FABIO JULIANO DA SILVA LOPES

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  • Artigo IPEN-doc 29870
    Collaborative development of the Lidar Processing Pipeline (LPP) for retrievals of atmospheric aerosols and clouds
    2023 - PALLOTTA, JUAN V.; CARVALHO, SILVANIA A. de; LOPES, FABIO J. da S.; CACHEFFO, ALEXANDRE; LANDULFO, EDUARDO; BARBOSA, HENRIQUE M.J.
    Atmospheric lidars can simultaneously measure clouds and aerosols with high temporal and spatial resolution and hence help understand cloud–aerosol interactions, which are the source of major uncertainties in future climate projections. However, atmospheric lidars are typically custom-built, with significant differences between them. In this sense, lidar networks play a crucial role as they coordinate the efforts of different groups, provide guidelines for quality-assured routine measurements and opportunities for side-by-side instrument comparisons, and enforce algorithm validation, all aiming to homogenize the physical retrievals from heterogeneous instruments in a network. Here we provide a high-level overview of the Lidar Processing Pipeline (LPP), an ongoing, collaborative, and open-source coordinated effort in Latin America. The LPP is a collection of tools with the ultimate goal of handling all the steps of a typical analysis of lidar measurements. The modular and configurable framework is generic enough to be applicable to any lidar instrument. The first publicly released version of the LPP produces data files at levels 0 (raw and metadata), 1 (averaging and layer mask), and 2 (aerosol optical properties). We assess the performance of the LPP through quantitative and qualitative analyses of simulated and measured elastic lidar signals. For noiseless synthetic 532 nm elastic signals with a constant lidar ratio (LR), the root mean square error (RMSE) in aerosol extinction within the boundary layer is about 0.1 %. In contrast, retrievals of aerosol backscatter from noisy elastic signals with a variable LR have an RMSE of 11 %, mostly due to assuming a constant LR in the inversion. The application of the LPP for measurements in São Paulo, further constrained by co-located AERONET data, retrieved a lidar ratio of 69.9 ± 5.2 sr at 532 nm, in agreement with reported values for urban aerosols. Over the Amazon, analysis of a 6 km thick multi-layer cirrus found a cloud optical depth of about 0.46, also in agreement with previous studies. From this exercise, we identify the need for new features and discuss a roadmap to guide future development, accommodating the needs of our community.
  • Artigo IPEN-doc 28866
    First lidar campaign in the industrial sites of Volta Redonda-RJ and Lorena-SP, Brazil
    2022 - LOPES, FABIO J. da S.; CARVALHO, SILVANIA A.; CATALANI, FERNANDO; SILVA, JONATAN J. da; ALMEIDA, ROGERIO M. de; RIBEIRO, FABIO de J.; FELLOWS, CARLOS E.; LANDULFO, EDUARDO; MENEGATTI, CARLOS R.; PEIXOTO, CARLOS J.T.
    We report on the first aerosol profiling campaign in the Paraíba valley, a hub connecting the region between the two largest Brazilian metropolitan areas, São Paulo and Rio de Janeiro. São Paulo Sanitation Technology Company (CETESB) air quality and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data show homogeneous behavior of the atmosphere throughout the region. A more detailed description of the particulate material in the local atmosphere, including its temporal dependence, can be obtained by using ground-based lidars. Measurements were carried out with a backscatter lidar system in two industrial cities, Volta Redonda and Lorena. The aerosol backscatter profiles present several peaks at different altitudes, indicating the presence of aerosol in several atmospheric layers. In addition, The Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) air-mass back-trajectories indicate a possible detection of long-range aerosol transported from biomass burning areas of South America. The present study emphasizes the importance of investigating and monitoring the emission of particulate matter at this important hub connection between two dense populated regions of Brazil.