Part of a new industry series Shipping the Future™: Climate Business Intelligence™ For The Maritime Industry

The Limitations of Current Risk Approaches

For decades, the maritime industry has depended on traditional methods for assessing and managing risk. Historical storm tracks, floodplain maps, and basic scenario tools have steered investments, insurance, and operations. Although these strategies once established a foundation for preparedness, they are increasingly insufficient in an era marked by climate volatility, complexity, and uncertainty. The conventional frameworks that managed past risks can no longer reliably predict future disruptions.

Historical Data Bias and the Problem of Non-Stationarity

Most maritime risk assessments rely heavily on historical data—such as past storm intensities, flood records, and temperature averages—to forecast future conditions. However, climate change has disrupted the assumption of stationarity: the belief that future risks resemble the past. Rising sea levels are elevating flood thresholds, tropical storms are becoming more intense than ever before, and oceanic heat waves are creating new disruptive patterns. By depending on outdated baseline data, maritime operators risk underestimating both how often and how severe hazards can be, leaving ports and fleets vulnerable to unexpected extremes.

Fragmented Data Sources and Siloed Decision-Making

Another limitation is the fragmented nature of risk data and governance. Meteorological agencies, port authorities, insurers, and shipping companies each hold pieces of the climate risk puzzle, but they rarely share or integrate them effectively. Siloed decision-making results in inconsistent standards, duplicated investments, and blind spots in risk awareness. For example, a port operator might assess flooding risk in isolation without considering cascading supply-chain impacts or energy system vulnerabilities. Without unified data governance and cross-sectoral intelligence, organizations lack the holistic view needed to predict systemic risks.

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