Understanding the relative importance of vertical and horizontal flow in ice-wedge polygons

Ice-wedge polygons are common Arctic landforms. The future of these landforms in a warming climate depends on the bidirectional feedback between the rate of ice-wedge degradation and changes in hydrological characteristics. This work aims to better understand the relative roles of vertical and horizontal water fluxes in the subsurface of polygonal landscapes, providing new insights and data to test and calibrate hydrological models. Field-scale investigations were conducted at an intensively instrumented location on the Barrow Environmental Observatory (BEO) near Utqiagvik, AK, USA. Using a conservative tracer, we examined controls of microtopography and the frost table on subsurface flow and transport within a low-centered and a high-centered polygon. Bromide tracer was applied at both polygons in July 2015 and transport was monitored through two thaw seasons. Sampler arrays placed in polygon centers, rims, and troughs were used to monitor tracer concentrations. In both polygons, the tracer first infiltrated vertically until encountering the frost table and was then transported horizontally. Horizontal flow occurred in more locations and at higher velocities in the low-centered polygon than in the high-centered polygon. Preferential flow, influenced by frost table topography, was significant between polygon centers and troughs. Estimates of horizontal hydraulic conductivity were within the range of previous estimates of vertical conductivity, highlighting the importance of horizontal flow in these systems. This work forms a basis for understanding complexity of flow in polygonal landscapes

Community Review of Southern Ocean Satellite Data Needs

This review represents the Southern Ocean community’s satellite data needs for the coming decade. Developed through widespread engagement, and incorporating perspectives from a range of stakeholders (both research and operational), it is designed as an important community-driven strategy paper that provides the rationale and information required for future planning and investment. The Southern Ocean is vast but globally connected, and the communities that require satellite-derived data in the region are diverse. This review includes many observable variables, including sea-ice properties, sea-surface temperature, sea-surface height, atmospheric parameters, marine biology (both micro and macro) and related activities, terrestrial cryospheric connections, sea-surface salinity, and a discussion of coincident and in situ data collection. Recommendations include commitment to data continuity, increase in particular capabilities (sensor types, spatial, temporal), improvements in dissemination of data/products/uncertainties, and innovation in calibration/validation capabilities. Full recommendations are detailed by variable as well as summarized. This review provides a starting point for scientists to understand more about Southern Ocean processes and their global roles, for funders to understand the desires of the community, for commercial operators to safely conduct their activities in the Southern Ocean, and for space agencies to gain greater impact from Southern Ocean-related acquisitions and missions.The authors acknowledge the Climate at the Cryosphere program and the Southern Ocean Observing System for initiating this community effort, WCRP, SCAR, and SCOR for endorsing the effort, and CliC, SOOS, and SCAR for supporting authors’ travel for collaboration on the review. Jamie Shutler’s time on this review was funded by the European Space Agency project OceanFlux Greenhouse Gases Evolution (Contract number 4000112091/14/I-LG)

High-resolution Velocity Fields of Low-mass Disk Galaxies. I. CO Observations

This paper is the first in a series whose aim is to examine the relative distributions of dark and baryonic matter as a function of star formation history in a representative sample of low-mass disk galaxies. In this paper, we present high-resolution 12 CO(j=1→0) interferometry for a sample of 26 nearby dwarf galaxies that were obtained from the Combined Array for Research in Millimeter-wave Astronomy (CARMA). Among these 26 galaxies, 14 have good CO detections, including 6 galaxies previously detected in single-dish CO measurements and 8 newly detected ones. We find a linear correlation between the CO flux and the mid- and far-IR flux from the WISE and IRAS catalogs. Compared to the far-IR flux, the mid-IR flux may be a better indication of whether a galaxy contains sufficient CO for detection at the level of instrument sensitivity of CARMA. This correlation might prove to be useful in future studies to help choosing other CO targets for observation. The median molecular mass (including helium) of our galaxies is 2.8×10 8 M⊙, which is consistent with past observations for dwarf galaxies. The molecular content is weakly correlated with the dynamical mass, r-band luminosity and size of the galaxies. The median ratios of molecular mass versus dynamical mass and molecular mass versus r-band luminosity are M mol M dyn ≈ 0.035 and M mol L r ≈ 0.078M⊙ L r , ⊙, respectively, which are also consistent with past observations for dwarf galaxies

Periodic pattern formation in reaction-diffusion systems -an introduction for numerical simulation

The aim of the present review is to provide a comprehensive explanation of Turing reaction–diffusion systems in sufficient detail to allow readers to perform numerical calculations themselves. The reaction–diffusion model is widely studied in the field of mathematical biology, serves as a powerful paradigm model for self-organization and is beginning to be applied to actual experimental systems in developmental biology. Despite the increase in current interest, the model is not well understood among experimental biologists, partly because appropriate introductory texts are lacking. In the present review, we provide a detailed description of the definition of the Turing reaction–diffusion model that is comprehensible without a special mathematical background, then illustrate a method for reproducing numerical calculations with Microsoft Excel. We then show some examples of the patterns generated by the model. Finally, we discuss future prospects for the interdisciplinary field of research involving mathematical approaches in developmental biology

High-resolution Velocity Fields of Low-mass Disk Galaxies. I. CO Observations

This paper is the first in a series whose aim is to examine the relative distributions of dark and baryonic matter as a function of star formation history in a representative sample of low-mass disk galaxies. In this paper, we present high-resolution 12 CO(j=1→0) interferometry for a sample of 26 nearby dwarf galaxies that were obtained from the Combined Array for Research in Millimeter-wave Astronomy (CARMA). Among these 26 galaxies, 14 have good CO detections, including 6 galaxies previously detected in single-dish CO measurements and 8 newly detected ones. We find a linear correlation between the CO flux and the mid- and far-IR flux from the WISE and IRAS catalogs. Compared to the far-IR flux, the mid-IR flux may be a better indication of whether a galaxy contains sufficient CO for detection at the level of instrument sensitivity of CARMA. This correlation might prove to be useful in future studies to help choosing other CO targets for observation. The median molecular mass (including helium) of our galaxies is 2.8×10 8 M⊙, which is consistent with past observations for dwarf galaxies. The molecular content is weakly correlated with the dynamical mass, r-band luminosity and size of the galaxies. The median ratios of molecular mass versus dynamical mass and molecular mass versus r-band luminosity are M mol M dyn ≈ 0.035 and M mol L r ≈ 0.078M⊙ L r , ⊙, respectively, which are also consistent with past observations for dwarf galaxies

From Relational Data to Graphs: Inferring Significant Links using Generalized Hypergeometric Ensembles

The inference of network topologies from relational data is an important problem in data analysis. Exemplary applications include the reconstruction of social ties from data on human interactions, the inference of gene co-expression networks from DNA microarray data, or the learning of semantic relationships based on co-occurrences of words in documents. Solving these problems requires techniques to infer significant links in noisy relational data. In this short paper, we propose a new statistical modeling framework to address this challenge. It builds on generalized hypergeometric ensembles, a class of generative stochastic models that give rise to analytically tractable probability spaces of directed, multi-edge graphs. We show how this framework can be used to assess the significance of links in noisy relational data. We illustrate our method in two data sets capturing spatio-temporal proximity relations between actors in a social system. The results show that our analytical framework provides a new approach to infer significant links from relational data, with interesting perspectives for the mining of data on social systems.Comment: 10 pages, 8 figures, accepted at SocInfo201

Transport phenomena in electrolyte solutions: Non-equilibrium thermodynamics and statistical mechanics

The theory of transport phenomena in multicomponent electrolyte solutions is presented here through the integration of continuum mechanics, electromagnetism, and non-equilibrium thermodynamics. The governing equations of irreversible thermodynamics, including balance laws, Maxwell's equations, internal entropy production, and linear laws relating the thermodynamic forces and fluxes, are derived. Green-Kubo relations for the transport coefficients connecting electrochemical potential gradients and diffusive fluxes are obtained in terms of the flux-flux time correlations. The relationship between the derived transport coefficients and those of the Stefan-Maxwell and infinitely dilute frameworks are presented, and the connection between the transport matrix and experimentally measurable quantities is described. To exemplify application of the derived Green-Kubo relations in molecular simulations, the matrix of transport coefficients for lithium and chloride ions in dimethyl sulfoxide is computed using classical molecular dynamics and compared with experimental measurements.Comment: fixed typos, added references, addressed comment

Deductively Definable Logics of Induction

A broad class of inductive logics that includes the probability calculus is defined by the conditions that the inductive strengths [A{pipe}B] are defined fully in terms of deductive relations in preferred partitions and that they are asymptotically stable. Inductive independence is shown to be generic for propositions in such logics; a notion of a scale-free inductive logic is identified; and a limit theorem is derived. If the presence of preferred partitions is not presumed, no inductive logic is definable. This no-go result precludes many possible inductive logics, including versions of hypothetico-deductivism. © 2010 Springer Science+Business Media B.V

Wave patterns in one-dimensional nonlinear degenerate diffusion equations

Several different types of wave patterns occur in physiology, chemistry and biology. In many cases such phenomena are modelled by reactive-diffusive parabolic systems (see, for example, Fisher 1937; Kolmogorov et al. 1937; Winfree 1988; Murray 1989; Swinney & Krinsky 1992). In many biological and physical situations, dispersal is modelled by a density-dependent diffusion coefficient, for example, the bacterium Rhizobium diffuses through the roots of some leguminosae plants according to a nonlinear diffusive law (Lara-Ochoa & Bustos 1990); nonlinear diffusion has been observed in the dispersion of some insects (Okubo 1980) and small rodents (Meyers & Krebs 1974)