Newman et al. The Southern Ocean Observing System time series of key variables, and delivers the greatest impact from data to all key end-users. Although the Southern Ocean remains one of the least-observed ocean regions, enhanced international coordination and advances in autonomous platforms have resulted in progress toward sustained observations of this region. Since 2009, the Southern Ocean community has deployed over 5700 observational platforms south of 40 • S. Large-scale, multi-year or sustained, multidisciplinary efforts have been supported and are now delivering observations of essential variables at space and time scales that enable assessment of changes being observed in Southern Ocean systems. The improved observational coverage, however, is predominantly for the open ocean, encompasses the summer, consists of primarily physical oceanographic variables, and covers surface to 2000 m. Significant gaps remain in observations of the ice-impacted ocean, the sea ice, depths >2000 m, the air-ocean-ice interface, biogeochemical and biological variables, and for seasons other than summer. Addressing these data gaps in a sustained way requires parallel advances in coordination networks, cyberinfrastructure and data management tools, observational platform and sensor technology, twoway platform interrogation and data-transmission technologies, modeling frameworks, intercalibration experiments, and development of internationally agreed sampling standards and requirements of key variables. This paper presents a community statement on the major scientific and observational progress of the last decade, and importantly, an assessment of key priorities for the coming decade, toward achieving the SOOS vision and delivering essential data to all end-users.
[1] In situ measurements of sea ice thickness (I), snow depth (S), and snow freeboard (F sn ) from drilling profile lines from 15 cruises into the Southern Ocean, Antarctica, were analyzed. I was calculated from in situ F sn and S using an isostatic approach. I was also directly estimated from F sn as can be obtained from laser altimetry. The root-mean-square difference (RMSD) between observed and calculated I reduces, and the correlation between F sn and I increases substantially, when (1) using values averaged over the survey lines ($50 m) instead of single drill hole measurements ($1 m) and (2) treating positive and negative sea ice freeboard (F i ) separately. For small F i , however, S approximates F sn pointing toward an isostatic balance also between S and I. Our linear regression analysis between the in situ measurements suggests a direct conversion of F sn into I using a region-specific set of equations. RMSD values are similar to those obtained employing isostatic balance models and treating positive and negative F i separately. However, more data would have been needed to obtain significant differences between most of the various models suggested. Still our new approach gives a viable alternative for Antarctic I retrieval from altimetric measurements of F sn alone. Correlation between in situ observations of F sn and S is high. RMSD between observed and calculated S is small. This suggests estimation of S from altimetric F sn measurements. Such S has an estimated precision of $5 cm, and is neither affected by snow wetness or grain size nor limited to S < 50 cm.Citation: Ozsoy-Cicek, B., S. Ackley, H. Xie, D. Yi, and J. Zwally (2013), Sea ice thickness retrieval algorithms based on in situ surface elevation and thickness values for application to altimetry,
Accurate circum-Antarctic sea-ice thickness is urgently required to better understand the different sea-ice cover evolution in both polar regions. Satellite radar and laser altimetry are currently the most promising tools for sea-ice thickness retrieval. We present qualitative inter-comparisons of winter and spring circum-Antarctic sea-ice thickness computed with different approaches from Ice Cloud and land Elevation Satellite (ICESat) laser altimeter total (sea ice plus snow) freeboard estimates. We find that approach A, which assumes total freeboard equals snow depth, and approach B, which uses empirical linear relationships between freeboard and thickness, provide the lowest sea-ice thickness and the smallest winter-to-spring increase in seasonal average modal and mean sea-ice thickness: A: 0.0 m and 0.04 m, B: 0.17 and 0.16 m, respectively. Approach C uses contemporary snow depth from satellite microwave radiometry, and we derive comparably large sea-ice thickness. Here we observe an unrealistically large winter-to-spring increase in seasonal average modal and mean sea-ice thickness of 0.68 m and 0.65 m, respectively, which we attribute to biases in the snow depth. We present a conceptually new approach D. It assumes that the two-layer system (sea ice, snow) can be represented by one layer. This layer has a modified density, which takes into account the influence of the snow on sea-ice buoyancy. With approach D we obtain thickness values and a winter-to-spring increase in average modal and mean sea-ice thickness of 0.17 m and 0.23 m, respectively, which lay between those of approaches B and C. We discuss retrieval uncertainty, systematic uncertainty sources, and the impact of grid resolution. We find that sea-ice thickness obtained with approaches C and D agrees best with independent sea-ice thickness information-if we take into account the potential bias of in situ and ship-based observations.
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