Planimetric ice-flow convergence and flow-orthonormal strain rate across the Antarctic Ice Sheet, with links to model result files

Fast-flowing ice streams discharge most of the ice from the interior of the Antarctic Ice Sheet coastward. Understanding how their tributary organisation is governed and evolves is essential for developing reliable models of the ice sheet's response to climate change. Despite much research on ice-stream mechanics, this problem is unsolved, because the complexity of flow within and across the tributary networks has hardly been interrogated. Here I present the first map of planimetric flow convergence across the ice sheet, calculated from satellite measurements of ice surface velocity, and use it to explore this complexity. The convergence map of Antarctica elucidates how ice-stream tributaries draw ice from the interior. It also reveals curvilinear zones of convergence along lateral shear margins of streaming, and abundant convergence ripples associated with nonlinear ice rheology and changes in bed topography and friction. Flow convergence on ice-stream tributaries and their feeding zones is markedly uneven, and interspersed with divergence at distances of the order of kilometres. For individual drainage basins as well as the ice sheet as a whole, the range of convergence and divergence decreases systematically with flow speed, implying that fast flow cannot converge or diverge as much as slow flow. I therefore deduce that flow in ice-stream networks is subject to mechanical regulation that limits flow-orthonormal strain rates. These properties and the gridded data of convergence and flow-orthonormal strain rate in this archive provide targets for ice- sheet simulations and motivate more research into the origin and dynamics of tributarization.

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.

EOT11a - Global Empirical Ocean Tide model from multi-mission satellite altimetry, with links to model results

EOT11a is a global (E)mpirical (O)cean (T)ide model derived in 2011 by residual analysis of multi-mission satellite (a)ltimeter data. EOT11a includes amplitudes and phases of the main astronomical tides M2, S2, N2, K2, 2N2, O1, K1, P2, and Q1, the non-linear constituent M4, the long period tides Mm and Mf, and the radiational tide S1. Ocean tides as well as loading tides are provided. EOT11a was computed by means of residual tidal analysis of multi-mission altimeter data from TOPEX/Poseidon, ERS-2, ENVISAT, and Jason-1/2, as far as acquired between September 1992 and April 2010. The resolution of 7.5'x7.5' is identical with FES2004 which was used as reference model for the residual tide analysis. The development of EOT11a was funded by the Deutsche Forschungsgemeinschaft (DFG) under grant BO1228/6-2.

Southern Ocean CO2 uptake and buffer factor from model run 2012-2100, with links to model results

The Southern Ocean is a key region for global carbon uptake and is characterised by a strong seasonality with the annual CO2 uptake being mediated by biological carbon draw-down in summer. Here, we show that the contribution of biology to CO2 uptake will become even more important until 2100. This is the case even if biological production remains unaltered and can be explained by the decreasing buffer capacity of the ocean as its carbon content increases. The same amount of biological carbon draw-down leads to a more than twice as large reduction in CO2 (aq) concentration and hence to a larger CO2 gradient between ocean and atmosphere that drives the gas-exchange. While the winter uptake south of 44°S changes little, the summer uptake increases largely and is responsible for the annual mean response. The combination of decreasing buffer capacity and strong seasonality of biological carbon draw-down introduces a strong and increasing seasonality in the anthropogenic carbon uptake.

Holocene precipitation change in different monsoon sub-regions (time-slices and transient data) simulated by different global climate models, with links to model results

The recently proposed global monsoon hypothesis interprets monsoon systems as part of one global-scale atmospheric overturning circulation, implying a connection between the regional monsoon systems and an in-phase behaviour of all northern hemispheric monsoons on annual timescales (Trenberth et al., 2000). Whether this concept can be applied to past climates and variability on longer timescales is still under debate, because the monsoon systems exhibit different regional characteristics such as different seasonality (i.e. onset, peak, and withdrawal). To investigate the interconnection of different monsoon systems during the pre-industrial Holocene, five transient global climate model simulations have been analysed with respect to the rainfall trend and variability in different sub-domains of the Afro-Asian monsoon region. Our analysis suggests that on millennial timescales with varying orbital forcing, the monsoons do not behave as a tightly connected global system. According to the models, the Indian and North African monsoons are coupled, showing similar rainfall trend and moderate correlation in rainfall variability in all models. The East Asian monsoon changes independently during the Holocene. The dissimilarities in the seasonality of the monsoon sub-systems lead to a stronger response of the North African and Indian monsoon systems to the Holocene insolation forcing than of the East Asian monsoon and affect the seasonal distribution of Holocene rainfall variations. Within the Indian and North African monsoon domain, precipitation solely changes during the summer months, showing a decreasing Holocene precipitation trend. In the East Asian monsoon region, the precipitation signal is determined by an increasing precipitation trend during spring and a decreasing precipitation change during summer, partly balancing each other. A synthesis of reconstructions and the model results do not reveal an impact of the different seasonality on the timing of the Holocene rainfall optimum in the different sub-monsoon systems. They rather indicate locally inhomogeneous rainfall changes and show, that single palaeo-records should not be used to characterise the rainfall change and monsoon evolution for entire monsoon sub-systems.

Medem Channel profiles based on stand-alone model simulation and corrections with nudging

State-of-the-art process-based models have shown to be applicable to the simulation and prediction of coastal morphodynamics. On annual to decadal temporal scales, these models may show limitations in reproducing complex natural morphological evolution patterns, such as the movement of bars and tidal channels, e.g. the observed decadal migration of the Medem Channel in the Elbe Estuary, German Bight. Here a morphodynamic model is shown to simulate the hydrodynamics and sediment budgets of the domain to some extent, but fails to adequately reproduce the pronounced channel migration, due to the insufficient implementation of bank erosion processes. In order to allow for long-term simulations of the domain, a nudging method has been introduced to update the model-predicted bathymetries with observations. The model-predicted bathymetry is nudged towards true states in annual time steps. Sensitivity analysis of a user-defined correlation length scale, for the definition of the background error covariance matrix during the nudging procedure, suggests that the optimal error correlation length is similar to the grid cell size, here 80-90 m. Additionally, spatially heterogeneous correlation lengths produce more realistic channel depths than do spatially homogeneous correlation lengths. Consecutive application of the nudging method compensates for the (stand-alone) model prediction errors and corrects the channel migration pattern, with a Brier skill score of 0.78. The proposed nudging method in this study serves as an analytical approach to update model predictions towards a predefined 'true' state for the spatiotemporal interpolation of incomplete morphological data in long-term simulations.