30 years of synoptic observations from Neumayer Station with links to datasets

The analysis of research data plays a key role in data-driven areas of science. Varieties of mixed research data sets exist and scientists aim to derive or validate hypotheses to find undiscovered knowledge. Many analysis techniques identify relations of an entire dataset only. This may level the characteristic behavior of different subgroups in the data. Like automatic subspace clustering, we aim at identifying interesting subgroups and attribute sets. We present a visual-interactive system that supports scientists to explore interesting relations between aggregated bins of multivariate attributes in mixed data sets. The abstraction of data to bins enables the application of statistical dependency tests as the measure of interestingness. An overview matrix view shows all attributes, ranked with respect to the interestingness of bins. Complementary, a node-link view reveals multivariate bin relations by positioning dependent bins close to each other. The system supports information drill-down based on both expert knowledge and algorithmic support. Finally, visual-interactive subset clustering assigns multivariate bin relations to groups. A list-based cluster result representation enables the scientist to communicate multivariate findings at a glance. We demonstrate the applicability of the system with two case studies from the earth observation domain and the prostate cancer research domain. In both cases, the system enabled us to identify the most interesting multivariate bin relations, to validate already published results, and, moreover, to discover unexpected relations.

Soil, snow, weather, and sub-surface storage data from a mountain catchment in the rain-snow transition zone

A comprehensive hydroclimatic data set is presented for the 2011 water year to improve understanding of hydrologic processes in the rain-snow transition zone. This type of dataset is extremely rare in scientific literature because of the quality and quantity of soil depth, soil texture, soil moisture, and soil temperature data. Standard meteorological and snow cover data for the entire 2011 water year are included, which include several rain-on-snow events. Surface soil textures and soil depths from 57 points are presented as well as soil texture profiles from 14 points. Meteorological data include continuous hourly shielded, unshielded, and wind corrected precipitation, wind speed, air temperature, relative humidity, dew point temperature, and incoming solar and thermal radiation data. Sub-surface data included are hourly soil moisture data from multiple depths from 7 soil profiles within the catchment, and soil temperatures from multiple depths from 2 soil profiles. Hydrologic response data include hourly stream discharge from the catchment outlet weir, continuous snow depths from one location, intermittent snow depths from 5 locations, and snow depth and density data from ten weekly snow surveys. Though it represents only a single water year, the presentation of both above and below ground hydrologic condition makes it one of the most detailed and complete hydro-climatic datasets from the climatically sensitive rain-snow transition zone for a wide range of modeling and descriptive studies.

Changes in bottom water corrosiveness and carbonate ion concentrations in the sub-Antarctic Atlantic during the last glacial period

The glacial climate system transitioned rapidly between cold (stadial) and warm (interstadial) conditions in the Northern Hemisphere. This variability, referred to as Dansgaard-Oeschger variability, is widely believed to arise from perturbations of the Atlantic Meridional Overturning Circulation. Evidence for such changes during the longer Heinrich stadials has been identified, but direct evidence for overturning circulation changes during Dansgaard-Oeschger events has proven elusive. Here we reconstruct bottom water [CO3]2- variability from B/Ca ratios of benthic foraminifera and indicators of sedimentary dissolution, and use these reconstructions to infer the flow of northern-sourced deep water to the deep central sub-Antarctic Atlantic Ocean. We find that nearly every Dansgaard-Oeschger interstadial is accompanied by a rapid incursion of North Atlantic Deep Water into the deep South Atlantic. Based on these results and transient climate model simulations, we conclude that North Atlantic stadial-interstadial climate variability was associated with significant Atlantic overturning circulation changes that were rapidly transmitted across the Atlantic. However, by demonstrating the persistent role of Atlantic overturning circulation changes in past abrupt climate variability, our reconstructions of carbonate chemistry further indicate that the carbon cycle response to abrupt climate change was not a simple function of North Atlantic overturning.

Effects of ocean acidification on visual risk assessment in coral reef fishes

1. With the global increase in CO2 emissions, there is a pressing need for studies aimed at understanding the effects of ocean acidification on marine ecosystems. Several studies have reported that exposure to CO2 impairs chemosensory responses of juvenile coral reef fishes to predators. Moreover, one recent study pointed to impaired responses of reef fish to auditory cues that indicate risky locations. These studies suggest that altered behaviour following exposure to elevated CO2 is caused by a systemic effect at the neural level. 2. The goal of our experiment was to test whether juvenile damselfish Pomacentrus amboinensis exposed to different levels of CO2 would respond differently to a potential threat, the sight of a large novel coral reef fish, a spiny chromis, Acanthochromis polyancanthus, placed in a watertight bag. 3. Juvenile damselfish exposed to 440 (current day control), 550 or 700 µatm CO2 did not differ in their response to the chromis. However, fish exposed to 850 µatm showed reduced antipredator responses; they failed to show the same reduction in foraging, activity and area use in response to the chromis. Moreover, they moved closer to the chromis and lacked any bobbing behaviour typically displayed by juvenile damselfishes in threatening situations. 4. Our results are the first to suggest that response to visual cues of risk may be impaired by CO2 and provide strong evidence that the multi-sensory effects of CO2 may stem from systematic effects at the neural level.

Active methane seepage in the Southern Ocean, off the sub-Antarctic island of South Georgia

An extensive submarine cold-seep area was discovered on the northern shelf of South Georgia during R/V Polarstern cruise ANT-XXIX/4 in spring 2013. Hydroacoustic surveys documented the presence of 133 gas bubble emissions, which were restricted to glacially-formed fjords and troughs. Video-based sea floor observations confirmed the sea floor origin of the gas emissions and spatially related microbial mats. Effective methane transport from these emissions into the hydrosphere was proven by relative enrichments of dissolved methane in near-bottom waters. Stable carbon isotopic signatures pointed to a predominant microbial methane formation, presumably based on high organic matter sedimentation in this region. Although known from many continental margins in the world's oceans, this is the first report of an active area of methane seepage in the Southern Ocean. Our finding of substantial methane emission related to a trough and fjord system, a topographical setting that exists commonly in glacially-affected areas, opens up the possibility that methane seepage is a more widespread phenomenon in polar and sub-polar regions than previously thought.

Probability sampling protocol of classification maps from spaceborne/airborne image

To deliver sample estimates provided with the necessary probability foundation to permit generalization from the sample data subset to the whole target population being sampled, probability sampling strategies are required to satisfy three necessary not sufficient conditions: (i) All inclusion probabilities be greater than zero in the target population to be sampled. If some sampling units have an inclusion probability of zero, then a map accuracy assessment does not represent the entire target region depicted in the map to be assessed. (ii) The inclusion probabilities must be: (a) knowable for nonsampled units and (b) known for those units selected in the sample: since the inclusion probability determines the weight attached to each sampling unit in the accuracy estimation formulas, if the inclusion probabilities are unknown, so are the estimation weights. This original work presents a novel (to the best of these authors' knowledge, the first) probability sampling protocol for quality assessment and comparison of thematic maps generated from spaceborne/airborne Very High Resolution (VHR) images, where: (I) an original Categorical Variable Pair Similarity Index (CVPSI, proposed in two different formulations) is estimated as a fuzzy degree of match between a reference and a test semantic vocabulary, which may not coincide, and (II) both symbolic pixel-based thematic quality indicators (TQIs) and sub-symbolic object-based spatial quality indicators (SQIs) are estimated with a degree of uncertainty in measurement in compliance with the well-known Quality Assurance Framework for Earth Observation (QA4EO) guidelines. Like a decision-tree, any protocol (guidelines for best practice) comprises a set of rules, equivalent to structural knowledge, and an order of presentation of the rule set, known as procedural knowledge. The combination of these two levels of knowledge makes an original protocol worth more than the sum of its parts. The several degrees of novelty of the proposed probability sampling protocol are highlighted in this paper, at the levels of understanding of both structural and procedural knowledge, in comparison with related multi-disciplinary works selected from the existing literature. In the experimental session the proposed protocol is tested for accuracy validation of preliminary classification maps automatically generated by the Satellite Image Automatic MapperT (SIAMT) software product from two WorldView-2 images and one QuickBird-2 image provided by DigitalGlobe for testing purposes. In these experiments, collected TQIs and SQIs are statistically valid, statistically significant, consistent across maps and in agreement with theoretical expectations, visual (qualitative) evidence and quantitative quality indexes of operativeness (OQIs) claimed for SIAMT by related papers. As a subsidiary conclusion, the statistically consistent and statistically significant accuracy validation of the SIAMT pre-classification maps proposed in this contribution, together with OQIs claimed for SIAMT by related works, make the operational (automatic, accurate, near real-time, robust, scalable) SIAMT software product eligible for opening up new inter-disciplinary research and market opportunities in accordance with the visionary goal of the Global Earth Observation System of Systems (GEOSS) initiative and the QA4EO international guidelines.