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.

Seaweed - epiphyte - mesograzer communities were tested for their responses to elevated seawater temperature and [CO2] in benthic mesocosms experiments across four consecutive seasons of one year in Kiel, Germany

Rising seawater temperature and CO2 concentrations (ocean acidification) represent two of the most influential factors impacting marine ecosystems in the face of global climate change. In ecological climate change research full-factorial experiments across seasons in multi-species, cross-trophic level set-ups are essential as they allow making realistic estimations about direct and indirect effects and the relative importance of both major environmental stressors on ecosystems. In benthic mesocosm experiments we tested the responses of coastal Baltic Sea Fucus vesiculosus communities to elevated seawater temperature and CO2 concentrations across four seasons of one year. While increasing [CO2] levels only had minor effects, warming had strong and persistent effects on grazers which affected the Fucus community differently depending on season. In late summer a temperature-driven collapse of grazers caused a cascading effect from the consumers to the foundation species resulting in overgrowth of Fucus thalli by epiphytes. In fall/ winter, outside the growing season of epiphytes, intensified grazing under warming resulted in a significant reduction of Fucus biomass. Thus, we confirm the prediction that future increasing water temperatures influence marine food-web processes by altering top-down control, but we also show that specific consequences for food-web structure depend on season. Since Fucus vesiculosus is the dominant habitat-forming brown algal system in the Baltic Sea, its potential decline under global warming implicates the loss of key functions and services such as provision of nutrient storage, substrate, food, shelter and nursery grounds for a diverse community of marine invertebrates and fish in Baltic Sea coastal waters.