The North Atlantic heat budget: an Argo based study

The Argo dataset is used to obtain estimates of the heat storage and heat divergence with<br/>the aim of the assessing the usefulness of the Argo array for investigating the North<br/>Atlantic heat budget. The accuracy of the Argo-based mixed layer heat storage varies<br/>significantly throughout the North Atlantic. Errors are smallest, around 10-20 Wm-2 on<br/>monthly timescales for 10° x 10° boxes, reducing to 5-10 Wm-2 on seasonal scales in the<br/>subtropics and eastern basin. Heat storage errors over a fixed 300 m layer are higher, but<br/>typically remain below 20 Wm-2 on seasonal timescales away from the western boundary.<br/>The heat budget is closed (using net heat fluxes from the NCEP climatology and NOC<br/>reanalysis) within the estimated error throughout the subtropical and eastern North Atlantic,<br/>indicating the value of the Argo dataset in studies of this nature. However, within the<br/>western boundary the heat budget residual typically exceeds 50 Wm-2, with the heat storage<br/>overestimated or the heating from the net heat flux and/or advective and diffusive<br/>divergence underestimated. Assuming that heat storage error estimates are accurate and<br/>considering results in the literature regarding the bias in net heat flux products, it is likely<br/>that heating from divergence is underestimated. The heating contribution from this term<br/>may be large on scales that cannot be resolved using Argo. In the eastern and subtropical<br/>North Atlantic, the errors in the Argo-based heat budget terms are smaller than the<br/>uncertainty in the net heat flux products and can thus be used to provide insight into which<br/>atmospheric dataset (the NCEP reanalysis or the NOC climatology) may be more accurate.<br/>The NOC net heat flux is more accurate than that from NCEP throughout the year in the<br/>subtropics and during the first half of the year in the eastern mid-latitudes.<br/>The errors in the mixed layer heat storage are smaller than the interannual variability in<br/>this term. Thus Argo can be used to investigate variability on this scale. While the current<br/>Argo dataset is on the short side for studies of this nature, continued funding of the array is<br/>expected to provide more insightful results.

Name dc:type.qualificationname

Ph.D.

Level dc:type.qualificationlevel

doctoral

Grantor dc:publisher.institution

University of Southampton

Year dc:date.issued

2007

Author dc:creator

• Hadfield, Rachel Elaine