Numerical simulations of the Mediterranean sea outflow: impact of the entrainment parameterization in an isopycnic coordinate ocean model

Gravity current entrainment is essential in determining the properties of the interior ocean water masses that result from marginal sea overflows. Although the individual entraining billows will be unresolvable in large-scale ocean models for the foreseeable future, some large-scale simulations are now being carried out that do resolve the intermediate scale environment which may control the rate of entrainment. Hallberg [Mon. Wea. Rev. 128 (2000) 1402] has recently developed an implicit diapycnal mixing scheme for isopycnic coordinate ocean models that includes the Richardson number dependent entrainment parameterization of Turner [J. Fluid Mech. 173 (1986) 431], and which may be capable of representing the gravity current evolution in large-scale ocean models. The present work uses realistic regional simulations with the Miami Isopycnic Coordinate Ocean Model (MICOM) to evaluate ability of this scheme to simulate the entrainment that is observed to occur in the bottom boundary currents downstream of the Mediterranean outflow. These simulations are strikingly similar to the observations, indicating that this scheme does produce realistic mixing between the Mediterranean outflow and the North Atlantic Central Water. Sensitivity studies identify the critical Richardson number below which vigorous entrainment occurs as a particularly important parameter. Some of these experiments also show meddies detaching from the Mediterranean undercurrent at locations that appear to be highly influenced by topographic features.     

Channel response to a dam-removal sediment pulse captured at high-temporal resolution using routine gage data

In this study, we captured how a river channel responds to a sediment pulse originating from a dam removal using multiple lines of evidence derived from streamflow gages along the Patapsco River, Maryland, USA. Gages captured characteristics of the sediment pulse, including travel times of its leading edge (~7.8 km yr⁻¹) and peak (~2.6 km yr⁻¹) and suggest both translation and increasing dispersion. The pulse also changed local hydraulics and energy conditions, increasing flow velocities and Froude number, due to bed fining, homogenization and/or slope adjustment. Immediately downstream of the dam, recovery to pre-pulse conditions occurred within the year, but farther downstream recovery was slower, with the tail of the sediment pulse working through the lower river by the end of the study 7 years later. The patterns and timing of channel change associated with the sediment pulse were not driven by large flow or suspended sediment-transporting events, with change mostly occurring during lower flows. This suggests pulse mobility was controlled by process-factors largely independent of high flow. In contrast, persistent changes occurred to out-of-channel flooding dynamics. Stage associated with flooding increased during the arrival of the sediment pulse, 1 to 2 years after dam removal, suggesting persistent sediment deposition at the channel margins and nearby floodplain. This resulted in National Weather Service-indicated flood stages being attained by 3–43% smaller discharges compared to earlier in the study period. This study captured a two-signal response from the sediment pulse: (1) short- to medium-term (weeks to months) translation and dispersion within the channel, resulting in aggradation and recovery of bed elevations and changing local hydraulics; and (2) dispersion and persistent longer-term (years) effects of sediment deposition on overbank surfaces. This study further demonstrated the utility of US Geological Survey gage data to quantify geomorphic change, increase temporal resolution, and provide insights into trajectories of change over varying spatial and temporal scales.     

Subarctic catchment water storage and carbon cycling – Leading the way for future studies using integrated datasets at Pallas,Finland

Subarctic ecohydrological processes are changing rapidly, but detailed and integrated ecohydrological investigations are not as widespread as necessary. We introduce an integrated research catchment site (Pallas) for atmosphere, ecosystems, and ecohydrology studies in subarctic conditions in Finland that can be used for a new set of comparative catchment investigations. The Pallas site provides unique observational data and high-intensity field measurement datasets over long periods. The infrastructure for atmosphere- to landscape-scale research in ecosystem processes in a subarctic landscape has recently been complemented with detailed ecohydrological measurements. We identify three dominant processes in subarctic ecohydrology: (a) strong seasonality drives ecohydrological regimes, (b) limited dynamic storage causes rapid stream response to water inputs (snowmelt and intensive storms), and (c) hydrological state of the system regulates catchment-scale dissolved carbon dynamics and greenhouse (GHG) fluxes. Surface water and groundwater interactions play an important role in regulating catchment-scale carbon balances and ecosystem respiration within subarctic peatlands, particularly their spatial variability in the landscape. Based on our observations from Pallas, we highlight key research gaps in subarctic ecohydrology and propose several ways forward. We also demonstrate that the Pallas catchment meets the need for sustaining and pushing the boundaries of critical long-term integrated ecohydrological research in high-latitude environments.     

New snow metrics for a warming world

Snow is Earth's most climatically sensitive land cover type. Traditional snow metrics may not be able to adequately capture the changing nature of snow cover. For example, April 1 snow water equivalent (SWE) has been an effective index for streamflow forecasting, but it cannot express the effects of midwinter melt events, now expected in warming snow climates, nor can we assume that station-based measurements will be representative of snow conditions in future decades. Remote sensing and climate model data provide capacity for a suite of multi-use snow metrics from local to global scales. Such indicators need to be simple enough to “tell the story” of snowpack changes over space and time, but not overly simplistic or overly complicated in their interpretation. We describe a suite of spatially explicit, multi-temporal snow metrics based on global satellite data from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) and downscaled climate model output for the U.S. We describe and provide examples for Snow Cover Frequency (SCF), Snow Disappearance Date (SDD), At-Risk Snow (ARS), and Frequency of a Warm Winter (FWW). Using these retrospective and prospective snow metrics, we assess the current and future snow-related conditions in three hydroclimatically different U.S. watersheds: the Truckee, Colorado Headwaters, and Upper Connecticut. In the two western U.S. watersheds, SCF and SDD show greater sensitivity to annual differences in snow cover compared with data from the ground-based Snow Telemetry (SNOTEL) network. The eastern U.S. watershed does not have a ground-based network of data, so these MODIS-derived metrics provide uniquely valuable snow information. The ARS and FWW metrics show that the Truckee Watershed is highly vulnerable to conversion from snowfall to rainfall (ARS) and midwinter melt events (FWW) throughout the seasonal snow zone. In comparison, the Colorado Headwaters and Upper Connecticut Watersheds are colder and much less vulnerable through mid- and late-century.     

The dark matter environment of the Abell 901/902 supercluster: a weak lensing analysis of the HST STAGES survey

We present a high-resolution dark matter reconstruction of the   z = 0.165  Abell 901/902 supercluster from a weak lensing analysis of the Hubble Space Telescope STAGES survey. We detect the four main structures of the supercluster at high significance, resolving substructure within and between the clusters. We find that the distribution of dark matter is well traced by the cluster galaxies, with the brightest cluster galaxies marking out the strongest peaks in the dark matter distribution. We also find a significant extension of the dark matter distribution of Abell 901a in the direction of an infalling X-ray group Abell 901α. We present mass, mass-to-light and mass-to-stellar mass ratio measurements of the structures and substructures that we detect. We find no evidence for variation of the mass-to-light and mass-to-stellar mass ratio between the different clusters. We compare our space-based lensing analysis with an earlier ground-based lensing analysis of the supercluster to demonstrate the importance of space-based imaging for future weak lensing dark matter 'observations'.     

Dimensionless measures of turbulent magnetohydrodynamic dissipation rates

The magnetic Reynolds number, R _M, is defined as the product of a characteristic scale and associated flow speed divided by the microphysical magnetic diffusivity. For laminar flows, R _M also approximates the ratio of advective to dissipative terms in the total magnetic energy equation, but for turbulent flows this latter ratio depends on the energy spectra and approaches unity in a steady state. To generalize for flows of arbitrary spectra we define an effective magnetic dissipation number,   R _M,e  , as the ratio of the advection to microphysical dissipation terms in the total magnetic energy equation, incorporating the full spectrum of scales, arbitrary magnetic Prandtl numbers, and distinct pairs of inner and outer scales for magnetic and kinetic spectra. As expected, for a substantial parameter range   R _M,e∼ O (1) ≪ R _M  . We also distinguish   R _M,e  from     where the latter is an effective magnetic Reynolds number for the mean magnetic field equation when a turbulent diffusivity is explicitly imposed as a closure. That   R _M,e  and     approach unity even if   R _M≫ 1  highlights that, just as in hydrodynamic turbulence, energy dissipation of large-scale structures in turbulent flows via a cascade can be much faster than the dissipation of large-scale structures in laminar flows. This illustrates that the rate of energy dissipation by magnetic reconnection is much faster in turbulent flows, and much less sensitive to microphysical reconnection rates compared to laminar flows.     

The lacustrine microbial carbonate factory of the successive Lake Bonneville and Great Salt Lake,Utah, USA

The Bonneville Basin is a continental lacustrine system accommodating extensive microbial carbonate deposits corresponding to two distinct phases: the deep Lake Bonneville (30 000 to 11 500 ¹⁴C bp ) and the shallow Great Salt Lake (since 11 500 ¹⁴C bp ). A characterization of these microbial deposits and their associated sediments provides insights into their spatio‐temporal distribution patterns. The Bonneville phase preferentially displays vertical distribution of the microbial deposits resulting from high‐amplitude lake level variations. Due to the basin physiography, the microbial deposits were restricted to a narrow shoreline belt following Bonneville lake level variations. Carbonate production was more efficient during intervals of relative lake level stability as recorded by the formation of successive terraces. In contrast, the Great Salt Lake microbial deposits showed a great lateral distribution, linked to the modern flat bottom configuration. A low vertical distribution of the microbial deposits was the result of the shallow water depth combined with a low amplitude of lake level fluctuations. These younger microbial deposits display a higher diversity of fabrics and sizes. They are distributed along an extensive ‘shore to lake’ transect on a flat platform in relation to local and progressive accommodation space changes. Microbial deposits are temporally discontinuous throughout the lake history showing longer hiatuses during the Bonneville phase. The main parameters controlling the rate of carbonate production are related to the interaction between physical (kinetics of the mineral precipitation, lake water temperature and runoff), chemical (Ca²⁺, Mg²⁺ and HCO₃^? concentrations, Mg/Ca ratio, dilution and depletion) and/or biological (trophic) factors. The contrast in evolution of Lake Bonneville and Great Salt Lake microbial deposits during their lacustrine history leads to discussions on major chemical and climatic changes during this interval as well as the role of physiography. Furthermore, it provides novel insights into the composition, structure and formation of microbialite‐rich carbonate deposits under freshwater and hypersaline conditions.     

Tectonic environments of ancient civilizations in the eastern hemisphere

The map distribution of ancient civilizations shows a remarkable correspondence with tectonic boundaries related to the southern margin of the Eurasian plate. Quantification of this observation shows that the association is indeed significant, and both historical records and archaeoseismological work show that these civilizations commonly suffered earthquake damage. Close association of ancient civilizations with tectonic activity seems to be a pattern of some kind. In the hope that dividing the civilizations into subsets might clarify the meaning of this relation, primary and derivative civilizations were compared. Derivative civilizations prove to be far more closely related to the tectonic boundaries. Similarly, the civilizations that endured the longest (and that have been described as most static) are systematically the farthest from plate boundaries. It is still unclear how the relation actually worked in ancient cultures, i.e., what aspects of tectonism promoted complexity. Linkages to water and other resources, trade (broadly construed), and societal response seem likely. Volcanism appears not to be involved. © 2008 Wiley Periodicals, Inc.     

Crack nucleation in saturated porous media

Crack nucleation has been the subject of important contributions in the last two last decades. However, it seems that few attention has been granted to the case of saturated porous media. This is the question addressed in the present paper which is devoted to nucleation in traction mode. From a physical point of view, nucleation is a sudden phenomenon, so that the material response is both adiabatic and undrained. In the spirit of the variational approach, the nucleated crack is viewed as the final state of a region of space in which the material undergoes a full damage process. In traction mode, the opening of a saturated crack in undrained condition induces a drop of fluid pressure. In case of low fluid compressibility, the presence of the fluid delays the brittle failure usually associated with nucleation, as long as the fluid pressure remains above the saturation vapor pressure. Nucleation is therefore possible only if a partial vaporization of the fluid takes place.     

Leveraging parallel spatio-temporal computing for crime analysis in large datasets: analyzing trends in near-repeat phenomenon of crime in cities

ABSTRACT

Crime often clusters in space and time. Near-repeat patterns improve understanding of crime communicability and their space–time interactions. Near-repeat analysis requires extensive computing resources for the assessment of statistical significance of space–time interactions. A computationally intensive Monte Carlo simulation-based approach is used to evaluate the statistical significance of the space-time patterns underlying near-repeat events. Currently available software for identifying near-repeat patterns is not scalable for large crime datasets. In this paper, we show how parallel spatial programming can help to leverage spatio-temporal simulation-based analysis in large datasets. A parallel near-repeat calculator was developed and a set of experiments were conducted to compare the newly developed software with an existing implementation, assess the performance gain due to parallel computation, test the scalability of the software to handle large crime datasets and assess the utility of the new software for real-world crime data analysis. Our experimental results suggest that, efficiently designed parallel algorithms that leverage high-performance computing along with performance optimization techniques could be used to develop software that are scalable with large datasets and could provide solutions for computationally intensive statistical simulation-based approaches in crime analysis.