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Abstract We investigate changes in the vertical structure of the ocean temperature annual cycle amplitude (TEMP_AC) down to a depth of 300 m, providing important insights into the relative contributions of anthropogenic and natural influences. Using observations and phase 6 of the Coupled Model Intercomparison Project (CMIP6) simulations, we perform a detection and attribution analysis by applying a standard pattern-based “fingerprint” method to zonal-mean TEMP_ACanomalies for three major ocean basins. In all model historical simulations and observational datasets, TEMP_ACincreases significantly in the surface layer, except in the Southern Ocean, and weakens within the subsurface ocean. There is a decrease in TEMP_ACbelow the annual-mean mixed layer depth, mainly due to a deep-reaching winter warming signal. The temporal evolution of signal-to-noise (S/N) ratios in observations indicates an identifiable anthropogenic fingerprint in both surface and interior ocean annual temperature cycles. These findings are consistent across three different observational datasets, with variations in fingerprint detection time likely related to differences in dataset coverage, interpolation method, and accuracy. Analysis of CMIP6 single-forcing simulations reveals the dominant influence of greenhouse gases and anthropogenic aerosols on TEMP_ACchanges. Our identification of an anthropogenic TEMP_ACfingerprint is robust to the selection of different analysis periods. S/N ratios derived with model data only are consistently larger than ratios calculated with observational signals, primarily due to model versus observed TEMP_ACdifferences in the Atlantic. Human influence on the seasonality of surface and subsurface ocean temperature may have profound consequences for fisheries, marine ecosystems, and ocean chemistry. Significance StatementThe seasonal cycle is a fundamental aspect of our climate, and gaining insight into how anthropogenic forcing has impacted seasonality is of scientific, economic, and societal importance. Using observations and CMIP6 model simulations, this research applies a pattern-based detection and attribution method to ocean temperature annual cycle amplitude (TEMP_AC) down to 300 m across three major ocean basins. Key findings reveal significant increases in surface layer TEMP_ACexcept in the Southern Ocean and a weakening of TEMP_ACwithin the subsurface ocean. Importantly, the analysis confirms human influence on TEMP_AC. These findings underscore the profound influence of human-caused climate change on the world’s oceans and have important implications for marine ecosystems, fisheries, and ocean chemistry. 

We provide the first scientific evidence that a human-caused signal in the seasonal cycle of sea surface temperature (SST) has emerged from the background noise of natural variability. Geographical patterns of changes in SST seasonal cycle amplitude (SSTAC) reveal two distinctive features: an increase at mid-latitudes in the Northern Hemisphere related to mixed-layer depth changes, and a robust dipole pattern between 40˚S and 55˚S in the Southern Hemisphere which is mainly driven by surface wind changes. The model-predicted pattern of SSTAC change is identifiable with high statistical confidence in four observed SST products and in 51 individual model realizations of historical climate evolution. Simulations with individual forcing reveal that greenhouse gas increases drive most of the change in SSTAC, with smaller but distinct contributions from anthropogenic aerosol and ozone forcing. The robust human influence identified here on the seasonality of SST is likely to have wide-ranging impacts on marine ecosystems. 

Modeled water-mass changes in the North Pacific thermocline, both in the subsurface and at the surface, reveal the impact of the competition between anthropogenic aerosols (AAs) and greenhouse gases (GHGs) over the past 6 decades. The AA effect overwhelms the GHG effect during 1950–1985 in driving salinity changes on density surfaces, while after 1985 the GHG effect dominates. These subsurface water-mass changes are traced back to changes at the surface, of which ~70% stems from the migration of density surface outcrops, equatorward due to regional cooling by AAs and subsequent poleward due to warming by GHGs. Ocean subduction connects these surface outcrop changes to the main thermocline. Both observations and models reveal this transition in climate forcing around 1985 and highlight the important role of AA climate forcing on our oceans’ water masses. 

Abstract The Global Ocean Biogeochemistry (GO-BGC) Array is a project funded by the US National Science Foundation to build a global network of chemical and biological sensors on Argo profiling floats. The network will monitor biogeochemical cycles and ocean health. The floats will collect from a depth of 2,000 meters to the surface, augmenting the existing Argo array that monitors ocean temperature and salinity. Data will be made freely available within a day of being collected via the Argo data system. These data will allow scientists to pursue fundamental questions concerning ocean ecosystems, monitor ocean health and productivity, and observe the elemental cycles of carbon, oxygen, and nitrogen through all seasons of the year. Such essential data are needed to improve computer models of ocean fisheries and climate, to monitor and forecast the effects of ocean warming and ocean acidification on sea life, and to address key questions identified in “Sea Change: 2015‐2025 Decadal Survey of Ocean Sciences” such as: What is the ocean's role in regulating the carbon cycle? What are the natural and anthropogenic drivers of open ocean deoxygenation? What are the consequences of ocean acidification? How do physical changes in mixing and circulation affect nutrient availability and ocean productivity? 

Abstract OneArgo is a major expansion of the Argo program, which has provided two decades of transformative physical data for the upper 2 km of the global ocean. The present Argo array will be expanded in three ways: (1) Global Core: the existing upper ocean measurements will be extended to high latitudes and marginal seas and with enhanced coverage in the tropics and western boundaries of the major ocean basins; (2) Deep: deep ocean measurements will be obtained for the 50% of the global oceans that are below 2,000-m depth; and (3) Biogeochemical: dissolved oxygen, pH, nitrate, chlorophyll, optical backscatter, and irradiance data will be collected to investigate biogeochemical variability of the upper ocean and the processes by which these cycles respond to a changing climate. The technology and infrastructure necessary for this expansion is now being developed through large-scale regional pilots to further refine the floats and sensors and to demonstrate the utility of these measurements. Further innovation is expected to improve the performance of the floats and sensors and to develop the analyses necessary to provide research-quality data. A fully global OneArgo should be operational within 5‐10 years. 

Abstract Separating the climate response to external forcing from internal climate variability is a key challenge. While most previous studies have focused on surface responses, here we examine zonal‐mean patterns of North Pacific subsurface temperature responses. In particular, the changes since 1950 driven by anthropogenic aerosol emissions are found by using a pattern recognition method. Based on the single‐forcing large‐ensemble simulations from two models, we show that aerosol forcing caused a nonmonotonic temporal response and a characteristic zonal‐mean pattern within North Pacific, which is distinct from the pattern associated with internal variability. The aerosol‐forced pattern with the nonmonotonic temporal feature shows a substantial temperature change in subpolar regions and a reversed change on the southern flank of the subtropical gyre. A similar characteristic pattern and nonmonotonic time evolution are extracted from the subsurface observations, which likely reflect the subsurface responses to the aerosol forcing, although differences exist with the simulated responses. 

Abstract Unlike greenhouse gases (GHGs), anthropogenic aerosol (AA) concentrations have increased and then decreased over the past century or so, with the timing of the peak concentration varying in different regions. To date, it has been challenging to separate the climate impact of AAs from that due to GHGs and background internal variability. We use a pattern recognition method, taking advantage of spatiotemporal covariance information, to isolate the forced patterns for the surface ocean and associated atmospheric variables from the all-but-one forcing Community Earth System Model ensembles. We find that the aerosol-forced responses are dominated by two leading modes, with one associated with the historical increase and future decrease of global mean aerosol concentrations (dominated by the Northern Hemisphere sources) and the other due to the transition of the primary sources of AA from the west to the east and also from Northern Hemisphere extratropical regions to tropical regions. In particular, the aerosol transition effect, to some extent compensating the global mean effect, exhibits a zonal asymmetry in the surface temperature and salinity responses. We also show that this transition effect dominates the total AA effect during recent decades, e.g., 1967–2007.