Particulate and phytoplankton absorption during POLARSTERN cruises ANT-XXVI/3 and ANT-XXVIII/3

The euphotic depth (Zeu) is a key parameter in modelling primary production (PP) using satellite ocean colour. However, evaluations of satellite Zeu products are scarce. The objective of this paper is to investigate existing approaches and sensors to estimate Zeu from satellite and to evaluate how different Zeu products might affect the estimation of PP in the Southern Ocean (SO). Euphotic depth was derived from MODIS and SeaWiFS products of (i) surface chlorophyll-a (Zeu-Chla) and (ii) inherent optical properties (Zeu-IOP). They were compared with in situ measurements of Zeu from different regions of the SO. Both approaches and sensors are robust to retrieve Zeu, although the best results were obtained using the IOP approach and SeaWiFS data, with an average percentage of error (E) of 25.43% and mean absolute error (MAE) of 0.10 m (log scale). Nevertheless, differences in the spatial distribution of Zeu-Chla and Zeu-IOP for both sensors were found as large as 30% over specific regions. These differences were also observed in PP. On average, PP based on Zeu-Chla was 8% higher than PP based on Zeu-IOP, but it was up to 30% higher south of 60°S. Satellite phytoplankton absorption coefficients (aph) derived by the Quasi-Analytical Algorithm at different wavelengths were also validated and the results showed that MODIS aph are generally more robust than SeaWiFS. Thus, MODIS aph should be preferred in PP models based on aph in the SO. Further, we reinforce the importance of investigating the spatial differences between satellite products, which might not be detected by the validation with in situ measurements due to the insufficient amount and uneven distribution of the data.

Secchi depth maps for the Baltic Sea, 2003-2012, with links to GeoTIFs

Secchi depth is a measure of water transparency. In the Baltic Sea region, Secchi depth maps are used to assess eutrophication and as input for habitat models. Due to their spatial and temporal coverage, satellite data would be the most suitable data source for such maps. But the Baltic Sea's optical properties are so different from the open ocean that globally calibrated standard models suffer from large errors. Regional predictive models that take the Baltic Sea's special optical properties into account are thus needed. This paper tests how accurately generalized linear models (GLMs) and generalized additive models (GAMs) with MODIS/Aqua and auxiliary data as inputs can predict Secchi depth at a regional scale. It uses cross-validation to test the prediction accuracy of hundreds of GAMs and GLMs with up to 5 input variables. A GAM with 3 input variables (chlorophyll a, remote sensing reflectance at 678 nm, and long-term mean salinity) made the most accurate predictions. Tested against field observations not used for model selection and calibration, the best model's mean absolute error (MAE) for daily predictions was 1.07 m (22%), more than 50% lower than for other publicly available Baltic Sea Secchi depth maps. The MAE for predicting monthly averages was 0.86 m (15%). Thus, the proposed model selection process was able to find a regional model with good prediction accuracy. It could be useful to find predictive models for environmental variables other than Secchi depth, using data from other satellite sensors, and for other regions where non-standard remote sensing models are needed for prediction and mapping. Annual and monthly mean Secchi depth maps for 2003-2012 come with this paper as Supplementary materials.

Model - data comparison of western African rainfall evolutions during the Last Interglacial (130-115 ka)

This dataset characterizes the evolution of western African precipitation indicated by marine sediment geochemical records in comparison to transient simulations using CCSM3 global climate model throughout the Last Interglacial (130-115 ka). It contains (1) defined tie-points (age models), newly published stable isotopes of benthic foraminifera and Al/Si log-ratios of eight marine sediment cores from the western African margin and (2) annual and seasonal rainfall anomalies (relative to pre-industrial values) for six characteristic latitudinal bands in western Africa simulated by CCSM3 (two transient simulations: one non-accelerated and one accelerated experiment).

Calcareous nannofossils and planktic foraminiferal assemblages of ODP Hole 198-1210A

Calcareous nannofossil and planktic foraminiferal assemblages from ODP Hole 1210A in the northwestern Pacific Ocean were used to reconstruct surface-water conditions for the past 500 kyr. Stratigraphic control was provided by calcareous nannofossil events that are thought to be synchronous over a broad range of latitudes. Calcareous nannofossil and planktic foraminiferal assemblages and abundance patterns indicate the unlikelihood of long term (Milankovitch-scale) latitudinal shifts of the Kuroshio Extension over the last 500 kyr and illustrate two successive surface water-mass states, one that prevailed prior to 300 ka and one that existed after 300 ka. The relative abundance of very small placoliths and the absolute abundance of the upper photic zone (UPZ) coccolith species decrease abruptly at approximately 300 ka. The relative abundance of the lower photic zone (LPZ) species Florisphaera profunda greatly increases at the same time, although intervals during which the relative abundance of this taxon is very low or absent also occur prior to 300 ka. The absolute abundance of planktic foraminifera gradually increased after the 300-ka boundary, including peaks of Globoconella inflata. These assemblage and abundance changes suggest significant modifications to the surface water-mass structure. Surface water was weakly stratified prior to 300 ka, but alternated between intensely stratified and vertically mixed after 300 ka. Changes in the surface water-mass structure suggest an intensification of the East Asian summer and winter monsoon after 300 ka.

Amino acid racemization of Neogloboquadrina pachyderma from the Arctic Ocean

The long-term rate of racemization for amino acids preserved in planktonic foraminifera was determined by using independently dated sediment cores from the Arctic Ocean. The racemization rates for aspartic acid (Asp) and glutamic acid (Glu) in the common taxon, Neogloboquadrina pachyderma, were calibrated for the last 150 ka using 14C ages and the emerging Quaternary chronostratigraphy of Arctic Ocean sediments. An analysis of errors indicates realistic age uncertainties of about ±12% for Asp and ±17% for Glu. Fifty individual tests are sufficient to analyze multiple subsamples, identify outliers, and derive robust sample mean values. The new age equation can be applied to verify and refine age models for sediment cores elsewhere in the Arctic Ocean, a critical region for understanding the dynamics of global climate change.

Sequential variation of carbonate cycles in South Atlantic DSDP locations

We report well-dated Late Cretaceous and Early Tertiary precessional climatic cycles, recorded by rhythmic carbonate maxima and minima in South Atlantic deep sea sites. Spectral analyses of digitized sediment color, a suitable carbonate proxy, show prominent regularities in the spacing marl-carbonate beds. Magnetostratigraphic dating over a number of magnetic chrons constrains the duration of the cycles, which can be detected over at least 20 Myr of sedimentation at 7 coring locations. Their mean absolute period of 23.5 +/- 4.4kyr agrees closely with the predicted late Cretaceous precessional period of 20.8 kyr. Because they can be matched to a physical forcing mechanism with a known repeat time, the cycles offer a new high-resolution tool to measure rates of climate change before and after the Cretaceous-Tertiary (K/T) boundary. From counts of carbonate cycles, we derive the position of the K/T boundary within C29R at 350 kyr after the base of the reversal. The constancy of cycle thickness (linearly related to sedimentation rate) and amplitude up to the "boundary clay" does not give evidence for climate instability preceding the boundary. Orbital chronometry records a step-function decrease in sediment accumulation rate at the Cretaceous-Tertiary boundary that is consistent with a geologically instantaneous event.

Gridded climate data from 5 Global Climate Models (GCM) of the Last Glacial Maximum (LGM) downscaled to 30 arc seconds for Europe, with links to NetCDF files

Studies on the impact of historical, current and future global change require very high-resolution climate data (less or equal 1km) as a basis for modelled responses, meaning that data from digital climate models generally require substantial rescaling. Another shortcoming of available datasets on past climate is that the effects of sea level rise and fall are not considered. Without such information, the study of glacial refugia or early Holocene plant and animal migration are incomplete if not impossible. Sea level at the last glacial maximum (LGM) was approximately 125m lower, creating substantial additional terrestrial area for which no current baseline data exist. Here, we introduce the development of a novel, gridded climate dataset for LGM that is both very high resolution (1km) and extends to the LGM sea and land mask. We developed two methods to extend current terrestrial precipitation and temperature data to areas between the current and LGM coastlines. The absolute interpolation error is less than 1°C and 0.5 °C for 98.9% and 87.8% of all pixels for the first two 1 arc degree distance zones. We use the change factor method with these newly assembled baseline data to downscale five global circulation models of LGM climate to a resolution of 1km for Europe. As additional variables we calculate 19 'bioclimatic' variables, which are often used in climate change impact studies on biological diversity. The new LGM climate maps are well suited for analysing refugia and migration during Holocene warming following the LGM.

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.