The University of Southampton
University of Southampton Institutional Repository

Surface forcing of the North Atlantic: accuracy and variability

Surface forcing of the North Atlantic: accuracy and variability
Surface forcing of the North Atlantic: accuracy and variability
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 latent heat flux trends. These reduced trends are
thought to be more realistic. The wind speed trend after adjustment is more similar to
the trends reported in previous studies using reanalysis model output. However, there
are still some differences in the trends, with the VOS based estimates larger, leading to
uncertainty in trend estimates. The trends in the adjusted latent and sensible heat flux
estimates are similar to those seen in other flux datasets but when compared to changes
in the upper ocean heat content may still be too large. This may be due to the
overestimate of the wind speed trend. Overall the uncertainty in the wind speed trend
gives the largest uncertainty in the flux trends.
Finally, the advances made in developing the new methodology are summarised and
the potential uses of the new dataset identified. Future work and improvements are then
suggested.
Berry, David Inglis
55ffc590-f459-49c8-aecf-842d65aeb0fb
Berry, David Inglis
55ffc590-f459-49c8-aecf-842d65aeb0fb

Berry, David Inglis (2009) Surface forcing of the North Atlantic: accuracy and variability. University of Southampton, School of Ocean and Earth Science, Doctoral Thesis, 176pp.

Record type: Thesis (Doctoral)

Abstract

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 latent heat flux trends. These reduced trends are
thought to be more realistic. The wind speed trend after adjustment is more similar to
the trends reported in previous studies using reanalysis model output. However, there
are still some differences in the trends, with the VOS based estimates larger, leading to
uncertainty in trend estimates. The trends in the adjusted latent and sensible heat flux
estimates are similar to those seen in other flux datasets but when compared to changes
in the upper ocean heat content may still be too large. This may be due to the
overestimate of the wind speed trend. Overall the uncertainty in the wind speed trend
gives the largest uncertainty in the flux trends.
Finally, the advances made in developing the new methodology are summarised and
the potential uses of the new dataset identified. Future work and improvements are then
suggested.

Text
Berry_2009_PhD.pdf - Other
Download (22MB)

More information

Published date: November 2009
Organisations: University of Southampton

Identifiers

Local EPrints ID: 145001
URI: http://eprints.soton.ac.uk/id/eprint/145001
PURE UUID: b6882d7a-541b-462a-a619-92078b47e057

Catalogue record

Date deposited: 15 Apr 2010 14:30
Last modified: 14 Mar 2024 00:49

Export record

Contributors

Author: David Inglis Berry

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×