Equipment used to collect water samples and measure a range of variables including temperature
© George Slesser, Marine Scotland Science
For the immediate future, we should sustain measurements of ocean process variables at least at their present intensity. However, we could significantly reduce the uncertainties in future assessments by increasing the quality and quantity of these observations, notably for sub-surface temperature and salinity. Moreover, the accuracy of reported variability and trends in several variables is limited by the spatial density of observations. Uncertainty in monthly mean air temperature estimates over the Atlantic near the UK increased many-fold from 1970/74 to 2004/08 owing to fewer voluntary observing ships, implying reduced confidence in marine air temperature trends. In UK shelf seas, salinity, current and wave measurements are sparse and are inadequate for sampling local variations.
Better prediction of short-term variability in circulation will require both model validation and the development of new observational networks. For currents, temperature and salinity, model experiments could help design measurement arrays: i.e. the density, frequency and allowable time-delay in observed data sets (assimilated in forecasting models) that provide the best cost/ benefit value both for making predictions, and for assessing the current state of UK waters.
Long-term, decadal-scale trends in variables such as temperature, precipitation, salinity, circulation, waves, and suspended particulate matter and its dependent biogeochemistry, are often obscured by larger short-term variability from year to year, season to season and from one weather event to the next. To separate out the longer-term trends and make a better assessment of the contribution of human-induced climate changes, we will need long-term yet frequent measurements, as in UK coastal observatories, and/or understanding and models that enable shorter-term variations to be estimated from their known causes. Data buoys and ships of opportunity now demonstrate much improved temporal and spatial coverage in a cost-effective manner.