Mean dynamic topography and oceanographic parameters estimated from an inverse model and satellite geodesy, with link to model result in one single NetCDF file (392 MB), including the inverse data error covariance

Geostrophic surface velocities can be derived from the gradients of the mean dynamic topography-the difference between the mean sea surface and the geoid. Therefore, independently observed mean dynamic topography data are valuable input parameters and constraints for ocean circulation models. For a successful fit to observational dynamic topography data, not only the mean dynamic topography on the particular ocean model grid is required, but also information about its inverse covariance matrix. The calculation of the mean dynamic topography from satellite-based gravity field models and altimetric sea surface height measurements, however, is not straightforward. For this purpose, we previously developed an integrated approach to combining these two different observation groups in a consistent way without using the common filter approaches (Becker et al. in J Geodyn 59(60):99-110, 2012, doi:10.1016/j.jog.2011.07.0069; Becker in Konsistente Kombination von Schwerefeld, Altimetrie und hydrographischen Daten zur Modellierung der dynamischen Ozeantopographie, 2012, http://nbn-resolving.de/nbn:de:hbz:5n-29199). Within this combination method, the full spectral range of the observations is considered. Further, it allows the direct determination of the normal equations (i.e., the inverse of the error covariance matrix) of the mean dynamic topography on arbitrary grids, which is one of the requirements for ocean data assimilation. In this paper, we report progress through selection and improved processing of altimetric data sets. We focus on the preprocessing steps of along-track altimetry data from Jason-1 and Envisat to obtain a mean sea surface profile. During this procedure, a rigorous variance propagation is accomplished, so that, for the first time, the full covariance matrix of the mean sea surface is available. The combination of the mean profile and a combined GRACE/GOCE gravity field model yields a mean dynamic topography model for the North Atlantic Ocean that is characterized by a defined set of assumptions. We show that including the geodetically derived mean dynamic topography with the full error structure in a 3D stationary inverse ocean model improves modeled oceanographic features over previous estimates.

CaCO3, foraminifer fragmentation, benthic carbon isotopes, coarse lithic counts and radiogenic isotopes (Sr, Nd, Pb) of the Pliocene and earliest Pleistocene terrigenous component (3.3-2.4 Ma) of IODP Site 306-U1313

We present Plio-Pleistocene records of sediment color, %CaCO3, foraminifer fragmentation, benthic carbon isotopes (d13C) and radiogenic isotopes (Sr, Nd, Pb) of the terrigenous component from IODP Site U1313, a reoccupation of benchmark subtropical North Atlantic Ocean DSDP Site 607. We show that (inter)glacial cycles in sediment color and %CaCO3 pre-date major northern hemisphere glaciation and are unambiguously and consistently correlated to benthic oxygen isotopes back to 3.3 million years ago (Ma) and intermittently so probably back to the Miocene/Pliocene boundary. We show these lithological cycles to be driven by enhanced glacial fluxes of terrigenous material (eolian dust), not carbonate dissolution (the classic interpretation). Our radiogenic isotope data indicate a North American source for this dust (~3.3-2.4 Ma) in keeping with the interpreted source of terrestrial plant wax-derived biomarkers deposited at Site U1313. Yet our data indicate a mid latitude provenance regardless of (inter)glacial state, a finding that is inconsistent with the biomarker-inferred importance of glaciogenic mechanisms of dust production and transport. Moreover, we find that the relation between the biomarker and lithogenic components of dust accumulation is distinctly non-linear. Both records show a jump in glacial rates of accumulation from Marine Isotope Stage, MIS, G6 (2.72 Ma) onwards but the amplitude of this signal is about 3-8 times greater for biomarkers than for dust and particularly extreme during MIS 100 (2.52 Ma). We conclude that North America shifted abruptly to a distinctly more arid glacial regime from MIS G6, but major shifts in glacial North American vegetation biomes and regional wind fields (exacerbated by the growth of a large Laurentide Ice Sheet during MIS 100) likely explain amplification of this signal in the biomarker records. Our findings are consistent with wetter-than-modern reconstructions of North American continental climate under the warm high CO2 conditions of the Early Pliocene but contrast with most model predictions for the response of the hydrological cycle to anthropogenic warming over the coming 50 years (poleward expansion of the subtropical dry zones).