Diagnostic analysis of atmospheric moisture and clear-sky radiative feedback in the Hadley Centre and Geophysical Fluid Dynamics Laboratory (GFDL) climate models

The interannual variability of the hydrological cycle is diagnosed from the Hadley Centre and Geophysical Fluid Dynamics Laboratory (GFDL) climate models, both of which are forced by observed sea surface temperatures. The models produce a similar sensitivity of clear-sky outgoing longwave radiation to surface temperature of ∼2 W m−2 K−1, indicating a consistent and positive clear-sky radiative feedback. However, differences between changes in the temperature lapse-rate and the height dependence of moisture fluctuations suggest that contrasting mechanisms bring about this result. The GFDL model appears to give a weaker water vapor feedback (i.e., changes in specific humidity). This is counteracted by a smaller upper tropospheric temperature response to surface warming, which implies a compensating positive lapse-rate feedback.

Efficient non-linear data assimilation in geophysical fluid dynamics

New ways of combining observations with numerical models are discussed in which the size of the state space can be very large, and the model can be highly nonlinear. Also the observations of the system can be related to the model variables in highly nonlinear ways, making this data-assimilation (or inverse) problem highly nonlinear. First we discuss the connection between data assimilation and inverse problems, including regularization. We explore the choice of proposal density in a Particle Filter and show how the ’curse of dimensionality’ might be beaten. In the standard Particle Filter ensembles of model runs are propagated forward in time until observations are encountered, rendering it a pure Monte-Carlo method. In large-dimensional systems this is very inefficient and very large numbers of model runs are needed to solve the data-assimilation problem realistically. In our approach we steer all model runs towards the observations resulting in a much more efficient method. By further ’ensuring almost equal weight’ we avoid performing model runs that are useless in the end. Results are shown for the 40 and 1000 dimensional Lorenz 1995 model.

Hamiltonian geophysical fluid dynamics

Hamiltonian dynamics describes the evolution of conservative physical systems. Originally developed as a generalization of Newtonian mechanics, describing gravitationally driven motion from the simple pendulum to celestial mechanics, it also applies to such diverse areas of physics as quantum mechanics, quantum field theory, statistical mechanics, electromagnetism, and optics – in short, to any physical system for which dissipation is negligible. Dynamical meteorology consists of the fundamental laws of physics, including Newton’s second law. For many purposes, diabatic and viscous processes can be neglected and the equations are then conservative. (For example, in idealized modeling studies, dissipation is often only present for numerical reasons and is kept as small as possible.) In such cases dynamical meteorology obeys Hamiltonian dynamics. Even when nonconservative processes are not negligible, it often turns out that separate analysis of the conservative dynamics, which fully describes the nonlinear interactions, is essential for an understanding of the complete system, and the Hamiltonian description can play a useful role in this respect. Energy budgets and momentum transfer by waves are but two examples.

Efficient fully nonlinear data assimilation for geophysical fluid dynamics

A potential problem with Ensemble Kalman Filter is the implicit Gaussian assumption at analysis times. Here we explore the performance of a recently proposed fully nonlinear particle filter on a high-dimensional but simplified ocean model, in which the Gaussian assumption is not made. The model simulates the evolution of the vorticity field in time, described by the barotropic vorticity equation, in a highly nonlinear flow regime. While common knowledge is that particle filters are inefficient and need large numbers of model runs to avoid degeneracy, the newly developed particle filter needs only of the order of 10-100 particles on large scale problems. The crucial new ingredient is that the proposal density cannot only be used to ensure all particles end up in high-probability regions of state space as defined by the observations, but also to ensure that most of the particles have similar weights. Using identical twin experiments we found that the ensemble mean follows the truth reliably, and the difference from the truth is captured by the ensemble spread. A rank histogram is used to show that the truth run is indistinguishable from any of the particles, showing statistical consistency of the method.

Structure of polyaniline formed in different inorganic porous materials: A spectroscopic study

In this work, the electronic and structural characterization of polyaniline (PANI) formed in cavities of zeolites Y (ZY) and Mordenite (MOR) and montmorillonite (MMT) clay having Cu(II) as oxidant agent are presented. The formation of PANI and its structure is analyzed by Resonance Raman, UV-Vis-NIR, FT-IR and N K XANES techniques. In all cases the structure of PANT formed is different from the ""free"" polymer. The presence of azo bonds linked to phenazine-like rings are observed only for PANI-MMT composites, independent of the kind of oxidant agent employed in the synthesis. The presence of Cu(II) ions leads to the formation of Phenosafranine-like rings. The presence of these phenazine-like rings in the structure of confined PANT chains can also contribute to the enhancement of the thermal stability observed for all composites. (C) 2008 Elsevier Ltd. All rights reserved.

Computer simulation of the stochastic transport equation

Trabalho apresentado no 37th Conference on Stochastic Processes and their Applications - July 28 - August 01, 2014 -Universidad de Buenos Aires

Numeric simulation of pollutant dispersion by a control-volume based on finite element method

The dispersion of pollutants in the environment is an issue of great interest as it directly affects air quality, mainly in large cities. Experimental and numerical tools have been used to predict the behavior of pollutant species dispersion in the atmosphere. A software has been developed based on the control-volume based on the finite element method in order to obtain two-dimensional simulations of Navier-Stokes equations and heat or mass transportation in regions with obstacles, varying position of the pollutant source. Numeric results of some applications were obtained and, whenever possible, compared with literature results showing satisfactory accordance. Copyright (C) 2010 John Wiley & Sons, Ltd.

PRODUCTION of THERMAL PHOTONS IN VISCOUS FLUID DYNAMICS WITH TEMPERATURE-DEPENDENT SHEAR VISCOSITY

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Shear viscosity from thermal fluctuations in relativistic conformal fluid dynamics

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Noncommutative fluid dynamics in the Snyder space-time

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Rheological properties and fluid dynamics of egg yolk

The rheological behavior of egg yolk was studied at a range of temperatures (277-333 K) using a concentric cylinder viscometer. Rheological behavior was pseudoplastic and flow curves fitted by the power law model. The consistency and behavior indexes, dependent on temperature, were expressed by an Arrhenius-type equation. The rheological parameters, together with experimental values of pressure loss in tube flow were used to calculate friction factors. The good agreement between predicted and observed values confirmed the reliability of the equations proposed for describing the flow behavior of the egg yolk. (c) 2005 Published by Elsevier Ltd.