A case study of the direct radiative effect of biomass burning aerosols on precipitation in the Eastern Amazon

Numerical experiments with the Brazilian additions to the Regional Atmospheric Modeling System were performed with two nested grids (50 and 10 km horizontal resolution, respectively) with and without the effect of biomass burning for 8 different situations for 96 h integrations. Only the direct radiative effect of aerosols is considered. The results were analyzed in large areas encompassing the BR163 road (one of the main areas of deforestation in the Amazon). mainly where most of the burning takes place. The precipitation change due to the direct radiative impact of biomass burning is generally negative (i.e., there is a decrease of precipitation). However, there are a few cases with a positive impact. Two opposite forcing mechanisms were explored: (a) the thermodynamic forcing that is generally negative in the sense that the aerosol tends to stabilize the lower atmosphere and (b) the dynamic impact associated with the low level horizontal pressure gradients produced by the aerosol plumes. In order to understand the non-linear relationship between the two effects, experiments were performed with 4-fold emissions. In these cases, the dynamic effect overcomes the stabilization produced by the radiative forcing and precipitation increase is observed in comparison with the control experiment. This study suggests that. in general, the biomass burning radiative forcing decreases the precipitation. However, very large concentrations of aerosols may lead to an increase of precipitation due to the dynamical forcing associated with the horizontal pressure gradients. (C) 2009 Elsevier B.V. All rights reserved.

Impact of biomass burning aerosols on precipitation in the Amazon: A modeling case study

A study of the potential role of aerosols in modifying clouds and precipitation is presented using a numerical atmospheric model. Measurements of cloud condensation nuclei (CCN) and cloud size distribution properties taken in the southwestern Amazon region during the transition from dry to wet seasons were used as guidelines to define the microphysical parameters for the simulations. Numerical simulations were carried out using the Brazilian Development on Regional Atmospheric Modeling System, and the results presented considerable sensitivity to changes in these parameters. High CCN concentrations, typical of polluted days, were found to result in increases or decreases in total precipitation, depending on the level of pollution used as a reference, showing a complexity that parallels the aerosol-precipitation interaction. Our results show that on the grids evaluated, higher CCN concentrations reduced low-to-moderate rainfall rates and increased high rainfall rates. The principal consequence of the increased pollution was a change from a warm to a cold rain process, which affected the maximum and overall mean accumulated precipitation. Under polluted conditions, cloud cover diminished, allowing greater amounts of solar radiation to reach the surface. Aerosol absorption of radiation in the lower layers of the atmosphere delayed convective evolution but produced higher maximum rainfall rates due to increased instability. In addition, the intensity of the surface sensible heat flux, as well as that of the latent heat flux, was reduced by the lower temperature difference between surface and air, producing greater energy stores at the surface.

Inferential Implications of Over-Parametrization: A Case Study in Incomplete Categorical Data

P>In the context of either Bayesian or classical sensitivity analyses of over-parametrized models for incomplete categorical data, it is well known that prior-dependence on posterior inferences of nonidentifiable parameters or that too parsimonious over-parametrized models may lead to erroneous conclusions. Nevertheless, some authors either pay no attention to which parameters are nonidentifiable or do not appropriately account for possible prior-dependence. We review the literature on this topic and consider simple examples to emphasize that in both inferential frameworks, the subjective components can influence results in nontrivial ways, irrespectively of the sample size. Specifically, we show that prior distributions commonly regarded as slightly informative or noninformative may actually be too informative for nonidentifiable parameters, and that the choice of over-parametrized models may drastically impact the results, suggesting that a careful examination of their effects should be considered before drawing conclusions.Resume Que ce soit dans un cadre Bayesien ou classique, il est bien connu que la surparametrisation, dans les modeles pour donnees categorielles incompletes, peut conduire a des conclusions erronees. Cependant, certains auteurs persistent a negliger les problemes lies a la presence de parametres non identifies. Nous passons en revue la litterature dans ce domaine, et considerons quelques exemples surparametres simples dans lesquels les elements subjectifs influencent de facon non negligeable les resultats, independamment de la taille des echantillons. Plus precisement, nous montrons comment des a priori consideres comme peu ou non-informatifs peuvent se reveler extremement informatifs en ce qui concerne les parametres non identifies, et que le recours a des modeles surparametres peut avoir sur les conclusions finales un impact considerable. Ceci suggere un examen tres attentif de l`impact potentiel des a priori.

The Development of Dalton`s Atomic Theory as a Case Study in the History of Science: Reflections for Educators in Chemistry

The inclusion of the history of science in science curricula-and specially, in the curricula of science teachers-is a trend that has been followed in several countries. The reasons advanced for the study of the history of science are manifold. This paper presents a case study in the history of chemistry, on the early developments of John Dalton`s atomic theory. Based on the case study, several questions that are worth discussing in educational contexts are pointed out. It is argued that the kind of history of science that was made in the first decades of the twentieth century (encyclopaedic, continuist, essentially anachronistic) is not appropriate for the development of the competences that are expected from the students of sciences in the present. Science teaching for current days will benefit from the approach that may be termed the ""new historiography of science"".