Using Weather Pattern Typology to Identify Calm Weather Windows for Local Marine Operations

• DOI: 10.4043/28784-ms
• Publication Date: 2018-04-24T18:18:04Z
• Authors: Edward Steele; Robert Neal; Rutger Dankers; Nicolas Fournier; Kenneth Mylne; Paul Newell; Andrew Saulter; Alasdair Skea; Jon Upton
• Keywords: Hindcast; Predictability; Extreme Weather

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