Surface forcing of the North Atlantic: accuracy and variability

• Main Author: Berry, David Inglis
• Format: Text
• Language: English
• Published: 2009
• Subjects: North Atlantic
• Online Access: http://nora.nerc.ac.uk/id/eprint/245001/; https://nora.nerc.ac.uk/id/eprint/245001/1/Berry_2009_PhD.pdf

A new methodology to estimate the turbulent air – sea heat and moisture fluxes and their uncertainty is developed and assessed using Voluntary Observing Ship (VOS) observations. Whilst important drivers of the global oceanic and atmospheric circulation these fluxes remain poorly quantified, both in terms of mean value and uncertainty. The new methodology addresses both of these issues and is extensible to other data sources. The individual observations are first bias and height adjusted to remove systematic errors and the impact of changing observing heights. They are then characterised in terms of random errors using a semi-variogram analysis and a range of variogram models. The data quality and sampling are then taken into account using optimal interpolation (OI) to grid the observations, producing daily mean fields and uncertainty estimates. These are then used to estimate the fluxes and flux uncertainty on both daily and monthly time scales. Comparisons of the mean fields and fluxes to the original input data and to independent buoy observations show the fields not to be significantly biased. The adjustments applied before gridding and flux calculation are also shown to improve the agreement with the buoy observations. The uncertainty estimates are assessed using a series of cross validation experiments and 3-way error analyses to make alternative estimates of the uncertainty. These alternative estimates are shown to be of the same order of magnitude as the OI uncertainty estimates and generally to be within 10 – 20% of the OI estimate. Whilst all three estimates are similar there are some systematic differences. The OI uncertainty estimates tend to be lower (higher) than the alternative estimates in high (low) variability regions. The representation of the variability in the new dataset is examined and shown to be improved compared to previous VOS based datasets. The adjustments are shown to have little impact on the temporal trends in temperature and humidity whilst reducing the wind speed and sensible and ...