Notes on approximations for turbulent flows with large temperature differences

The diffusion terms in the mean velocity and temperature equations of turbulent flow are analysed to decide when variations of fluid properties can produce appreciable errors. # A theoretical demonstration is given that in the mean-flow continuity equation for a gas the error in assuming constant density is small if the flow is turbulent, even when the temperature variations are large. # Separate discussion is given of the case of local heat sources in turbulence, as large errors can occur there.

Three-dimensional laminar compressible boundary layers with large injection

The effect of large mass injection on the following three-dimensional laminar compressible boundary-layer flows is investigated by employing the method of matched asymptotic expansions: (i) swirling flow in a laminar compressible boundary layer over an axisymmetric surface with variable cross-section and (ii) laminar compressible boundary-layer flow over a yawed infinite wing in a hypersonic flow. The resulting equations are solved numerically by combining the finite-difference technique with quasi-linearization. An increase in the swirl parameter, the yaw angle or the wall temperature is found to be capable of bringing the viscous layer nearer the surface and reducing the effects of massive blowing.

Denaturant mediated unfolding of both native and molten globule states of maltose binding protein are accompanied by large [Delta]Cp's

Maltose binding protein (MBP) is a large, monomeric two domain protein containing 370 amino acids. In the absence of denaturant at neutral pH, the protein is in the native state, while at pH 3.0 it forms a molten globule. The molten globule lacks a tertiary circular dichroism signal but has secondary structure similar to that of the native state. The molten globule binds 8-anilino-1-naphthalene sulfonate (ANS). The unfolding thermodynamics of MBP at both pHs were measured by carrying out a series of isothermal urea melts at temperatures ranging from 274–329 K. At 298 K, values of [Delta]G°, [Delta]Cp, and Cm were 3.1 ± 0.2 kcal mol−1, 5.9 ± 0.8 kcal mol−1 K−1 (15.9 cal (mol-residue)−1 K−1), and 0.8 M, respectively, at pH 3.0 and 14.5 ± 0.4 kcal mol−1, 8.3 ± 0.7 kcal mol−1 K−1 (22.4 kcal (mol-residue)−1 K−1), and 3.3 M, respectively, at pH 7.1. Guanidine hydrochloride denaturation at pH 7.1 gave values of [Delta]G° and [Delta]Cp similar to those obtained with urea. The m values for denaturation are strongly temperature dependent, in contrast to what has been previously observed for small globular proteins. The value of [Delta]Cp per mol-residue for the molten globule is comparable to corresponding values of [Delta]Cp for the unfolding of typical globular proteins and suggests that it is a highly ordered structure, unlike molten globules of many small proteins. The value of [Delta]Cp per mol-residue for the unfolding of the native state is among the highest currently known for any protein.

Dynamic subspace clustering for very large high-dimensional databases

Emerging high-dimensional data mining applications needs to find interesting clusters embeded in arbitrarily aligned subspaces of lower dimensionality. It is difficult to cluster high-dimensional data objects, when they are sparse and skewed. Updations are quite common in dynamic databases and they are usually processed in batch mode. In very large dynamic databases, it is necessary to perform incremental cluster analysis only to the updations. We present a incremental clustering algorithm for subspace clustering in very high dimensions, which handles both insertion and deletions of datapoints to the backend databases.

Mapping of large scale 158 mu m [CII] line emission: Orion A

We present the first results of an observational programme undertaken to map the fine structure line emission of singly ionized carbon ([ CII] 157 : 7409 mum) over extended regions using a Fabry Perot spectrometer newly installed at the focal plane of a 100 cm balloon- borne far- infrared telescope. This new combination of instruments has a velocity resolution of similar to 200 km s(-1) and an angular resolution of 1.'5. During the first flight, an area of 30' x 15' in Orion A was mapped. These observations extend over a larger area than previous observations, the map is fully sampled and the spectral scanning method used enables reliable estimation of the continuum emission at frequencies adjacent to the [ CII] line. The total [ CII] line luminosity, calculated by considering up to 20% of the maximum line intensity is 0.04% of the luminosity of the far- infrared continuum. We have compared the [ CII] intensity distribution with the velocity- integrated intensity distributions of (CO)-C-13(1- 0), CI(1- 0) and CO( 3- 2) from the literature. Comparison of the [ CII], [ CI] and the radio continuum intensity distributions indicates that the largescale [ CII] emission originates mainly from the neutral gas, except at the position of M 43, where no [ CI] emission corresponding to the [ CII] emission is seen. Substantial part of the [ CII] emission from here originates from the ionized gas. The observed line intensities and ratios have been analyzed using the PDR models by Kaufman et al. ( 1999) to derive the incident UV flux and volume density at a few selected positions. The models reproduce the observations reasonably well at most positions excepting the [ CII] peak ( which coincides with the position of theta(1) Ori C). Possible reason for the failure could be the simplifying assumption of a homogeneous plane parallel slab in place of a more complicated geometry.

Regionalization of precipitation in data sparse areas using large scale atmospheric variables - A fuzzy clustering approach

Delineation of homogeneous precipitation regions (regionalization) is necessary for investigating frequency and spatial distribution of meteorological droughts. The conventional methods of regionalization use statistics of precipitation as attributes to establish homogeneous regions. Therefore they cannot be used to form regions in ungauged areas, and they may not be useful to form meaningful regions in areas having sparse rain gauge density. Further, validation of the regions for homogeneity in precipitation is not possible, since the use of the precipitation statistics to form regions and subsequently to test the regional homogeneity is not appropriate. To alleviate this problem, an approach based on fuzzy cluster analysis is presented. It allows delineation of homogeneous precipitation regions in data sparse areas using large scale atmospheric variables (LSAV), which influence precipitation in the study area, as attributes. The LSAV, location parameters (latitude, longitude and altitude) and seasonality of precipitation are suggested as features for regionalization. The approach allows independent validation of the identified regions for homogeneity using statistics computed from the observed precipitation. Further it has the ability to form regions even in ungauged areas, owing to the use of attributes that can be reliably estimated even when no at-site precipitation data are available. The approach was applied to delineate homogeneous annual rainfall regions in India, and its effectiveness is illustrated by comparing the results with those obtained using rainfall statistics, regionalization based on hard cluster analysis, and meteorological sub-divisions in India. (C) 2011 Elsevier B.V. All rights reserved.

Influence of land use changes in river basins on diversity and distribution of amphibians

Land-use changes influence local biodiversity directly, and also cumulatively, contribute to regional and global changes in natural systems and quality of life. Consequent to these, direct impacts on the natural resources that support the health and integrity of living beings are evident in recent times. The Western Ghats being one of the global biodiversity hotspots, is reeling under a tremendous pressure from human induced changes in terms of developmental projects like hydel or thermal power plants, big dams, mining activities, unplanned agricultural practices,monoculture plantations, illegal timber logging, etc. This has led to the once contiguous forest habitats to be fragmented in patches, which in turn has led to the shrinkage of original habitat for the wildlife, change in the hydrological regime of the catchment, decreased inflow in streams,human-animal conflicts, etc. Under such circumstances, a proper management practice is called for requiring suitable biological indicators to show the impact of these changes, set priority regions and in developing models for conservation planning. Amphibians are regarded as one of the best biological indicators due to their sensitivity to even the slightest changes in the environment and hence they could be used as surrogates in conservation and management practices. They are the predominating vertebrates with a high degree of endemism (78%) in Western Ghats. The present study is an attempt to bring in the impacts of various land-uses on anuran distribution in three river basins. Sampling was carried out for amphibians during all seasons of 2003-2006 in basins of Sharavathi, Aghanashini and Bedthi. There are as many as 46 species in the region, one of which is new to science and nearly 59% of them are endemic to the Western Ghats. They belong to nine families, Dicroglossidae being represented by 14 species,followed by Rhacophoridae (9 species) and Ranidae (5 species). Species richness is high in Sharavathi river basin, with 36 species, followed by Bedthi 33 and Aghanashini 27. The impact of land-use changes, was investigated in the upper catchment of Sharavathi river basin. Species diversity indices, relative abundance values, percentage endemics gave clear indication of differences in each sub-catchment. Karl Pearson’s correlation coefficient (r) was calculated between species richness, endemics, environmental descriptors, land-use classes and fragmentation metrics. Principal component analysis was performed to depict the influence of these variables. Results show that sub-catchments with lesser percentage of forest, low canopy cover, higher amount of agricultural area, low rainfall have low species richness, less endemic species and abundant non-endemic species, whereas endemism, species richness and abundance of endemic species are more in the sub-catchments with high tree density, endemic trees, canopy cover, rainfall and lower amount of agriculture fields. This analysis aided in prioritising regions in the Sharavathi river basin for further conservation measures.

Modeling Indian Ocean circulation: Bay of Bengal fresh water plume and the Arabian Sea Mini Warm Pool

The Indian subcontinent divides the north Indian Ocean into two tropical basins, namely the Arabian Sea and the Bay of Bengal. The Arabian Sea has high salinity whereas the salinity of the Bay of Bengal is much lower due to the contrast in freshwater forcing of the two basins. The freshwater received by the Bay in large amounts during the summer monsoon through river discharge is flushed out annually by ocean circulation. After the withdrawal of the summer monsoon, the Ganga – Brahmaputra river plume flows first along the Indian coast and then around Sri Lanka into the Arabian Sea creating a low salinity pool in the southeastern Arabian Sea (SEAS). In the same region, during the pre-monsoon months of February – April, a warm pool, known as the Arabian Sea Mini Warm Pool (ASMWP), which is distinctly warmer than the rest of the Indian Ocean, takes shape. In fact, this is the warmest region in the world oceans during this period. Simulation of the river plume and its movement as well as its implications to thermodynamics has been a challenging problem for models of Indian Ocean. Here we address these issues using an ocean general circulation model – first we show that the model is capable of reproducing fresh plumes in the Bay of Bengal as well as its movement and then we use the model to determine the processes that lead to formation of the ASMWP. Hydrographic observations from the western Bay of Bengal have shown the presence of a fresh plume along the northern part of the Indian coast during summer monsoon. The Indian Ocean model when forced by realistic winds and climatological river discharge reproduces the fresh plume with reasonable accuracy. The fresh plume does not advect along the Indian coast until the end of summer monsoon. The North Bay Monsoon Current, which flows eastward in the northern Bay, separates the low salinity water from the more saline southern parts of the bay and thus plays an important role in the fresh water budget of the Bay of Bengal. The model also reproduces the surge of the fresh-plume along the Indian coast, into the Arabian Sea during northeast monsoon. Mechanisms that lead to the formation of the Arabian Sea Mini Warm Pool are investigated using several numerical experiments. Contrary to the existing theories, we find that salinity effects are not necessary for the formation of the ASMWP. The orographic effects of the Sahyadris (Western Ghats) and resulting reduction in wind speed leads to the formation of the ASMWP. During November – April, the SEAS behave as a low-wind heatdominated regime where the evolution of sea surface temperature is solely determined by atmospheric forcing. In such regions the evolution of surface layer temperature is not dependent on the characteristics of the subsurface ocean such as the barrier layer and temperature inversion.

Correction for Bias in Downscaling GCM Simulations for Hydrologic Impact Assessment

In a statistical downscaling model, it is important to remove the bias of General Circulations Model (GCM) outputs resulting from various assumptions about the geophysical processes. One conventional method for correcting such bias is standardisation, which is used prior to statistical downscaling to reduce systematic bias in the mean and variances of GCM predictors relative to the observations or National Centre for Environmental Prediction/ National Centre for Atmospheric Research (NCEP/NCAR) reanalysis data. A major drawback of standardisation is that it may reduce the bias in the mean and variance of the predictor variable but it is much harder to accommodate the bias in large-scale patterns of atmospheric circulation in GCMs (e.g. shifts in the dominant storm track relative to observed data) or unrealistic inter-variable relationships. While predicting hydrologic scenarios, such uncorrected bias should be taken care of; otherwise it will propagate in the computations for subsequent years. A statistical method based on equi-probability transformation is applied in this study after downscaling, to remove the bias from the predicted hydrologic variable relative to the observed hydrologic variable for a baseline period. The model is applied in prediction of monsoon stream flow of Mahanadi River in India, from GCM generated large scale climatological data.