Acceleration of the ocean warming from 1961 to 2022 unveiled by large-ensemble reanalyses.

Long-term changes in ocean heat content (OHC) represent a fundamental global warming indicator and are mostly caused by anthropogenic climate-altering gas emissions. OHC increases heavily threaten the marine environment, therefore, reconstructing OHC before the well-instrumented period (i.e., before the Argo floats deployment in the mid-2000s) is crucial to understanding the multi-decadal climate change in the ocean. Here, we shed light on ocean warming and its uncertainty for the 1961-2022 period through a large ensemble reanalysis system that spans the major sources of uncertainties. Results indicate a 62-year warming of 0.43 ± 0.08 W m-2, and a statistically significant acceleration rate equal to 0.15 ± 0.04 W m-2 dec-1, locally peaking at high latitudes. The 11.6% of the global ocean area reaches the maximum yearly OHC in 2022, almost doubling any previous year. At the regional scale, major OHC uncertainty is found in the Tropics; at the global scale, the uncertainty represents about 40% and 15% of the OHC variability, respectively before and after the mid-2000s. The uncertainty of regional trends is mostly affected by observation calibration (especially at high latitudes), and sea surface temperature data uncertainty (especially at low latitudes).

Evaluation of different Maritime rapid environmental assessment procedures with a focus on acoustic performance.

Four different Marine Rapid Environmental Assessment (MREA) procedures are compared with a focus on underwater acoustic performance. Co-located oceanographic-acoustic data were collected during the summer of 2015 in the Northwestern Mediterranean in the framework of a sea trial led by the NATO Centre for Maritime Research and Experimentation. The data were used to link MREA procedures and ocean-acoustic validation in a seamless framework. The MREA procedures consider Conductivity Temperature Depth (CTD) data, operational products from the Copernicus Marine Service, and two dynamical downscaling systems (with and without data assimilation). A portion of the oceanographic data are used for the assimilation procedure, and the remaining portion is withheld from the assimilation system for use as an independent verifying dataset. The accuracy of modelled acoustic properties is evaluated using the sound speed estimates from the different MREA methodologies as inputs to an acoustic model, and then comparing the modelled and observed acoustic arrival intensities and temporal structure. In 95% of the studied cases, the assimilative dynamical downscaling approach provides acoustic results equaling or exceeding in skill those modelled with the sound speed extracted from CTD casts. Acoustic assessment results indicate that our implementation of dynamical downscaling has skill at oceanographic scales of 4 km, about ten times larger than the ocean model horizontal resolution.

Polar Ocean Observations: A Critical Gap in the Observing System and Its Effect on Environmental Predictions From Hours to a Season.

There is a growing need for operational oceanographic predictions in both the Arctic and Antarctic polar regions. In the former, this is driven by a declining ice cover accompanied by an increase in maritime traffic and exploitation of marine resources. Oceanographic predictions in the Antarctic are also important, both to support Antarctic operations and also to help elucidate processes governing sea ice and ice shelf stability. However, a significant gap exists in the ocean observing system in polar regions, compared to most areas of the global ocean, hindering the reliability of ocean and sea ice forecasts. This gap can also be seen from the spread in ocean and sea ice reanalyses for polar regions which provide an estimate of their uncertainty. The reduced reliability of polar predictions may affect the quality of various applications including search and rescue, coupling with numerical weather and seasonal predictions, historical reconstructions (reanalysis), aquaculture and environmental management including environmental emergency response. Here, we outline the status of existing near-real time ocean observational efforts in polar regions, discuss gaps, and explore perspectives for the future. Specific recommendations include a renewed call for open access to data, especially real-time data, as a critical capability for improved sea ice and weather forecasting and other environmental prediction needs. Dedicated efforts are also needed to make use of additional observations made as part of the Year of Polar Prediction (YOPP; 2017-2019) to inform optimal observing system design. To provide a polar extension to the Argo network, it is recommended that a network of ice-borne sea ice and upper-ocean observing buoys be deployed and supported operationally in ice-covered areas together with autonomous profiling floats and gliders (potentially with ice detection capability) in seasonally ice covered seas. Finally, additional efforts to better measure and parameterize surface exchanges in polar regions are much needed to improve coupled environmental prediction.

Observational Needs for Improving Ocean and Coupled Reanalysis, S2S Prediction, and Decadal Prediction.

Developments in observing system technologies and ocean data assimilation (DA) are symbiotic. New observation types lead to new DA methods and new DA methods, such as coupled DA, can change the value of existing observations or indicate where new observations can have greater utility for monitoring and prediction. Practitioners of DA are encouraged to make better use of observations that are already available, for example, taking advantage of strongly coupled DA so that ocean observations can be used to improve atmospheric analyses and vice versa. Ocean reanalyses are useful for the analysis of climate as well as the initialization of operational long-range prediction models. There are many remaining challenges for ocean reanalyses due to biases and abrupt changes in the ocean-observing system throughout its history, the presence of biases and drifts in models, and the simplifying assumptions made in DA solution methods. From a governance point of view, more support is needed to bring the ocean-observing and DA communities together. For prediction applications, there is wide agreement that protocols are needed for rapid communication of ocean-observing data on numerical weather prediction (NWP) timescales. There is potential for new observation types to enhance the observing system by supporting prediction on multiple timescales, ranging from the typical timescale of NWP, covering hours to weeks, out to multiple decades. Better communication between DA and observation communities is encouraged in order to allow operational prediction centers the ability to provide guidance for the design of a sustained and adaptive observing network.

Remote subsurface ocean temperature as a predictor of Atlantic hurricane activity.

Predicting North Atlantic hurricane activity months in advance is of great potential societal significance. The ocean temperature, both in terms of North Atlantic/tropical averages and upper ocean heat content, is demonstrated to be a significant predictor. To investigate the relationship between the thermal state of the Atlantic Ocean and the tropical cyclone (TC) activity in terms of accumulated cyclone energy (ACE), we use observed 1980-2015 TC records and a 1/4° resolution global ocean reanalysis. This paper highlights the nonlocal effect associated with eastern Atlantic Ocean temperature, via a reduction of wind shear, and provides additional predictive skill of TC activity, when considering subsurface temperature instead of sea surface temperature (SST) only. The most active TC seasons occur for lower than normal wind shear conditions over the main development region, which is also driven by reduced trade wind strength. A significant step toward operationally reliable TC activity predictions is gained after including upper ocean mean temperatures over the eastern Atlantic domain. Remote effects are found to provide potential skill of ACE up to 3 months in advance. These results indicate that consideration of the upper 40-m ocean average temperature improves upon a prediction of September Atlantic hurricane activity using only SST.

Role of subsurface ocean in decadal climate predictability over the South Atlantic.

Decadal climate predictability in the South Atlantic is explored by performing reforecast experiments using a coupled general circulation model with two initialization schemes; one is assimilated with observed sea surface temperature (SST) only, and the other is additionally assimilated with observed subsurface ocean temperature and salinity. The South Atlantic is known to undergo decadal variability exhibiting a meridional dipole of SST anomalies through variations in the subtropical high and ocean heat transport. Decadal reforecast experiments in which only the model SST is initialized with the observation do not predict well the observed decadal SST variability in the South Atlantic, while the other experiments in which the model SST and subsurface ocean are initialized with the observation skillfully predict the observed decadal SST variability, particularly in the Southeast Atlantic. In-depth analysis of upper-ocean heat content reveals that a significant improvement of zonal heat transport in the Southeast Atlantic leads to skillful prediction of decadal SST variability there. These results demonstrate potential roles of subsurface ocean assimilation in the skillful prediction of decadal climate variability over the South Atlantic.

Understanding large-scale, long-term larval connectivity patterns: The case of the Northern Line Islands in the Central Pacific Ocean.

Protecting key hotspots of marine biodiversity is essential to maintain ecosystem services at large spatial scales. Protected areas serve not only as sources of propagules colonizing other habitats, but also as receptors, thus acting as protected nurseries. To quantify the geographical extent and the temporal persistence of ecological benefits resulting from protection, we investigate larval connectivity within a remote archipelago, characterized by a strong spatial gradient of human impact from pristine to heavily exploited: the Northern Line Islands (NLIs), including part of the Pacific Remote Islands Marine National Monument (PRI-MNM). Larvae are described as passive Lagrangian particles transported by oceanic currents obtained from a oceanographic reanalysis. We compare different simulation schemes and compute connectivity measures (larval exchange probabilities and minimum/average larval dispersal distances from target islands). To explore the role of PRI-MNM in protecting marine organisms with pelagic larval stages, we drive millions of individual-based simulations for various Pelagic Larval Durations (PLDs), in all release seasons, and over a two-decades time horizon (1991-2010). We find that connectivity in the NLIs is spatially asymmetric and displays significant intra- and inter-annual variations. The islands belonging to PRI-MNM act more as sinks than sources of larvae, and connectivity is higher during the winter-spring period. In multi-annual analyses, yearly averaged southward connectivity significantly and negatively correlates with climatological anomalies (El Niño). This points out a possible system fragility and susceptibility to global warming. Quantitative assessments of large-scale, long-term marine connectivity patterns help understand region-specific, ecologically relevant interactions between islands. This is fundamental for devising scientifically-based protection strategies, which must be space- and time-varying to cope with the challenges posed by the concurrent pressures of human exploitation and global climate change.

Facets of Arctic energy accumulation based on observations and reanalyses 2000-2015.

Various observation- and reanalysis-based estimates of sea ice mass and ocean heat content trends imply that the energy imbalance of the Arctic climate system was similar [1.0 (0.9,1.2) Wm-2] to the global ocean average during the 2000-2015 period. Most of this extra heat warmed the ocean, and a comparatively small fraction went into sea ice melt. Poleward energy transports and radiation contributed to this energy increase at varying strengths. On a seasonal scale, stronger radiative energy input during summer associated with the ice-albedo feedback enhances seasonal oceanic heat uptake and sea ice melt. In return, lower sea ice extent and higher sea surface temperatures lead to enhanced heat release from the ocean during fall. This weakens meridional temperature gradients, consequently reducing atmospheric energy transports into the polar cap. The seasonal cycle of the Arctic energy budget is thus amplified, whereas the Arctic's long-term energy imbalance is close to the global mean.