{"id":{"repo_id":"soton","oai_identifier":"oai:eprints.soton.ac.uk:145001"},"canonical_url":"https://search.dev.ndltd.org/etd/soton/oai:eprints.soton.ac.uk:145001","repository":{"repo_id":"soton","name":"University of Southampton","base_url":"https://eprints.soton.ac.uk/cgi/oai2"},"display":{"title":"Surface forcing of the North Atlantic: accuracy and variability","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.","abstract_html":"A new methodology to estimate the turbulent air – sea heat and moisture fluxes and<br/>their uncertainty is developed and assessed using Voluntary Observing Ship (VOS)<br/>observations. Whilst important drivers of the global oceanic and atmospheric circulation<br/>these fluxes remain poorly quantified, both in terms of mean value and uncertainty. The<br/>new methodology addresses both of these issues and is extensible to other data sources.<br/>The individual observations are first bias and height adjusted to remove systematic<br/>errors and the impact of changing observing heights. They are then characterised in<br/>terms of random errors using a semi-variogram analysis and a range of variogram<br/>models. The data quality and sampling are then taken into account using optimal<br/>interpolation (OI) to grid the observations, producing daily mean fields and uncertainty<br/>estimates. These are then used to estimate the fluxes and flux uncertainty on both daily<br/>and monthly time scales.<br/>Comparisons of the mean fields and fluxes to the original input data and to<br/>independent buoy observations show the fields not to be significantly biased. The<br/>adjustments applied before gridding and flux calculation are also shown to improve the<br/>agreement with the buoy observations. The uncertainty estimates are assessed using a<br/>series of cross validation experiments and 3-way error analyses to make alternative<br/>estimates of the uncertainty. These alternative estimates are shown to be of the same<br/>order of magnitude as the OI uncertainty estimates and generally to be within 10 – 20%<br/>of the OI estimate. Whilst all three estimates are similar there are some systematic<br/>differences. The OI uncertainty estimates tend to be lower (higher) than the alternative<br/>estimates in high (low) variability regions.<br/>The representation of the variability in the new dataset is examined and shown to be<br/>improved compared to previous VOS based datasets. The adjustments are shown to<br/>have little impact on the temporal trends in temperature and humidity whilst reducing<br/>the wind speed and sensible and latent heat flux trends. These reduced trends are<br/>thought to be more realistic. The wind speed trend after adjustment is more similar to<br/>the trends reported in previous studies using reanalysis model output. However, there<br/>are still some differences in the trends, with the VOS based estimates larger, leading to<br/>uncertainty in trend estimates. The trends in the adjusted latent and sensible heat flux<br/>estimates are similar to those seen in other flux datasets but when compared to changes<br/>in the upper ocean heat content may still be too large. This may be due to the<br/>overestimate of the wind speed trend. Overall the uncertainty in the wind speed trend<br/>gives the largest uncertainty in the flux trends.<br/>Finally, the advances made in developing the new methodology are summarised and<br/>the potential uses of the new dataset identified. Future work and improvements are then<br/>suggested.","abstract_has_math":false,"creators":["Berry, David Inglis"],"institution":"University of Southampton","degree_name":"Ph.D.","degree_level":"doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2009,"date_issued":"2009-11","date_published":"2009-11","updated_at":"2026-07-24T04:36:14Z","subjects":[],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Berry, David Inglis"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2009-11"]},{"key":"dc:date.issued","label":"Date","values":["2009-11"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["National Oceanography Centre,Southampton (pre 2011 reorg)","Ocean and Earth Science (pre 2011 reorg)","School of Ocean and Earth Science"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["University of Southampton"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://eprints.soton.ac.uk/145001/"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["Ph.D."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://eprints.soton.ac.uk/145001/1/Berry_2009_PhD.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["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."]},{"key":"dc:format","label":"Dc Format","values":["text"]},{"key":"dc:title","label":"Title","values":["Surface forcing of the North Atlantic: accuracy and variability"]}]}],"canonical_facts":{"dc:creator":["Berry, David Inglis"],"dc:date":["2009-11"],"dc:date.issued":["2009-11"],"dc:description.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."],"dc:format":["text"],"dc:identifier.uri":["https://eprints.soton.ac.uk/145001/1/Berry_2009_PhD.pdf"],"dc:publisher.department":["National Oceanography Centre,Southampton (pre 2011 reorg)","Ocean and Earth Science (pre 2011 reorg)","School of Ocean and Earth Science"],"dc:publisher.institution":["University of Southampton"],"dc:relation.isreferencedby":["https://eprints.soton.ac.uk/145001/"],"dc:title":["Surface forcing of the North Atlantic: accuracy and variability"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["doctoral"],"dc:type.qualificationname":["Ph.D."]},"updated_at":"2026-07-24T04:36:14Z"}