpretationreasoning
    § 2. A hierarchical definition of marine heatwaves · p. 7

    A marine heatwave is not just limited to the warmer months, since for some biological applications the consideration of heatwaves in colder months is essential.

    “This also means that a MHW is not just limited to the warmer months, since for some biological applications the consideration of heatwaves in colder months is essential.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Interpretationreasoning
    § 3. Monitoring and forecasting marine heatwaves · p. 15

    The metrics can be used to estimate the prevalence of future MHWs.

    “Besides near real-time monitoring, the metrics can be used to estimate the prevalence of future MHWs.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given
    § 3. Monitoring and forecasting marine heatwaves · p. 14

    Metrics discussed here and applied to daily SST data would allow warnings to be issued when bleaching.

    “metrics discussed here and applied to daily SST data would allow warnings to be issued when bleaching (http://coralreefwatch.noaa.gov/satellite/index.php).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Interpretationreasoning
    § 2.2. Datasets matter in defining heatwaves · p. 13

    For other research applications, such as studies of large-scale climate variability, MHW metrics may require further modification based on the resolution of datasets being used.

    “For other research applications, such as studies of large-scale climate variability, MHW metrics may require further modification based on the resolution of datasets being used.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning
    § 2.2. Datasets matter in defining heatwaves · p. 13

    Different datasets can generate different values for the same metric, and certain indices may simply not be appropriate or derivable from some data sources.

    “Not only can different datasets generate different values for the same metric, certain indices may simply not be appropriate or derivable from some data sources.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Interpretationreasoning
    § 2.2. Datasets matter in defining heatwaves · p. 13

    Resolution may be reduced due to the coarseness of spatial grids and, in the case of regional models, the domain they cover.

    “However, resolution may be reduced due to the coarseness of spatial grids and, in the case of regional models, the domain they cover.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Interpretationown data
    § 2. A hierarchical definition of marine heatwaves · p. 9

    Five days is a balance to achieve relatively uniform global marine heatwave counts under current climatic conditions.

    “Therefore, we recommend five days as a balance to achieve relatively uniform global MHW counts under current climatic conditions.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: A five-day minimum duration is appropriate for ecological processes and impacts.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation
    § 3. Monitoring and forecasting marine heatwaves · p. 15

    Australia's Bureau of Meteorology POAMA model predicts monthly SSTs for the upcoming nine months.

    “their POAMA model predicts monthly SSTs for the upcoming nine months (www.bom.gov.au/climate/poama2.4/poama.shtml)”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites www.bom.gov.au/climate/poama2.4/poama.shtml

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based).

    Interpretationnone given
    § 2.1. Measurement of marine heatwaves · p. 10

    Primary metrics allow for the most general comparison between duration and magnitude (intensity).

    “Primary metrics allow for the most general comparison between duration and magnitude (intensity).”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Interpretationreasoning
    § 2.1. Measurement of marine heatwaves · p. 10

    This set of metrics allows different marine heatwave events to be uniquely described and compared.

    “This set of metrics allows different MHW events to be uniquely described and compared ( Figure 2 ).”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning
    § 2.1. Measurement of marine heatwaves · p. 10

    A hierarchy is useful because different temperature datasets, based on their spatial and temporal resolution, have different abilities to provide different metrics.

    “A hierarchy is useful as different temperature datasets, based on their spatial and temporal resolution, have different abilities to provide different metrics.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationnone given
    § 2. A hierarchical definition of marine heatwaves · p. 8

    By using a percentile rather than a standard deviation definition, no assumption is made regarding the underlying distribution of anomalies.

    “Moreover, by using a percentile rather than standard deviation definition no assumption is made regarding the underlying distribution of anomalies.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: A 90th percentile threshold is appropriate for defining marine heatwaves across regions.

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Interpretationnone given
    § 3. Monitoring and forecasting marine heatwaves · p. 14

    Near real-time monitoring of ocean surface temperatures based on satellite data is possible.

    “Near real-time monitoring of ocean surface temperatures based on satellite data is possible”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationcitation
    § 2.1. Measurement of marine heatwaves · p. 12

    Preconditioning metrics will likely be specific to particular habitats, regions and species via potential local adaptation to extremes.

    “these metrics will likely be specific to particular habitats, regions and species via potential local adaptation to extremes (Palumbi et al. 2014)”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites Palumbi et al. 2014 source

  • Probably not a substantial claim: may not pass S2 (checkable). May combine two claims.

    Interpretationreasoning
    § 2. A hierarchical definition of marine heatwaves · p. 8

    A percentile threshold is recommended rather than an absolute value above the climatological value because the magnitude of variability across a range of timescales varies considerably by region.

    “A percentile threshold is recommended rather than an absolute value above the climatological value as the magnitude of variability across a range of timescales varies considerably by region.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: A 90th percentile threshold is appropriate for defining marine heatwaves across regions.

  • Classified as probably not a substantial claim.

    Interpretationreasoning
    § 3. Monitoring and forecasting marine heatwaves · p. 15

    Using them within a forecasting framework would lead to near-term prediction of MHWs.

    “Using them within a forecasting framework would lead to near-term prediction of MHWs.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.

    Interpretationreasoning
    § 2.2. Datasets matter in defining heatwaves · p. 13

    Coarser resolution datasets may provide information about larger areas and/or longer time periods, but this information may not be particularly relevant for marine managers or policy makers who require accurate local scale information, particularly on magnitude, to assess likely impacts.

    “While coarser resolution datasets may provide information about larger areas and/or longer time periods, this information may not be particularly relevant for marine managers or policy makers who require accurate local scale information, particularly on magnitude, to assess likely impacts.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S4 (based).

    Interpretationreasoning
    § 2. A hierarchical definition of marine heatwaves · p. 8

    An absolute threshold, such as a 2°C anomaly, would only be relevant in terms of impacts in some regions but not in others, for example due to species acclimation.

    “An absolute threshold (e.g. 2°C anomaly) would only be relevant in terms of impacts in some regions but not in others (e.g. due to species acclimation).”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: A 90th percentile threshold is appropriate for defining marine heatwaves across regions.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationnone given
    § Figure Legends · p. 31

    A short marine heat wave is distinguished by its duration (D).

    “A lower intensity MHW (panel d ) is distinguished by its maximum intensity (imax), while a short MHW (panel e ) is distinguished by its duration ( D ).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.

    Interpretationnone given
    § 4. Recommendations and conclusions · p. 16

    The three-tier framework allows for an over-arching and consistent measurement of heatwaves, while also providing flexibility in specifying additional metrics, if necessary.

    “The three-tier framework allows for an over-arching and consistent measurement of heatwaves, while also providing flexibility in specifying additional metrics, if necessary.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning
    § 3. Monitoring and forecasting marine heatwaves · p. 15

    Including MHW metrics in forecasting based on daily predictions would help to identify areas where MHWs may occur and actions could be implemented weeks ahead of time.

    “Including MHW metrics in the forecasting based on daily predictions would help to identify areas where MHWs may occur and actions could be implemented weeks ahead of time”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based).

    Interpretationnone given
    § 4. Recommendations and conclusions · p. 16

    Adoption of consistent terminology, definitions and metrics will facilitate the comparison of observed events against those simulated in model projections, which will be very useful in understanding plausible future changes in MHWs.

    “It will also facilitate the comparison of observed events against those simulated in model projections, which will be very useful in understanding plausible future changes in MHWs.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

    Interpretationnone given
    § 3. Monitoring and forecasting marine heatwaves · p. 15

    Projections beyond the near-term could identify future MHW risk areas.

    “Projections beyond the near-term could identify future MHW risk areas.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S4 (based).

    Interpretationnone given
    § 4. Recommendations and conclusions · p. 16

    Adoption of consistent terminology, definitions and metrics by a broad range of researchers will facilitate comparisons between different MHW events, across seasons and at regional scales.

    “This will facilitate comparisons between different MHW events, across seasons and at regional scales.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisereasoning
    § 4. Recommendations and conclusions · p. 16

    10% of days will be above the 90th percentile threshold.

    “While 10% of days will be above this threshold”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning
    § 3. Monitoring and forecasting marine heatwaves · p. 15

    The likelihood of an area experiencing extreme climatic events could be used to decide which areas should be protected and which are less resilient and prone to strong impacts with low expectations of recovery.

    “The likelihood of an area experiencing extreme climatic events could thus be used to decide which areas should be protected and which are less resilient and prone to strong impacts with low expectations of recovery.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based). May combine two claims.

    Interpretationnone given
    § 4. Recommendations and conclusions · p. 17

    Marine heatwaves are an emerging area of interdisciplinary research with potential for collaborative initiatives in understanding these phenomena.

    “Marine heatwaves are an emerging area of interdisciplinary research with potential for collaborative initiatives in understanding these phenomena.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable).

    Interpretationreasoning
    § 4. Recommendations and conclusions · p. 17

    The 2013-2015 northeast Pacific event, along with the 2003 Mediterranean Sea, 2011 Western Australia and 2012 Northwest Atlantic MHW, provide an opportunity to investigate the drivers and anomalous properties of MHWs under a hierarchical framework.

    “This event, along with the 2003 Mediterranean Sea, 2011 Western Australia and 2012 Northwest Atlantic MHW, provide an opportunity to investigate the drivers and anomalous properties of MHWs under a hierarchical framework.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.

    Interpretationreasoning
    § 4. Recommendations and conclusions · p. 17

    Such an approach can be used to identify regions that may be particularly susceptible to MHWs or regions where ecological impacts may be particularly severe.

    “Such an approach can be used to identify regions that may be particularly susceptible to MHWs (i.e. areas subjected to intense human impacts) or regions where ecological impacts may be particularly severe (i.e. hotspots of biodiversity).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Premisenone given
    § 4. Recommendations and conclusions · p. 15

    The adverse impacts of marine heatwaves span a vast range of marine ecosystems.

    “The adverse impacts of these events span a vast range of marine ecosystems.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Interpretationreasoning
    § 4. Recommendations and conclusions · p. 16

    Daily climatological threshold time series may need to be smoothed in order to extract a useful climatology from inherently variable data.

    “Daily climatological threshold time series (e.g. 90 th percentile) may need to be smoothed in order to extract a useful climatology from inherently variable data.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Interpretationnone given
    § Figure Legends · p. 31

    An asymmetric marine heat wave can be distinguished from one with a slow onset and rapid decline by the rate of warming (ronset) metric.

    “This asymmetric MHW (b) is distinguished from one with a slow onset and rapid decline (panel c ) by the rate of warming (ronset) metric.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

    Interpretationreasoning
    § 4. Recommendations and conclusions · p. 17

    Assessments of spatial and temporal variability in the occurrence of MHWs can be combined with analyses of other important aspects of the marine environment.

    “Assessments of spatial and temporal variability in the occurrence of MHWs can be combined with analyses of other important aspects of the marine environment”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).

    Interpretationnone given
    § 4. Recommendations and conclusions · p. 16

    Use of standardised software would ensure consistency in calculating metrics.

    “The use of standardised software would ensure consistency in calculating metrics”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Interpretationnone given
    § References · p. 29

    Preconditioning factors such as time of year relative to the onset of the marine heat wave, or periods of above-mean temperature preceding the marine heat wave, may lead to greater impacts.

    “Factors such as time of year relative to the onset of the MHW, or periods of above mean temperature preceding the MHW may lead to greater impacts.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Interpretationnone given
    § Figure Legends · p. 31

    A lower intensity marine heat wave is distinguished by its maximum intensity (imax).

    “A lower intensity MHW (panel d ) is distinguished by its maximum intensity (imax), while a short MHW (panel e ) is distinguished by its duration ( D ).”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Interpretationnone given
    § Figure Legends · p. 31

    A marine heat wave with regular warming onset and decline can be distinguished from one with similar duration and maximum intensity but asymmetric warming by the cumulative intensity metric (icum).

    “A marine heat wave (MHW) with regular warming onset and decline (panel a ) can be distinguished from one with similar duration and maximum intensity but asymmetric warming (panel b ) by the cumulative intensity metric (icum).”
    Quote in the paperSubstantial claim
70 of 70

  • The paper relies on this without support.

    A five-day minimum duration is appropriate for ecological processes and impacts.

    “Our general recommendation is that the MHW needs to persist for at least five days.”
    “the definition should be relevant to ecological processes and thresholds (based on evidence of impact), but for each process this threshold may be different.”

  • The paper relies on this without support.

    A 90th percentile threshold is appropriate for defining marine heatwaves across regions.

    “A MHW should be defined relative to a high percentile threshold (e.g. 90%).”

  • The paper relies on this without support.

    The thermal thresholds of performance of different biological traits must be known to identify the risk of MHW impacts on biological activity.

    “In order to identify the risk of MHW impacts on biological activity, the thermal thresholds of the performance of different biological traits must also be known, and is the subject of ongoing research.”

  • The paper relies on this without support.

    It is generally rare for five consecutive days above their relative 90th percentile to occur.

    “it is generally 'rare' for (five) consecutive days above their relative 90 th percentile to occur.”

  • The paper relies on this without support.

    Shorter heat spikes may have ecological impacts in the ocean.

    “Shorter heat spikes may have ecological impacts in the ocean, but these are distinct features”

  • The paper relies on this without support.

    Confidence in the robust detection of MHWs and capacity to compare between events and examine spatiotemporal trends will only be achieved with the use of high-quality datasets.

    “Confidence in the robust detection of MHWs (and capacity to compare between events and examine spatiotemporal trends) will only be achieved with the use of high-quality datasets.”

  • The paper relies on this without support.

    The satellite-derived SST dataset allows for robust detection of MHWs.

    “the satellite-derived SST dataset allows for robust detection of MHWs but should be complemented with high quality in situ data (e.g. from coastal temperature loggers or oceanographic moorings).”

  • The paper relies on this without support.

    Atmospheric heatwaves are analogous to marine heatwaves.

    “analogous to atmospheric heatwaves”

  • The authors state this as an assumption.

    The marine heat wave definitions use daily sea surface temperature data and treat a marine heat wave as having a discrete start day and end day.

    “All definitions assume that daily SST data, T, and that a MHW has a discrete start day and end day.”
9 of 9

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Table 3 assigns the wrong unit to mean intensity

    Minor

    Table 3 groups mean intensity and cumulative intensity under °C days, whereas Table 2 assigns mean intensity the unit °C. °C days applies to cumulative intensity, not mean intensity.

  • Figure 4 dates the 2011 Ningaloo Niño to the following summer

    Minor

    The text places the Western Australia heatwave in the austral summer of 2011 and links it to the 2010/11 La Niña, but the Figure 4 legend marks the heatwave from December 2011 to April 2012.

2 of 2

Cites

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3 of the 81 references couldn’t be matched to a known paper.

Cited by

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Related

Authors
Hobday, A. J., Alexander, L. V., Perkins, S. E., Smale, D. A., Straub, S. C., Oliver, E. C. J., Benthuysen, J. A., Burrows, M. T., Donat, M. G., Feng, M., Holbrook, N. J., Moore, P. J., Scannell, H. A., Sen Gupta, A., & Wernberg, T.
Affiliations
  • CSIRO Oceans and Atmosphere (AU)
  • UNSW Sydney (AU)
  • Marine Biological Association of the United Kingdom (GB)
Corresponding author
Hobday, Alistair J.
Venue
Progress in Oceanography
Publisher
Elsevier BV
Published
2016-02
Volume
141
Pages
227-238
ISSN
0079-6611 (ISSN-L)
DOI
10.1016/j.pocean.2015.12.014
OpenAlex
W2230443456
Semantic Scholar
08446f63a48c06f446c5b35fa80aa5d2250e9d08
Cited by
2,377
References
81
Citations by year
2026: 410 · 2025: 466 · 2024: 422 · 2023: 341 · 2022: 261 · 2021: 187 · 2020: 115 · 2019: 87 · 2018: 40 · 2017: 33 · 2016: 12 · 2015: 1
FWCI
46.67
Type
journal article
Language
en
Open access
Licence
Locations
  • Progress In Oceanography (acceptedVersion)
  • Marine Biological Association (acceptedVersion)
  • NOAA Institutional Repository (submittedVersion, public-domain)
  • eCite Digital Repository (University of Tasmania) (submittedVersion)
  • UWA Profiles and Research Repository (UWA) (submittedVersion)
  • UNSWorks (UNSW Sydney) (submittedVersion, cc-by-nc-nd)
  • Figshare (submittedVersion, cc-by)
  • ANU Open Research (Australian National University) (submittedVersion)
  • UNSWorks (University of New South Wales, Sydney, Australia) (submittedVersion, cc-by-nc-nd)
  • Newcastle University ePrints (Newcastle Univesity)
Funders
  • University of Western Australia Research Collaboration Award
  • UWA School of Plant Biology
  • ARC Centre of Excellence for Climate System Science
  • ARC (DE140100952)
  • MGD (DE150100456)
  • LVA (CE110001028)
  • NERC (NE/J024082/1)
Topics
  • Physical Sciences › Earth and Planetary Sciences › Oceanography › Oceanographic and Atmospheric Processes
  • Physical Sciences › Environmental Science › Global and Planetary Change › Marine and fisheries research
  • Physical Sciences › Environmental Science › Ecology › Coral and Marine Ecosystems Studies
Keywords
marine heatwaves, ocean temperature anomalies, climate change impacts, range shifts, fisheries impacts, aquaculture impacts

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-16.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-16.

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