Development of a regional model for the North Indian Ocean

We have developed a one-way nested Indian Ocean regional model. The model combines the National Oceanic and Atmospheric Administration (NOAA) Geophysical Fluid Dynamics Laboratory's (GFDL) Modular Ocean Model (MOM4p1) at global climate model resolution (nominally one degree), and a regional Indian Ocean MOM4p1 configuration with 25 km horizontal resolution and 1 m vertical resolution near the surface. Inter-annual global simulations with Coordinated Ocean-Ice Reference Experiments (CORE-II) surface forcing over years 1992-2005 provide surface boundary conditions. We show that relative to the global simulation, (i) biases in upper ocean temperature, salinity and mixed layer depth are reduced, (ii) sea surface height and upper ocean circulation are closer to observations, and (iii) improvements in model simulation can be attributed to refined resolution, more realistic topography and inclusion of seasonal river runoff. Notably, the surface salinity bias is reduced to less than 0.1 psu over the Bay of Bengal using relatively weak restoring to observations, and the model simulates the strong, shallow halocline often observed in the North Bay of Bengal. There is marked improvement in subsurface salinity and temperature, as well as mixed layer depth in the Bay of Bengal. Major seasonal signatures in observed sea surface height anomaly in the tropical Indian Ocean, including the coastal waveguide around the Indian peninsula, are simulated with great fidelity. The use of realistic topography and seasonal river runoff brings the three dimensional structure of the East India Coastal Current and West India Coastal Current much closer to observations. As a result, the incursion of low salinity Bay of Bengal water into the southeastern Arabian Sea is more realistic. (C) 2013 Elsevier Ltd. All rights reserved.

Suppression of gravitational instabilities by dominant dark matter halo in low-surface-brightness galaxies

The low-surface-brightness galaxies are gas rich and yet have a low star formation rate; this is a well-known puzzle. The spiral features in these galaxies are weak and difficult to trace, although this aspect has not been studied much. These galaxies are known to be dominated by the dark matter halo from the innermost regions. Here, we do a stability analysis for the galactic disc of UGC 7321, a low-surface-brightness, superthin galaxy, for which the various observational input parameters are available. We show that the disc is stable against local, linear axisymmetric and non-axisymmetric perturbations. The Toomre Q parameter values are found to be large (>> 1) mainly due to the low disc surface density, and the high rotation velocity resulting due to the dominant dark matter halo, which could explain the observed low star formation rate. For the stars-alone case, the disc shows finite swing amplification but the addition of dark matter halo suppresses that amplification almost completely. Even the inclusion of the low-dispersion gas which constitutes a high disc mass fraction does not help in causing swing amplification. This can explain why these galaxies do not show strong spiral features. Thus, the dynamical effect of a halo that is dominant from inner regions can naturally explain why star formation and spiral features are largely suppressed in low-surface-brightness galaxies, making these different from the high-surface-brightness galaxies.

Regional flood frequency analysis using kernel- based fuzzy clustering approach

Regionalization approaches are widely used in water resources engineering to identify hydrologically homogeneous groups of watersheds that are referred to as regions. Pooled information from sites (depicting watersheds) in a region forms the basis to estimate quantiles associated with hydrological extreme events at ungauged/sparsely gauged sites in the region. Conventional regionalization approaches can be effective when watersheds (data points) corresponding to different regions can be separated using straight lines or linear planes in the space of watershed related attributes. In this paper, a kernel-based Fuzzy c-means (KFCM) clustering approach is presented for use in situations where such linear separation of regions cannot be accomplished. The approach uses kernel-based functions to map the data points from the attribute space to a higher-dimensional space where they can be separated into regions by linear planes. A procedure to determine optimal number of regions with the KFCM approach is suggested. Further, formulations to estimate flood quantiles at ungauged sites with the approach are developed. Effectiveness of the approach is demonstrated through Monte-Carlo simulation experiments and a case study on watersheds in United States. Comparison of results with those based on conventional Fuzzy c-means clustering, Region-of-influence approach and a prior study indicate that KFCM approach outperforms the other approaches in forming regions that are closer to being statistically homogeneous and in estimating flood quantiles at ungauged sites. Key Points Kernel-based regionalization approach is presented for flood frequency analysis Kernel procedure to estimate flood quantiles at ungauged sites is developed A set of fuzzy regions is delineated in Ohio, USA

Revised density of magnetized nuclear matter at the neutron drip line

We study the onset of the neutron drip in high-density matter in the presence of a magnetic field. It has been found that, for systems having only protons and electrons, in the presence of a magnetic field greater than or similar to 10(15) G, neutronization occurs at a density that is at least an order of magnitude higher compared to that in a nonmagnetic system. In a system with heavier ions, the effect of the magnetic field, however, starts arising at a much higher field, greater than or similar to 10(17) G. These results may have important implications for high-magnetic-field neutron stars and white dwarfs and, in general, in nuclear astrophysics when the system is embedded within a strong magnetic field.

Flocking at a distance in active granular matter

The self-organized motion of vast numbers of creatures in a single direction is a spectacular example of emergent order. Here, we recreate this phenomenon using actuated nonliving components. We report here that millimetre-sized tapered rods, rendered motile by contact with an underlying vibrated surface and interacting through a medium of spherical beads, undergo a phase transition to a state of spontaneous alignment of velocities and orientations above a threshold bead area fraction. Guided by a detailed simulation model, we construct an analytical theory of this flocking transition, with two ingredients: a moving rod drags beads; neighbouring rods reorient in the resulting flow like a weathercock in the wind. Theory and experiment agree on the structure of our phase diagram in the plane of rod and bead concentrations and power-law spatial correlations near the phase boundary. Our discovery suggests possible new mechanisms for the collective transport of particulate or cellular matter.

Off-site impacts of agricultural composting: role of terrestrially derived organic matter in structuring aquatic microbial communities and their metabolic potential

While considered as sustainable and low-cost agricultural amendments, the impacts of organic fertilizers on downstream aquatic microbial communities remain poorly documented. We investigated the quantity and quality of the dissolved organic matter leaching from agricultural soil amended with compost, vermicompost or biochar and assessed their effects on lake microbial communities, in terms of viral and bacterial abundances, community structure and metabolic potential. The addition of compost and vermicompost significantly increased the amount of dissolved organic carbon in the leachate compared with soil alone. Leachates from these additions, either with or without biochar, were highly bioavailable to aquatic microbial communities, although reducing the metabolic potential of the community and harbouring more specific communities. Although not affecting bacterial richness or taxonomic distributions, the specific addition of biochar affected the original lake bacterial communities, resulting in a strongly different community. This could be partly explained by viral burst and converging bacterial abundances throughout the samples. These results underline the necessity to include off-site impacts of agricultural amendments when considering their cascading effect on downstream aquatic ecosystems.

Active Viscoelastic Matter: From Bacterial Drag Reduction to Turbulent Solids

A paradigm for internally driven matter is the active nematic liquid crystal, whereby the equations of a conventional nematic are supplemented by a minimal active stress that violates time-reversal symmetry. In practice, active fluids may have not only liquid-crystalline but also viscoelastic polymer degrees of freedom. Here we explore the resulting interplay by coupling an active nematic to a minimal model of polymer rheology. We find that adding a polymer can greatly increase the complexity of spontaneous flow, but can also have calming effects, thereby increasing the net throughput of spontaneous flow along a pipe (a ``drag-reduction'' effect). Remarkably, active turbulence can also arise after switching on activity in a sufficiently soft elastomeric solid.

Evaluating Methods to Predict Streamflow at Ungauged Sites using Regional Flow Duration Curves: A Case Study

Precise information on streamflows is of major importance for planning and monitoring of water resources schemes related to hydro power, water supply, irrigation, flood control, and for maintaining ecosystem. Engineers encounter challenges when streamflow data are either unavailable or inadequate at target locations. To address these challenges, there have been efforts to develop methodologies that facilitate prediction of streamflow at ungauged sites. Conventionally, time intensive and data exhaustive rainfall-runoff models are used to arrive at streamflow at ungauged sites. Most recent studies show improved methods based on regionalization using Flow Duration Curves (FDCs). A FDC is a graphical representation of streamflow variability, which is a plot between streamflow values and their corresponding exceedance probabilities that are determined using a plotting position formula. It provides information on the percentage of time any specified magnitude of streamflow is equaled or exceeded. The present study assesses the effectiveness of two methods to predict streamflow at ungauged sites by application to catchments in Mahanadi river basin, India. The methods considered are (i) Regional flow duration curve method, and (ii) Area Ratio method. The first method involves (a) the development of regression relationships between percentile flows and attributes of catchments in the study area, (b) use of the relationships to construct regional FDC for the ungauged site, and (c) use of a spatial interpolation technique to decode information in FDC to construct streamflow time series for the ungauged site. Area ratio method is conventionally used to transfer streamflow related information from gauged sites to ungauged sites. Attributes that have been considered for the analysis include variables representing hydrology, climatology, topography, land-use/land- cover and soil properties corresponding to catchments in the study area. Effectiveness of the presented methods is assessed using jack knife cross-validation. Conclusions based on the study are presented and discussed. (C) 2015 The Authors. Published by Elsevier B.V.

Analytical approach to quantile estimation in regional frequency analysis based on fuzzy framework

Regional frequency analysis is widely used for estimating quantiles of hydrological extreme events at sparsely gauged/ungauged target sites in river basins. It involves identification of a region (group of watersheds) resembling watershed of the target site, and use of information pooled from the region to estimate quantile for the target site. In the analysis, watershed of the target site is assumed to completely resemble watersheds in the identified region in terms of mechanism underlying generation of extreme event. In reality, it is rare to find watersheds that completely resemble each other. Fuzzy clustering approach can account for partial resemblance of watersheds and yield region(s) for the target site. Formation of regions and quantile estimation requires discerning information from fuzzy-membership matrix obtained based on the approach. Practitioners often defuzzify the matrix to form disjoint clusters (regions) and use them as the basis for quantile estimation. The defuzzification approach (DFA) results in loss of information discerned on partial resemblance of watersheds. The lost information cannot be utilized in quantile estimation, owing to which the estimates could have significant error. To avert the loss of information, a threshold strategy (TS) was considered in some prior studies. In this study, it is analytically shown that the strategy results in under-prediction of quantiles. To address this, a mathematical approach is proposed in this study and its effectiveness in estimating flood quantiles relative to DFA and TS is demonstrated through Monte-Carlo simulation experiments and case study on Mid-Atlantic water resources region, USA. (C) 2015 Elsevier B.V. All rights reserved.

Maximum magnitude estimation considering the regional rupture character

The main objective of the paper is to develop a new method to estimate the maximum magnitude (M (max)) considering the regional rupture character. The proposed method has been explained in detail and examined for both intraplate and active regions. Seismotectonic data has been collected for both the regions, and seismic study area (SSA) map was generated for radii of 150, 300, and 500 km. The regional rupture character was established by considering percentage fault rupture (PFR), which is the ratio of subsurface rupture length (RLD) to total fault length (TFL). PFR is used to arrive RLD and is further used for the estimation of maximum magnitude for each seismic source. Maximum magnitude for both the regions was estimated and compared with the existing methods for determining M (max) values. The proposed method gives similar M (max) value irrespective of SSA radius and seismicity. Further seismicity parameters such as magnitude of completeness (M (c) ), ``a'' and ``aEuro parts per thousand b `` parameters and maximum observed magnitude (M (max) (obs) ) were determined for each SSA and used to estimate M (max) by considering all the existing methods. It is observed from the study that existing deterministic and probabilistic M (max) estimation methods are sensitive to SSA radius, M (c) , a and b parameters and M (max) (obs) values. However, M (max) determined from the proposed method is a function of rupture character instead of the seismicity parameters. It was also observed that intraplate region has less PFR when compared to active seismic region.

Regional hydrological impacts of climate change: implications for water management in India

Climate change is most likely to introduce an additional stress to already stressed water systems in developing countries. Climate change is inherently linked with the hydrological cycle and is expected to cause significant alterations in regional water resources systems necessitating measures for adaptation and mitigation. Increasing temperatures, for example, are likely to change precipitation patterns resulting in alterations of regional water availability, evapotranspirative water demand of crops and vegetation, extremes of floods and droughts, and water quality. A comprehensive assessment of regional hydrological impacts of climate change is thus necessary. Global climate model simulations provide future projections of the climate system taking into consideration changes in external forcings, such as atmospheric carbon-dioxide and aerosols, especially those resulting from anthropogenic emissions. However, such simulations are typically run at a coarse scale, and are not equipped to reproduce regional hydrological processes. This paper summarizes recent research on the assessment of climate change impacts on regional hydrology, addressing the scale and physical processes mismatch issues. Particular attention is given to changes in water availability, irrigation demands and water quality. This paper also includes description of the methodologies developed to address uncertainties in the projections resulting from incomplete knowledge about future evolution of the human-induced emissions and from using multiple climate models. Approaches for investigating possible causes of historically observed changes in regional hydrological variables are also discussed. Illustrations of all the above-mentioned methods are provided for Indian regions with a view to specifically aiding water management in India.

Modelling the influence of land-use changes on biophysical and biochemical interactions at regional and global scales

Land-use changes since the start of the industrial era account for nearly one-third of the cumulative anthropogenic CO2 emissions. In addition to the greenhouse effect of CO2 emissions, changes in land use also affect climate via changes in surface physical properties such as albedo, evapotranspiration and roughness length. Recent modelling studies suggest that these biophysical components may be comparable with biochemical effects. In regard to climate change, the effects of these two distinct processes may counterbalance one another both regionally and, possibly, globally. In this article, through hypothetical large-scale deforestation simulations using a global climate model, we contrast the implications of afforestation on ameliorating or enhancing anthropogenic contributions from previously converted (agricultural) land surfaces. Based on our review of past studies on this subject, we conclude that the sum of both biophysical and biochemical effects should be assessed when large-scale afforestation is used for countering global warming, and the net effect on global mean temperature change depends on the location of deforestation/afforestation. Further, although biochemical effects trigger global climate change, biophysical effects often cause strong local and regional climate change. The implication of the biophysical effects for adaptation and mitigation of climate change in agriculture and agroforestry sectors is discussed. center dot Land-use changes affect global and regional climates through both biochemical and biophysical process. center dot Climate effect from biophysical process depends on the location of land-use change. center dot Climate mitigation strategies such as afforestation/reforestation should consider the net effect of biochemical and biophysical processes for effective mitigation. center dot Climate-smart agriculture could use bio-geoengineering techniques that consider plant biophysical characteristics such as reflectivity and water use efficiency.

Does size matter? Comparative population genetics of two butterflies with different wingspans

The dispersal ability of a species is central to its biology, affecting other processes like local adaptation, population and community dynamics, and genetic structure. Among the intrinsic, species-specific factors that affect dispersal ability in butterflies, wingspan was recently shown to explain a high amount of variance in dispersal ability. In this study, a comparative approach was adopted to test whether a difference in wingspan translates into a difference in population genetic structure. Two closely related butterfly species from subfamily Satyrinae, family Nymphalidae, which are similar with respect to all traits that affect dispersal ability except for wingspan, were studied. Melanitis leda (wingspan 60-80 mm) and Ypthima baldus (wingspan 30-40 mm) were collected from the same areas along the Western Ghats of southern India. Amplified fragment length polymorphisms were used to test whether the species with a higher wingspan (M. leda) exhibited a more homogenous population genetic structure, as compared to a species with a shorter wingspan (Y. baldus). In all analyses, Y. baldus exhibited greater degree of population genetic structuring. This study is one of the few adopting a comparative approach to establish the relationship between traits that affect dispersal ability and population genetic structure.

A simplified model for dark matter interacting primarily with gluons

We consider a simple renormalizable model providing a UV completion for dark matter whose interactions with the Standard Model are primarily via the gluons. The model consists of scalar dark matter interacting with scalar colored mediator particles. A novel feature is the fact that (in contrast to more typical models containing dark matter whose interactions are mediated via colored scalars) the colored scalars typically decay into multi-quark final states, with no associated missing energy. We construct this class of models and examine associated phenomena related to dark matter annihilation, scattering with nuclei, and production at colliders.