Tropical cyclones dissipate large amounts of energy into the upper ocean, locally enhancing vertical mixing and cooling the sea surface. In this study, we investigate how the response of the ocean to tropical cyclones is affected by additional mixing from unbroken surface waves. This “Surface Wave Mixing” (SWM) is represented by a novel parameterization, in which the wave orbital motion contributes directly to the production of turbulent kinetic energy. The parameterization is implemented here as a modification to the k‐ε turbulence scheme, used within an ocean model with 1/4° horizontal resolution (MOM5). This model is forced with idealized tropical cyclone wind fields based on observed case studies. Relative to simulations without SMW, the inclusion of SWM leads to surface temperature differences of around 0.5°C near the storm track, typically with warm anomalies on the side with the strongest winds and cool anomalies in other regions. This pattern is explained by an initial wave‐induced deepening of the mixed layer, which can modify the subsequent shear‐induced entrainment and upwelling. The temperature anomalies from SWM could potentially influence tropical cyclone intensity and structure.

Sea surface temperature (SST) products that can resolve fine scale features, such as sub-mesoscale eddies, ocean fronts and coastal upwelling, are increasingly in demand. In response to user requirements for gap-free, highest spatial resolution, best quality and highest accuracy SST data, the Australian Bureau of Meteorology (BoM) produces operational, real-time Multi-sensor SST level 3 products by compositing SST from Advanced Very-High-Resolution Radiometer (AVHRR) sensors on Meteorological Operational satellite (MetOp)-B and National Oceanic and Atmospheric Administration (NOAA) 18, along with SST from Visible Infrared Imaging Radiometer Suite (VIIRS) sensors on the Suomi National Polar-orbiting Partnership (Suomi NPP) and NOAA 20 polar-orbiting satellites for the Australian Integrated Marine Observing System (IMOS) project. Here we discuss our method to combine data from different sensors and present validation of the satellite-derived SST against in situ SST data. The Multi-sensor Level 3 Super Collated (L3S) SSTs exhibit significantly greater spatial coverage and improved accuracy compared with the pre-existing IMOS AVHRR-only L3S SSTs. When compared to the Geo Polar Blended level 4 analysis SST data over the Great Barrier Reef, Multi-sensor L3S SST differs by less than 1 ${}^{°}$C while exhibiting a wider range of SSTs over the region. It shows more variability and restores small-scale features better than the Geo Polar Blended level 4 analysis SST data. The operational Multi-sensor L3S SST products are used as input for applications such as IMOS OceanCurrent and the BoM ReefTemp Next-Generation Coral Bleaching Nowcasting service and provide useful insight into the study of marine heatwaves and ocean upwelling in near-coastal regions.

A new parameterization of mixing processes in the upper ocean is tested in a ¼° resolution global ocean climate model. The parameterization represents the effect of turbulent mixing by unbroken waves as an additional turbulent shear production term in the k‐epsilon mixing scheme. The results show that the inclusion of this parameterization has a noticeable effect on ocean climate, particularly in regions of high wave activity such as the Southern Ocean. Inclusion of this process also leads to some reduction in the biases of the simulated climate, including mixed layer depth, compared with available observations.

This study has evaluated five years (2016–2020) of Himawari-8 (H8) Sea Surface Temperature (SST) Level 2 Pre-processed (L2P) data produced by the Australian Bureau of Meteorology (Bureau) against shipborne radiometer SST measurements obtained from the Infrared SST Autonomous Radiometer (ISAR) onboard research vessel RV Investigator. Before being used, all data sets employed in this study have gone through careful quality control, and only the most trustworthy measurements are retained. With a large matchup database (31,871 collocations in total, including 16,418 during daytime and 15,453 during night-time), it is found that the Bureau H8 SST product is of good quality, with a mean bias ± standard deviation (SD) of −0.12 °C ± 0.47 °C for the daytime and −0.04 °C ± 0.37 °C for the night-time. The performance of the H8 data under different environmental conditions, determined by the observations obtained concurrently from RV Investigator, is examined. Daytime and night-time satellite data behave slightly differently. During the daytime, a cold bias can be seen under almost all environmental conditions, including for most values of wind speed, SST, and relative humidity. On the other hand, the performance of the night-time H8 SST product is consistently more stable under most meteorological conditions with the mean bias usually close to zero.

As the ocean has warmed, in recent decades marine heatwaves (MHWs) have emerged as a major threat to marine ecosystems and ecosystem services, presenting challenges for management of marine fisheries, aquaculture, tourism, and conservation, including for marine protected areas (MPAs). An MHW is a period of unusually high ocean temperatures, often defined as ocean temperatures that are warmer than 90% of the previous observations for a given time of year. MHWs along Australia’s coastal regions have led to mass coral bleaching on the Great Barrier Reef, damage to kelp forests and seagrass meadows in Western Australia, shifts in species, and fish and invertebrate mortality, all creating pressures on fisheries management (as reviewed in Smith et al., 2023). Understanding how climate change influences ocean extremes and impacts societal and natural values is key for evaluating future risks. Growing concerns around the effects of MHWs on marine industries, food security, ecosystem dynamics, and conservation efforts led to the development of MHW response plans for Tasmania and New South Wales during the summer of 2023/24 (Hobday et al., 2024).

Oceanic fronts play a significant role in marine ecosystems by enhancing vertical exchange, promoting the aggregation of plankton, and drawdown of organic carbon. Anthropogenic emission of carbon dioxide and other greenhouse gases in the twentieth century has driven global warming, leading to rising ocean temperatures. Specific regions warming faster than the global average—known as ‘ocean warming hotspots’—have been identified, impacting geophysical and biogeochemical dynamics of local ecosystems. Here, we aim to characterize the variability of sea surface temperature (SST) fronts in the southeast and southwest Australia hotspots. Using a histogram frontal detection method, we derived fronts from AVHRR-only and Multi-sensor 6-day SST composites on a 0.02 × 0.02 grid between January 1993 and December 2019. Our results indicate that frontal frequency and frontal density have increased in both regions in the past three decades, by around 0.2–0.3%. In addition, both regions exhibit higher frequency and density of fronts in austral winter and fewer in austral summer. Our calculations show that changes in frontal frequency/density show some relationship to El Niño-Southern Oscillation and Indian Ocean Dipole. Changes in frontal activity could strongly impact local ocean biogeochemistry and marine ecosystems. A better understanding changing fronts in hotspots will help predict and manage future changes in regional oceans to warming.