Preprints  

Coastal areas are critical for society, with a significant portion of the global population residing near the coast. Predicting ocean conditions in these regions is challenging due to the need to model complex processes like tidal currents, wind-wave interactions, and shallow water dynamics. This paper explores advancements in high-resolution coastal modeling and observations, which improve predictions and refine monitoring systems. It highlights innovative approaches to enhance coastal realism

Ocean forecast systems provide information about a future state of the ocean. This information is provided in the form of decision support tools, or downstream applications, that can be accessed by various stakeholders to support livelihoods, coastal resilience, as well as the good governance of the marine environment. This manuscript provides an overview of the various downstream applications of ocean forecast systems that are utilised around the world.

Predicting the ocean state in support of human activities, environmental monitoring and policymaking across different regions worldwide is fundamental. The status of operational ocean forecasting systems (OOFS) in 8 key regions worldwide is provided. A discussion follows on the numerical strategy and available OOFS, pointing out the straightness and the ways forward to improve the essential ocean variables predictability from regional to coastal scales, products reliability and accuracy.

This work examines the current classification of numerical models of increasing complexity – from individuals and population and stock assessment models to models representing the whole ecosystem by covering all trophic levels – and presents examples and their operational maturity, finally demonstrating their use for supporting marine resource management, conservation, planning and mitigation actions.

This article describes the various stages of research and development that have been carried out over the last few decades to produce an operational reference service for global ocean monitoring and forecasting.

Ocean prediction relies on the integration between models, satellite and in-situ observations through data assimilation techniques. The authors discuss the role of observations in operational ocean forecasting systems, describing the state-of-the-art of satellite and in-situ observing networks and defining the paths for addressing multi-scale monitoring and forecasting.

The study illustrates the way atmospheric fields are used in ocean models as boundary conditions for the provisioning of the exchanges of heat, freshwater and momentum fluxes. Such fluxes can be based on remote-sensing instruments or provided directly by Numerical Weather Prediction systems. Air-sea flux datasets are defined by their spatial and temporal resolutions and are limited by associated biases. Air-sea flux data sets for ocean models should be chosen with the applications in mind.

We describe, at an elementary level, the spatially varying properties of the ocean that physical ocean models represent, the principles they use to evolve these properties with time, the physical phenomena that they simulate, and some of the roles these phenomena play within the Earth system. We also describe, in some technical detail, the methods and approximations that the models use and the difficulties that limit their accuracy or reliability.

An historical review over the last three decades on intercomparison projects of ocean numerical reanalysis or forecast is first proposed. From this, main issues and lessons learned are discussed in order to propose an overview of best practices and key considerations to facilitate intercomparison activities in operational oceanography.

This paper is a description of the OceanPrediction DCC and an introduction to this special issue. The objective of this compilation is to describe the actual status of ocean forecasting, detailing its degree of development in the different regions of the world and the most recent advances in all the relevant specific aspects associated with the technique, such as artificial intelligence, cloud computing, and many others.

This paper explores how using multiple predictions instead of just one can improve ocean forecasts and help prepare for changes in ocean conditions. By combining different forecasts, scientists can better understand the uncertainty in predictions, leading to more reliable forecasts and better decision-making. This method is useful for responding to hazards like oil spills, improving climate forecasts, and supporting decision-making in fields like marine safety and resource management.

Cloud computing technology offers scalable and measurable resources that are crucial for operational forecasting systems. This review offers an overview of existing service models, broadly used in ICT that can impact next generation of applications and services for Blue Economy.

This paper discusses the vital role of observations in ocean predictions and forecasting, highlighting the need for effective access, management, and integration of data to improve models and decision-making. The paper also explores opportunities for standardizing protocols and the potential of citizen-based, cost-effective data collection methods.

Ocean forecasting is traditionally done independently from atmospheric, wave, or river modeling. We discuss the benefits and challenges of bringing all these modelling systems together for ocean forecasting.

The paper describes the significant role that ocean forecasting systems play in the Blue Economy, demonstrating their direct benefits in improving prediction accuracy and downstream applications.

Forecasting the sea level is crucial for supporting coastal management through early warning systems and for adopting adaptation strategies to climate changes impacts. We provide here an overview on models commonly used for sea level forecasting, that can be based on storm surge models or ocean circulation ones, integrated on structured or unstructured grids, including an outlook on new approaches based on ensemble methods.

Numerical ocean forecasting is a key part of accurate models of the earth system. However, they require powerful computing resources and the architectures of the necessary computers are evolving rapidly. Unfortunately, this is a disruptive change – an ocean model must be modified to enable it to make use of this new computing hardware. This paper reviews what has been done in this area and identifies solutions to enable operational ocean forecasts to make use of the new computing hardware.

This review discusses the scope of ocean literacy for increasing awareness of climate change and marine resources and shares an overview of primary frameworks for capacity development in ocean science. Through education, training and community exchanges, capacity development initiatives emerge at the global and regional scales. These frameworks are under structuration and must pursue being refined, to further evaluate their impact, improve their reach and increase their effectiveness.

Rivers, vital to the Earth's system, connect the ocean with the land, governing hydrological and biogeochemical contributions and influencing processes like upwelling and mixing. This paper reviews advancements in river modeling, focusing on estuaries, from coarse-resolution ocean forecasting to more precise coastal coupling approaches. It discusses river data sources and examines how river forcing is treated in global, regional and coastal operational systems.

Marine biogeochemistry refers to the cycling of chemical elements resulting from physical transport, chemical reaction, uptake, and processing by living organisms. Biogeochemical models can have a wide range of complexity, from single parameterizations of processes to fully explicit representations of several nutrients, trophic levels, and functional groups. Uncertainty sources are the lack of knowledge about the parameterizations, initial and boundary conditions and the lack of observations

Observations of the ocean from satellites and platforms in the ocean are combined with information from computer models to produce predictions of how the ocean temperature, salinity and currents will evolve over the coming days and weeks, as well as to describe how the ocean has evolved in the past. This paper summarises the methods used to produce these ocean forecasts at various centres around the world and outlines the practical considerations for implementing such forecasting systems.

Forecasts of sea ice are in high demand in the polar regions, they are also quickly improving and becoming more easily accessible to non-experts. We provide here a brief status of the short-term forecasting services – typically 10 days ahead – and an outlook of their upcoming developments.

Operational ocean forecasting systems integrate advanced numerical modelling, aimed at resolving ocean dynamics and processes from global to coastal scale, and robust computational suites that are devoted to run models, orchestrating different data pre- and post-processing blocks, with the ultimate goal of providing high quality and reliable ocean forecasts. The main phases of its workflow are: pre-processing, modelling component(s) run, and post-processing.

Operational forecasting systems requires best practices for assessing the quality of ocean products. The Authors discusses on the role of observing network for performing validation of ocean models, identifying current gaps, but also emphasizing the need of new metrics. An analysis on the level of maturity of validation processes from global to regional systems is provided. A rich variety of approaches exists. Example of Copernicus Marine product quality organization is provided.  

This article provides an overview of the main characteristics of ocean forecast systems covering a limited region of the ocean. Their main components are described, as well as the spatial and temporal scales they resolve. The oceanic variables that these systems are able to predict are also explained. An overview of the main forecasting systems currently in operation is also provided.