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Cited by 150Climate variability and modelsOceanographic and Atmospheric ProcessesMarine and coastal ecosystems

Tendencies, variability and persistence of sea surface temperature anomalies

Open access
Bulgin, Claire E., Merchant, Christopher J., Ferreira, David·2020·Scientific Reports
DOI 10.1038/s41598-020-64785-9PMC PMC7224223
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Abstract

Quantifying global trends and variability in sea surface temperature (SST) is of fundamental importance to understanding changes in the Earth’s climate. One approach to observing SST is via remote sensing. Here we use a 37-year gap-filled, daily-mean analysis of satellite SSTs to quantify SST trends, variability and persistence between 1981–2018. The global mean warming trend is 0.09 K per decade globally, with 95% of local trends being between −0.1 K and + 0.35 K. Excluding perennial sea-ice regions, the mean warming trend is 0.11 K per decade. After removing the long-term trend we calculate the SST power spectra over different time periods. The maximum variance in the SST power spectra in the equatorial Pacific is 1.9 K 2 on 1–5 year timescales, dominated by ENSO processes. In western boundary currents characterised by an intense mesoscale activity, SST power on sub-annual timescales dominates, with a maximum variance of 4.9 K 2. Persistence timescales tend to be shorter in the summer hemisphere due to the shallower mixed layer. The median short-term persistence length is 11–14 days, found over 71–79% of the global ocean area, with seasonal variations. The mean global correlation between monthly SST anomalies with a three-month time-lag is 0.35, with statistically significant correlations over 54.0% of the global oceans, and notably in the northern and equatorial Pacific, and the sub-polar gyre south of Greenland. At six months, the mean global SST anomaly correlation falls to 0.18. The satellite data record enables the detailed characterisation of temporal changes in SST over almost four decades.

AI snapshot

Written from the paper’s full text.

TL;DR

Using a 37-year gap-filled daily satellite SST analysis (1981–2018), the paper quantifies global SST trends, variability, and persistence. It finds a global mean warming trend of 0.09 K per decade, ENSO-dominated 1–5 year variability in the equatorial Pacific, and short-term anomaly persistence typically 11–14 days over most of the ocean.

Key findings

  • Global mean SST warming trend is 0.09 ± 0.006 K per decade including perennial sea-ice regions and 0.11 ± 0.008 K per decade excluding them; 95% of local trends lie between −0.1 K and +0.35 K.
  • After detrending, maximum SST power-spectrum variance in the equatorial Pacific is 1.9 K² on 1–5 year timescales, dominated by ENSO; in western boundary currents, sub-annual power reaches a maximum variance of 4.9 K² in the Brazilian-Falkland confluence.
  • Median short-term SSTA persistence length is 11–14 days, found over 71–79% of the global ocean area, with seasonal variations.
  • Mean global SSTA correlation at a three-month lag is 0.35, with statistically significant correlations over 54.0% of the global oceans; at six months the mean global correlation falls to 0.18.

Methods

  • Uses the ESA CCI SST analysis: gap-filled, daily-mean satellite SST from Sept 1981–Dec 2018, originally 0.05° grid and spatially averaged to 0.25°, combining AVHRR and ATSR-series retrievals.
  • Trends are calculated with the Theil-Sen estimator; variability is assessed from decad (10-day) detrended SSTA power spectra over sub-annual, 1–5 year, and >5 year timescales.
  • Short-term persistence is derived from daily detrended SSTA autocorrelations, fitted with a Savitzky-Golay filter and exponential decay, using a correlation threshold of 0.6; longer persistence/re-emergence is assessed via Pearson correlations at 3-, 6-, and 12-month lags.

Limitations

  • Stated: the 37-year record is relatively short for estimating >5-year SST power; 12-month lag correlations use 36 years; persistence estimates are sensitive to temporal resolution, persistence definition, and fit window; re-emergence can skew exponential fits; high spatial resolution may make co-located re-emergence harder to identify.
  • Stated: uncertainty values exclude instrument instability over time, estimated at about 0.05 K per decade; point-by-point significance over a spatially correlated field means some local significant areas are expected by chance; dust events can bias retrieved SST cold and create artificial short-term persistence in the equatorial Atlantic.
  • Evident from the text: the analysis is satellite-era only and depends on the ESA CCI product’s retrieval and gap-filling characteristics, with limited ability to resolve long-term or re-emergence signals in noisy or advective regions.

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

Integrity signals

Registry

Crossref · 10.1038/s41598-020-64785-9

Cites

74 of 75 references verified0 citation errors · 1 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

36 of 101 cited sources checked · 11 supported · 0 flagged · accuracy not yet measured

  • Findingcitation

    The AMV region shows a step change in the SSTA centred on 1995, corresponding to the change to a positive phase of the AMV.

    “The AMV region shows a step change in the SSTA centred on 1995, corresponding to the change to a positive phase of the AMV30.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [30] Sutton, R. T. et al. Atlantic Multidecadal Variability and the UK ACSIS Program. BAMS 415–425 (2018). source

      The 'Observed Characteristics of AMV' section (page unavailable) places the cool phase at approximately 1965–95 and the warm phase from 2000 onward, and explicitly describes a 1990s shift to positive AMV. It does not describe a step change in sea-surface-temperature anomalies centred on 1995, so that characterization is not established by the text. (LLM, conf=0.83)

      Experimental — accuracy not yet measured
  • Premisecitation

    The strongest re-emergence signals are in the NW Pacific, NW Atlantic and Southern Ocean.

    “Regional studies have demonstrated the independence of the re-emergence signal from ENSO variability15 with the strongest re-emergence signals in the NW Pacific, NW Atlantic and Southern Ocean16–18.”
    Quote in the paperNot a substantial claim1 of 4 sources checked
    • cites [15] Zhao, X. & Li, J. Winter-to-Winter Recurrence of Sea Surface Temperature Anomalies in the Northern Hemisphere. Journal of Climate 32, 3835–3854 (2010). source

      The Spatiotemporal distribution of the SSTA WWR section (page unavailable) reports recurrence across much of the North Pacific and North Atlantic, including the northwestern Pacific. It does not identify these as the strongest re-emergence signals or assess the Southern Ocean; the study is limited to the Northern Hemisphere. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
    • cites [16] de Coetlogon, G. & Frankignoul, C. The Persistence of Winter Sea Surface Temperature in the North Atlantic. Journal of Climate 16, 1364–1377 (2002). source
    • cites [17] Timlin, M. S., Alexander, M. A. & Deser, C. On the Reemergence of North Atlantic SST Anomalies. Journal of Climate 15, 2707–2712 (2002). source
    • cites [18] Alexander, M. A., Deser, C. & Timlin, M. S. The Reemergence of SST Anomalies in the North Pacific Ocean. Journal of Climate 12, 2419–2433 (1999). source
  • Premisecitation

    The ESA CCI SST dataset is to the maximum degree possible independent of in-situ observations.

    “This dataset is to the maximum degree possible independent of in-situ observations2.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [2] Merchant, C. J. et al. Satellite-based time-series of sea-surface temperature since 1981 for climate applications. Scientific Data 6, https://doi.org/10.1038/s41597-019-0236-x (2019). source

      The Background & Summary says the dataset’s objective is to be as independent of in-situ observations as possible, and that a high degree of independence was achieved from 1995 onward. It also says in-situ SSTs were needed as a calibration reference for 1981–1995, when independence was lost to a significant degree. The claim presents the objective as a property of the dataset without that time-period qualification. (LLM, conf=0.88)

      Experimental — accuracy not yet measured
  • Premisecitation

    Regions characterised by a strong seasonal variation in MLD may display the phenomenon of re-emergence of winter-to-winter SSTA.

    “Regions characterised by a strong seasonal variation in MLD may also display the phenomenon of re-emergence of winter-to-winter SSTA9–13.”
    Quote in the paperNot a substantial claim1 of 5 sources checked
    • cites [9] Byju, P., Dommenget, D. & Alexander, M. A. Widespread reemergence of sea surface temperature anomalies in the global oceans, including tropical regions forced by reemerging winds. Geophysical Research Letters, https://doi.org/10.1029/2018GL079137 7683–7691 (2018). source
    • cites [10] Hanawa, K. & Sugimoto, S. ‘Reemergence’ areas of winter sea surface temperature anomalies in the world’s oceans. Geophysical Research Letters 31, https://doi.org/10.1029/2004GL019904 (2004). source
    • cites [11] Alexander, M. A. & Deser, C. A Mechanism for the Recurrence of Wintertime Midlatitude SST anomalies. Journal of Physical Oceanography 25, 122–135 (1994). source
    • cites [12] Alexander, M. A., Timlin, M. S. & James, D. S. Winter-to-winter recurrence of sea surface temperature, salinity and mixed layer depth anomalies. Process in Oceanography 49, 41–61 (2001). source
    • cites [13] Namias, J. & Born, R. M. Temporal Coherence in North Pacific Sea-Surface Temperature Patterns. Journal of Geophysical Research 75, 5952–5955 (1970). source
  • Findingcitation

    The NE Pacific warm anomaly of 2014-2016 is markedly stronger (in this location) than any previous period in the dataset.

    “The NE Pacific warm anomaly of 2014–2016 is markedly stronger (in this location) than any previous period in the dataset and is attributed to strong, persistent, positive sea-level pressure anomalies32.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [32] Bond, N. A., Cronin, M. F., Freeland, H. & Mantua, N. Causes and impacts of the 2014 warm anomaly in the NE Pacific. Geophysical Research Letters 3414–3420 (2015). source

      The Introduction says the February 2014 temperature anomalies were the greatest observed in the region for that month since at least the 1980s. The Abstract attributes the anomaly to an unusually strong, persistent high-pressure pattern. The paper does not establish that the entire 2014–2016 anomaly was stronger than every previous period in the citing document’s dataset; its reported observations extend only into 2015. (LLM, conf=0.88)

      Experimental — accuracy not yet measured
  • May combine two claims. 49
  • Classified as probably not a substantial claim. 13
  • The quote only partly states this claim. 1

  • May combine two claims.

    Premisecitation

    Changes in the AMV are coupled with the North Atlantic Oscillation and Atlantic Meridional Overturning Circulation (AMOC), with a positive phase of the AMV associated with warmer SSTs.

    “Changes in the AMV are coupled with the North Atlantic Oscillation and Atlantic Meridional Overturning Circulation (AMOC), with a positive phase of the AMV associated with warmer SSTs30.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [30] Sutton, R. T. et al. Atlantic Multidecadal Variability and the UK ACSIS Program. BAMS 415–425 (2018). source

  • May combine two claims.

    Premisecitation

    ENSO state influences SSTA persistence in the Indian Ocean, where SSTA variability is comparatively small.

    “In turn, ENSO state influences SSTA persistence in the Indian Ocean, where SSTA variability is comparatively small7.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [7] Ding, R. & Li, J. Influences of ENSO Teleconnection on the Persistence of Sea Surface Temperature in the Tropical Indian Ocean. Journal of Climate 25, 8177–8195 (2012). source

      The Summary (page unavailable) reports that SSTA persistence barriers in parts of the tropical Indian Ocean weaken or disappear during weak or normal ENSO conditions, supporting the claim that ENSO state influences persistence. The paper does not establish that Indian Ocean SSTA variability is comparatively small overall; Section 3 (page unavailable) describes very small anomalies only for normal ENSO cases. (LLM, conf=0.85)

      Experimental — accuracy not yet measured

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

    Premisecitation

    The North-East Pacific warm anomaly of 2014-2016 had impacts on fisheries and regional weather.

    “The North-East Pacific between 45–55 N and 130–150 W is of interest due to the significant warm anomaly in the SST seen between 2014–2016, which had impacts on fisheries and regional weather32.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [32] Bond, N. A., Cronin, M. F., Freeland, H. & Mantua, N. Causes and impacts of the 2014 warm anomaly in the NE Pacific. Geophysical Research Letters 3414–3420 (2015). source

      The Abstract says the anomaly affected downwind air temperatures in Washington state, and Biological Impacts describes unusual salmon movements and tuna catches in 2014. The Introduction reports anomalously warm SSTs persisting through March 2015; this paper does not establish the claimed 2014–2016 span. Page numbers are unavailable in our copy. (LLM, conf=0.88)

      Experimental — accuracy not yet measured

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

    Premisecitation

    Western boundary currents are turbulent areas of water characterised by strong ocean-atmosphere interaction, poleward heat transport and ocean-atmosphere heat exchange.

    “Western boundary currents (WBCs) are turbulent areas of water characterised by strong ocean-atmosphere interaction, poleward heat transport and ocean-atmosphere heat exchange20.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [20] Kwon, Y.-O. et al. Role of the Gulf Stream and Kuroshio-Oyashio Systems in Large-Scale Atmosphere-Ocean Interaction: A Review. Journal of Climate 23, 3249–3281 (2010). source

  • May combine two claims.

    Premisecitation

    Winter SST anomalies persist at depth during the summer months below the shallow mixed layer, reemerging in the SSTA the following winter as the summer seasonal thermocline is eroded.

    “Winter SST anomalies persist at depth during the summer months below the shallow mixed layer, reemerging in the SSTA the following winter as the summer seasonal thermocline is eroded.”
    Quote in the paperSubstantial claim1 of 5 sources checked
    • cites [9] Byju, P., Dommenget, D. & Alexander, M. A. Widespread reemergence of sea surface temperature anomalies in the global oceans, including tropical regions forced by reemerging winds. Geophysical Research Letters, https://doi.org/10.1029/2018GL079137 7683–7691 (2018). source
    • cites [10] Hanawa, K. & Sugimoto, S. ‘Reemergence’ areas of winter sea surface temperature anomalies in the world’s oceans. Geophysical Research Letters 31, https://doi.org/10.1029/2004GL019904 (2004). source
    • cites [11] Alexander, M. A. & Deser, C. A Mechanism for the Recurrence of Wintertime Midlatitude SST anomalies. Journal of Physical Oceanography 25, 122–135 (1994). source
    • cites [12] Alexander, M. A., Timlin, M. S. & James, D. S. Winter-to-winter recurrence of sea surface temperature, salinity and mixed layer depth anomalies. Process in Oceanography 49, 41–61 (2001). source
    • cites [13] Namias, J. & Born, R. M. Temporal Coherence in North Pacific Sea-Surface Temperature Patterns. Journal of Geophysical Research 75, 5952–5955 (1970). source

  • May combine two claims.

    Findingcitation

    In the sub-polar gyre there is significant warming in the 1990s and cooling in the 2010s whilst the reverse is true for the north-east Pacific in the region of the recent warm anomaly.

    “In the sub-polar gyre we see significant warming in the 1990’s and cooling in the 2010’s whilst the reverse is true for the north-east Pacific in the region of the recent warm anomaly32.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [32] Bond, N. A., Cronin, M. F., Freeland, H. & Mantua, N. Causes and impacts of the 2014 warm anomaly in the NE Pacific. Geophysical Research Letters 3414–3420 (2015). source

  • May combine two claims.

    Interpretationcitation

    The sub-Greenland gyre SSTA variability is consistent with subsurface temperature trends (warming from the mid-80s to 2006 and cooling thereafter), with a time-lag between subsurface temperatures and subsequent surface temperature signals.

    “It is also consistent with the subsurface temperature trends (warming from the mid-80’s to 2006 and cooling thereafter), with a time-lag between subsurface temperatures and subsequent surface temperature signals41.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [41] Ruiz-Barradas, A., Chafik, L., Nigam, S. & Hakkinen, S. Recent subsurface North Atlantic cooling trend in context of Atlantic decadal-to-multidecadal variability. Tellus 70 (2018). source

  • Classified as probably not a substantial claim.

    Findingcitation

    The 'global warming hiatus' refers to a decade (2000 to 2009) during which global mean SSTA changed less than in the previous or subsequent decade.

    “The “global warming hiatus”47,48, is seen in Fig. 1e, referring to a decade (2000 to 2009) during which global mean SSTA changed less than in the previous or subsequent decade.”
    Quote in the paperSubstantial claim2 of 2 sources checked
    • cites [47] Trenberth, K. E. & Fasullo, J. T. An apparent hiatus in global warming? Earth’s Future 1, 19–32 (2013). source

      The Introduction (page unavailable) calls the slowed rise in global mean temperature during the 2000s a “hiatus or plateau.” The paper discusses global surface temperature, not the claimed decade-by-decade comparison of global mean sea-surface temperature anomalies; published in 2013, it does not establish how 2000–2009 compares with the subsequent decade. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
    • cites [48] Fyfe, J. C. et al. Making sense of the early-2000s warming slowdown. Nature Climate Change 6, 224–228 (2016). source

      The Concluding remarks say that global mean surface temperature warmed more slowly in the early 21st century than in the previous few decades. But the Figure 1 caption starts the slowdown in 2001, and the paper discusses it through 2014; it does not define the hiatus as 2000–2009 or establish the claimed comparison with the subsequent decade in global mean sea-surface temperature anomaly (SSTA). (LLM, conf=0.87)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Interpretationcitation

    SSTA variability in the sub-Greenland gyre region has been linked to the AMOC, which was moving into a positive phase in the 1990s, peaking in the 2000s and then declining in the 2010s.

    “SSTA variability in this region has been linked to the AMOC, which was moving into a positive phase in the 1990’s (warming trend in SSTAs), peaking in the 2000’s and then declining in the 2010’s (cooling trend in SSTAs)37–40.”
    Quote in the paperSubstantial claim2 of 4 sources checked
    • cites [37] Reverdin, G. et al. North Atlantic extratropical and subpolar gyre variability during the last 120 years: a gridded dataset of surface temperature, salinity, and density. Part 1: Dataset validation and RMS variability. Ocean Dynamics 69, 385–403 (2019). source

      The Introduction (page unavailable) links subpolar-gyre surface properties to the AMOC, but says the connection between surface changes and the AMOC remains under discussion. The passages do not establish that the AMOC entered a positive phase in the 1990s, peaked in the 2000s, or declined in the 2010s; the paper’s SST observations do not by themselves establish that AMOC chronology. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
    • cites [38] Deser, C., Alexander, M., Xie, S.-P. & Phillips, A. S. Sea Surface Temperature Variability: Patterns and Mechanisms. Annual Review of Marine Science 2, 115–43 (2010). source
    • cites [39] Chen, X. & Tung, K. K. Global surface warming enhanced by weak Atlantic overturning circulation. Nature 559, 387–391 (2018). source
    • cites [40] Robson, J., Ortega, P. & Sutton, R. A reversal of climatic trends in the North Atlantic since 2005. Nature Geoscience 9, 513–517 (2016). source

      The Abstract links rapid subpolar-gyre warming in the mid-1990s to a strengthening AMOC and reports cooling since 2005 consistent with weaker ocean circulation. It does not establish an AMOC peak in the 2000s; instead, it says measurements suggest circulation strength has declined since the mid-1990s. (LLM, conf=0.85)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Findingcitation

    The areas with the strongest warming trends during 2010-2018 are the North and East Pacific, the trend being driven by the warm anomalies observed here between 2014-2016.

    “The areas with the strongest warming trends during 2010–2018 are the North and East Pacific, the trend being driven by the warm anomalies observed here between 2014–201632,49.”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites [32] Bond, N. A., Cronin, M. F., Freeland, H. & Mantua, N. Causes and impacts of the 2014 warm anomaly in the NE Pacific. Geophysical Research Letters 3414–3420 (2015). source

      The Introduction (page not available) documents unusually warm NE Pacific waters in 2014 and says anomalously warm sea surface temperatures persisted through March 2015. It does not assess which regions had the strongest warming trends in 2010–2018 or establish that anomalies through 2016 drove those trends. (LLM, conf=0.88)

      Experimental — accuracy not yet measured
    • cites [49] Gentemann, C. L., Fewings, M. R. & Garcia-Reyes, M. Satellite sea surface temperatures along the West Coast of the United States during the 2014-2016 northeast Pacific marine heatwave. Geophysical Research Letters 44, 312–319 (2017). source

  • May combine two claims.

    Findingcitation

    Decadal temperature trends south of Greenland are consistent in sign with the sub-polar gyre, but much smaller in magnitude with an overall neutral trend between 1981-2018, also seen in in-situ data records.

    “Decadal temperature trends here are consistent in sign with the sub-polar gyre, but much smaller in magnitude with an overall neutral trend between 1981–2018, also seen in-situ data records37.”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [37] Reverdin, G. et al. North Atlantic extratropical and subpolar gyre variability during the last 120 years: a gridded dataset of surface temperature, salinity, and density. Part 1: Dataset validation and RMS variability. Ocean Dynamics 69, 385–403 (2019). source

      Section 3.3 (page unavailable) reports good agreement between two surface-temperature records in the subpolar gyre and regions farther south. Section 4 (page unavailable) reports spatially varying temperature trends, including cooling near West Greenland and the central Labrador Sea. Neither passage establishes a smaller trend south of Greenland or an overall neutral trend for 1981–2018; the paper’s reported trend analysis ends in 2015. (LLM, conf=0.82)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Interpretationcitation

    Dust events not flagged as cloud can cause an artificial timescale in the SSTA correlation, which then appears as short-term SSTA persistence.

    “Where dust events are not flagged as cloud in the retrieval, they tend to bias the retrieved SST cold2,61,62 and can cause an artificial timescale in the SSTA correlation, which then appears as short-term SSTA persistence.”
    Quote in the paperSubstantial claim2 of 3 sources checked
    • cites [2] Merchant, C. J. et al. Satellite-based time-series of sea-surface temperature since 1981 for climate applications. Scientific Data 6, https://doi.org/10.1038/s41597-019-0236-x (2019). source

      The Usage Notes (Fitness-for-purpose assessment) say that unscreened desert dust causes intermittent cold biases in retrieved SST and an exaggerated trend in SST anomalies. They do not say that dust creates an artificial timescale in SSTA correlation or apparent short-term persistence. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
    • cites [61] Corlett, G. K. et al. The accuracy of SST retrievals from AATSR: An initial assessment through geophysical validation against in situ radiometers, buoys and other SST data sets. Advances in Space Research 37, 764–769 (2006). source
    • cites [62] Reynolds, R. W., Gentemann, C. L. & Corlett, G. C. Evaluation of AATSR and TMI Satellite SST Data. Journal of Climate 23, 152–165 (2009). source

      Section 3 (Data comparisons; page unavailable) reports that Saharan dust aerosols may bias infrared SST retrievals cold, with negative biases observed in AVHRR data. It does not establish that dust events escape cloud flagging or that they create an artificial timescale in SSTA correlations or apparent short-term persistence. (LLM, conf=0.86)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Premisecitation

    Winter-to-winter re-emergence is typically characterised by a time lag that can be variable, ranging from 7-13 months, and is usually seen in the mid-latitudes.

    “This is typically characterised as winter-to-winter re-emergence although the time lag can be variable, ranging from 7–13 months15, and is usually seen in the mid-latitudes12,15–19.”
    Quote in the paperNot a substantial claim1 of 6 sources checked
    • cites [15] Zhao, X. & Li, J. Winter-to-Winter Recurrence of Sea Surface Temperature Anomalies in the Northern Hemisphere. Journal of Climate 32, 3835–3854 (2010). source
    • cites [12] Alexander, M. A., Timlin, M. S. & James, D. S. Winter-to-winter recurrence of sea surface temperature, salinity and mixed layer depth anomalies. Process in Oceanography 49, 41–61 (2001). source
    • cites [16] de Coetlogon, G. & Frankignoul, C. The Persistence of Winter Sea Surface Temperature in the North Atlantic. Journal of Climate 16, 1364–1377 (2002). source
    • cites [17] Timlin, M. S., Alexander, M. A. & Deser, C. On the Reemergence of North Atlantic SST Anomalies. Journal of Climate 15, 2707–2712 (2002). source
    • cites [18] Alexander, M. A., Deser, C. & Timlin, M. S. The Reemergence of SST Anomalies in the North Pacific Ocean. Journal of Climate 12, 2419–2433 (1999). source
    • cites [19] Sugimoto, S. & Hanawa, K. Remote reemergence of areas of winter sea surface temperature anomalies in the north Pacific. Geophysical Research Letters 32 (2005). source

  • May combine two claims.

    Premisecitation

    The Pacific Decadal Oscillation transitioned from a positive to negative phase over the 1980s-2000s, becoming more neutral in the 2010s.

    “The Pacific Decadal Oscillation (PDO) also transitioned from a positive to negative phase over the 1980’s-2000’s, becoming more neutral in the 2010’s.”
    Quote in the paperNot a substantial claim1 of 2 sources checked
    • cites [35] Falvey, M. & Garreaud, R. D. Regional cooling in a warming world: Recent temperature trends in the southeast Pacific and along the west coast of subtropical South America (1979-2006). Journal of Geophysical Research 114 (2009). source
    • cites [78] Meehl, G. A. et al. Sustained ocean changes contributed to sudden Antarctic sea ice retreat in late 2016. Nature Communications 10 (2019). source

      The Introduction (page unavailable) describes a positive-to-negative shift across 1979–2000 and the post-2000 period, but it identifies the oscillation as the IPO, not the PDO. It also describes a transition toward a positive IPO phase in 2014–2016, rather than saying it became more neutral in the 2010s. (LLM, conf=0.84)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Interpretationcitation

    Cooling in the Southern Pacific is consistent with the PDO becoming more negative (1980s-2000s) and warming consistent with a return towards a positive index (2010s).

    “Cooling in the Southern Pacific is consistent with the PDO becoming more negative (1980’s-2000’s) and warming consistent with a return towards a positive index (2010’s)35,78.”
    Quote in the paperNot a substantial claim1 of 2 sources checked
    • cites [35] Falvey, M. & Garreaud, R. D. Regional cooling in a warming world: Recent temperature trends in the southeast Pacific and along the west coast of subtropical South America (1979-2006). Journal of Geophysical Research 114 (2009). source
    • cites [78] Meehl, G. A. et al. Sustained ocean changes contributed to sudden Antarctic sea ice retreat in late 2016. Nature Communications 10 (2019). source

      The Introduction (page not specified) links below-normal southern-latitude sea-surface temperatures to a negative interdecadal Pacific oscillation (IPO) and describes a possible transition toward a positive IPO in 2014–2016. But it places the negative phase in 2000–2014 and the positive phase in 1979–2000, contrary to the claim’s 1980s–2000s timing. It discusses the IPO, not the PDO. (LLM, conf=0.86)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Interpretationreasoning

    The failure of CMIP5 models to simulate Southern Ocean SST cooling may suggest that natural decadal variability is important or that the timing of different response mechanisms in the models is not adequately resolved.

    “this may suggest that natural decadal variability is also important73,76, or that the timing of different response mechanisms in the models is not adequately resolved74,77.”
    Quote in the paperSubstantial claim2 of 4 sources checked
    • cites [73] Armour, K. C. & Bitz, C. M. Observed and projected trends in Antarctic sea ice. US CLIVAR Variations 13, 12–19 (2015).

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

    • cites [76] Fan, T., Deser, C. & Schneider, D. P. Recent Antarctic sea ice trends in the context of Southern Ocean surface climate variations since 1950. Geophysical Research Letters 141, 2419–2426 (2014). source
    • cites [74] Kostov, Y. et al. Fast and slow responses of Southern Ocean sea surface temperature to SAM in coupled climate models. Climate Dynamics 48, 1595–1609 (2017). source
    • cites [77] Ferreira, D. & Marshall, J. Antarctic Ocean and Sea Ice Response to Ozone Depletion: A Two-Time-Scale Problem. Journal of Climate 28, 1206–1226 (2015). source

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

    Premisecitation

    From the end of 2016 onwards, a sharp decrease in Antarctic sea-ice has been observed.

    “From the end of 2016 onwards, a sharp decrease in Antarctic sea-ice has also been observed78”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [78] Meehl, G. A. et al. Sustained ocean changes contributed to sudden Antarctic sea ice retreat in late 2016. Nature Communications 10 (2019). source

  • May combine two claims.

    Findingown data

    The strongest warming trends are in the Northern Hemisphere close to the Arctic sea-ice boundary, in the Mediterranean, in the Black Sea and along the northern edge of the Northern Hemisphere western boundary currents (Gulf Stream and Kuroshio Extension).

    “The strongest warming trends are in the Northern Hemisphere close to the Arctic sea-ice boundary, in the Mediterranean, in the Black Sea and along the northern edge of the Northern Hemisphere western boundary currents (Gulf Stream and Kuroshio Extension).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    SSTA fluctuations in the Nino 3.4 region have a range of ~3-5 K, with positive SSTA's associated with El-Nino events.

    “SSTA fluctuations in the Nino 3.4 region have a range of ~3–5 K, with positive SSTA’s associated with El-Nino events.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The median global short-term persistence length is 12 days in December, 14 days in March, 11 days in June and 12 days in September.

    “The median global short-term persistence length is 12 days in December, 14 days in March, 11 days in June and 12 days in September.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Short-term SSTA persistence is observed over 70.9, 71.0, 71.6 and 78.5% of the global oceans in December, March, June and September respectively.

    “Short-term SSTA persistence is observed over 70.9, 71.0, 71.6 and 78.5% of the global oceans in each season respectively.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The localised trends in SSTA are in general significantly smaller in the 2000s than in other decades, with a standard deviation in the SSTA trends of 0.33 K in the 2000s compared with 0.49-0.66 K for the other decades.

    “Moreover, the localised trends in SSTA are in general significantly smaller than in other decades, with a standard deviation in the SSTA trends of 0.33 K in the 2000’s compared with 0.49–0.66 K for the other decades.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingcitation

    The annual cycle in the northern mid-latitudes is greater than that of the southern mid-latitudes, with a mean standard deviation of 3.4 K for 30-50 N vs. 1.6 K for 30-50 S.

    “The cycle in the northern mid-latitudes is greater than that of the southern mid-latitudes51, with a mean standard deviation of 3.4 K for 30–50 N vs. 1.6 K for 30–50 S.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [51] Casey, K. S. & Cornillon, P. A Comparision of Satellite and In Situ-Based Sea Surface Temperature Climatologies. Journal of Climate 12, 1848–1863 (1998). source

  • May combine two claims.

    Findingcitation

    The warm anomaly maximum was observed in the offshore northerly region and along the west coast of the USA.

    “The warm anomaly maximum was observed in the offshore northerly region and along the west coast of the USA49.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [49] Gentemann, C. L., Fewings, M. R. & Garcia-Reyes, M. Satellite sea surface temperatures along the West Coast of the United States during the 2014-2016 northeast Pacific marine heatwave. Geophysical Research Letters 44, 312–319 (2017). source

  • May combine two claims.

    Findingown data

    In the ENSO region the timeseries trend is non-linear with a cooling in the 1980s and 1990s and a warming in the 2010s following the hiatus period of the 2000s.

    “In the ENSO region the timeseries trend is also non-linear with a cooling in the 1980’s and 1990’s and a warming in the 2010’s following the hiatus period of the 2000’s.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingnone given

    Temperature anomalies in the ENSO region of the tropical, eastern Pacific exhibit decadal variability: cooling in the 1980s, warming close to the South American west coast in the 1990s with cooling in the equatorial waters, weak warming in the 2000s during the hiatus period, and a strong warming signal both close to the South American coast and in equatorial waters in the 2010s.

    “Temperature anomalies in the ENSO region of the tropical, eastern Pacific exhibit decadal variability - cooling in the 1980’s, warming close to the South American west coast in the 1990’s with cooling in the equatorial waters, weak warming in the 2000’s during the hiatus period, and a strong warming signal both close the the South American coast and in equatorial waters in the 2010’s.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Some SST variability in western boundary currents can be attributed to SST processes operating on annual to five-year timescales, although this may be aliasing given the relatively short length of the timeseries.

    “We see that some SST variability in western boundary currents can be attributed to SST processes operating on those timescales, although this may be aliasing given the relatively short length of the timeseries.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    In the ENSO region, SST power is dominated by SST processes on 1-5 year timescales, with a maximum SSTA variance of 1.9 K2.

    “In the ENSO region, SST power is dominated by SST processes on 1–5 year timescales, with a maximum SSTA variance of 1.9 K2.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The annual cycle is small (~1 K) at equatorial and very high latitudes, and is at a maximum at mid-latitudes.

    “The annual cycle is small (~1 K) at equatorial and very high latitudes, and is at a maximum at mid-latitudes.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    There is considerable inter-decadal variation in within-decade temperature tendencies, which is particularly notable in the sub-Greenland gyre.

    “There is considerable inter-decadal variation in within-decade temperature tendencies (Fig. 1c–f), which is particularly notable in the sub-Greenland gyre.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The fitting uncertainties for decadal trends are similarly distributed to those for the full timeseries, but are larger as the timeseries are shorter.

    “Here we see that the fitting uncertainties are similarly distributed to those for the full timeseries, but are larger as the timeseries are shorter.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The twelve-month-lag SSTA correlations over the sub-polar gyre south of Greenland are strongest and have the greatest areal extent from March to March.

    “These correlations are strongest and have the greatest aereal extent from March to March.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The most convincing positive correlations at a three-month time-lag are found in the ENSO region of the equatorial Pacific, in the sub-polar gyre south of Greenland, in the northern and southern Pacific, parts of the Southern Ocean in boreal winter and in the equatorial and southern Atlantic.

    “The most convincing are the positive correlations found in the ENSO region of the equatorial Pacific, in the sub-polar gyre south of Greenland, in the northern and southern Pacific, parts of the Southern Ocean in boreal winter and in the equatorial and southern Atlantic.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    In the north and eastern Pacific and sub-polar gyre south of Greenland some short-term SSTA persistence is observed but this is typically in the range of 15-30 days and does not encompass the entire aerial extent of these features.

    “In the north and eastern Pacific and sub-polar gyre south of Greenland some short-term SSTA persistence is observed but this is typically in the range of 15–30 days and does not encompass the entire aerial extent of these features.”
    Quote in the paperNot a substantial claim

  • The quote only partly states this claim.

    Findingown data

    Statistically significant SSTA correlations occur over the sub-polar gyre south of Greenland in boreal winter, for start months December and March, at a twelve-month time-lag.

    “Statistically significant SSTA correlations occur over the sub-polar gyre south of Greenland in boreal winter, for the start months of December and March.”
    Quote in the paperNot a substantial claim

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

    Findingreasoning

    Short-term SSTA persistence is also observed in the equatorial Atlantic, west of Africa, in the regions typically affected by wind-blown Saharan dust.

    “Short-term SSTA persistence is also observed in the equatorial Atlantic, west of Africa, in the regions typically affected by wind-blown Saharan dust.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    The six-month-lag SSTA correlations in the sub-polar gyre south of Greenland are observed year round but are strongest from June to December.

    “These correlations are observed over six-month time periods year round, but are strongest from June to December.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Positive SSTA correlations in the eastern north Pacific from March to March and in the northern hemisphere tropical Pacific from September to September are statistically significant at a twelve-month time-lag.

    “Positive SSTA correlations in the eastern north Pacific from March to March and in the northern hemisphere tropical Pacific from September to September are also statistically significant.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingcitation

    Peaks in the uncertainties in 1982 and 1991 correspond to the major volcanic eruptions of El Chichon and Mount Pinatubo respectively.

    “Peaks in the uncertainties in 1982 and 1991 correspond to the major volcanic eruptions of El Chichon and Mount Pinatubo respectively71.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [71] Merchant, C. J. & Saunders, M. Infrared Satellite Retrievals in the Presence of Stratospheric Aerosol. Journal of Atmospheric and Oceanic Technology 15, 835–840 (1997). source
    • The authors state this as an assumption: The daily data are fully correlated over the spatial scale when regridding from 0.05° to 0.25°.
    • The authors state this as an assumption: The temporal correlation length scale is 3 days and the spatial correlation is 100 km for uncertainty propagation.

  • May combine two claims.

    Premisecitation

    The ESA CCI SST products validate well against Argo match-ups, with lower standard deviation of the SST differences than for other reanalysis products, including the Reynolds AVHRR optimal interpolation.

    “The ESA CCI SST products validate well against Argo match-ups, with lower standard deviation of the SST differences than for other reanalysis products, including the Reynolds AVHRR optimal interpolation4.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [4] Rayner, N. et al. SST CCI Phase II Climate Assessment Report, http://www.esa-sst-cci.org/PUG/pdf/SST_CCI-CAR-UKMO-201_Issue_1-signed.pdf (2019).

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

  • Classified as probably not a substantial claim.

    Interpretationnone given

    The satellite data record enables detailed characterisation of temporal changes in SST over almost four decades.

    “The satellite data record enables the detailed characterisation of temporal changes in SST over almost four decades.”
    Quote in the paperSubstantial claim

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

    Interpretationcitation

    The warming trend is consistent with other estimates made during the satellite era (1979-2012) cited within the IPCC Assessment Review 5.

    “This warming trend is consistent with other estimates made during the satellite era (1979–2012) cited within the Intergovernmental Panel on Climate Change (IPCC) Assessment Review 533,34.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [33] Hartmann, D. L., Albert M. G, Klein T. & Rusticucci, M. Intergovernmental Panel on Climate Change, Climate Change 2013, Physical Science Basis, Chapter 2: Observations: Atmosphere and Surface, https://www.ipcc.ch/report/ar5/wg1/ (2013).

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

    • cites [34] Pachauri, R. K. et al. Intergovernmental Panel on Climate Change, Climate Change 2014, Synthesis Report, https://www.ipcc.ch/report/ar5/syr/ (2014).

      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).

    Premisecitation

    Sustained SST anomalies of +/−0.4 K in the NINO 3.4 region over six months are indicative of El Nino or La Nina events respectively.

    “Sustained SST anomalies of +/−0.4 K in this region over six months are indicative of El Nino or La Nina events respectively31.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [31] Shea, D. NINO SST Indices (NINO 1+2, 3, 3.4, 4: ONI and TNI), https://climatedataguide.ucar.edu/climate-data/nino-sst-indices-nino-12-3-34-4-oni-and-tni (2018).

      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). May combine two claims.

    Premisecitation

    ENSO SSTA variance is smallest in boreal summer and largest in winter.

    “ENSO SSTA variance is smallest in boreal summer and largest in winter6.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [6] Xue, Y., Smith, T. M. & Reynolds, R. W. Interdecadal Changes of 30-Yr SST Normals during 1871-2000. Journal of Climate 16, 1601–1612 (2003). source

  • May combine two claims.

    Interpretationcitation

    South of the Gulf Stream, a localised cooling trend (40°N, 60°W) is observed in the 1990s, indicative of the northward shift in the Gulf Stream with a return to a positive phase of the North Atlantic Oscillation (NAO).

    “South of the Gulf Stream, a localised cooling trend (40°N, 60°W) is observed in the 1990’s, indicative of the northward shift in the Gulf Stream with a return to a positive phase of the North Atlantic Oscillation (NAO)42,43 (Fig. 1d).”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [42] Frankignoul, C., de Goetlogon, G., Joyce, T. M. & Dong, S. Gulf Stream Variability and Ocean-Atmosphere Interactions. Journal of Physical Oceanography 31, 3516–3529 (2001). source
    • cites [43] Hurrell, J., Kushnir, Y., Ottersen, G. & Visbeck, M. An overview of the North Atlantic Oscillation, The North Atlantic Oscillation: Climate Significance and Environmental Impact, 134, 1–36 (2003). source

  • May combine two claims.

    Premisecitation

    SST anomalies in the Pacific respond to multiple processes: atmosphere-ocean interaction, ENSO, SST re-emergence and the SSTA patterns described by the Pacific Decadal Oscillation.

    “SST anomalies in the Pacific respond to multiple processes: atmosphere-ocean interaction, ENSO, SST re-emergence and the SSTA patterns described by the Pacific Decadal Oscillation50.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [50] Newman, M. et al. The Pacific Decadal Oscillation, Revisited. Journal of Climate 29, 4399–4427 (2016). source

  • May combine two claims.

    Study design and conductown data

    The SSTA data are detrended using a local linear fit, but in the ENSO region, north-east Pacific and sub-polar gyre south of Greenland the long-term signal is non-linear.

    “The SSTA data are detrended using a local linear fit, but in these regions (Fig. 1) we see that the long-term signal is non-linear.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    The Indian Ocean Dipole is most likely to transition into its strongest phase between September and November, as it is phase-locked to the annual cycle.

    “corresponding to the time of year where the Indian Ocean Dipole is most likely to transition into its strongest phase as it is phase-locked to the annual cycle66.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [66] Saji, N. H., Goswami, B. N., Vinayachandran, P. N. & Yamagata, T. A dipole mode in the tropical Indian Ocean. Nature 401, 360–363 (1999). source

  • May combine two claims.

    Premisecitation

    El Nino tends to be a single-year event, with equatorial Pacific SST anomalies decaying in boreal spring (March to May).

    “El Nino tends to be a single-year event, with equatorial Pacific SST anomalies decaying in boreal spring (March to May)55,63,65.”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [55] Zhao, X., Li, J. & Zhang, W. Summer Persistence Barrier of Sea Surface Temperature Anomalies in the Central Western North Pacific. Advances in Atmospheric Sciences 29, 1159–1173 (2012). source
    • cites [63] Stein, K., Timmermann, A. & Schneider, N. Phase Synchronization of the El Nino Oscillation with the Annual Cycle. Physical Review Letters 107 (2011). source
    • cites [65] Spencer, H. Role of the atmosphere in seasonal phase locking of El Nino. Geophysical Research Letters 31 (2004). source

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

    Interpretationreasoning

    The positive SSTA correlations in the eastern north Pacific and northern hemisphere tropical Pacific at twelve-month lag may arise from the significant warming signal in the north Pacific within the 2010s.

    “These may arise from the significant warming signal in the north Pacific within the 2010s.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationnone given

    The primary control on both SSTA persistence and re-emergence is the mixed layer depth and in regions where this has significant intra-annual variability, re-emergence may be seen.

    “The primary control on both is the mixed layer depth and in regions where this has significant intra-annual variability, re-emergence may be seen.”
    Quote in the paperSubstantial claim

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

    Study design and conductreasoning

    The significance is calculated point-by-point across a data field containing spatial correlation and therefore, for any chosen confidence level, some local areas of statistical significance are expected to arise by chance.

    “The significance is calculated point-by-point across a data field containing spatial correlation and therefore, for any chosen confidence level, some local areas of statistical significance are expected to arise by chance, which should be kept in mind when interpreting the hatching.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    If present, re-emergence will skew an exponential fit to the auto-correlation timeseries and result in erroneously long SSTA persistence timescales.

    “If present, re-emergence will skew an exponential fit to the auto-correlation timeseries, and result in erroneously long SSTA persistence timescales.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    Fan et al. observed a 0.2-0.4 K cooling per decade in annual mean SST over the Southern Ocean between 1979-2011, with a corresponding 12% increase in annual mean Antarctic sea-ice concentration.

    “Fan et al.76 observed a 0.2–0.4 K cooling per decade in the annual mean SST over the Southern Ocean between 1979–2011 with a corresponding 12% increase in the annual mean Antarctic sea-ice concentration.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [76] Fan, T., Deser, C. & Schneider, D. P. Recent Antarctic sea ice trends in the context of Southern Ocean surface climate variations since 1950. Geophysical Research Letters 141, 2419–2426 (2014). source

  • May combine two claims.

    Interpretationreasoning

    The sharp decrease in Antarctic sea-ice from the end of 2016 occurs over a small fraction of the time series and does not dominate the long-term trends in the satellite era.

    “As this only occurs over a small fraction of the time series it does not dominate the long-term trends we see in the satellite era.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Premisecitation

    CMIP5 climate models do not simulate SST cooling in the Southern Ocean or reproduce the suggested mechanisms for SST cooling.

    “As climate models in the Coupled Model Intercomparison Project Phase 5 (CMIP5) do not simulate SST cooling in this region or reproduce the suggested mechanisms for SST cooling76”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [76] Fan, T., Deser, C. & Schneider, D. P. Recent Antarctic sea ice trends in the context of Southern Ocean surface climate variations since 1950. Geophysical Research Letters 141, 2419–2426 (2014). source

  • May combine two claims.

    Interpretationreasoning

    The results of exponential decay fits are sensitive to the temporal resolution of the data, the definition of persistence, and the time window over which the fit is made.

    “The results are then sensitive to the temporal resolution of the data used, the definition of persistence and the time window over which the exponential fit is made.”
    Quote in the paperSubstantial claim

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

    Interpretationnone given

    In the South Pacific, both ERSST and HadISST products will relax towards the SST prior in the absence of observations.

    “So in the South Pacific, both ERSST and HadISST products will relax towards the SST prior in the absence of observations.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationreasoning

    SSTAs are advected within the ocean over time, and in high-resolution data there is greater likelihood that an anomaly re-emerges in a different resolved location.

    “SSTAs are advected within the ocean over time, and in high-resolution data there is greater likelihood that an anomaly re-emerges in a different resolved location.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    It is common practice to represent anomaly decay over time using an exponential function.

    “it is common practice to represent anomaly decay over time using an exponential function16,57.”
    Quote in the paperSubstantial claim0 of 2 sources checked
    • cites [16] de Coetlogon, G. & Frankignoul, C. The Persistence of Winter Sea Surface Temperature in the North Atlantic. Journal of Climate 16, 1364–1377 (2002). source
    • cites [57] Deser, C., Alexander, M. & Timlin, M. S. Understanding the Persistence of Sea Surface Temperature Anomalies in Midlatitudes. Journal of Climate 16, 57–72 (2003). source

  • May combine two claims.

    Study design and conductreasoning

    Using decad products increases the temporal resolution of the data over monthly averages, resolving mesoscale features whilst ensuring independence by recognising the temporal error correlation in the analysis product of order 3 days.

    “Using decad products increases the temporal resolution of the data over monthly averages, resolving mesoscale features whilst ensuring independence by recognising the temporal error correlation in the analysis product; of order 3 days due to the analysis observation window.”
    Quote in the paperSubstantial claim
61 of 61

  • The authors state this as an assumption.

    The daily data are fully correlated over the spatial scale when regridding from 0.05° to 0.25°.

    “assuming that these data are fully correlated over this spatial scale”

  • The authors state this as an assumption.

    The temporal correlation length scale is 3 days and the spatial correlation is 100 km for uncertainty propagation.

    “assuming a temporal correlation length scale of 3 days and a spatial correlation of 100 km”
2 of 2

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.

  • NE Pacific region has conflicting boundaries

    Major

    The introduction identifies the NE Pacific region of interest as 45-55 N, 130-150 W, whereas the Figure 1 caption gives substantially different bounds for the NE Pacific time series.

  • September correlation panel is misidentified

    Minor

    The text cites panel 4c for the period starting in September, but the Figure 4 caption assigns September to panel 4d.

2 of 2

Cites

Flagged first, then by citations

2 of the 77 references couldn’t be matched to a known paper.

Research works printed but not linked: 6

  1. Hartmann, D. L., Albert M. G, Klein T. & Rusticucci, M. Intergovernmental Panel on Climate Change, Climate Change 2013, Physical Science Basis, Chapter 2: Observations: Atmosphere and Surface, https://www.ipcc.ch/report/ar5/wg1/ (2013).
  2. Casey, K. S. & Cornillon, P. A Comparision of Satellite and In Situ-Based Sea Surface Temperature Climatologies. Journal of Climate 12, 1848–1863 (1998). · DOI
  3. Hanley, D. E., Bourassa, M. A., O’Brien, J. J., Smith, S. R. & Spade, E. R. A Quantitative Evaluation of ENSO Indices. Journal of Climate 16, 1249–1258 (2003). · DOI
  4. Rayner, N. A. & Kennedy, J. J. Comparison of satellite and in situ measured estimates of sea surface temperature focusing on the ESA Climate Change Initiative v2.1 products. Earth and Space Science (In review, 2020).
  5. Reynolds, R. W., Rayner, N. A., Smith, T. M., Stokes, D. C. & Wang, W. An Improved In Situ and Satellite SST Analysis for Climate. Journal of Climate 15, 1610–1625 (2002). · DOI
  6. Armour, K. C. & Bitz, C. M. Observed and projected trends in Antarctic sea ice. US CLIVAR Variations 13, 12–19 (2015).

Cited by

Sorted by citations

Related

Authors
Bulgin, C. E., Merchant, C. J., & Ferreira, D.
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2020-05-14
Volume
10
Issue
1
Pages
7986-7986
ISSN
2045-2322 (ISSN-L)
DOI
10.1038/s41598-020-64785-9
PMC
PMC7224223
OpenAlex
W3022238508
Semantic Scholar
f041011a9c371300f8eead5b48479ed7375a5023
Cited by
150
References
77
Citations by year
2026: 15 · 2025: 24 · 2024: 39 · 2023: 21 · 2022: 27 · 2021: 24
FWCI
6.55
Type
journal article
Language
en
Open access
Licence
Locations
  • Scientific Reports (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • CentAUR (University of Reading) (acceptedVersion)
  • PubMed Central (submittedVersion, cc-by)
Funders
  • European Space Agency
  • Sight Research UK (NE/R016518/1, nceo020006)
  • Natural Environment Research Council (nceo020006, NE/R016518/1)
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Climate variability and models
  • Physical Sciences › Earth and Planetary Sciences › Oceanography › Oceanographic and Atmospheric Processes
  • Physical Sciences › Earth and Planetary Sciences › Oceanography › Marine and coastal ecosystems
Keywords
sea surface temperature anomalies, ocean variability, power spectrum, ENSO, western boundary currents, mesoscale variability, mixed layer depth, seasonal variation, global ocean warming

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.

Cited sources are checked by gpt-6-sol.

Statistics and arithmetic are recomputed, not judged.

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