Methods

We used 150 years (1870–2019) of gridded, monthly reconstructed historical SST data sources to evaluate centennial changes in global occurrences of extreme marine heat events: the Hadley Centre Sea Ice and SST dataset (HadISSTv1.1) [33] and the Characteristics of the Global SST data (COBESSTv2) [34] (Table A in S1 File). These independent and complementary global SST products were reconstructed from instrument records and the historical network of in situ measurements and have been widely deployed as ground-truthed SST fields [35, 36].

Our statistical definitions frame how we characterized the frequency and extent of extreme heat events across space and time. For each month, in each 1° × 1° grid, we defined the extreme marine heat as a monthly average SST value that exceeds the 98^th percentile SST value observed over 1870–1919 (corresponds to the period of second industrial revolution), or hottest temperature observed in the earliest 50-year period of record (Fig A in S1 File) [37–39]. Such percentile based thresholds can be derived from climatological data and are robust to drivers or variabilities associated with individual extreme events [10]. Our particular percentile based threshold also easily relates to the standard deviation (σ) which offers an alternative expression of dataset anomaly–the 98^th percentile is when σ = 2.05. Though they are limited in describing daily and hourly extremes, we selected monthly SST products in order to evaluate the properties of extreme marine heat events at a 1° × 1° scale within the longest historical context possible– 150 years. At daily scales, species may respond to stressful abnormal temperatures by changing distributions but could suffer greater thermal-induced stress if an extreme heat event persists beyond one month. In addition, extreme heat events at shorter time scales are more likely to be smaller in scale than our analyzed spatial units (e.g., EEZs, large marine ecosystems). Furthermore, statistical analysis of monthly-resolved temperature variations can offer centennial-scale proxies of the frequency of extreme heat event properties [11].

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Next, to highlight any different information presented in our approach, we compared the global variability of the LEHI to a more traditional SST anomaly metric. For the year 2019, we computed both spatial outputs from the same 1870–1919 climatology and the same spatial scale (1° × 1°) to ensure that any differences are from the methodology alone. SST anomalies are widely used and an important impact parameter in climate extreme studies [10, 11, 21]. The difference in distributions of two climate indices derived from the same baseline period offers an alternative assessment of climate stress from the conventional anomaly-from-mean signals.

We conducted all data wrangling and analyses in the R programming environment [43], and provided our data and scripts in open access repositories (https://bit.ly/2QjhYld) and through the Open Science Framework (https://osf.io/mj8u7/).

This extract is from: Tanaka KR, Van Houtan KS (2022) The recent normalization of historical marine heat extremes. PLOS Clim 1(2): e0000007. https://doi.org/10.1371/journal.pclm.0000007