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.

Karte eines Teiles der Mittelinsel von Nordland ("Insel der Oktober-Revolution") (Ergänzungsheft 216, Tafel 1, png-format 37 MB)

Unterlage für diese Karte bilden in der Hauptsache Aufnahmen, die mit der Zweifach-Reihenbildkammer am 28. Juli 1931 in der Zeit von 6 Uhr 30 Min. MGZ. bis 9 Uhr 45 Min. aufgenommen worden sind. Außerdem sechs Aufnahmen mit der Handmeßkammer. Zur Ergänzung konnten 14 Aufnahmen der Panoramakammer herangezogen werden. Die Karte umfaßt einen nördlichen Teil vom Sund der Roten Armee bis zum Beginn des Matussewitsch-Sees mit einem Teil der Nordostküste und einen südlichen Teil mit Schokalski-Sund und dessen östlicher Begrenzung durch die Südinsel. Zwischen beiden Teilen der Karte klafft eine Lücke, hervorgerufen durch eine für die photographische Aufnahme undurchdringliche Nebeldecke.

Orthophotokarte Vernagtferner 1979 in jpg-Format (54 MB)

For the production of the orthophoto map Vernagtferner 1979, scale I: 10000, photographs of the flight "Hintereisferner 1979" were used, which have been found to be very suitable for differential rectification. Control points were determined before the flight took place. The processing of nine stereopairs was carried out on an analytical plotter. Simultaneously with the on-line plotting of the contour lines the reference data for the computation of the profiles for the differential rectification were recorded. The orthophoto map was covered by four aerial photographs. A smooth data transfer was ensured because the same computer was used for the data acquisition and the differential rectification. Two printing originals were prepared, one for the outline drawings with contour lines and another for the orthophoto. The print was done in black for the two copies. The data acquisition, the computation of the scanning profiles for the othoprojector and the procedure of the differential rectification are described. The reason for the use of on-line drawn contour lines is explained. Further applications, also for digital contour lines, are introduced. Possibilities for the achievement of high photo quality during the reproduction are discussed.

Spatially explicit methane inventory for Switzerland with 500 m x 500 m resolution for 2011 (NetCDF 25 MB)

We present the first high-resolution (500 m × 500 m) gridded methane (CH4) emission inventory for Switzerland, which integrates the national emission totals reported to the United Nations Framework Convention on Climate Change (UNFCCC) and recent CH4 flux studies conducted by research groups across Switzerland. In addition to anthropogenic emissions, we also include natural and semi-natural CH4 fluxes, i.e., emissions from lakes and reservoirs, wetlands, wild animals as well as uptake by forest soils. National CH4 emissions were disaggregated using detailed geostatistical information on source locations and their spatial extent and process- or area-specific emission factors. In Switzerland, the highest CH4 emissions in 2011 originated from the agricultural sector (150 Gg CH4/yr), mainly produced by ruminants and manure management, followed by emissions from waste management (15 Gg CH4/yr) mainly from landfills and the energy sector (12 Gg CH4/yr), which was dominated by emissions from natural gas distribution. Compared to the anthropogenic sources, emissions from natural and semi-natural sources were relatively small (6 Gg CH4/yr), making up only 3 % of the total emissions in Switzerland. CH4 fluxes from agricultural soils were estimated to be not significantly different from zero (between -1.5 and 0 Gg CH4/yr), while forest soils are a CH4 sink (approx. -2.8 Gg CH4/yr), partially offsetting other natural emissions. Estimates of uncertainties are provided for the different sources, including an estimate of spatial disaggregation errors deduced from a comparison with a global (EDGAR v4.2) and a European CH4 inventory (TNO/MACC). This new spatially-explicit emission inventory for Switzerland will provide valuable input for regional scale atmospheric modeling and inverse source estimation.

Global Ocean Biomes: Mean and time-varying maps (NetCDF 7.8 MB)

Large-scale studies of ocean biogeochemistry and carbon cycling have often partitioned the ocean into regions along lines of latitude and longitude despite the fact that spatially more complex boundaries would be closer to the true biogeography of the ocean. Herein, we define 17 open-ocean biomes classified from four observational data sets: sea surface temperature (SST), spring/summer chlorophyll a concentrations (Chl a), ice fraction, and maximum mixed layer depth (maxMLD) on a 1° × 1° grid. By considering interannual variability for each input, we create dynamic ocean biome boundaries that shift annually between 1998 and 2010. Additionally we create a core biome map, which includes only the grid cells that do not change biome assignment across the 13 years of the time-varying biomes. These biomes can be used in future studies to distinguish large-scale ocean regions based on biogeochemical function.

Modeled uncertainties in marine N2O emissions with links to source files (52 MB, zipped)

The ocean is responsible for up to a third of total global nitrous oxide (N2O) emissions, but uncertainties in emission rates of this potent greenhouse gas are high (>100%). Here we use a marine biogeochemical model to assess six major uncertainties in estimates of N2O production, thereby providing guidance in how future studies may most effectively reduce uncertainties in current and future marine N2O emissions. Potential surface N2O production from nitrification causes the largest uncertainty in N2O emissions (estimated up to ~1.6 Tg N/yr, or 48% of modeled values), followed by the unknown oxygen concentration at which N2O production switches to N2O consumption (0.8 Tg N/yr, or 24% of modeled values). Other uncertainties are minor, cumulatively changing regional emissions by <15%. If production of N2O by surface nitrification could be ruled out in future studies, uncertainties in marine N2O emissions would be halved.