Grain size distribution of Oligocene and Miocene sediments from the Indus Fan

The Owen Ridge south of Oman represents oceanic crust that was uplifted by compressional tectonic forces in the early Miocene. Build-out of the Indus Fan led to deposition of a thick sequence of turbidites over the site of the Ridge during the late Oligocene and early Miocene. Early Miocene uplift of the Ridge led to a pelagic cap of nannofossil chalks. Two short sequences of turbidites from the pre- and syn-uplift phases were chosen for detailed grain size analysis. The upper Oligocene section at Site 731 is composed of thin (centimeter-decimeter scale) graded mud turbidites separated by relatively thick (decimeter-meter scale) intervals of homogeneous, non-bioturbated clayey siltstones. These finer intervals are unusually silt-rich (about 60%) for ungraded material and were probably deposited as undifferentiated muds from a series of turbidity current tails. By contrast, the lower Miocene section at Site 722 is comprised of a sequence of interbedded turbidites and hemipelagic carbonates. Sharp-based silt turbidites are overlain by burrow-mottled marly nannofossil chalks. The Oligocene sequence may have accumulated in an overbank setting on the middle fan - the local topographic position favoring frequent deposition from turbidity current tails and occasional deposition from the body of a turbidity flow. Uplift of the Ridge in the early Miocene led to pelagic carbonate deposition interrupted only by turbidity currents capable of overcoming a topographic barrier. Further uplift eventually led to entirely pelagic carbonate deposition.

Integrated topographic database for King George Island, South Shetland Islands, with links to shapefiles

SCAR KGIS (SCAR King George Island GIS Project) was an integrated topographic database for King George Island, South Shetland Islands, including the SCAR Feature Catalogue to semantically integrate the data sets. The project, operated by the University of Freiburg, was available at http://portal.uni-freiburg.de/AntSDI as "The Antarctic Spatial Data Infrastructure (AntSDI)". Operation ended in 2007. The remaining data files were archived in shape format (zipped) in projections as recommended by SCAR. The source data was provided by a variety of institutions which were not referenced in the original product.

Topographic model of Greenland (elevation lines in PanMap and ASCII format)

In this paper, a new high-resolution elevation model of Greenland, including the ice sheet as well as the ice free regions, is presented. It is the first published full coverage model, computed with an average resolution of 2 km and providing an unprecedented degree of detail. The topography is modeled from a wide selection of data sources, including satellite radar altimetry from Geosat and ERS 1, airborne radar altimetry and airborne laser altimetry over the ice sheet, and photogrammetric and manual map scannings in the ice free region. The ice sheet model accuracy is evaluated by omitting airborne laser data from the analysis and treating them as ground truth observations. The mean accuracy of the ice sheet elevations is estimated to be 12-13 m, and it is found that on surfaces of a slope between 0.2° and 0.8°, corresponding to approximately 50% of the ice sheet, the model presents a 40% improvement over models based on satellite altimetry alone. On coastal bedrock, the model is compared with stereo triangulated reference points, and it is found that the model accuracy is of the order of 25-35 m in areas covered by stereo photogrammetry scannings and between 200 and 250 m elsewhere.

Modeled monthly local topographic lapse rates, Pacific Northwest, USA

An emerging approach to downscaling the projections from General Circulation Models (GCMs) to scales relevant for basin hydrology is to use output of GCMs to force higher-resolution Regional Climate Models (RCMs). With spatial resolution often in the tens of kilometers, however, even RCM output will likely fail to resolve local topography that may be climatically significant in high-relief basins. Here we develop and apply an approach for downscaling RCM output using local topographic lapse rates (empirically-estimated spatially and seasonally variable changes in climate variables with elevation). We calculate monthly local topographic lapse rates from the 800-m Parameter-elevation Regressions on Independent Slopes Model (PRISM) dataset, which is based on regressions of observed climate against topographic variables. We then use these lapse rates to elevationally correct two sources of regional climate-model output: (1) the North American Regional Reanalysis (NARR), a retrospective dataset produced from a regional forecasting model constrained by observations, and (2) a range of baseline climate scenarios from the North American Regional Climate Change Assessment Program (NARCCAP), which is produced by a series of RCMs driven by GCMs. By running a calibrated and validated hydrologic model, the Soil and Water Assessment Tool (SWAT), using observed station data and elevationally-adjusted NARR and NARCCAP output, we are able to estimate the sensitivity of hydrologic modeling to the source of the input climate data. Topographic correction of regional climate-model data is a promising method for modeling the hydrology of mountainous basins for which no weather station datasets are available or for simulating hydrology under past or future climates.

Macro-epibenthic communities, bathymetry and enviromental information at the tip of the Antarctic Peninsula

The Southern Ocean ecosystem at the Antarctic Peninsula has steep natural environmental gradients, e.g. in terms of water masses and ice cover, and experiences regional above global average climate change. An ecological macroepibenthic survey was conducted in three ecoregions in the north-western Weddell Sea, on the continental shelf of the Antarctic Peninsula in the Bransfield Strait and on the shelf of the South Shetland Islands in the Drake Passage, defined by their environmental envelop. The aim was to improve the so far poor knowledge of the structure of this component of the Southern Ocean ecosystem and its ecological driving forces. It can also provide a baseline to assess the impact of ongoing climate change to the benthic diversity, functioning and ecosystem services. Different intermediate-scaled topographic features such as canyon systems including the corresponding topographically defined habitats 'bank', 'upper slope', 'slope' and 'canyon/deep' were sampled. In addition, the physical and biological environmental factors such as sea-ice cover, chlorophyll-a concentration, small-scale bottom topography and water masses were analysed. Catches by Agassiz trawl showed high among-station variability in biomass of 96 higher systematic groups including ecological key taxa. Large-scale patterns separating the three ecoregions from each other could be correlated with the two environmental factors, sea-ice and depth. Attribution to habitats only poorly explained benthic composition, and small-scale bottom topography did not explain such patterns at all. The large-scale factors, sea-ice and depth, might have caused large-scale differences in pelagic benthic coupling, whilst small-scale variability, also affecting larger scales, seemed to be predominantly driven by unknown physical drivers or biological interactions.

A suite of global, cross-scale topographic variables for environmental and biodiversity modeling, links to files in GeoTIFF format

Topographic variation, the spatial variation in elevation and terrain features, underpins a myriad of patterns and processes in geography and ecology and is key to understanding the variation of life on the planet. The characterization of this variation is scale-dependent, i.e. it varies with the distance over which features are assessed and with the spatial grain (grid cell resolution) of analysis. A fully standardized and global multivariate product of different terrain features has the potential to support many large-scale basic research and analytical applications, however to date, such technique is unavailable. Here we used the digital elevation model products of global 250 m GMTED and near-global 90 m SRTM to derive a suite of topographic variables: elevation, slope, aspect, eastness, northness, roughness, terrain roughness index, topographic position index, vector ruggedness measure, profile and tangential curvature, and 10 geomorphological landform classes. We aggregated each variable to 1, 5, 10, 50 and 100 km spatial grains using several aggregation approaches (median, average, minimum, maximum, standard deviation, percent cover, count, majority, Shannon Index, entropy, uniformity). While a global cross-correlation underlines the high similarity of many variables, a more detailed view in four mountain regions reveals local differences, as well as scale variations in the aggregated variables at different spatial grains. All newly-developed variables are available for download at http://www.earthenv.org and can serve as a basis for standardized hydrological, environmental and biodiversity modeling at a global extent.