Análise de superfície de tendência aplicada à chuva, medida por radar meteorológico, nas regiões de Assis e Piracicaba, SP

This paper presents the results from lineal trend surface analysis technique application. The purpose was to detect positive and negative anomalies in the rain measure distribution obtained by the meteorological radar Doppler, band S, located in Bauru, during the period of 21 of October/2004 to 29 of April/2005 in the areas of Assis and Piracicaba. Using three Z-R radar relations for rain quantification was chosen the specific equation Z = 32R1,65, as the best one. The results showed that the applied methodology was able to indicate the space distribution of the rain accumulated, identifying and locating the regions where there was rainy excess and rainy lack during each analyzed period. Such results indicate areas with larger pluvial impact and consequently more favorable for environmental damages.

Lidar observation campaign of sugar cane fires and industrial emissions in the State of São Paulo, Brazil

Brazil has an important role in the biomass burning, with the detection of approximately 100,000 burning spots in a single year (2007). Most of these spots occur in the southern part of the Amazon basin during the dry season (from August to november) and these emissions reach the southeast of the country, a highly populated region and with serious urban air pollution problems. With the growing demand on biofuels, sugarcane is considerably expanding in the state of São Paulo, being a strong contributor to the bad air quality in this region. In the state of São Paulo, the main land use are pasture and sugarcane crop, that covers around 50% and 10% of the total area, respectively. Despite the aerosol from sugarcane burning having reduced atmospheric residence time, from a few days to some weeks, they might get together with those aerosol which spread over long distances (hundreds to thousands of kilometers). In the period of June through February 2010 a LIDAR observation campaign was carried in the state of São Paulo, Brazil, in order to observe and characterize optically the aerosols from two distinct sources, namely, sugar cane biomass burning and industrial emissions. For this purpose 2 LIDAR systems were available, one mobile and the other placed in a laboratory, both working in the visible (532 nm) and additionally the mobile system had a Raman channel available (607 nm). Also this campaign counted with a SODAR, a meteorological RADAR specially set up to detect aerosol echoes and gas-particle analyzers. To guarantee a good regional coverage 4 distinct sites were available to deploy the instruments, 2 in the near field of biomass burning activities (Rio Claro and Bauru), one for industrial emissions (Cubatão) and others from urban sources (São Paulo). The whole campaign provide the equivalent of 30 days of measurements which allowed us to get aerosol optical properties such as backscattering/extinction coefficients, scatter and LIDAR ratios, those were used to correlate with air quality and meteorological indicators and quantities. In this paper we should focus on the preliminary results of the Raman LIDAR system and its derived aerosol optical quantities. © 2010 Copyright SPIE - The International Society for Optical Engineering.

Um filtro gaussiano adaptativo para análise comparativa de imagens de radares e satélites meteorológicos

Meteorological satellite and radar data comparative analysis allows to correlate the precipitation structures observed in both images. Such analysis would make feasible the extension of the range of ground-based meteorological radars. In addition to the different spatial and temporal resolution of these images this comparative analysis presents difficulties due to the effects of rotation and distortion, besides the different formats, projections, and coordinate systems. This work employed an approach based on a Gaussian adaptive filter in order to compare such images. The statistical results obtained from the comparison of the images are matched to those produced by other methods.

Initial analysis from a Lidar observation campaign of sugar cane fires in the central and western portion of the S̃ao Paulo State - Brazil

The central and western portion of the S̃ao Paulo State has large areas of sugar cane plantations, and due to the growing demand for biofuels, the production is increasing every year. During the harvest period some plantation areas are burnt a few hours before the manual cutting, causing significant quantities of biomass burning aerosol to be injected into the atmosphere. During August 2010, a field campaign has been carried out in Ourinhos, situated in the south-western region of S̃ao Paulo State. A 2-channel Raman Lidar system and two meteorological S-Band Doppler Radars are used to indentify and quantify the biomass burning plumes. In addiction, CALIPSO Satellite observations were used to compare the aerosol optical properties detected in that region with those retrieved by Raman Lidar system. Although the campaign yielded 30 days of measurements, this paper will be focusing only one case study, when aerosols released from nearby sugar cane fires were detected by the Lidar system during a CALIPSO overpass. The meteorological radar, installed in Bauru, approximately 110 km northeast from the experimental site, had recorded echoes (dense smoke comprising aerosols) from several fires occurring close to the Raman Lidar system, which also detected an intense load of aerosol in the atmosphere. HYSPLIT model forward trajectories presented a strong indication that both instruments have measured the same air masss parcels, corroborated with the Lidar Ratio values from the 532 nm elastic and 607 nm Raman N2 channel analyses and data retrieved from CALIPSO have indicated the predominance of aerosol from biomass burning sources. © 2011 SPIE.

An intelligent system to real time rainfall prediction using radar data

This work presents a new approach for rainfall measurements making use of weather radar data for real time application to the radar systems operated by institute of Meteorological Research (IPMET) - UNESP - Bauru - SP-Brazil. Several real time adjustment techniques has been presented being most of them based on surface rain-gauge network. However, some of these methods do not regard the effect of the integration area, time integration and distance rainfall-radar. In this paper, artificial neural networks have been applied for generate a radar reflectivity-rain relationships which regard all effects described above. To evaluate prediction procedure, cross validation was performed using data from IPMET weather Doppler radar and rain-gauge network under the radar umbrella. The preliminary results were acceptable for rainfalls prediction. The small errors observed result from the spatial density and the time resolution of the rain-gauges networks used to calibrate the radar.

Geoestatística aplicada à acumulação da precipitação pluviométrica com radar meteorológico

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Avaliação da chuva produzida pelo modelo eta de previsão do tempo para o Estado de São Paulo com uso de radar meteorológico para aplicações agrícolas

Pós-graduação em Agronomia (Irrigação e Drenagem) - FCA

Raman Lidar monitors emissions from sugar cane fires in the State of São Paulo: a pilot-project integrating radar, sodar, aerosol and gas observations

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

A dense GNSS meteorological network for observing deep convection in the Amazon

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

Atributos polarimétricos de imagem radar na inferência de parâmetros morfológicos de macrófitas

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

Monitoramento da atenuação natural de pluma de contaminação pelo método de radar de penetração no solo (GPR)

O monitoramento da atenuação natural em áreas contaminadas tem se mostrado uma técnica alternativa e de baixo custo para a remediação de áreas contaminadas. A degradação por microorganismos é um dos processos mais importantes na atenuação natural de contaminantes, especialmente compostos de fase líquida não aquosa (NAPL). em muitos casos, a ação efetiva deste processo resulta na geração de ácidos orgânicos, que sob elevadas concentrações ocasionam a dissolução de minerais presentes em subsuperfície onde se encontra a contaminação, com conseqüente liberação de íons. O aumento na quantidade de íons colabora para o aumento da condutividade elétrica do meio. O princípio físico da técnica de Radar de Penetração no Solo (GPR) é a emissão de ondas eletromagnéticas de alta freqüência. A propagação da onda eletromagnética é condicionada à freqüência de sinal emitido e as propriedades elétricas do meio. O aumento da condutividade elétrica do meio resulta na atenuação do sinal e, por conseqüência, na diminuição da profundidade de penetração da onda eletromagnética. Este fator permite o monitoramento de áreas contaminadas sob atenuação natural a partir de análises temporais com o GPR. Este trabalho apresenta um estudo comparativo entre perfis de GPR adquiridos em 1998 e 2003 em uma área contaminada por compostos de fase líquida leve não aquosa (LNAPL), sob atenuação natural. Os resultados indicam um aumento da condutividade elétrica do meio, a partir da atenuação acentuada do sinal GPR observada nas seções de 2003. Este aumento pode estar associado à liberação de íons por dissolução de minerais, pelo ataque de ácidos orgânicos resultantes do processo de biodegradação.

Estimativa de ocorrência de precipitação em áreas agrícolas utilizando floresta de caminhos ótimos

As condições meteorológicas são determinantes para a produção agrícola; a precipitação, em particular, pode ser citada como a mais influente por sua relação direta com o balanço hídrico. Neste sentido, modelos agrometeorológicos, os quais se baseiam nas respostas das culturas às condições meteorológicas, vêm sendo cada vez mais utilizados para a estimativa de rendimentos agrícolas. Devido às dificuldades de obtenção de dados para abastecer tais modelos, métodos de estimativa de precipitação utilizando imagens dos canais espectrais dos satélites meteorológicos têm sido empregados para esta finalidade. O presente trabalho tem por objetivo utilizar o classificador de padrões floresta de caminhos ótimos para correlacionar informações disponíveis no canal espectral infravermelho do satélite meteorológico GOES-12 com a refletividade obtida pelo radar do IPMET/UNESP localizado no município de Bauru, visando o desenvolvimento de um modelo para a detecção de ocorrência de precipitação. Nos experimentos foram comparados quatro algoritmos de classificação: redes neurais artificiais (ANN), k-vizinhos mais próximos (k-NN), máquinas de vetores de suporte (SVM) e floresta de caminhos ótimos (OPF). Este último obteve melhor resultado, tanto em eficiência quanto em precisão.

Modelling short-term temporal changes of bare soil CO2 emissions in a tropical agrosystem by using meteorological data

Determining the variability of carbon dioxide emission from soils is an important task as soils are among the largest sources of carbon in biosphere. In this work the temporal variability of bare soil CO2 emissions was measured over a 3-week period. Temporal changes in soil CO2 emission were modelled in terms of the changes that occurred in solar radiation (SR), air temperature (T-air), air humidity (AR), evaporation (EVAP) and atmospheric pressure (ATM) registered during the time period that the experiment was conducted. The multiple regression analysis (backward elimination procedure) includes almost all the meteorological variables and their interactions into the final model (R-2 = 0.98), but solar radiation showed to be the one of the most relevant variables. The present study indicates that meteorological data could be taken into account as the main forces driving the temporal variability of carbon dioxide emission from bare soils, where microbial activity is the sole source of carbon dioxide emitted. (C) 2003 Elsevier B.V. All rights reserved.