Ricardo Hallak | USP - Academia.edu (original) (raw)

Papers by Ricardo Hallak

Atmosphere, Oct 26, 2022

This article is an open access article distributed under the terms and conditions of the Creative... more This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY

Um modelo matemático simples foi utilizado para estudar o efeito da distribuição de tamanho das p... more Um modelo matemático simples foi utilizado para estudar o efeito da distribuição de tamanho das partículas sobre a eficiência de remoção por deposição seca. Para esta finalidade foram utilizadas duas distribuições de tamanho de aerossóis, típicas de ambientes poluídos: uma distribuição de ambiente de queimada (Amazônia) e outra de ambi-ente urbano (São Paulo). Os resultados mostraram que partículas origi-nárias de ambiente urbano são mais eficientemente removidas por depo-sição seca do que partículas de queimada. Este comportamento está as-sociado ao fato de que a natureza de remoção das partículas por deposi-ção seca é pouco eficiente para diâmetros entre 0,1 e 1,0 mm, domínio em que se concentra a maior parte das partículas de queimada. Esse me-canismo diferencial de deposição é o que explica o maior efeito deletério das partículas ultra-finas no sistema respiratório humano. 1.

Remote Sensing of Environment

Aerosol and Air Quality Research

The Metropolitan Area of São Paulo (MASP) is one of the largest urban environments of the planet ... more The Metropolitan Area of São Paulo (MASP) is one of the largest urban environments of the planet with a population of over 18 million people. It is located within the Alto Tietê River

Revista Brasileira De Meteorologia, 2012

Este trabalho discute a eficacia de variados indices termodinâmicos e cinematicos como previsores... more Este trabalho discute a eficacia de variados indices termodinâmicos e cinematicos como previsores de uma serie de chuvas que produziram alta acumulacao de precipitacao e algumas enchentes repentinas na regiao metropolitana de Sao Paulo no periodo de 27 de janeiro a 05 de fevereiro de 2004. De um modo geral, mostrou-se que nao ha informacao fisica suficiente em cada um dos indices que pudessem justificar grande confianca no uso dessas quantidades como variaveis prognosticas de eventos severos. De cinco indices termodinâmicos verificados, apenas um, o indice de Showalter, proposto em 1947, mostrou maior consistencia com as observacoes de precipitacao severa. Entretanto, este mesmo indice foi extremamente afetado em um dia em que se registrou forte inversao termica na camada limite planetaria. A serie temporal de energia potencial convectiva disponivel mostrou concordância de fase com a serie temporal do indice levantado, com alta correlacao linear entre ambas. Os resultados mostram, p...

Unmanned aerial vehicles (UAVs) and machine learning are relatively new research tools in the geo... more Unmanned aerial vehicles (UAVs) and machine learning are relatively new research tools in the geosciences that can be used to collect and analyze large data sets rapidly. We combine the power of rapid data collection using unmanned aerial vehicles with machine learning algorithms to develop a field-based system to identify targeted geological features. For data collection, we have used a commercial-grade UAV which carried visible-wavelength and multispectral (visibleinfrared) cameras. We analyzed the data with machine learning and machine vision algorithms that can classify rock units exposed in a field area. We have identified algorithms that in previous literature have proven to be reliable in predicting characteristics. These include k-Nearest Neighbors, Support Vector Machines, K-Means Clustering and Convolutional Neural Networks which we tested to determine their effectiveness in geologic mapping. Several filtering operations were applied to the collected imagery. K-Means clustering was used to generate some preliminary segmentation of lithology on the ground. We then ran 3 supervised machine learning algorithms and the results were field tested to determine how they compared to a professional grade geologic map. The results show that consumer-grade machine learning algorithms and consumer-grade UAV platforms can be integrated into a package that can act as a field assistant and generate preliminary geologic maps. The accuracy results of the algorithms were tested by employing a test/train split of the labeled dataset. The highest accuracy reported was for the SVM algorithm with an accuracy reported of 76% in the classification of 2 visually distinct rock units. We have also shown that by introducing Kuwahara and Median filters, normally used in computer vision applications, we can reduce effects of vegetation and increase the prediction accuracy. vi

Environmental Research, 2021

Journal of Applied Meteorology and Climatology, 2020

This work presents an analysis of the observed trends in extreme precipitation events in the Para... more This work presents an analysis of the observed trends in extreme precipitation events in the Paraná River basin (PRB) from 1977 to 2016 (40 yr) based on daily records from 853 stations. The Mann–Kendall test and inverse-distance-weighted interpolation were applied to annual and seasonal precipitation and also for four extreme precipitation indices. The results show that the negative trends (significance at 95% confidence level) in annual and seasonal series are mainly located in the northern and northeastern parts of the basin. In contrast, except in the autumn season, positive trends were concentrated in the southern and southeastern regions of the basin, most notably for annual and summer precipitation. The spatial distributions of the indices of annual maximum 5-day precipitation and number of rainstorms indicate that significant positive trends are mostly located in the south-southeast part of the basin and that significant negative trends are mostly located in the north-northea...

Atmospheric Research, 2019

This is a PDF file of an article that has undergone enhancements after acceptance, such as the ad... more This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

International Journal of Applied Earth Observation and Geoinformation, 2019

This study presents a new land cover map for the Upper Paraná River Basin (UPRB-2015), with high ... more This study presents a new land cover map for the Upper Paraná River Basin (UPRB-2015), with high spatial resolution (30 m), and a high number of calibration and validation sites. To the new map, 50 Landsat-8 scenes were classified with the Support Vector Machine (SVM) algorithm and their level of agreement was assessed using overall accuracy and Kappa coefficient. The generated map was compared by area and by pixel with six global products (MODIS, GlobCover, Globeland30, FROM-GLC, CCI-LC and, GLCNMO). The results of the new classification showed an overall accuracy ranging from 67% to 100%, depending on the sub-basin (80.0% for the entire UPRB). Kappa coefficient was observed ranging from 0.50 to 1.00 (average of 0.73 in the whole basin). Anthropic areas cover more than 70% of the entire UPRB in the new product, with Croplands covering 46.0%. The new mapped areas of croplands are consistent with local socioeconomic statistics but don't agree with global products, especially FROM-GLC (14,9%), MODIS (33.8%), GlobCover (71.2%), and CCI (67.8%). In addition, all global products show generalized spatial disagreement, with some sub-basins showing areas of cropland varying by an order of magnitude, compared to UPRB-2015. In the case of Grassland, covering 25.6% of the UPRB, it was observed a strong underestimation by all global products. Even for the Globeland30 and MODIS, which show some significant fraction of pasture areas, there is a high level of disagreement in the spatial

RESUMO -O desempenho do sistema de previsão Advanced Regional Prediction System (ARPS) com resolu... more RESUMO -O desempenho do sistema de previsão Advanced Regional Prediction System (ARPS) com resolução de 2 km numa área de 320 km x 300 km centrada na Região Metropolitana de São Paulo foi verificado no período de fevereiro e março de 2006. Utilizou-se nesta verificação a precipitação acumulada horária estimada com o radar meteorológico de São Paulo. Uma breve descrição do ARPS é apresentada bem como os indicadores de desempenho do modelo. Os resultados indicam que o modelo tem desempenho crescente da previsão de convecção isolada para a previsão de frentes frias, de 18% para 47%. Ainda, o desempenho do modelo decresce das mais baixas para as mais altas acumulações de precipitação. Por exemplo, o desempenho para os limites de acumulação de 0,0 mm e 4,0 mm são 30% e 10%, respectivamente. Estes resultados, apesar de baixos são compatíveis com os obtidos na literatura e, indicam que as previsões com o sistema ARPS são viáveis, operacionalmente. ABSTRACT -The performance of the Advanced ...

Aerosol and Air Quality Research, 2018

The long-range transport of aerosols is a global issue since it may significantly affect the air ... more The long-range transport of aerosols is a global issue since it may significantly affect the air quality of regions without high concentrations of fine particulate matter (PM 2.5). Two significant occurrences of long-range transport of aerosols over the state of Parana in Brazil, which occurred during the periods Aug. 16-18 and Sep. 10-14 of 2016, were studied in order to characterize the atmospheric synoptic conditions of these events and to estimate their contribution to the air quality conditions in the northern region of the state. The South American Low Level Jet (SALLJ) was the key meteorological component used to define the origin of the air mass trajectories over the region. In the first event, the SALLJ lost its configuration, bringing air masses from the western part of São Paulo (state), while in the second event, the SALLJ formed over southern Brazil and brought air masses from the northern and central parts of the nation. The significant number of fires from biomass burning in central Brazil associated with synoptic conditions contributed to the increase in PM 2.5 concentrations by approximately 70-87% in the region. The transport of aerosols was a determining factor in PM 2.5 exceeding the air quality standard in the region. Therefore, to minimize this problem, it is imperative to control biomass burning in Brazil.