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The proliferation of icebergs from Antarctica over the past decade has raised questions about their potential impact on the surrounding pelagic ecosystem. Two free-drifting icebergs, 0.1 and 30.8 square kilometers in aerial surface area, and the surrounding waters were sampled in the northwest Weddell Sea during austral spring 2005. There was substantial enrichment of terrigenous material, and there were high concentrations of chlorophyll, krill, and seabirds surrounding each iceberg, extending out to a radial distance of ~3.7 kilometers. Extrapolating these results to all icebergs in the same size range, with the use of iceberg population estimates from satellite surveys, indicates that they similarly affect 39% of the surface ocean in this region. These results suggest that free-drifting icebergs can substantially affect the pelagic ecosystem of the Southern Ocean and can serve as areas of enhanced production and sequestration of organic carbon to the deep sea.

Regional warming around West Antarctica, including the Antarctic Peninsula, is related to the retreat of glaciers that has resulted in significant ice mass loss in recent decades (De Angelis and Skvarca, 2003). Large icebergs (> 18.5 km long) originating from ice shelves in the Ross and Weddell Seas (Scambos et al., 2000) are attributed primariry to major loss events in these regions. Once free, icebergs become entrained in the counterclockwise Antarctic Coastal Current (Figure 1), eventually entering a strong northward flow in the Northwest Weddell Sea. We examined free-drifting icebergs in the Atlantic sector of the Southern Ocean in December 2005, aboard ARSV Laurence M. Gould, and in June 2008 and March/April 2009, aboard RVIB Nathaniel B. Palmer. Prior to these studies, little information was available about the effects of icebergs on the pelagic realm. On these cruises, we investigated the \"iceberg ecosystem\" (Smith et al., 2007; Smith, 2011) to assess the degree to which icebergs are (1) hotspots of biological activity across multiple trophic levels, and (2) focal points for enhanced export of organic carbon to the deep sea. An important focus of this work was to examine the fundamental mechanisms by which icebergs affect the pelagic ecosystem, including physical disruption and effects on the availability of critical nutrients (e.g., iron, nitrate).

We describe the results from a spatial cyberinfrastructure developed to characterize the meltwater field around individual icebergs and integrate the results with regional- and global-scale data. During the course of the cyberinfrastructure development, it became clear that we were also building an integrated sampling planning capability across multidisciplinary teams that provided greater agility in allocating expedition resources resulting in new scientific insights. The cyberinfrastructure-enabled method is a complement to the conventional methods of hydrographic sampling in which the ship provides a static platform on a station-by-station basis. We adapted a sea-floor mapping method to more rapidly characterize the sea surface geophysically and biologically. By jointly analyzing the multisource, continuously sampled biological, chemical, and physical parameters, using Global Positioning System time as the data fusion key, this surface-mapping method enables us to examine the relationship between the meltwater field of the iceberg to the larger-scale marine ecosystem of the Southern Ocean. Through geospatial data fusion, we are able to combine very fine-scale maps of dynamic processes with more synoptic but lower-resolution data from satellite systems. Our results illustrate the importance of spatial cyberinfrastructure in the overall scientific enterprise and identify key interfaces and sources of error that require improved controls for the development of future Earth observing systems as we move into an era of peta- and exascale, data-intensive computing.

Accurate forecasts of precipitation during landfalling atmospheric rivers (ARs) are critical because ARs play a large role in water supply and flooding for many regions. In this study, we have used hundreds of observations to verify global and regional model forecasts of atmospheric rivers making landfall in Northern California and offshore in the midlatitude northeast Pacific Ocean. We have characterized forecast error and the predictability limit in AR water vapor transport, static stability, onshore precipitation, and standard atmospheric fields. Analysis is also presented that apportions the role of orographic forcing and precipitation response in driving errors in forecast precipitation after AR landfall. It is found that the global model and the higher-resolution regional model reach their predictability limit in forecasting the atmospheric state during ARs at similar lead times, and both present similar and important errors in low-level water vapor flux, moiststatic stability, and precipitation. However, the relative contribution of forcing and response to the incurred precipitation error is very different in the two models. It can be demonstrated using the analysis presented herein that improving water vapor transport accuracy can significantly reduce regional model precipitation errors during ARs, while the same cannot be demonstrated for the global model.

The Milky Way’s (MW) satellite population is a powerful probe of warm dark matter (WDM) models as the abundance of small substructures is very sensitive to the properties of the WDM particle. However, only a partial census of the MW’s complement of satellite galaxies exists because surveys of the MW’s close environs are incomplete both in depth and in sky coverage. We present a new Bayesian analysis that combines the sample of satellites recently discovered by the Dark Energy Survey (DES) with those found in the Sloan Digital Sky Survey (SDSS) to estimate the total satellite galaxy luminosity function down to M v = 0. We find that there should be at least$124_{ - 27}^{ + 40}$(68% CL, statistical error) satellites as bright or brighter than M v = 0 within 300 kpc of the Sun, with only a weak dependence on MW halo mass. When it comes online the Large Synoptic Survey Telescope should detect approximately half of this population. We also show that WDM models infer the same number of satellites as in ΛCDM, which will allow us to rule out those models that produce insufficient substructure to be viable.

The Milky Way is surrounded by 11 ‘classical’ satellite galaxies in a remarkable configuration: a thin plane that is possibly rotationally supported. Such a structure is thought to be highly unlikely to arise in the standard (ΛCDM) cosmological model (Λ cold dark matter model, where Λ is the cosmological constant). While other apparent discrepancies between predictions and observations of Milky Way satellite galaxies may be explained either through baryonic effects or by invoking alternative forms of dark matter particles, there is no known mechanism for making rotating satellite planes within the dispersion-supported dark matter haloes predicted to surround galaxies such as the Milky Way. This is the so-called ‘plane of satellites problem’, which challenges not only the ΛCDM model but the entire concept of dark matter. Here we show that the reportedly exceptional anisotropy of the Milky Way satellites is explained, in large part, by their lopsided radial distribution combined with the temporary conjunction of the two most distant satellites, Leo I and Leo II. Using Gaia proper motions, we show that the orbital pole alignment is much more common than previously reported, and reveal the plane of satellites to be transient rather than rotationally supported. Comparing with new simulations, where such short-lived planes are common, we find the Milky Way satellites to be compatible with standard model expectations.The ‘plane of satellite galaxies’ surrounding our Milky Way seemed to defy dark matter theory for 40 years. Observations now suggest that the alignment is transient, while new simulations form similar structures far more often than previously thought.

The cold dark matter model has become the leading theoretical picture for the formation of structure in the Universe. This model, together with the theory of cosmic inflation, makes a clear prediction for the initial conditions for structure formation and predicts that structures grow hierarchically through gravitational instability. Testing this model requires that the precise measurements delivered by galaxy surveys can be compared to robust and equally precise theoretical calculations. Here we present a simulation of the growth of dark matter structure using 2,160 3 particles, following them from redshift z = 127 to the present in a cube-shaped region 2.230 billion lightyears on a side. In postprocessing, we also follow the formation and evolution of the galaxies and quasars. We show that baryon-induced features in the initial conditions of the Universe are reflected in distorted form in the low-redshift galaxy distribution, an effect that can be used to constrain the nature of dark energy with future generations of observational surveys of galaxies. Evolution of the universe Computer simulations have been used to blend the giant snapshot of cosmic history provided by modern galaxy surveys into a coherent picture displaying the underlying physical processes of galaxy formation and evolution. The growth of 20 million galaxies in a huge cosmological volume was modelled and it proved possible to identify the unusual formation sites and eventual fate of the first bright quasars. It was shown that large surveys are likely to include features in the galaxy distribution that directly reflect physics in the early Universe and may clarify the nature of the mysterious dark energy driving its current accelerated expansion. The cover shows the distribution of dark matter in a slice of thickness 60 million lightyears through the simulated universe.

Issues related to data preservation and sharing are receiving increased attention from scientific societies, funding agencies, and the broad scientific community. Ecologists, for example, are increasingly using data collected by other scientists to address questions at broader spatial, temporal, and thematic scales (e.g., global change, biodiversity, sustainability). No data set is perfect and self-explanatory. Ecologists must, therefore, rely upon a set of instructions or documentation to acquire a specific data set, determine its suitability for meeting specific research objectives, and accurately interpret results from subsequent processing, analysis, and modeling. \"Metadata\" represent the set of instructions or documentation that describe the content, context, quality, structure, and accessibility of a data set. Although geospatial metadata standards have been developed and widely endorsed by the geographical science community, such standards do not yet exist for the ecological sciences. In this paper, we examine potential benefits and costs associated with developing and implementing metadata for nongeospatial ecological data. We present a set of generic metadata descriptors that could serve as the basis for a \"metadata standard\" for nongeospatial ecological data. Alternative strategies for metadata implementation that meet differing organizational or investigator-specific objectives are presented. Finally, we conclude with several recommendations related to future development and implementation of ecological metadata.

The Local Group of galaxies offer some of the most discriminating tests of models of cosmic structure formation. For example, observations of the Milky Way (MW) and Andromeda satellite populations appear to be in disagreement with N-body simulations of the \"Lambda Cold Dark Matter\" ({\\Lambda}CDM) model: there are far fewer satellite galaxies than substructures in cold dark matter halos (the \"missing satellites\" problem); dwarf galaxies seem to avoid the most massive substructures (the \"too-big-to-fail\" problem); and the brightest satellites appear to orbit their host galaxies on a thin plane (the \"planes of satellites\" problem). Here we present results from APOSTLE (A Project Of Simulating The Local Environment), a suite of cosmological hydrodynamic simulations of twelve volumes selected to match the kinematics of the Local Group (LG) members. Applying the Eagle code to the LG environment, we find that our simulations match the observed abundance of LG galaxies, including the satellite galaxies of the MW and Andromeda. Due to changes to the structure of halos and the evolution in the LG environment, the simulations reproduce the observed relation between stellar mass and velocity dispersion of individual dwarf spheroidal galaxies without necessitating the formation of cores in their dark matter profiles. Satellite systems form with a range of spatial anisotropies, including one similar to that of the MW, confirming that such a configuration is not unexpected in {\\Lambda}CDM. Finally, based on the observed velocity dispersion, size, and stellar mass, we provide new estimates of the maximum circular velocity for the halos of nine MW dwarf spheroidals.