Validating NCAR-CCSM last glacial maximum sea surface temperature in the tropical and South Atlantic with proxy-data

Last Glacial Maximum simulated sea surface temperature from the Paleo-Climate version of the National Center for Atmospheric Research Coupled Climate Model (NCAR-CCSM) are compared with available reconstructions and data-based products in the tropical and south Atlantic region. Model results are compared to data proxies based on the Multiproxy Approach for the Reconstruction of the Glacial Ocean surface product (MARGO). Results show that the model sea surface temperature is not consistent with the proxy-data in all of the region of interest. Discrepancies are found in the eastern, equatorial and in the high-latitude South Atlantic. The model overestimates the cooling in the southern South Atlantic (near 50 degrees S) shown by the proxy-data. Near the equator, model and proxies are in better agreement. In the eastern part of the equatorial basin the model underestimates the cooling shown by all proxies. A northward shift in the position of the subtropical convergence zone in the simulation suggests a compression or/and an equatorward shift of the subtropical gyre at the surface, consistent with what is observed in the proxy reconstruction. (C) 2008 Elsevier B.V. All rights reserved

Application of the log-conformation tensor to three-dimensional time-dependent free surface flows

The numerical simulation of flows of highly elastic fluids has been the subject of intense research over the past decades with important industrial applications. Therefore, many efforts have been made to improve the convergence capabilities of the numerical methods employed to simulate viscoelastic fluid flows. An important contribution for the solution of the High-Weissenberg Number Problem has been presented by Fattal and Kupferman [J. Non-Newton. Fluid. Mech. 123 (2004) 281-285] who developed the matrix-logarithm of the conformation tensor technique, henceforth called log-conformation tensor. Its advantage is a better approximation of the large growth of the stress tensor that occur in some regions of the flow and it is doubly beneficial in that it ensures physically correct stress fields, allowing converged computations at high Weissenberg number flows. In this work we investigate the application of the log-conformation tensor to three-dimensional unsteady free surface flows. The log-conformation tensor formulation was applied to solve the Upper-Convected Maxwell (UCM) constitutive equation while the momentum equation was solved using a finite difference Marker-and-Cell type method. The resulting developed code is validated by comparing the log-conformation results with the analytic solution for fully developed pipe flows. To illustrate the stability of the log-conformation tensor approach in solving three-dimensional free surface flows, results from the simulation of the extrudate swell and jet buckling phenomena of UCM fluids at high Weissenberg numbers are presented. (C) 2012 Elsevier B.V. All rights reserved.

Influence diagnostics in Gaussian spatial linear models

Spatial linear models have been applied in numerous fields such as agriculture, geoscience and environmental sciences, among many others. Spatial dependence structure modelling, using a geostatistical approach, is an indispensable tool to estimate the parameters that define this structure. However, this estimation may be greatly affected by the presence of atypical observations in the sampled data. The purpose of this paper is to use diagnostic techniques to assess the sensitivity of the maximum-likelihood estimators, covariance functions and linear predictor to small perturbations in the data and/or the spatial linear model assumptions. The methodology is illustrated with two real data sets. The results allowed us to conclude that the presence of atypical values in the sample data have a strong influence on thematic maps, changing the spatial dependence structure.

Focusing surface plasmons on Er3+ ions through gold planar plasmonic lenses

Gold plasmonic lenses consisting of a planar concentric rings-groove with different periods were milled with a focused gallium ion beam on a gold thin film deposited onto an Er3+-doped tellurite glass. The plasmonic lenses were vertically illuminated with an argon ion laser highly focused by means of a 50x objective lens. The focusing mechanism of the plasmonic lenses is explained using a coherent interference model of surface plasmon-polariton (SPP) generation on the circular grating due to the incident field. As a result, phase modulation can be accomplished by the groove gap, similar to a nanoslit array with different widths. This focusing allows a high confinement of SPPs that can excite the Er3+ ions of the glass. The Er3+ luminescence spectra were measured in the far-field (500-750 nm wavelength range), where we could verify the excitation yield via the plasmonic lens on the Er3+ ions. We analyze the influence of the geometrical parameters on the luminescence spectra. The variation of these parameters results in considerable changes of the luminescence spectra.

Comparison between 2.5-D and 3-D realistic models for wind field adjustment

[EN]In previous works, many authors have widely used mass consistent models for wind field simulation by the finite element method. On one hand, we have developed a 3-D mass consistent model by using tetrahedral meshes which are simultaneously adapted to complex orography and to terrain roughness length. In addition, we have included a local refinement strategy around several measurement or control points, significant contours, as for example shorelines, or numerical solution singularities. On the other hand, we have developed a 2.5-D model for simulating the wind velocity in a 3-D domain in terms of the terrain elevation, the surface temperature and the meteorological wind, which is consider as an averaged wind on vertical boundaries...

A model for diffusive and displacive phase transitions in steels

Heat treatment of steels is a process of fundamental importance in tailoring the properties of a material to the desired application; developing a model able to describe such process would allow to predict the microstructure obtained from the treatment and the consequent mechanical properties of the material. A steel, during a heat treatment, can undergo two different kinds of phase transitions [p.t.]: diffusive (second order p.t.) and displacive (first order p.t.); in this thesis, an attempt to describe both in a thermodynamically consistent framework is made; a phase field, diffuse interface model accounting for the coupling between thermal, chemical and mechanical effects is developed, and a way to overcome the difficulties arising from the treatment of the non-local effects (gradient terms) is proposed. The governing equations are the balance of linear momentum equation, the Cahn-Hilliard equation and the balance of internal energy equation. The model is completed with a suitable description of the free energy, from which constitutive relations are drawn. The equations are then cast in a variational form and different numerical techniques are used to deal with the principal features of the model: time-dependency, non-linearity and presence of high order spatial derivatives. Simulations are performed using DOLFIN, a C++ library for the automated solution of partial differential equations by means of the finite element method; results are shown for different test-cases. The analysis is reduced to a two dimensional setting, which is simpler than a three dimensional one, but still meaningful.

Kinetic and affinity analysis of hybridization reactions between PNA probes and DNA targets using surface plasmon field-enhanced fluorescence spectroscopy (SPFS)

Sequenz spezifische biomolekulare Analyseverfahren erweisen sich gerade im Hinblick auf das Humane Genom Projekt als äußerst nützlich in der Detektion von einzelnen Nukleotid Polymorphismen (SNPs) und zur Identifizierung von Genen. Auf Grund der hohen Anzahl von Basenpaaren, die zu analysieren sind, werden sensitive und effiziente Rastermethoden benötigt, welche dazu fähig sind, DNA-Proben in einer geeigneten Art und Weise zu bearbeiten. Die meisten Detektionsarten berücksichtigen die Interaktion einer verankerten Probe und des korrespondierenden Targets mit den Oberflächen. Die Analyse des kinetischen Verhaltens der Oligonukleotide auf der Sensoroberfläche ist infolgedessen von höchster Wichtigkeit für die Verbesserung bereits bekannter Detektions - Schemata. In letzter Zeit wurde die Oberflächen Plasmonen feld-verstärkte Fluoreszenz Spektroskopie (SPFS) entwickelt. Sie stellt eine kinetische Analyse - und Detektions - Methode dar, die mit doppelter Aufzeichnung, d.h. der Änderung der Reflektivität und des Fluoreszenzsignals, für das Interphasen Phänomen operiert. Durch die Verwendung von SPFS können Kinetikmessungen für die Hybridisierung zwischen Peptid Nukleinsäure (PNA), welche eine synthetisierte Nukleinsäure DNA imitiert und eine stabilere Doppelhelix formt, und DNA auf der Sensoroberfläche ausgeführt werden. Mittels einzel-, umfassend-, und titrations- Experimenten sowohl mit einer komplementär zusammenpassenden Sequenz als auch einer mismatch Sequenz können basierend auf dem Langmuir Modell die Geschwindigkeitskonstanten für die Bindungsreaktion des oligomer DNA Targets bzw. des PCR Targets zur PNA ermittelt werden. Darüber hinaus wurden die Einflüsse der Ionenstärke und der Temperatur für die PNA/DNA Hybridisierung in einer kinetischen Analyse aufgezeigt.

Black-scholes type equations

In this work we are concerned with the analysis and numerical solution of Black-Scholes type equations arising in the modeling of incomplete financial markets and an inverse problem of determining the local volatility function in a generalized Black-Scholes model from observed option prices. In the first chapter a fully nonlinear Black-Scholes equation which models transaction costs arising in option pricing is discretized by a new high order compact scheme. The compact scheme is proved to be unconditionally stable and non-oscillatory and is very efficient compared to classical schemes. Moreover, it is shown that the finite difference solution converges locally uniformly to the unique viscosity solution of the continuous equation. In the next chapter we turn to the calibration problem of computing local volatility functions from market data in a generalized Black-Scholes setting. We follow an optimal control approach in a Lagrangian framework. We show the existence of a global solution and study first- and second-order optimality conditions. Furthermore, we propose an algorithm that is based on a globalized sequential quadratic programming method and a primal-dual active set strategy, and present numerical results. In the last chapter we consider a quasilinear parabolic equation with quadratic gradient terms, which arises in the modeling of an optimal portfolio in incomplete markets. The existence of weak solutions is shown by considering a sequence of approximate solutions. The main difficulty of the proof is to infer the strong convergence of the sequence. Furthermore, we prove the uniqueness of weak solutions under a smallness condition on the derivatives of the covariance matrices with respect to the solution, but without additional regularity assumptions on the solution. The results are illustrated by a numerical example.

Stochastic models and dynamic measures for the characterization of bistable circuits

During the last few years, a great deal of interest has risen concerning the applications of stochastic methods to several biochemical and biological phenomena. Phenomena like gene expression, cellular memory, bet-hedging strategy in bacterial growth and many others, cannot be described by continuous stochastic models due to their intrinsic discreteness and randomness. In this thesis I have used the Chemical Master Equation (CME) technique to modelize some feedback cycles and analyzing their properties, including experimental data. In the first part of this work, the effect of stochastic stability is discussed on a toy model of the genetic switch that triggers the cellular division, which malfunctioning is known to be one of the hallmarks of cancer. The second system I have worked on is the so-called futile cycle, a closed cycle of two enzymatic reactions that adds and removes a chemical compound, called phosphate group, to a specific substrate. I have thus investigated how adding noise to the enzyme (that is usually in the order of few hundred molecules) modifies the probability of observing a specific number of phosphorylated substrate molecules, and confirmed theoretical predictions with numerical simulations. In the third part the results of the study of a chain of multiple phosphorylation-dephosphorylation cycles will be presented. We will discuss an approximation method for the exact solution in the bidimensional case and the relationship that this method has with the thermodynamic properties of the system, which is an open system far from equilibrium.In the last section the agreement between the theoretical prediction of the total protein quantity in a mouse cells population and the observed quantity will be shown, measured via fluorescence microscopy.

Efficiency limits for silicon/perovskite tandem solar cells: a theoretical model

The primary goal of this work is related to the extension of an analytic electro-optical model. It will be used to describe single-junction crystalline silicon solar cells and a silicon/perovskite tandem solar cell in the presence of light-trapping in order to calculate efficiency limits for such a device. In particular, our tandem system is composed by crystalline silicon and a perovskite structure material: metilammoniumleadtriiodide (MALI). Perovskite are among the most convenient materials for photovoltaics thanks to their reduced cost and increasing efficiencies. Solar cell efficiencies of devices using these materials increased from 3.8% in 2009 to a certified 20.1% in 2014 making this the fastest-advancing solar technology to date. Moreover, texturization increases the amount of light which can be absorbed through an active layer. Using Green’s formalism it is possible to calculate the photogeneration rate of a single-layer structure with Lambertian light trapping analytically. In this work we go further: we study the optical coupling between the two cells in our tandem system in order to calculate the photogeneration rate of the whole structure. We also model the electronic part of such a device by considering the perovskite top cell as an ideal diode and solving the drift-diffusion equation with appropriate boundary conditions for the silicon bottom cell. We have a four terminal structure, so our tandem system is totally unconstrained. Then we calculate the efficiency limits of our tandem including several recombination mechanisms such as Auger, SRH and surface recombination. We focus also on the dependence of the results on the band gap of the perovskite and we calculare an optimal band gap to optimize the tandem efficiency. The whole work has been continuously supported by a numerical validation of out analytic model against Silvaco ATLAS which solves drift-diffusion equations using a finite elements method. Our goal is to develop a simpler and cheaper, but accurate model to study such devices.

Surface cloud radiative forcing from broadband radiation measurements on the Antarctic plateau

Surface based measurements systems play a key role in defining the ground truth for climate modeling and satellite product validation. The Italian-French station of Concordia is operative year round since 2005 at Dome C (75°S, 123°E, 3230 m) on the East Antarctic Plateau. A Baseline Surface Radiation Network (BSRN) site was deployed and became operational since January 2006 to measure downwelling components of the radiation budget, and successively was expanded in April 2007 to measure upwelling radiation. Hence, almost a decade of measurement is now available and suitable to define a statistically significant climatology for the radiation budget of Concordia including eventual trends, by specifically assessing the effects of clouds and water vapor on SW and LW net radiation. A well known and robust clear sky-id algorithm (Long and Ackerman, 2000) has been operationally applied on downwelling SW components to identify cloud free events and to fit a parametric equation to determine clear-sky reference along the Antarctic daylight periods (September to April). A new model for surface broadband albedo has been developed in order to better describe the features the area. Then, a novel clear-sky LW parametrization, based on a-priori assumption about inversion layer structure, combined with daily and annual oscillations of the surface temperature, have been adopted and validated. The longwave based method is successively exploited to extend cloud radiative forcing studies to nighttime period (winter). Results indicated inter-annual and intra-annual warming behaviour, i.e. 13.70 W/m2 on the average, specifically approaching neutral effect in summer, when SW CRF compensates LW CRF, and warming along the rest of the year due prevalentely to CRF induced on the LW component.

Use of hydroclimatic forecasts for improved water management in central Texas

Accurate seasonal to interannual streamflow forecasts based on climate information are critical for optimal management and operation of water resources systems. Considering most water supply systems are multipurpose, operating these systems to meet increasing demand under the growing stresses of climate variability and climate change, population and economic growth, and environmental concerns could be very challenging. This study was to investigate improvement in water resources systems management through the use of seasonal climate forecasts. Hydrological persistence (streamflow and precipitation) and large-scale recurrent oceanic-atmospheric patterns such as the El Niño/Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), the Atlantic Multidecadal Oscillation (AMO), the Pacific North American (PNA), and customized sea surface temperature (SST) indices were investigated for their potential to improve streamflow forecast accuracy and increase forecast lead-time in a river basin in central Texas. First, an ordinal polytomous logistic regression approach is proposed as a means of incorporating multiple predictor variables into a probabilistic forecast model. Forecast performance is assessed through a cross-validation procedure, using distributions-oriented metrics, and implications for decision making are discussed. Results indicate that, of the predictors evaluated, only hydrologic persistence and Pacific Ocean sea surface temperature patterns associated with ENSO and PDO provide forecasts which are statistically better than climatology. Secondly, a class of data mining techniques, known as tree-structured models, is investigated to address the nonlinear dynamics of climate teleconnections and screen promising probabilistic streamflow forecast models for river-reservoir systems. Results show that the tree-structured models can effectively capture the nonlinear features hidden in the data. Skill scores of probabilistic forecasts generated by both classification trees and logistic regression trees indicate that seasonal inflows throughout the system can be predicted with sufficient accuracy to improve water management, especially in the winter and spring seasons in central Texas. Lastly, a simplified two-stage stochastic economic-optimization model was proposed to investigate improvement in water use efficiency and the potential value of using seasonal forecasts, under the assumption of optimal decision making under uncertainty. Model results demonstrate that incorporating the probabilistic inflow forecasts into the optimization model can provide a significant improvement in seasonal water contract benefits over climatology, with lower average deficits (increased reliability) for a given average contract amount, or improved mean contract benefits for a given level of reliability compared to climatology. The results also illustrate the trade-off between the expected contract amount and reliability, i.e., larger contracts can be signed at greater risk.

Hierarchical Markov Random Fields Applied to Model Soft Tissue Deformations on Graphics Hardware

Many methodologies dealing with prediction or simulation of soft tissue deformations on medical image data require preprocessing of the data in order to produce a different shape representation that complies with standard methodologies, such as mass–spring networks, finite element method s (FEM). On the other hand, methodologies working directly on the image space normally do not take into account mechanical behavior of tissues and tend to lack physics foundations driving soft tissue deformations. This chapter presents a method to simulate soft tissue deformations based on coupled concepts from image analysis and mechanics theory. The proposed methodology is based on a robust stochastic approach that takes into account material properties retrieved directly from the image, concepts from continuum mechanics and FEM. The optimization framework is solved within a hierarchical Markov random field (HMRF) which is implemented on the graphics processor unit (GPU See Graphics processing unit ).

Net CO 2 surface emissions at Bern, Switzerland inferred from ambient observations of CO 2 , δ(O 2 /N 2 ), and 222 Rn using a customized radon tracer inversion

The 222Radon tracer method is a powerful tool to estimate local and regional surface emissions of, e.g., greenhouse gases. In this paper we demonstrate that in practice, the method as it is commonly used, produces inaccurate results in case of nonhomogeneously spread emission sources, and we propose a different approach to account for this. We have applied the new methodology to ambient observations of CO2 and 222Radon to estimate CO2 surface emissions for the city of Bern, Switzerland. Furthermore, by utilizing combined measurements of CO2 and δ(O2/N2) we obtain valuable information about the spatial and temporal variability of the main emission sources. Mean net CO2 emissions based on 2 years of observations are estimated at (11.2 ± 2.9) kt km−2 a−1. Oxidative ratios indicate a significant influence from the regional biosphere in summer/spring and fossil fuel combustion processes in winter/autumn. Our data indicate that the emissions from fossil fuels are, to a large degree, related to the combustion of natural gas which is used for heating purposes.

Hybrid stochastic simulations of intracellular reaction-diffusion systems.

With the observation that stochasticity is important in biological systems, chemical kinetics have begun to receive wider interest. While the use of Monte Carlo discrete event simulations most accurately capture the variability of molecular species, they become computationally costly for complex reaction-diffusion systems with large populations of molecules. On the other hand, continuous time models are computationally efficient but they fail to capture any variability in the molecular species. In this study a hybrid stochastic approach is introduced for simulating reaction-diffusion systems. We developed an adaptive partitioning strategy in which processes with high frequency are simulated with deterministic rate-based equations, and those with low frequency using the exact stochastic algorithm of Gillespie. Therefore the stochastic behavior of cellular pathways is preserved while being able to apply it to large populations of molecules. We describe our method and demonstrate its accuracy and efficiency compared with the Gillespie algorithm for two different systems. First, a model of intracellular viral kinetics with two steady states and second, a compartmental model of the postsynaptic spine head for studying the dynamics of Ca+2 and NMDA receptors.