Satellite ocean front maps reveal dynamic surface currents: improved metocean for offshore oil and gas

Date/Time:

14 Mar 2012
16:30-17:00

Location:

South Galleries

Dr Peter Miller, Plymouth Marine Laboratory

Seminar Details
We have developed novel Earth observation (EO) methods for visualising and inferring the spatio-temporal distribution of dynamic oceanic fronts, in order to provide additional information on physical oceanography pertinent to the offshore oil and gas industry. For instance, this analysis may reveal if there is more eddy activity at particular locations or times of year, or predictable seasonal changes in the width of the slope current. EO front maps from a 30-year time-series can be integrated with other metocean information, for instance current meters or ADCP that reveal physical processes at depth but are restricted to small regions and limited time span. Examples will be shown for regions of interest to oil and gas industry, such as the Faroe-Shetland Channel and the Gulf of Mexico. Potential applications include site selection and design, real-time operations and spill management. It may also address conservation concerns by incorporating information on marine mammal and seabird usage of fronts into detailed site selection. Oceanic fronts are formed at the boundary between water masses of different temperature or density, and are often associated with enhanced mixing. Fronts that extend to the sea surface may be observed by satellite if the water masses differ in temperature or colour, and such observations may allow interpretation of the location and dynamics of mesoscale processes including meanders and eddies. We are even able to detect major fronts when completely obscured by cloud cover. Ocean colour may reveal additional physical processes even if there is no SST signal. This research is based on the composite front map approach, which is to combine the location, strength and persistence of all fronts observed over several days into a single map, improving interpretation of dynamic mesoscale structures (Miller, 2009). These techniques are robust and applicable to any geographic area.