A stakeholder-guided marine heatwave hazard index for fisheries and aquaculture

Marine heatwaves pose an increasing threat to fisheries and aquaculture around the world under climate change. However, the threat has not been estimated for the coming decades in a form that meets the needs of these industries. Tasmanian fisheries and aquaculture in southeast Australia have been severely impacted by marine heatwaves in recent years, especially the oyster, abalone, and salmon industries. In a series of semi-structured interviews with key Tasmanian fishery and aquaculture stakeholders, information was gathered about the following: (i) the impacts they have experienced to date from marine heatwaves, (ii) their planning for future marine heatwaves, and (iii) the information that would be most useful to aid planning. Using CMIP6 historical and future simulations of sea surface temperatures around Tasmania, we developed a marine heatwave hazard index guided by these stakeholder conversations. The region experienced a severe marine heatwave during the austral summer of 2015/16, which has been used here as a reference point to define the index. Our marine heatwave hazard index shows that conditions like those experienced in 2015/16 are projected to occur approximately 1-in-5 years by the 2050s under a low emissions scenario (SSP1-2.6) or 1-in-2 years under a high emissions scenario (SSP5-8.5). Increased frequency of marine heatwaves will likely reduce productivity by both direct (mortality) and in-direct (ecosystem change, greater incidence of disease) impacts on target species. The illustrative hazard index is one step towards a marine heatwave risk index, which would also need to consider aspects of exposure and vulnerability to be of greater utility to stakeholders

Predictability of marine heatwaves off Western Australia using a linear inverse model

Marine heatwaves (MHWs) off Western Australia (110°E−116°E, 22°S−32°S; hereafter, WA MHWs) can cause devastating ecological impacts, as was evidenced by the 2011 extreme event. Previous studies suggest that La Niña is the major large-scale driver of WA MHWs, while Indian Ocean Dipole (IOD) may also play a role. Here, we investigate historical WA MHWs and their connections to these large-scale climate modes in an ocean model (ACCESS−OM2) simulation driven by a prescribed atmosphere from JRA55−do over 1959–2018. Rather than analysing sea surface temperature, the WA MHWs and climate mode indices were characterized and investigated in vertically averaged temperature (VAT) to ~300m depth to afford the longer ocean dynamic time scales, including remote oceanic connections. We develop a cyclostationary linear inverse model (CS-LIM; from 35°S−10°N, across the Indo-Pacific Ocean), to investigate the relative contributions of La Niña VAT and positive IOD VAT to the predictability of WA VAT MHWs. Using a large ensemble of CSLIM simulations, we found that ~50% of WA MHWs were preceded about 5 months by La Niña, and 30% of the MHWs by positive IOD about 20 months prior. While precursor La Niña or positive IOD, on their own, were found to correspond with increased WA MHW likelihood in the months following (~2.7 times or ~1.5 times more likely than by chance, respectively), in combination these climate mode phases were found to produce the largest enhancement in MHW likelihood (~3.2 times more likely than by chance). Additionally, we found that stronger and longer La Niña and/or positive IOD tend to lead stronger and longer WA MHWs

Impacts of marine heatwaves on tropical western and central Pacific Island nations and their communities

Marine heatwaves can have devastating impacts on marine species and habitats, often with flow-on effects to human communities and livelihoods. This is of particular importance to Pacific Island countries that rely heavily on coastal and ocean resources, and for which projected increases in future marine heatwave (MHW) frequency, intensity, and duration could be detrimental across the Pacific Island region. In this study, we investigate MHWs in the tropical western and central Pacific Ocean region, focusing on observed MHWs, their associated impacts, and future projections using Coupled Model Intercomparison Project phase 6 (CMIP6) simulations under a low (SSP1–2.6) and a high (SSP5–8.5) greenhouse gas emissions scenario. Documented impacts from “Moderate” mean intensity MHW events in Fiji, Samoa, and Palau, that were categorised as “Strong” at their peak, included fish and invertebrate mortality and coral bleaching. Based on CMIP6 multi-model mean estimates, and relative to current baselines, “Moderate” intensity MHWs are projected to increase from recent historical (1995–2014) values of 10–50 days per year (dpy) across the region to the equivalent of >100 dpy by the year 2050 under the low emissions scenario, and > 200 dpy nearer the equator. Under the high emissions scenario, 200 dpy of Moderate MHW intensities are projected across most of the region by 2050, with >300 dpy nearer the equator. For the most intense “Extreme” category of MHW, estimates range from 50 dpy projected under the high emissions scenario by 2050. In contrast, “Extreme” MHWs are projected to increase to <5 dpy by 2050 under the low emissions scenario, highlighting the importance for Pacific Island nations that global emissions more closely follow the low emissions scenario trajectory

Model under-representation of decadal Pacific trade wind trends and its link to tropical Atlantic bias

The strengthening of the Pacific trade winds in recent decades has been unmatched in the observational record stretching back to the early twentieth century. This wind strengthening has been connected with numerous climate-related phenomena, including accelerated sea-level rise in the western Pacific, alterations to Indo-Pacific ocean currents, increased ocean heat uptake, and a slow-down in the rate of global-mean surface warming. Here we show that models in the Coupled Model Intercomparison Project phase 5 underestimate the observed range of decadal trends in the Pacific trade winds, despite capturing the range in decadal sea surface temperature (SST) variability. Analysis of observational data suggests that tropical Atlantic SST contributes considerably to the Pacific trade wind trends, whereas the Atlantic feedback in coupled models is muted. Atmosphere-only simulations forced by observed SST are capable of recovering the time-variation and the magnitude of the trade wind trends. Hence, we explore whether it is the biases in the mean or in the anomalous SST patterns that are responsible for the under-representation in fully coupled models. Over interannual time-scales, we find that model biases in the patterns of Atlantic SST anomalies are the strongest source of error in the precipitation and atmospheric circulation response. In contrast, on decadal time-scales, the magnitude of the model biases in Atlantic mean SST are directly linked with the trade wind variability response

Atlantic meridional overturning circulation observed by the RAPID-MOCHA-WBTS (RAPID-Meridional Overturning Circulation and Heatflux Array-Western Boundary Time Series) array at 26N from 2004 to 2023 (v2023.1)

The RAPID-MOCHA-WBTS (RAPID-Meridional Overturning Circulation and Heatflux Array-Western Boundary Time Series) programme has produced a continuous time series of the Atlantic Meridional Overturning Circulation (AMOC) at 26N that started in April 2004. This release of the time series covers the period from April 2004 to February 2023. The 26N AMOC time series is derived from measurements of temperature, salinity, pressure and water velocity from an array of moored instruments that extend from the east coast of the Bahamas to the continental shelf off Africa east of the Canary Islands. The AMOC calculation also uses estimates of the transport in the Florida Strait derived from sub-sea cable measurements calibrated by regular hydrographic cruises. The component of the AMOC associated with the wind driven Ekman layer is derived from ERA5 reanalysis. This release of the data includes a document with a brief description of the calculation of the AMOC time series and references to more detailed description in published papers. The 26N AMOC time series and the data from the moored array are curated by the British Oceanographic Data Centre (BODC). The RAPID-MOCHA-WBTS programme is a joint effort between NERC in the UK (Principal Investigator Ben Moat since 2021, Eleanor Frajka-Williams since 2020 to 2021, David Smeed 2012 to 2020, and Stuart Cunningham from 2004 to 2012), NOAA (PIs Ryan Smith and Denis Volkov) and NSF (PIs Prof. Bill Johns and Prof. Shane Elipot, Uni. Miami) in the USA

Pantropical climate interactions.

The El Niño-Southern Oscillation (ENSO), which originates in the Pacific, is the strongest and most well-known mode of tropical climate variability. Its reach is global, and it can force climate variations of the tropical Atlantic and Indian Oceans by perturbing the global atmospheric circulation. Less appreciated is how the tropical Atlantic and Indian Oceans affect the Pacific. Especially noteworthy is the multidecadal Atlantic warming that began in the late 1990s, because recent research suggests that it has influenced Indo-Pacific climate, the character of the ENSO cycle, and the hiatus in global surface warming. Discovery of these pantropical interactions provides a pathway forward for improving predictions of climate variability in the current climate and for refining projections of future climate under different anthropogenic forcing scenarios

Pantropical climate interactions

The El Nino-Southern Oscillation (ENSO), which originates in the Pacific, is the strongest and most well-known mode of tropical climate variability. Its reach is global, and it can force climate variations of the tropical Atlantic and Indian Oceans by perturbing the global atmospheric circulation. Less appreciated is how the tropical Atlantic and Indian Oceans affect the Pacific. Especially noteworthy is the multidecadal Atlantic warming that began in the late 1990s, because recent research suggests that it has influenced Indo-Pacific climate, the character of the ENSO cycle, and the hiatus in global surface warming. Discovery of these pantropical interactions provides a pathway forward for improving predictions of climate variability in the current climate and for refining projections of future climate under different anthropogenic forcing scenarios