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DOISST v2.1 noise steps make 1985-2023 coral heat-stress (DHW) trends 11-16% too low at 1,763 reef pixels; mean-warming differences between products are a larger uncertainty

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Question: NOAA DOISST v2.1 lost fast (day-to-day) SST variance in steps at satellite input changes. Degree Heating Weeks (DHW), the standard coral bleaching heat-stress index, adds only SST excesses of 1 C or more above the warmest-month mean, so it is a convex function of daily SST. Do the noise steps bias reef DHW trends? Approach: At 1,763 DOISST reef pixels (sites of a global coral-bleaching database), we calculated Coral Reef Watch statistics (CoralTemp v3.1 method) for raw DOISST and for three versions in which the spectrum at periods shorter than about 32 days is homogenised to one input segment. We tested the method on synthetic data, at 149 moorings (97 GTMBA, 52 NDBC; 2,816 buoy-years) on matched days, and against ESA SST CCI v3.0.1 on every day of 1982-2024 at 683 reef pixels in three boxes. Results: Relative to 2007-2015, reef 4-8 day power was 1.86 times larger in 1985-2006 and 0.29 times smaller after 2021. The 1985-2023 trend of annual maximum DHW was +0.92 C-weeks per decade (0.66 to 1.18) in raw DOISST and +1.04 to +1.10 after homogenisation; the trend of the reef fraction at DHW >= 4 was +9.8% and +10.4 to +11.7% per decade. Raw DOISST overstates 1985-2006 heat stress (mean annual maximum DHW 1.67 against 1.41 C-weeks) and understates 2022-2025 heat stress (6.35 against 6.66). Homogenisation recovered the synthetic truth (0.980 against 0.983). At 74 GTMBA moorings, after removal of the DOISST-minus-buoy mean warming drift (median +0.04 C per decade), the raw DOISST-minus-buoy DHW trend was -0.13 C-weeks per decade (-0.22 to -0.04) and the homogenised trend was +0.005 (-0.08 to +0.09); without this removal the two errors cancel. In the boxes, CCI gave +0.56 C-weeks per decade and DOISST +1.05; DOISST with the CCI mean warming gave +0.60, so about 90% of the product difference is the mean warming trend (DOISST +0.06 C per decade faster). Conclusion: The input steps make DOISST DHW trends too low by about 11-21%, opposite in sign to the heatwave-duration bias. Differences in mean warming between products change reef DHW trends by a factor of about two. Limitations: the true fast variance is unknown; moorings are not at reefs and are DOISST inputs; CCI has its own variance changes and covers three boxes to 2023; we did not test the CoralTemp product or bleaching observations.

degree heating weeks · coral bleaching · sea surface temperature · OISST · DOISST · ESA SST CCI · data homogeneity · satellite input change · heat stress · Coral Reef Watch · spectral homogenisation · moored buoys · TAO/TRITON · climate data record · marine heatwaves

References

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  1. supportsMost of the 1982-2025 rise in daily SST memory in DOISST v2.1 is a loss of fast variance that steps at satellite input changes and is absent in 34 NDBC buoys
  2. uses, supportsStep changes in OISST v2.1 product noise cause most of the 1982-2025 rise in daily SST-anomaly persistence; 126 moored buoys show no clear rise
  3. uses, supportsESA CCI v3 and buoys show no 1982-2023 change in the slow decay of daily SST anomalies; DOISST v2.1 variance steps cause half its memory trend, its slow-decay rise and a false variance fall
  4. supportsNoise steps cause 30-55% of the 1982-2025 marine heatwave duration rise in OISST v2.1, hide a peak-intensity rise and reverse the cold-spell duration trend at 60S-60N; heatwave-day trends are robust
  5. supportsOISST v2.1 input steps bias 1982-2025 trends of daily SST extremes and marine heatwaves; cold-spell lengthening is an artifact and heatwave-duration trends depend on product noise
  6. DOISST v2.1 input changes put steps of up to x3 into 1982-2024 SST front statistics that ESA CCI v3 lacks; CCI steps at its own sensor changes, and with step terms both agree on small trends
  7. Satellite input changes step the spatial detail of DOISST v2.1 and ESA CCI v3 daily SST and cause most 1982-2021 trends of SST front fraction and small-scale variance (60S-60N)
  8. Daily OISST v2.1 shows a near tripling of 1-day SST memory in 1982-2025, but it comes from less day-to-day variance and a 2022 input step; other products show no common weekly or monthly rise
  9. usesdoi:10.3390/rs12233856
  10. usesdoi:10.3390/rs61111579
  11. usesdoi:10.1175/JCLI-D-20-0166.1
  12. useshttps://downloads.psl.noaa.gov/Datasets/noaa.oisst.v2.highres/
  13. useshttps://www.ncei.noaa.gov/products/optimum-interpolation-sst
  14. usesdoi:10.5285/4a9654136a7148e39b7feb56f8bb02d2
  15. usesdoi:10.1038/s41597-024-03147-w
  16. usesdoi:10.1038/s41597-022-01121-y
  17. useshttps://www.bco-dmo.org/dataset/773466
  18. useshttps://www.ndbc.noaa.gov/data/historical/stdmet/
  19. useshttps://data.pmel.noaa.gov/pmel/erddap/tabledap/pmelTaoDySst.html
  20. doi:10.1038/s41558-025-02245-w

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