Dive depth profile and at surface behaviour data of emperor penguins from Pointe Géologie, Adélie Land, Antarctica, from expedition DDU 2005

Adult male and female emperor penguins (Aptenodytes forsteri) were fitted with satellite transmitters at Pointe-Géologie (Adélie Land), Dumont d'Urville Sea coast, in November 2005. Nine of 30 data sets were selected for analyses to investigate the penguins' diving behaviour at high resolution (doi:10.1594/PANGAEA.633708, doi:10.1594/PANGAEA.633709, doi:10.1594/PANGAEA.633710, doi:10.1594/PANGAEA.633711). The profiles are in synchrony with foraging trips of the birds during austral spring (doi:10.1594/PANGAEA.472171, doi:10.1594/PANGAEA.472173, doi:10.1594/PANGAEA.472164, doi:10.1594/PANGAEA.472160, doi:10.1594/PANGAEA.472161). Corresponding high resolution winter data (n = 5; archived elsewhere) were provided by A. Ancel, Centre d'Ecologie et Physiologie Energétiques, CNRS, Strasbourg, France. Air-breathing divers tend to increase their overall dive duration with increasing dive depth. In most penguin species, this occurs due to increasing transit (descent and ascent) durations but also because the duration of the bottom phase of the dive increases with increasing depth. We interpreted the efficiency with which emperor penguins can exploit different diving depths by analysing dive depth profile data of nine birds studied during the early and late chick-rearing period in Adélie Land, Antarctica. Another eight datasets of dive depth and duration frequency recordings (doi:10.1594/PANGAEA.472150, doi:10.1594/PANGAEA.472152, doi:10.1594/PANGAEA.472154, doi:10.1594/PANGAEA.472155, doi:10.1594/PANGAEA.472142, doi:10.1594/PANGAEA.472144, doi:10.1594/PANGAEA.472146, doi:10.1594/PANGAEA.472147), which backup the analysed high resolution depth profile data, and dive depth and duration frequency recordings of another bird (doi:10.1594/PANGAEA.472156, doi:10.1594/PANGAEA.472148) did not match the requirement of high resolution for analyses. Eleven additional data sets provide information on the overall foraging distribution of emperor penguins during the period analysed (doi:10.1594/PANGAEA.472157, doi:10.1594/PANGAEA.472158, doi:10.1594/PANGAEA.472162, doi:10.1594/PANGAEA.472163, doi:10.1594/PANGAEA.472166, doi:10.1594/PANGAEA.472167, doi:10.1594/PANGAEA.472168, doi:10.1594/PANGAEA.472170, doi:10.1594/PANGAEA.472172, doi:10.1594/PANGAEA.472174, doi:10.1594/PANGAEA.472175).

San Francisco Coastal System grain size and geochemical data for sand provenance study

Over 150 million cubic meter of sand-sized sediment has disappeared from the central region of the San Francisco Bay Coastal System during the last half century. This enormous loss may reflect numerous anthropogenic influences, such as watershed damming, bay-fill development, aggregate mining, and dredging. The reduction in Bay sediment also appears to be linked to a reduction in sediment supply and recent widespread erosion of adjacent beaches, wetlands, and submarine environments. A unique, multi-faceted provenance study was performed to definitively establish the primary sources, sinks, and transport pathways of beach sized-sand in the region, thereby identifying the activities and processes that directly limit supply to the outer coast. This integrative program is based on comprehensive surficial sediment sampling of the San Francisco Bay Coastal System, including the seabed, Bay floor, area beaches, adjacent rock units, and major drainages. Analyses of sample morphometrics and biological composition (e.g., Foraminifera) were then integrated with a suite of tracers including 87Sr/86Sr and 143Nd/144Nd isotopes, rare earth elements, semi-quantitative X-ray diffraction mineralogy, and heavy minerals, and with process-based numerical modeling, in situ current measurements, and bedform asymmetry to robustly determine the provenance of beach-sized sand in the region.

Model simulation output data (CCSM3) related to uplift of Africa and Himalaya/Tibet Plateau and the influence on tropical African vegetation

Hominid evolution in the late Miocene has long been hypothesized to be linked to the retreat of the tropical rainforest in Africa. One cause for the climatic and vegetation change often considered was uplift of Africa, but also uplift of the Himalaya and the Tibetan Plateau was suggested to have impacted rainfall distribution over Africa. Recent proxy data suggest that in East Africa open grassland habitats were available to the common ancestors of hominins and apes long before their divergence and do not find evidence for a closed rainforest in the late Miocene. We used the coupled global general circulation model CCSM3 including an interactively coupled dynamic vegetation module to investigate the impact of topography on African hydro-climate and vegetation. We performed sensitivity experiments altering elevations of the Himalaya and the Tibetan Plateau as well as of East and Southern Africa. The simulations confirm the dominant impact of African topography for climate and vegetation development of the African tropics. Only a weak influence of prescribed Asian uplift on African climate could be detected. The model simulations show that rainforest coverage of Central Africa is strongly determined by the presence of elevated African topography. In East Africa, despite wetter conditions with lowered African topography, the conditions were not favorable enough to maintain a closed rainforest. A discussion of the results with respect to other model studies indicates a minor importance of vegetation-atmosphere or ocean-atmosphere feedbacks and a large dependence of the simulated vegetation response on the land surface/vegetation model.

E-RUN version 1.1: Observational gridded runoff estimates for Europe, link to data in NetCDF format (69 MB)

River runoff is an essential climate variable as it is directly linked to the terrestrial water balance and controls a wide range of climatological and ecological processes. Despite its scientific and societal importance, there are to date no pan-European observation-based runoff estimates available. Here we employ a recently developed methodology to estimate monthly runoff rates on regular spatial grid in Europe. For this we first assemble an unprecedented collection of river flow observations, combining information from three distinct data bases. Observed monthly runoff rates are first tested for homogeneity and then related to gridded atmospheric variables (E-OBS version 12) using machine learning. The resulting statistical model is then used to estimate monthly runoff rates (December 1950 - December 2015) on a 0.5° x 0.5° grid. The performance of the newly derived runoff estimates is assessed in terms of cross validation. The paper closes with example applications, illustrating the potential of the new runoff estimates for climatological assessments and drought monitoring.

E-RUN version 1.0: Observational gridded runoff estimates for Europe, link to data in NetCDF format (68 MB)

River runoff is an essential climate variable as it is directly linked to the terrestrial water balance and controls a wide range of climatological and ecological processes. Despite its scientific and societal importance, there are to date no pan-European observation-based runoff estimates available. Here we employ a recently developed methodology to estimate monthly runoff rates on regular spatial grid in Europe. For this we first collect an unprecedented collection of river flow observations, combining information from three distinct data bases. Observed monthly runoff rates are first tested for homogeneity and then related to gridded atmospheric variables (E-OBS version 11) using machine learning. The resulting statistical model is then used to estimate monthly runoff rates (December 1950-December 2014) on a 0.5° × 0.5° grid. The performance of the newly derived runoff estimates is assessed in terms of cross validation. The paper closes with example applications, illustrating the potential of the new runoff estimates for climatological assessments and drought monitoring.

Reference list of 265 sources used for the discovery of relationships between data clusters and metadata properties

Visual cluster analysis provides valuable tools that help analysts to understand large data sets in terms of representative clusters and relationships thereof. Often, the found clusters are to be understood in context of belonging categorical, numerical or textual metadata which are given for the data elements. While often not part of the clustering process, such metadata play an important role and need to be considered during the interactive cluster exploration process. Traditionally, linked-views allow to relate (or loosely speaking: correlate) clusters with metadata or other properties of the underlying cluster data. Manually inspecting the distribution of metadata for each cluster in a linked-view approach is tedious, specially for large data sets, where a large search problem arises. Fully interactive search for potentially useful or interesting cluster to metadata relationships may constitute a cumbersome and long process. To remedy this problem, we propose a novel approach for guiding users in discovering interesting relationships between clusters and associated metadata. Its goal is to guide the analyst through the potentially huge search space. We focus in our work on metadata of categorical type, which can be summarized for a cluster in form of a histogram. We start from a given visual cluster representation, and compute certain measures of interestingness defined on the distribution of metadata categories for the clusters. These measures are used to automatically score and rank the clusters for potential interestingness regarding the distribution of categorical metadata. Identified interesting relationships are highlighted in the visual cluster representation for easy inspection by the user. We present a system implementing an encompassing, yet extensible, set of interestingness scores for categorical metadata, which can also be extended to numerical metadata. Appropriate visual representations are provided for showing the visual correlations, as well as the calculated ranking scores. Focusing on clusters of time series data, we test our approach on a large real-world data set of time-oriented scientific research data, demonstrating how specific interesting views are automatically identified, supporting the analyst discovering interesting and visually understandable relationships.

Diatom isotope data from ODP Hole 178-1098A for the last deglaciation (12.2-12.8 ka BP)

Understanding the response of the Antarctic ice sheets during the rapid climatic change that accompanied the last deglaciation has implications for establishing the susceptibility of these regions to future 21st Century warming. A unique diatom d18O record derived from a high-resolution deglacial seasonally laminated core section off the west Antarctic Peninsula (WAP) is presented here. By extracting and analysing single species samples from individual laminae, season-specific isotope records were separately generated to show changes in glacial discharge to the coastal margin during spring and summer months. As well as documenting significant intra-annual seasonal variability during the deglaciation, with increased discharge occurring in summer relative to spring, further intra-seasonal variations are apparent between individual taxa linked to the environment that individual diatom species live in. Whilst deglacial d18O are typically lower than those for the Holocene, indicating glacial discharge to the core site peaked at this time, inter-annual and inter-seasonal alternations in excess of 3 per mil suggest significant variability in the magnitude of these inputs. These deglacial variations in glacial discharge are considerably greater than those seen in the modern day water column and would have altered both the supply of oceanic warmth to the WAP as well as regional marine/atmospheric interactions. In constraining changes in glacial discharge over the last deglaciation, the records provide a future framework for investigating links between annually resolved records of glacial dynamics and ocean/climate variability along the WAP.