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Climate change risk to global port operations

Nature Climate Change volume 11, pages 14–20 (2021)Cite this article

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Abstract

The ports sector is critical to global transport and trade. Climate change may compromise port operations, resulting in an increase in operational shutdowns and subsequent economic losses. Here, we present an analysis of historical global risk across the operations of 2,013 ports worldwide and the impacts under a high-end warming scenario, considering atmospheric and marine hazards, industry established operational thresholds, exposure and vulnerability. Increased coastal flooding and overtopping due to sea level rise, as well as the heat stress impacts of higher temperatures, are the main contributors to amplified risk. Ports located in the Pacific Islands, Caribbean Sea and Indian Ocean appear to be at extremely high risk by 2100, whereas those in the African Mediterranean and the Arabian Peninsula (Persian Gulf and Red Sea) are expected to experience very high risk. Estimating risks at the global scale cannot capture site-level details, but these results provide a benchmark for further research and decision-making.

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Fig. 1: Present multi-hazard conditions in world port operations.
Fig. 2: Multi-hazard severity across world port operations.
Fig. 3: Climate risk for the world port sector in the year 2100 under RCP8.5.

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Data availability

The atmospheric and marine frequency impact indicators that support the findings of this study are available from the IFC and were used under licence for the current study. Data are available from the authors upon request by contacting ihdata@ihcantabria.es, if permission from the IFC is granted.

Code availability

Computer codes or algorithms used to generate results that are reported in the paper and central to its main claims are available at: https://doi.org/10.5281/zenodo.3987516.

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Acknowledgements

We acknowledge the support from the Spanish Ministerio de Economía y Competitividad (MINECO) under the RISKOADAPT project (grant no. BIA2017-89401-R). We are grateful to C. Amman for his work in the development of atmospheric frequency impact indicators and A. Espejo for his useful comments. The atmospheric and marine frequency impact indicators have been developed jointly by NCAR and IHCantabria with the financial support of the IFC. This material is based in part on work supported by the NCAR, which is a major facility sponsored by the National Science Foundation under cooperative agreement no. 1852977. Computing resources were provided by the Climate Simulation Laboratory at the NCAR Computational and Information Systems Laboratory. We acknowledge the Working Group on Coupled Modelling of the World Climate Research Programme, which is responsible for the CMIP, and we thank the climate modelling groups for producing and making available their model output.

Author information

Authors and Affiliations

  1. IHCantabria-Instituto de Hidráulica Ambiental de la Universidad de Cantabria, Santander, Spain

    C. Izaguirre, I. J. Losada & P. Camus

  2. National Center for Atmospheric Research (NCAR), Boulder, CO, USA

    J. L. Vigh

  3. International Finance Corporation (IFC), World Bank Group, Washington DC, WA, USA

    V. Stenek

Authors
  1. C. Izaguirre
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Contributions

I.J.L. conceived the study and designed it with C.I. and P.C. jointly. C.I. and P.C. performed the analysis and developed the marine frequency indicators. J.L.V. developed the atmospheric frequency indicators. C.I., I.J.L. and V.S. wrote the manuscript. All of the authors contributed to make substantial improvements to the manuscript.

Corresponding author

Correspondence to I. J. Losada.

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The authors declare no competing interests.

Additional information

Peer review information Nature Climate Change thanks Austin Becker, Robert Nicholls, Joan Pau Sierra and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Extended data

Extended Data Fig. 1 Methodological overview of study.

Green colour represents vulnerability variables/indicators used and produced, orange represents exposure characteristics, and blue represents hazard variables/indicators. Grey boxes and arrows indicate the method/approach used for analysing information.

Extended Data Fig. 2 Future change in multihazard severity.

Multihazard change severity for each port in the year 2100 under RCP8.5 in terms of the improvement and worsening of present multihazard conditions.

Extended Data Fig. 3 Present risk level.

Present-day risk levels shown for all ports.

Extended Data Fig. 4 Present vulnerability level.

Present vulnerability level shown for each port.

Extended Data Fig. 5 Future risk levels.

Climate risk in the year 2100 under RCP8.5 across the operations of the largest OECD port cities. Marker size indicates the change in risk level.

Extended Data Fig. 6 Present exposure level.

Present-day exposure level shown for each port.

Extended Data Fig. 7 Dominant climatic drivers of port disruptions.

Spatial representation of dominant climatic drivers of port disruptions in 30 locations around the world.

Extended Data Fig. 8 Multihazard change conditions in world port operations.

a, Representative clusters of multihazard change conditions for each port in the year 2100 under RCP8.5. b, Characteristics of the clusters. Each panel contains the % of ports included in the cluster, the number of the cluster, the representation of the centroid (cross), the 5 and 95 percentiles of the data of the cluster (points) and the 25 and 75 percentiles of the data of the cluster (coloured line) on a normalized (0-1) scale for each frequency indicator. DaysW15 mph = average number of days per year with daily mean wind speed ≥ 15 m/s; DaysT40Deg = average number of days per year with daily maximum temperature ≥ 40°C; DaysP20 mm = average number of days per year with heavy precipitation (>20 mm); DaysHs2.5m = average number of days per year with significant wave height > 2.5 m in the navigation zone; DaysOv0.1 l = number of days per year with overtopping flow > 0.1 l/m/s; DaysCF = average number of days per year with coastal flooding; ProbTC = the annual exceedance probability of experiencing a Saffir-Simpson Hurricane Scale Category 1 or higher; and ProbMajorTC = the annual exceedance probability of experiencing a Saffir-Simpson Hurricane Scale Category 3 or higher (major hurricanes).

Extended Data Fig. 9 Present vulnerability conditions across clusters.

Present-day vulnerability conditions are shown for each port, categorized by cluster. a, Representative clusters of vulnerability conditions for each port. b, Characteristics of the clusters of vulnerability. Each panel contains the % of ports included in the cluster, the number of the cluster, the representation of the centroid (cross), the 5 and 95 percentiles of the data of the cluster (points) and the 25 and 75 percentiles of the data of the cluster (coloured line) on a normalized (0-1) scale for each vulnerability dimension: Tech. Cap = technological capacity; Resilience and Recov. Cap. = recovery capacity.

Extended Data Fig. 10 Present risk conditions across clusters.

Present-day risk conditions are shown for each port, categorized by cluster. a, Representative cluster of present risk conditions for each port. b, Characteristics of the clusters. Each panel contains the % of ports included in the cluster, the number of the cluster, the representation of the centroid (cross), the 5 and 95 percentiles of the data of the cluster (points) and the 25 and 75 percentiles of the data of the cluster (coloured line) on a normalized (0-1) scale for each frequency indicator.

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Supplementary Figs. 1–2, Discussions 1–7 and Tables 1–18.

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Izaguirre, C., Losada, I.J., Camus, P. et al. Climate change risk to global port operations. Nat. Clim. Chang. 11, 14–20 (2021). https://doi.org/10.1038/s41558-020-00937-z

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