Using weather pattern typology to identify calm weather windows for local marine operations

Edward Steele, Robert Neal, Rutger Dankers, Nicolas Fournier, Kenneth Mylne, Paul Newell, Andrew Saulter, Alasdair Skea, Jon Upton

Research output: Chapter in Book/Report/Conference proceedingConference paperAcademicpeer-review

10 Citations (Scopus)


The cost and complexity of offshore operations, combined with the vulnerability of equipment to prevailing conditions, requires weather-sensitive decisions to be made to ensure the continued accessibility and availability of marine assets. In the current economic context, this is especially important since the robust (timely) identification of calm weather windows has the potential to save many thousands of dollars per day in unplanned downtime and vessel contracting, allowing large efficiencies in sequencing, mobilisation and demobilisation costs if decisions are taken at the earliest possible opportunity. As forecasts extend weeks to months ahead, it is well known that predictability limits make the direct characterisation of small-scale weather events all but impossible, but there still remains a considerable amount of useful information contained within the large-scale weather circulation types. These circulation types, termed 'weather patterns', have a strong influence on the variability of marine wind and wave fields. Here, we present a new method for the tracking of calm weather windows out to several weeks ahead. Using a 34-year hindcast to elicit the daily maximum significant wave height experienced at the location of interest - and an analysis of the associated weather pattern under which they occurred - the circulation types are linked to the viability of offshore operations on a local scale. When subsequently applied in forecast mode, this method can enable earlier decision-making than is typically done at present. As weather patterns are more predictable than the actual weather itself at long lead-times, knowledge of the corresponding historic wave heights can enable identification of expected conditions within a probabilistic weather pattern forecasting system. In addition, the approach facilitates contingency planning; further supporting improved decisionmaking and reduced operational costs for the offshore oil and gas and marine renewable energy sector.

Original languageEnglish
Title of host publicationOffshore Technology Conference, OTC 2018
Number of pages8
ISBN (Electronic)9781510862531
Publication statusPublished - 2018
Externally publishedYes
EventOffshore Technology Conference, OTC 2018 - Houston, United States
Duration: 30 Apr 20183 May 2018

Publication series

NameProceedings of the Annual Offshore Technology Conference
ISSN (Print)0160-3663


ConferenceOffshore Technology Conference, OTC 2018
Country/TerritoryUnited States


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