Heat Extremes and the Changes Occurring in Marine Systems

By Laura ThomsonFeb 15 2022

The US Climate Normal is calculated by the National Oceanic and Atmospheric Administration (NOAA) using decadal averages of temperature and precipitation from the most recent climatological period. While the US Climate Normal can help predict what will happen locally in the near future, fixed historical standards may be better for characterizing current climate shifts and ecological disturbances.

Image Credit: Don Pablo/Shutterstock.com

The idea that exceptional climate norms are evolving in the ocean has been fostered by persistent warming of sea surface temperatures (SST) and increased frequency and severity of intense climatic occurrences. The identification and attributions of extreme marine heat occurrences under observed and modeled climate variability have received a lot of interest. Hobday devised a method for calculating the frequency and intensity of maritime heatwaves (MHWs).

Researchers have developed new statistical frameworks that allow for a more flexible characterization of extreme maritime heat events based on locally specified fixed or sliding baselines and a seasonally changing threshold (e.g., 90^th) that may be used to a wide range of spatial and temporal scales.

Background warming enhances the severity, frequency, and length of severe occurrences, according to the statistical study of past, current, and future extreme events. However, little is known about how extreme occurrences, particularly those linked to warming, have developed historically to become the new normal as a result of global warming.

While these projection-based studies are critical to climate adaptation efforts, the stochastic character of global climate systems can lead to significant errors and biases.

All Exclusive Economic Zones, Biogeochemical Provinces, and Large Maritime Ecosystems were studied for variations in the frequency of historical marine heat extremes. The goal of this study is to characterize the growth and expansion of extreme heat in the worldwide ocean, as well as to identify places with the highest and lowest frequency of extreme heat.

The current work is to contextualize the current state of marine regions, indicating current climate disruptions and ecosystem risk, as well as to offer a timeline for the global ocean when historically benchmarked extreme events took place more than 50% of the time, indicating that they have become “normal.”

Methodology

To examine centennial variations in worldwide occurrences of extreme marine heat events, the study utilized 150 years (1870–2019) of monthly reconstructed historical SST data sources: the Hadley Centre Sea Ice and SST dataset and the Characteristics of the Global SST data (COBESSTv2).

To illustrate any differences in the technique, the researchers compared the LEHI’s worldwide variability to a more standard SST anomaly measure. Researchers used the R programming environment to do all of our data manipulation and analysis. The data and scripts are shared through open access repositories and the Open Science Framework.

Results

From 1980 to 2019, Figure 1 depicts the decadal development of worldwide extreme maritime heat events.

Figure 1. Decadal evolution of frequency of extreme marine heat from 1980–2019. Extreme heat defined as exceeding the localized (1° × 1°), monthly, 98^th percentile of sea surface temperatures (SST) observed during 1870–1919, averaged from HadISSTv1.1 and COBESSTv2 products. Extreme heat, resolved for boreal winter (Jan-Mar) and summer (Jul-Sep), accumulates steadily over time beginning in the Southern, South Atlantic, and Indian basins. Regions of the mid North Atlantic and eastern South Pacific indicate a low occurrence. The base map layer was drawn using the “rworldmap” R package. Image Credit: Tanaka and Van Houtan, 2022

Figure 2. shows the EEZs, LMEs, and BGCPs where the present ocean climate stress is most intense are highlighted in the current LEHI summary from 2010–2019.

Figure 2. Regional variability of frequency of extreme marine heat during 2010–2019. Summaries for (a) biogeochemical provinces (b) Large marine ecosystems and (c) Exclusive economic zones, displaying the outer 15 regions (30 total) from larger sets of 55, 66, and 142 regions, respectively. Regions are ranked and sorted by median extreme value. Image Credit: Tanaka and Van Houtan, 2022

Figure 3 indicates a rise from <20% in the early 1900s to >50% in the 2010s in the proportion of global and regional ocean surfaces above the 1870–1919 extreme event threshold.

Figure 3. Synoptic frequency of extreme marine heat across ocean basins from 1900–2019. Fraction of the ocean surface annually experiencing extreme heat, grouped by (a) northern hemisphere and (b) southern hemisphere and Indian ocean basins. The Point of No Return (PoNR) occurs when each series surpasses and remains above 50% (dashed grey line), or when the historical baseline of extreme heat becomes “normal”. This first occurs in 1998 in the South Atlantic basin and for the global ocean occurs in 2014. Image Credit: Tanaka and Van Houtan, 2022

To give an additional climatic stress assessment at each moment in time, the geographical distribution of normalized LEHI may be compared to traditional climate indices calculated from IPCC-relevant data (1956–2005) in Figure 4.

Figure 4. Comparing extreme marine heat metrics for the year 2019. (a) Mean anomaly and (b) percent extreme heat for the global ocean where both series have baselines determined from 1870–1919. Regions in the 99th percentile for each series (+1.4 °C and 100% extreme, respectively) are highlighted in green. This metric constitutes 7% of the global ocean in the extreme heat series, (b) but only 1% for the more traditional mean anomaly approach, (a). The base map layer was drawn using the “rworldmap” R package. Image Credit: Tanaka and Van Houtan, 2022

Discussion

The method was based on a statistical framework that is routinely used to study variations in the occurrence of univariate climatic severe events over time and region. These findings are in line with prior research that showed the development of climate signals, which were previously undetectable at regional sizes.

Reconstructed data are often more reliable, particularly at the time when global or near-global in situ data were accessible, therefore detecting climate change impacts within a historical context has significant advantages. Historical records can also give fresh insights and empirical evidence for understanding the significance of non-equilibrium dynamics and the cumulative effects of unique thermal disturbances that have previously occurred in many areas.

Extreme marine heat occurrences can be normalized in a historical ecological context to assess the altering baseline of ocean health and identify climate susceptible places. If this trend continues, or worse, if heat extremes continue to rise, many ecosystems will be pushed beyond their thermal tolerance, leading to irreversible alterations. Extensive coral bleaching, mass death events, and toxic algal blooms have all been reported as negative effects of high maritime heat events.

Simultaneously, extreme climatic event classification and evaluation have become crucial criteria for a wide variety of policy choices. This research provides a solid historical framework for describing excessive maritime heat to better understand climate change implications at different geographical and temporal scales. Our efforts to improve public awareness and trust in severe climatic occurrences and their attribution to manmade climate change will continue.

Using the methodologies used here, the study identified that extreme climate change is a historical event that has already occurred in the global ocean, rather than a hypothetical future potential. Even though certain parts experienced excessive heat earlier, 50% of the ocean’s surface suffered extreme heat in 2014, and this has gradually grown since then.

Journal Reference

Tanaka, K. R., & Van Houtan, K. S. (2022). The recent normalization of historical marine heat extremes. PLOS Climate, 1(2), p.e0000007. Available Online: https://journals.plos.org/climate/article?id=10.1371/journal.pclm.0000007.

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