Nelson Jesus Ferreira

ESTIMATIVA DA EVAPOTRANSPIRAÇÃO REAL DIÁRIA UTILIZANDO-SE IMAGENS DIGITAIS TM - LANDSAT 5

Quantification of evapotranspiration is of great importance for hydrological and meteorological modeling and indispensable for water management of irrigated crops. In this sense the main objective of this study was the estimation of actual daily evapotranspiration (Etr), in local and regional scale, utilizing the SEBAL (Surface Energy Balance Algorithm for Land). The TM - Landsat 5 images and weather data were used in order to assess the energy balance components. The studied area is located in Cariri region, Ceara State, and is composed by irrigated areas, native vegetation and part of the Chapada do Araripe Reserve. Four TM - Landsat 5 images of September 29th, October 15th, October 31st and November 16th of 2005, were used. Daily ETr was estimated based on the density of latent heat flux, obtained as residue of the energy balance equation. The application of the SEBAL algorithm includes some steps as radiometric calibration, estimation of the reflectance and albedo, emissivity and vegetation index, based on the reflective bands of the orbital sensors and further on the surface temperature (thermal band) for the TM - Ladsat 5. Two irrigated fields of castor bean and cotton were used do validated the ETr estimated values. The reference evapotranspiration was obtained by FAO-Penman-Monteith method. The mean daily ETr over the studied area presented values of 3.8, 3.7, 4.6 and 3.4 mm.dia-1 on 29/09, 15/10, 31/10 and 16/11, respectively. When compared to measured data in the castor bean (Ricinus communis L.) and cotton (Gossypium hirsutum) irrigated crops, the ETr values obtained with SEBAL present differences smaller than 1,0 mm day-1, showing its importance and accuracy.

Novel approaches to entropic regularization

In this work, two new entropic regularization techniques are introduced. They represent a generalization of the standard MaxEnt regularization method, and allow for a greater flexibility for introducing any prior information about the expected structure of the true physical model, or its derivatives, into the inversion procedure. The first technique is based on the minimization of the entropy of the vector of first-differences of unknown parameters. Adopting standard terminology, it is known as the minimum first-order entropy method (MinEnt-1). To illustrate the essential feature of the method, MinEnt-1 is applied to the reconstruction of two-dimensional geoelectric conductivity distributions from magnetotelluric data. The second technique is based on the maximization of the entropy of the vector of second-differences of the unknown parameters, and is denoted as the MaxEnt-2 method. The MaxEnt-2 method is applied to the retrieval of vertical profiles of temperature in the atmosphere from remote sensing data.

Linear and Nonlinear Statistical Downscaling for Rainfall Forecasting over Southeastern Brazil

Abstract In this work linear and nonlinear downscaling are developed to establish empirical relationships between the synoptic-scale circulation and observed rainfall over southeastern Brazil. The methodology uses outputs from the regional Eta Model; prognostic equations for local forecasting were developed using an artificial neural network (ANN) and multiple linear regression (MLR). The final objective is the application of such prognostic equations to Eta Model output to generate rainfall forecasts. In the first experiment the predictors were obtained from the Eta Model and the predictand was rainfall data from meteorological stations in southeastern Brazil. In the second experiment the observed rainfall on the day prior to the forecast was included as a predictor. The threat score (TS) and bias, used to quantify the performance of the forecasts, showed that the ANN was superior to MLR in most seasons. When compared with Eta Model forecasts, it was observed that the ANN has a tendency to forecast moder...

Case Studies of Easterly Wave Disturbances over Northeast Brazil Using the Eta Model

AbstractThis research aims to analyze two easterly wave disturbance events that reached the east coast of Northeast Brazil (NEB) on 15 May 2005 and 20 June 2006. The performance of the regional Eta Model was evaluated through four sets of experiments using different horizontal resolutions (10 and 40 km) and convective parameterization schemes [Betts–Miller–Janjic (BMJ) and Kain–Fritsch (KF)]. Through analysis of 700-hPa wind fields, all experiments, with 40- and 10-km horizontal resolutions and using the BMJ and KF schemes, were shown to well represent a trough propagating westward from about 20°W to NEB, with a 5-day forecast range. When evaluating the model sensitivity to different convective parameterizations, all the experiments showed similar results and underestimated rainfall in most of the domain. The obtained results suggest the need to extend this analysis to a larger number of cases and to test other cumulus parameterizations in order to improve the rainfall forecast in eastern NEB.

MINERAÇÃO DE DADOS METEOROLÓGICOS PARA PREVISÃO DE EVENTOS SEVEROS

This work aims the early detection of possible occurrences of severe convective events in Central and Southeast Brazil by means of monitoring the output of the Eta numerical weather prediction model for each forecasted time interval and for a selected set of variables. The studied period ranges from January to February 2007. Classifiers were developed by two approaches, vector similarity and rough sets, in order to identify Eta outputs that can be associated to such events. It was assumed that severe convective events can be correlated to a large number of atmospheric electric discharges. The classifiers grouped the Eta meteorological model outputs for these selected variables based on the density of occurrences of cloud-to-ground atmospheric electrical discharges. Both classifiers show good performance for the chosen 2-month period at the three selected mini-regions of the Brazilian territory.

Determinação e modelagem da taxa de consumo de biomassa queimada

The present study evaluates the use of fire radiative energy (FRE) to estimate the emissions of particulate matter with diameter less than 2.5 μm (PM2,5µm) from the multiplicative coefficient relating the biomass consumption with the released FRE. The MODIS (Moderate Resolution Imaging Spectroradiometer) and GOES (Geostationary Operational Environmental Satellite) products were utilized to calculate the total amount of aerosol emitted to the atmosphere. The CCATT-BRAMS (Coupled Chemistry-Aerosol-Tracer Transport model coupled to Brazilian Regional Atmospheric Modelling System) model was used to estimate the PM2,5µm concentration generated by biomass burning. The model results were compared with data obtained from the LBA (Large Scale Biosphere-Atmosphere), SMOCC (Smoke, Aerosols, Clouds, rainfall, and Climate) and RaCCI (Radiation, Cloud, and Climate Interactions) field experiments. The estimated PM2,5µm emission has a correlation with the SMOCC/RaCCI data greater than 92%. It was also verified that the maximum daily consumption can exceed 5 Tg (5,000,000 ton.), with a daily average of 2.1 Tg. The resulting method from laboratory analysis estimated a total of 0.28 ± 0.01 Pg (1015 g) biomass consumed from July to November 2002 in South America.

Mesoscale convective complexes in Rio Grande do Sul between October and December of 2003 and associated precipitation.

This study investigates the occurrences of Mesoscale Convective Complexes (MCC) and the associated precipitation in the southernmost Brazilian state, Rio Grande do Sul (RS), from October to December of 2003. The identification of MCC events was done using ForTraCC. The MCC precipitation was based on the daily data of 31 local weather stations. Twenty-two MCC events were identified over RS during the three month study period, and this total, seven events occurred in October, seven in November and eight in December. Results point to an MCC associated precipitation average of 119 mm in October, 90 mm in November and 152 mm in December. The percentages for MCC precipitation averages, for the period, were 64% in October, 65% in November and 61% in December. The average accumulated volume of MCC precipitation for the three months was 361 mm (63%). This confirms that MCC events contributed significantly to the precipitation totals in RS, and were responsible for almost two thirds of the precipitation in RS, for the period.

Variabilidade dos ciclos anual e interanual da radiação de ondas longas emergentes sobre a América do Sul e vizinhanças

A principal component analysis was used to characterize the annual and interannual variability of outgoing longwave radiation over South America and neighboring regions. The data sample is comprised of monthly Advanced Very High Resolution Radiometer (AVHRR) data, covering the period January 1982 - December 1993. The results obtained characterize the behavior of the spatial pattern of the dominant weather systems acting over Brazil. The first component represents the mean convective activity pattern; the second and the fourth ones are respectively associated with the summer/winter and spring/autumn modes of the annual cycle. The third component shows spatial variability modulated by El Nino and the fifth one is associated with the semi-annual cycle.

Estimativa do fluxo do calor sensível utilizando o algoritmo SEBAL e imagens MODIS para a região Norte Fluminense, RJ

Images from the MODIS and SEBAL algorithm were used to evaluate two proposals for estimating sensible heat flux (H) based on the selection of anchor pixels used to determine the surface temperature difference (dT). The proposition in which pixels with extreme temperatures were used was called H-CLASSIC. The other one H-PESAGRO adopted for cold pixels the lowest temperature and for the hot pixels the value of H as a residue of the equation of Penman-Monteith FAO 56, using observed data from agrometeorological station. The results showed that the H-PESAGRO required a smaller number of interactions for the stabilization of the aerodynamic resistance (rah) values. H- CLASSIC estimated values were 58.35% higher than the estimated by H-PESAGRO. The estimated H values using Bowen ratio when compared with the sugar cane pixels presented correlation coefficients of r = 0.54 and r = 0.71 for the Propositions H-CLASSIC and H-PESAGRO, respectively.

Assessment of Evapotranspiration in North Fluminense Region, Brazil, Using Modis Products and Sebal Algorithm

Jose Carlos Mendonca1, Elias Fernandes de Sousa2, Romisio Geraldo Bouhid Andre3, Bernardo Barbosa da Silva4 and Nelson de Jesus Ferreira5 1Laboratorio de Meteorologia (LAMET/UENF). Rod. Amaral Peixoto, Av. Brennand s/n Imboassica, Macae, RJ 2Laboratorio de Engenharia Agricola (LEAG/UENF); Avenida Alberto Lamego, CCTA, sl 209, Parque California, Campos dos Goytacazes, RJ 3Instituto Nacional de Meteorologia (INMET/MAPA); Eixo Monumental, Via S1 – Sudoeste, Brasilia, DF 4Departamento de Ciencias Atmosfericas (DCA/UFCG); Avenida Aprigio Veloso, Bodocongo, Campina Grande, PB 5Centro de Previsao de Tempo e Estudos Climaticos (CPTEC/INPE); Av. dos Astronautas, Jardim da Granja, Sao Jose dos Campos, SP Brazil