Débora Regina Roberti

The Influence of Submeso Processes on Stable Boundary Layer Similarity Relationships

AbstractPrevious observational studies in the stable boundary layer diverge appreciably on the values of dimensionless ratios between turbulence-related quantities and on their stability dependence. In the present study, the hypothesis that such variability is caused by the influence of locally dependent nonturbulent processes, referred to as submeso, is tested and confirmed. This is done using six datasets collected at sites with different surface coverage. The time-scale dependence of wind components and temperature fluctuations is presented using the multiresolution decomposition, which allows the identification of the turbulence and submeso contributions to spectra and cospectra. In the submeso range, the spectra of turbulence kinetic energy range increases exponentially with time scale. The exponent decreases with the magnitude of the turbulent fluctuations at a similar manner at all sites. This fact is used to determine the smaller time scale with relevant influence of submeso processes and a ratio ...

Evaluation of a Dynamic Agroecosystem Model (Agro-IBIS) for Soybean in Southern Brazil

With the growing demands for food and biofuel, new tech- nologies and crop management systems are being used to increase productivity and minimize land-use impacts. In this context, estimates of productivity and the impacts of agriculture management practices are becoming increasingly important. Numerical models that describe the soil-surface-atmosphere inter- actions for natural and agricultural ecosystems are important tools to explore the impacts of these agronomical technologies and their environmental impacts.

Lagrangian stochastic dispersion modelling for the simulation of the release of contaminants from tall and low sources

A Lagrangian particle model is used to study the dispersion of pollutants released in two different tracer experiments: Prairie Grass and Copenhagen. The model is based on a generalized form of the Langevin equation. Turbulence inputs are parameterized according to a scheme able to generate continuous values in all stability conditions and in all heights in the planetary boundary layer. Predicted values of ground-level concentration agree quite well with observed ones. The major progress of this paper is as follows: For air quality modeling it is highly necessary to include a parameterization that allows a correct description of the turbulent transport of contaminants released simultaneously from low and tall sources.

Characterization of Wind Meandering in Low-Wind-Speed Conditions

Investigation of low-wind cases observed during the Urban Turbulent Project campaign (Torino, Italy) and at the Santa Maria meteorological station (Santa Maria, Brazil) provides insight into the wind-meandering phenomenon, i.e. large, non-turbulent oscillations of horizontal wind speed and temperature. Meandering and non-meandering cases are identified through analysis of the Eulerian autocorrelation functions of the horizontal wind-velocity components and temperature. When all three autocorrelation functions oscillate, meandering is present. As with weak turbulence, meandering shows no dependence on stability but is influenced by presence of buildings and depends on wind speed. We show that, while the standard deviation of the horizontal velocity is always large in low-wind conditions, the standard deviation of the vertical velocity shows very different behaviour in meandering and non-meandering conditions. In particular, the value of the ratio of the standard deviations of the vertical and horizontal velocities typifies the meandering condition.

Energy Partitioning and Evapotranspiration over a Rice Paddy in Southern Brazil

AbstractDuring approximately 80% of its growing season, lowland flooded irrigated rice ecosystems in southern Brazil are kept within a 5–10-cm water layer. These anaerobic conditions have an influence on the partitioning of the energy and water balance components. Furthermore, this cropping system differs substantially from any other upland nonirrigated or irrigated crop ecosystems. In this study, daily, seasonal, and annual dynamics of the energy and water balance components were analyzed over a paddy rice farm in a subtropical location in southern Brazil using eddy covariance measurements. In this region, rice is grown once a year in low wetlands while the ground is kept fallow during the remaining of the year. Results show that the energy budget residual corresponded to up to 20% of the net radiation during the rice-growing season and around 10% for the remainder of the year (fallow). The energy and water balance analysis also showed that because of the high water table in the region, soil was near sat...

Employing a Lagrangian stochastic dispersion model and classical diffusion experiments to evaluate two turbulence parameterization schemes

Considering a Lagrangian stochastic particle dispersion model and diffusion experiments, two turbulence parameterizations have been tested. The parameters obtained from the Taylor turbulence parameterization are derived from observed spectral properties and characteristics of energy containing eddies. Taylor turbulence scheme provides continuous values for the turbulent parameters in the planetary boundary layer. Hanna turbulence parameterization is obtained from theoretical considerations and second–order closure models and it does not provide continuous vertical profiles for the turbulent parameters. The predicted values by a Lagrangian diffusion model utilizing Taylor turbulence parameterization and the Hanna turbulence scheme are compared with observed concentration data from diffusion experiments. The use of Taylor turbulence scheme resulted in better results.

Estimativa da radiação fotossinteticamente ativa absorvida pela cultura da soja através de dados do sensor Modis

The objective of this study was to test a methodology of data generation of the spatial and temporal distribution of the absorbed photosynthetically active radiation (RFAa) by the soybean crop based on the quantification of the relation between the normalized difference vegetation index (NDVI) and the fraction of absorbed photosynthetically active radiation (FRFAa) by the crop. The study covered the county of Cruz Alta, one of the largest producers of soybean in Rio Grande do Sul, Brazil, during the period of two harvest seasons: 2008/09 and 2009/10. The data of the incident photosynthetically active radiation (RFAi) were collected on the experimental area and the orbital data came from two platforms: Landsat/TM and Terra/MODIS, both with free distribution, but with distinct characteristics. A simple linear relation was established between the NDVI of the MODIS images and the FRFAa, obtained during two important periods of the cycle: sowing and maximum plant growth. The results showed that there is an association between the NDVI and the FRFAa that can, therefore, be used on the generation of RFAa data by the soybean crop throughout the development cycle, allowing the temporal monitoring of this element.

Parallel implementation of a Lagrangian stochastic model for pollution dispersion

Pollutant dispersion models in the atmosphere can describe by Eulerian or Lagrangian approaches. Lagrangian models belong to the class of Monte Carlo methods. This type of method is very flexible, solving more complex problems, however this computational cost is greater than Eulerian models, as it is well established in the atmospheric pollutant and nuclear engineering communities. A parallel version of the Lagrangian particle model - LAMBDA - is developed using the MPI message passing communication library. Performance tests were executed in a distributed memory parallel machine, a multicomputer based on IA-32 architecture. Portions of the pollutant in the air are considered particles emitted from a pollutant source, evolving under stochastic forcing. This yields independent evolution equations for each particle of the model that can be executed by a different processor in a parallel implementation. Speed-up results show that the parallel implementation is suitable for the used architecture.

Identifying Counter-Gradient term in atmospheric convective boundary layer

Since Deardoff [5] derived the counter-gradient term contribution, a good representation has been searched for this term. An inverse problem methodology is used to identify this property. The inverse analysis is performed minimizing an objective function: the square difference between experimental and model data added to a regularization function. Two regularization functions are used: second-order maximum entropy, and Tikhonov regularization of second-order. The scheme is tested with synthetic noise data. A new formulation for the counter-gradient is also presented.

Parallel implementation of a Lagrangian stochastic model for pollutant dispersion

Lagrangian dispersion models have shown to be effective and reliable tools for simulating the airborne pollutant dispersion. However, the main drawback for their use as regulatory models is the associated high computational costs. Consequently, in this paper a parallel version of a Lagrangian particle model—LAMBDA—is developed using the MPI message passing communication library. Performance tests were executed in a distributed memory parallel machine, a multicomputer based on IA-32 architecture. Portions of the pollutant in the air emitted from its source are simulated as fictitious particles whose trajectories evolve under stochastic forcing. This yields independent evolution equations for each particle of the model that can be computed by a different processor in a parallel implementation. Speed-up results show that the parallel implementation is suitable for the used architecture.