Mapping Error in Southern Ocean Transport Computed from Satellite Altimetry and Argo

Michael Kosempa, Don P. Chambers

Research output: Contribution to journalArticlepeer-review

Abstract

In an effort to better estimate transport dynamics in response to wind forcing (primarily the Southern Annual Mode), this study quantifies the uncertainty in mapping zonal geostrophic transport of the Antarctic Circumpolar Current from sparse temperature, salinity and sea surface height observations. To do this, we sampled an ocean state estimate at the locations of both Argo floats and the Jason-1 altimeter groundtrack. These sampled values were then optimally interpolated to create SSH and temperature/salinity grids with 1° resolution. The temperature, salinity and SSH grids were then combined to compute the zonal geostrophic transport and compared to that estimated from the full state estimate. There are significant correlations between the baroclinic and barotropic error contributions to the total transport error. The increase in Argo floats in the Southern Ocean is effective in reducing mapping error. However, that error improvement is not uniform. By analyzing systematic errors in transport time series, we find the transects that are most appropriate for analyzing the dynamics of ACC transport using Argo and altimetric gridded fields. Based on our analysis, we conclude region south of Tasmania is most appropriate, with lowest uncertainty. Using real-world data, we calculated zonal transport variability at a transect south of Tasmania. There is an insignificant trend (0.3 ± 0.4 Sv yr −1 , 90% confidence) but significant low-frequency variability correlated with the Southern Annular Mode (0.53, p < 0.05). The barotropic component is most responsible for the low-frequency variability, and this would be unobservable from ship casts without velocity measurements at depth.

Original languageAmerican English
JournalJournal of Geophysical Research: Oceans
Volume121
DOIs
StatePublished - Jan 1 2016

Keywords

  • snow
  • reconstruction
  • Airborne Snow Observatory

Disciplines

  • Life Sciences

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