921 resultados para Fate and transport ocean model


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The simulation characteristics of the Asian-Australian monsoon are documented for the Community Climate System Model, version 4 (CCSM4). This is the first part of a two part series examining monsoon regimes in the global tropics in the CCSM4. Comparisons are made to an Atmospheric Model Intercomparison Project (AMIP) simulation of the atmospheric component in CCSM4 Community Atmosphere Model, version 4, (CAM4)] to deduce differences in the monsoon simulations run with observed sea surface temperatures (SSTs) and with ocean-atmosphere coupling. These simulations are also compared to a previous version of the model (CCSM3) to evaluate progress. In general, monsoon rainfall is too heavy in the uncoupled AMIP run with CAM4, and monsoon rainfall amounts are generally better simulated with ocean coupling in CCSM4. Most aspects of the Asian-Australian monsoon simulations are improved in CCSM4 compared to CCSM3. There is a reduction of the systematic error of rainfall over the tropical Indian Ocean for the South Asian monsoon, and well-simulated connections between SSTs in the Bay of Bengal and regional South Asian monsoon precipitation. The pattern of rainfall in the Australian monsoon is closer to observations in part because of contributions from the improvements of the Indonesian Throughflow and diapycnal diffusion in CCSM4. Intraseasonal variability of the Asian-Australian monsoon is much improved in CCSM4 compared to CCSM3 both in terms of eastward and northward propagation characteristics, though it is still somewhat weaker than observed. An improved simulation of El Nino in CCSM4 contributes to more realistic connections between the Asian-Australian monsoon and El Nino-Southern Oscillation (ENSO), though there is considerable decadal and century time scale variability of the strength of the monsoon-ENSO connection.

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The solubilities of various solid pollutants in supercritical carbon dioxide were investigated. The intermolecular interactions play a significant role in determining the solubilities of solids in supercritical carbon dioxide. A new model equation was derived by using the concepts of association and activity coefficient model to correlate the solubilities of solids. The model equation combines the association and Wilson activity coefficient models and includes the interaction potentials between the molecules, which are useful in understanding the behavior of the solid solutes in SCCO2. The new model equation involves five adjustable parameters to correlate the solubilities of solids by incorporating the interactions between the molecules. The equation correlated 75 solid systems with an average AARD of around 9%, which was better than the correlations obtained from standard models such as Mendez Santiago-Teja (MT) model and association model. (C) 2012 Elsevier B.V. All rights reserved.

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A spring-mass-lever (SML) model is introduced in this paper for a single-input-single-output compliant mechanism to capture its static and dynamic behavior. The SML model is a reduced-order model, and its five parameters provide physical insight and quantify the stiffness and inertia(1) at the input and output ports as well as the transformation of force and displacement between the input and output. The model parameters can be determined with reasonable accuracy without performing dynamic or modal analysis. The paper describes two uses of the SML model: computationally efficient analysis of a system of which the compliant mechanism is a part; and design of compliant mechanisms for the given user-specifications. During design, the SML model enables determining the feasible parameter space of user-specified requirements, assessing the suitability of a compliant mechanism to meet the user-specifications and also selecting and/or re-designing compliant mechanisms from an existing database. Manufacturing constraints, material choice, and other practical considerations are incorporated into this methodology. A micromachined accelerometer and a valve mechanism are used as examples to show the effectiveness of the SML model in analysis and design. (C) 2012 Published by Elsevier Ltd.

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The compatibility of the fast-tachocline scenario with a flux-transport dynamo model is explored. We employ a flux-transport dynamo model coupled with simple feedback formulae relating the thickness of the tachocline to the amplitude of the magnetic field or to the Maxwell stress. The dynamo model is found to be robust against the nonlinearity introduced by this simplified fast-tachocline mechanism. Solar-like butterfly diagrams are found to persist and, even without any parameter fitting, the overall thickness of the tachocline is well within the range admitted by helioseismic constraints. In the most realistic case of a time-and latitude-dependent tachocline thickness linked to the value of the Maxwell stress, both the thickness and its latitudinal dependence are in excellent agreement with seismic results. In nonparametric models, cycle-related temporal variations in tachocline thickness are somewhat larger than admitted by helioseismic constraints; we find, however, that introducing a further parameter into our feedback formula readily allows further fine tuning of the thickness variations.

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Using continuous and near-real time measurements of the mass concentrations of black carbon (BC) aerosols near the surface, for a period of 1 year (from January to December 2006) from a network of eight observatories spread over different environments of India, a space-time synthesis is generated. The strong seasonal variations observed, with a winter high and summer low, are attributed to the combined effects of changes in synoptic air mass types, modulated strongly by the atmospheric boundary layer dynamics. Spatial distribution shows much higher BC concentration over the Indo-Gangetic Plain (IGP) than the peninsular Indian stations. These were examined against the simulations using two chemical transport models, GOCART (Goddard Global Ozone Chemistry Aerosol Radiation and Transport) and CHIMERE for the first time over Indian region. Both the model simulations significantly deviated from the measurements at all the stations; more so during the winter and pre-monsoon seasons and over mega cities. However, the CHIMERE model simulations show better agreement compared with the measurements. Notwithstanding this, both the models captured the temporal variations; at seasonal and subseasonal timescales and the natural variabilities (intra-seasonal oscillations) fairly well, especially at the off-equatorial stations. It is hypothesized that an improvement in the atmospheric boundary layer (ABL) parameterization scheme for tropical environment might lead to better results with GOCART.

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Observations and models have shown the presence of intraseasonal fluctuations in 20-30-day and 10-20-day bands in the equatorial Indian Ocean west of 60 degrees E (WEIO). Their spatial and temporal structures characterize them as Yanai waves, which we label low-frequency (LFYW) and high-frequency (HFYW) Yanai waves, respectively. We explore the dynamics of these intraseasonal signals, using an ocean general circulation model (Modular Ocean Model) and a linear, continuously stratified model. Yanai waves are forced by the meridional wind tau(y) everywhere in the WEIO most strongly during the monsoon seasons. They are forced both directly in the interior ocean and by reflection of the interior response from the western boundary; interference between the interior and boundary responses results in a complex surface pattern that propagates eastward and has nodes. Yanai waves are also forced by instabilities primarily during June/July in a region offshore from the western boundary (52-55 degrees E). At that time, eddies, generated by barotropic instability of the Southern Gyre, are advected southward to the equator. There, they generate a westward-propagating, cross-equatorial flow field, v(eq), with a wave number/frequency spectrum that fits the dispersion relation of a number of Yanai waves, and these waves are efficiently excited. Typically, Yanai waves associated with several baroclinic modes are excited by both wind and eddy forcing; and typically, they superpose to create beams that carry energy vertically and eastward along ray paths. The same processes generate LFYWs and HFYWs, and hence, their responses are similar; differences are traceable to the property that HFYWs have longer wavelengths than LFYWs for each baroclinic mode.

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This paper presents the formulation and performance analysis of four techniques for detection of a narrowband acoustic source in a shallow range-independent ocean using an acoustic vector sensor (AVS) array. The array signal vector is not known due to the unknown location of the source. Hence all detectors are based on a generalized likelihood ratio test (GLRT) which involves estimation of the array signal vector. One non-parametric and three parametric (model-based) signal estimators are presented. It is shown that there is a strong correlation between the detector performance and the mean-square signal estimation error. Theoretical expressions for probability of false alarm and probability of detection are derived for all the detectors, and the theoretical predictions are compared with simulation results. It is shown that the detection performance of an AVS array with a certain number of sensors is equal to or slightly better than that of a conventional acoustic pressure sensor array with thrice as many sensors.

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The first regional synthesis of long-term (back to similar to 25 years at some stations) primary data (from direct measurement) on aerosol optical depth from the ARFINET (network of aerosol observatories established under the Aerosol Radiative Forcing over India (ARFI) project of Indian Space Research Organization over Indian subcontinent) have revealed a statistically significant increasing trend with a significant seasonal variability. Examining the current values of turbidity coefficients with those reported similar to 50 years ago reveals the phenomenal nature of the increase in aerosol loading. Seasonally, the rate of increase is consistently high during the dry months (December to March) over the entire region whereas the trends are rather inconsistent and weak during the premonsoon (April to May) and summer monsoon period (June to September). The trends in the spectral variation of aerosol optical depth (AOD) reveal the significance of anthropogenic activities on the increasing trend in AOD. Examining these with climate variables such as seasonal and regional rainfall, it is seen that the dry season depicts a decreasing trend in the total number of rainy days over the Indian region. The insignificant trend in AOD observed over the Indo-Gangetic Plain, a regional hot spot of aerosols, during the premonsoon and summer monsoon season is mainly attributed to the competing effects of dust transport and wet removal of aerosols by the monsoon rain. Contributions of different aerosol chemical species to the total dust, simulated using Goddard Chemistry Aerosol Radiation and Transport model over the ARFINET stations, showed an increasing trend for all the anthropogenic components and a decreasing trend for dust, consistent with the inference deduced from trend in Angstrom exponent.

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This paper describes the use of liaison to better integrate product model and assembly process model so as to enable sharing of design and assembly process information in a common integrated form and reason about them. Liaison can be viewed as a set, usually a pair, of features in proximity with which process information can be associated. A liaison is defined as a set of geometric entities on the parts being assembled and relations between these geometric entities. Liaisons have been defined for riveting, welding, bolt fastening, screw fastening, adhesive bonding (gluing) and blind fastening processes. The liaison captures process specific information through attributes associated with it. The attributes are associated with process details at varying levels of abstraction. A data structure for liaison has been developed to cluster the attributes of the liaison based on the level of abstraction. As information about the liaisons is not explicitly available in either the part model or the assembly model, algorithms have been developed for extracting liaisons from the assembly model. The use of liaison is proposed to enable both the construction of process model as the product model is fleshed out, as well as maintaining integrity of both product and process models as the inevitable changes happen to both design and the manufacturing environment during the product lifecycle. Results from aerospace and automotive domains have been provided to illustrate and validate the use of liaisons. (C) 2014 Elsevier Ltd. All rights reserved.

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The 11-year sunspot cycle has many irregularities, the most prominent amongst them being the grand minima when sunspots may not be seen for several cycles. After summarizing the relevant observational data about the irregularities, we introduce the flux transport dynamo model, the currently most successful theoretical model for explaining the 11-year sunspot cycle. Then we analyze the respective roles of nonlinearities and random fluctuations in creating the irregularities. We also discuss how it has recently been realized that the fluctuations in meridional circulation also can be a source of irregularities. We end by pointing out that fluctuations in the poloidal field generation and fluctuations in meridional circulation together can explain the occurrences of grand minima.

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Using different proxies of solar activity, we have studied the following features of the solar cycle: i) The linear correlation between the amplitude of cycle and its decay rate, ii) the linear correlation between the amplitude of cycle and the decay rate of cycle , and iii) the anti-correlation between the amplitude of cycle and the period of cycle . Features ii) and iii) are very useful because they provide precursors for future cycles. We have reproduced these features using a flux-transport dynamo model with stochastic fluctuations in the Babcock-Leighton effect and in the meridional circulation. Only when we introduce fluctuations in meridional circulation, are we able to reproduce different observed features of the solar cycle. We discuss the possible reasons for these correlations.

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UHV power transmission lines have high probability of shielding failure due to their higher height, larger exposure area and high operating voltage. Lightning upward leader inception and propagation is an integral part of lightning shielding failure analysis and need to be studied in detail. In this paper a model for lightning attachment has been proposed based on the present knowledge of lightning physics. Leader inception is modeled based on the corona charge present near the conductor region and the propagation model is based on the correlation between the lightning induced voltage on the conductor and the drop along the upward leader channel. The inception model developed is compared with previous inception models and the results obtained using the present and previous models are comparable. Lightning striking distances (final jump) for various return stroke current were computed for different conductor heights. The computed striking distance values showed good correlation with the values calculated using the equation proposed by the IEEE working group for the applicable conductor heights of up to 8 m. The model is applied to a 1200 kV AC power transmission line and inception of the upward leader is analyzed for this configuration.

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Turbulence-transport-chemistry interaction plays a crucial role on the flame surface geometry, local and global reactionrates, and therefore, on the propagation and extinction characteristics of intensely turbulent, premixed flames encountered in LPP gas-turbine combustors. The aim of the present work is to understand these interaction effects on the flame surface annihilation and extinction of lean premixed flames, interacting with near isotropic turbulence. As an example case, lean premixed H-2-air mixture is considered so as to enable inclusion of detailed chemistry effects in Direct Numerical Simulations (DNS). The work is carried out in two phases namely, statistically planar flames and ignition kernel, both interacting with near isotropic turbulence, using the recently proposed Flame Particle Tracking (FPT) technique. Flame particles are surface points residing and commoving with an iso-scalar surface within a premixed flame. Tracking flame particles allows us to study the evolution of propagating surface locations uniquely identified with time. In this work, using DNS and FPT we study the flame speed, reaction rate and transport histories of such flame particles residing on iso-scalar surfaces. An analytical expression for the local displacement flame speed (SO is derived, and the contribution of transport and chemistry on the displacement flame speed is identified. An examination of the results of the planar case leads to a conclusion that the cause of variation in S-d may be attributed to the effects of turbulent transport and heat release rate. In the second phase of this work, the sustenance of an ignition kernel is examined in light of the S-curve. A newly proposed Damkohler number accounting for local turbulent transport and reaction rates is found to explain either the sustenance or otherwise propagation of flame kernels in near isotropic turbulence.

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Understanding of nanoparticle-membrane interactions is useful for various applications of nanoparticles like drug delivery and imaging. Here we report on the studies of interaction between hydrophilic charged polymer coated semiconductor quantum dot nanoparticles with model lipid membranes. Atomic force microscopy and X-ray reflectivity measurements suggest that cationic nanoparticles bind and penetrate bilayers of zwitterionic lipids. Penetration and binding depend on the extent of lipid packing and result in the disruption of the lipid bilayer accompanied by enhanced lipid diffusion. On the other hand, anionic nanoparticles show minimal membrane binding although, curiously, their interaction leads to reduction in lipid diffusivity. It is suggested that the enhanced binding of cationic QDs at higher lipid packing can be understood in terms of the effective surface potential of the bilayers which is tunable through membrane lipid packing. Our results bring forth the subtle interplay of membrane lipid packing and electrostatics which determine nanoparticle binding and penetration of model membranes with further implications for real cell membranes.

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With the advances in technology, seismological theory, and data acquisition, a number of high-resolution seismic tomography models have been published. However, discrepancies between tomography models often arise from different theoretical treatments of seismic wave propagation, different inversion strategies, and different data sets. Using a fixed velocity-to-density scaling and a fixed radial viscosity profile, we compute global mantle flow models associated with the different tomography models and test the impact of these for explaining surface geophysical observations (geoid, dynamic topography, stress, and strain rates). We use the joint modeling of lithosphere and mantle dynamics approach of Ghosh and Holt (2012) to compute the full lithosphere stresses, except that we use HC for the mantle circulation model, which accounts for the primary flow-coupling features associated with density-driven mantle flow. Our results show that the seismic tomography models of S40RTS and SAW642AN provide a better match with surface observables on a global scale than other models tested. Both of these tomography models have important similarities, including upwellings located in Pacific, Eastern Africa, Iceland, and mid-ocean ridges in the Atlantic and Indian Ocean and downwelling flows mainly located beneath the Andes, the Middle East, and central and Southeast Asia.