Why do we need ocean forecasting systems?

We have seen what ocean forecasting is and why the ocean matters. Now let’s look at this from a different angle: why do we actually need ocean forecasting systems? What happens when we don’t have them, and how do they change the way society manages risk?

Ocean forecasts: from reaction to action

The ocean supports a wide range of economic sectors collectively known as the Blue Economy (Gourvenec et al., 2025). Far from being a niche scientific tool, ocean forecasts play a direct, practical role across many of these sectors:

• In the marine food sector, forecasts help fisheries and aquaculture operators understand environmental conditions that affect productivity and ecosystem health — from predicting upwelling events that concentrate fish stocks, to anticipating conditions that stress farmed species
• For maritime safety, forecasts of waves, currents, and storms improve navigation and reduce risks for vessels and ships, helping captains plan safer routes and avoid dangerous conditions
• In coastal tourism, information on sea conditions, water quality, and coastal hazards helps protect visitors and infrastructure, from swimming safety advisories to storm preparedness for coastal resorts
• For climate adaptation, forecasts support resilience planning and help communities prepare for changing ocean conditions, informing everything from infrastructure design to evacuation planning
• In the area of ecosystem health, forecasting systems help monitor marine habitats, harmful algal blooms, and environmental changes, supporting conservation and early intervention
• In the energy sector, offshore renewable energy and oil and gas operations depend heavily on accurate forecasts for planning and safety, from scheduling maintenance windows to protecting offshore platforms during storms

The Copernicus Marine Service alone supports all of these sectors of the Blue Economy, illustrating just how broad the reach of operational ocean forecasting has become.

A sustainable Blue Economy depends on moving from reactive responses to proactive ocean management, as defined by UNEP. This means anticipating and mitigating risks — coastal flooding, marine pollution, extreme weather events, biodiversity loss, habitat degradation — rather than simply responding to them after they have already caused damage. The difference between a society that reacts to a disaster and one that anticipates it can be measured in lives saved, livelihoods protected, and costs avoided.

What kinds of risks are we talking about?

Ocean forecasting systems help society anticipate and manage a wide range of hazards. Each of these has its own physical drivers and its own consequences for coastal communities and economies:

• Coastal flooding occurs from multiple sources, including storm surges, waves and swell, seiches, riverine and flash floods near the coast, tides, sea-level rise, and tsunamis. It is most frequently the result of storm surges and high winds coinciding with high tides. The surge itself results from the raising of sea levels due to low atmospheric pressure. In particular configurations, such as major estuaries or confined sea areas, the piling up of water is amplified by a combination of the shallowing of the seabed and the retarding of return flow (source: UN Office for Disaster Risk Reduction).
• Marine heatwaves are warm ocean temperature extremes associated with increasingly intense and frequent impacts on marine organisms, ecosystems, and the human industries that rely on them (Capotondi et al., 2024). They can devastate coral reefs, shift fish populations, and disrupt entire food chains.
• Oil spills are leakages of petroleum onto the surface of a large body of water. Accidents due to oil spills remain among the most severe anthropogenic threats to marine ecosystems, with consequences spanning ecological, socio-economic, and human health domains (Keramea et al., 2026).
• Harmful algal blooms (HABs) are a growing environmental concern due to their adverse impacts on aquatic ecosystems, human health, and economic activities. These blooms are driven by a combination of nutrient enrichment, environmental factors, and hydrological conditions, leading to excessive algal growth. HABs produce toxins that threaten aquatic biodiversity, contaminate drinking water, and cause economic losses in fisheries and tourism (Brenckman et al., 2025).
• Sea ice extremes occur when the extent, area, thickness, or duration of sea ice is much higher or lower than normal. These extremes can occur in both the Arctic Ocean and the waters surrounding Antarctica. They affect climate regulation, weather patterns, marine ecosystems, coastal communities, ocean circulation, and economic activities. The ongoing decline of Arctic sea ice is one of the most visible signs of a warming planet (Parkinson and DiGirolamo, 2021).
• Coastal erosion is the loss of land bordering a body of water, characterised by the rate of change in the position or horizontal displacement of a shoreline over time, often exacerbated by natural events and human activities. It results from coastal dynamic forces — waves, currents, and wind — losing balance in the coastal process, leading to the long-term loss of sediment and the progressive retreat of the coastline (Yincan et al., 2017).
• Extreme waves mainly occur during major storms at sea, through the constructive interference of wave trains or nonlinear wave interaction, but they may also be associated with tsunami or meteotsunami events. When they reach the coast, extreme waves have the potential to cause extensive remodelling of the shoreline and significant damage to human infrastructure, threatening lives in the process (Hansom et al., 2015).

The importance of observations for the ocean value chain

Operational ocean forecasting systems (OOFS) provide the high-quality information needed to anticipate risks, support decision-making, and build resilience across all of the ocean sectors described above. This is achieved by combining ocean observations with numerical models to deliver the best possible monitoring and prediction of the ocean state (Le Traon et al., 2025a).

These systems rely fundamentally on the scientific and technological evolution of how we observe the ocean. Observational data is used by numerical models to improve predictions through data assimilation methods, and to validate the results those models produce — a relationship we will explore in much more detail later in this course.

Over the past twenty years, satellite altimetry has transformed our ability to observe the ocean continuously and in near-real time. From the launch of Jason-1 in 2001 to the SWOT mission in 2022, satellite altimetry capabilities have been steadily improved through refinements in geophysical corrections and processing algorithms, including real-time processing and the evolution of altimeter radar technology such as synthetic aperture radar (SAR) mode and swath altimetry (Le Traon et al., 2025b).

At the same time, in-situ observations remain essential. They provide the ground truth that complements what we observe remotely from earth-observing satellites, anchoring satellite measurements to direct, physical reality (Gould et al., 2013).

Without reliable observations feeding continuously into forecasting systems, none of the services described in this step would be possible.

Key takeaways

• Ocean forecasts directly support fisheries, maritime safety, tourism, climate adaptation, ecosystem health, and the energy sector — the full breadth of the Blue Economy
• A sustainable Blue Economy depends on moving from reactive to proactive ocean management, anticipating risks rather than simply responding to them
• Forecasting systems help society anticipate a wide range of hazards: coastal flooding, marine heatwaves, oil spills, harmful algal blooms, sea ice extremes, coastal erosion, and extreme waves
• Reliable ocean observations — from satellites and in-situ platforms alike — are the foundation that makes accurate forecasting, and everything built on top of it, possible

References

• Gourvenec, S., et al. (2025). Towards a sustainable blue economy. (Recent publication — please confirm the exact title and journal against the author’s source list.)
• Capotondi, A., et al. (2024). A global overview of marine heatwaves in a changing climate. Communications Earth & Environment, 5, 701. https://doi.org/10.1038/s43247-024-01806-9
• Keramea, P., et al. (2026). Oil spill modelling and impacts on marine ecosystems. (Recent publication — please confirm the exact title and journal against the author’s source list.)
• Brenckman, et al. (2025). Harmful algal blooms: drivers and impacts. (Recent publication — please confirm the exact title and journal against the author’s source list.)
• Parkinson, C. L., and DiGirolamo, N. E. (2021). Sea ice extents continue to set new records: Arctic, Antarctic, and global results. Remote Sensing of Environment, 267, 112753. https://doi.org/10.1016/j.rse.2021.112753
• Yincan, Y., et al. (2017). Marine Geo-Hazards in China. Elsevier / Science Press.
• Hansom, J. D., Switzer, A. D., and Pile, J. (2015). Extreme waves: causes, characteristics, and impact on coastal environments and society. In Coastal and Marine Hazards, Risks, and Disasters (pp. 307–334). Elsevier. https://doi.org/10.1016/B978-0-12-396483-0.00011-X
• Gould, J., et al. (2013). In situ ocean observations: a brief history, present status, and future directions. In Ocean Circulation and Climate: A 21st Century Perspective (International Geophysics, Vol. 103, pp. 59–81). Academic Press. https://doi.org/10.1016/B978-0-12-391851-2.00003-9
• Le Traon, P.-Y., Novellino, A., and Moore, A. M. (2025a). Connecting ocean observations with prediction. State of the Planet, 5-opsr, 7. https://doi.org/10.5194/sp-5-opsr-7-2025
• Le Traon, P.-Y., et al. (2025b). Satellite altimetry and operational oceanography: from Jason-1 to SWOT. Ocean Science, 21, 1329–1347. https://doi.org/10.5194/os-21-1329-2025