Making the Most of Probabilistic Marine Forecasts on Timescales of Days, Weeks and Months Ahead

Abstract

Marine forecasts are essential to operational planning, with decisions able to be guided by a host of different weather products spanning a period of days, weeks and even months ahead. The correct selection and subsequent application of these different types of weather products has the potential to save many thousands of dollars per day in operational downtime, however this is only possible when the science underpinning these marine forecasts is properly understood by the user. In the current economic context, this is especially relevant to the offshore industry – whose use of forecasting technology is traditionally very conservative, and therefore whose planning is often more reactive – allowing large savings (e.g. mobilization / demobilisation costs) if robust decisions are made as early as possible. Two established methods for the interpretation of probabilistic data based on cost-loss and weather regime analysis are described and applied to ocean wave forecasting. It is suggested the selection of methods will be dependant on the timescales of interest, with the cost-loss analysis optimised for supporting decisions at timescales on days to weeks ahead and the weather regime analysis optimized for supporting decisions at timescales of weeks to months ahead. The application of these methods are illustrated from the point of view of a North Sea asset manager planning the mobilization of equipment / personnel under conditions of calm weather, and the protection of equipment / personnel under conditions of severe weather. For such a user, efficient operational planning will be best supported by the use of marine forecasts across all such timescales, from days to months ahead. It is intended that this will enable more informed decision-making, and help reduce operational costs, by promoting increased confidence in longer-range forecasts than are typically used by the offshore oil & gas and marine renewable energy sector.

Shoreline modelling on timescales of days to decades

“…The application of ensemble approaches (e.g. Saetra and Bidlot, 2004, Bunney and Saulter, 2015, Alves et al, 2013 is considered best practice in mitigating the initial condition uncertainty on short term timescales (Steele et al, 2017, Siddorn et al, 2016. A pioneering example application is described in the context of shoreline evolution by Steele et al (2019).…”

Generating weather pattern definitions over South Africa suitable for future use in impact‐orientated medium‐range forecasting

“…Weather patterns are already being utilized for medium‐range (<2 weeks) forecasting tools in Europe (Ferranti et al, 2014; Neal et al, 2016) and India (Neal et al, 2020; Neal et al, 2022). The forecasting tool developed by Neal et al (2016)—which assigns ensemble members to the closest matching weather pattern and calculates daily weather pattern probabilities—has been followed by many forecasting applications for UK/Europe: these include forecasting extreme precipitation (Richardson, Neal, et al, 2020), significant wave heights (Steele et al, 2017; Steele et al, 2018), coastal flooding (Neal et al, 2018), meteorological droughts (Richardson et al, 2018; Richardson, Fowler, et al, 2020), temperature‐based excess mortality (Huang et al, 2020), London bike hire demand (Brown et al, 2019), risks associated with lightning activity (Wilkinson & Neal, 2021) and aviation risks associated with Icelandic volcanic ash (Harrison et al, 2022). Other papers to explore clustering analyses of weather patterns and their potential in forecasting include Coe et al (2021) for the United States, Arizmendi et al (2022) for South America and Howard et al (2022) for Southeast Asia.…”

The influence of future weather pattern changes and projected sea-level rise on coastal flood impacts around the UK

“…Once weather pattern characteristics are understood, in terms of their climatologies or impacts, it becomes possible to interpret forecast output and describe the likely consequences. Weather patterns have been exploited in several applications including assessing the likelihood of coastal flooding (Neal et al 2018), extreme rainfall (Richardson et al 2020), volcanic ash flow from Iceland (Harrison et al 2022), lightning occurrence (Wilkinson and Neal 2021) and extreme wave heights for decision-making within marine industries (Steele et al 2017(Steele et al , 2018. Weather pattern approaches have also been used to address climate timescale questions, such as assessing future changes in the frequency and persistence of different types (Pope et al 2022).…”