Lidar Observations in South America. Part II - Troposphere

Landulfo, Eduardo; Cacheffo, Alexandre; Yoshida, Alexandre Calzavara; Gomes, Antonio Arleques; Lopes, Fernando Silva; Moreira, Gregori de Arruda; Silva, Jonatan João da; Andrioli, V. F.; Pimenta, A. A.; Wang, Chi; Xu, Jing-yu; Martins, Minella Alves; Batista, P. P.; Barbosa, Henrique de Melo Jorge; Gouveia, D. A.; González, Boris Barja; Zamorano, Félix; Quel, E. J.; Pereira, Clodomyra; Wolfram, Elián; Casasola, Facundo Ismael; Orte, Facundo; Salvador, Jacobo; Pallotta, J.; Otero, Lidia Ana; Prieto, María; Ristori, P.; Brusca, S.; Estupiñan, John Henry Reina; Barrera, Estiven S.; Marrero, Juan Carlos Antuña; Forno, Ricardo; Andrade, Marcos; Hoelzemann, Judith J.; Guedes, Anderson Guimarães; Sousa, Cristina Tobler de; Oliveira, Daniel Camilo Fortunato dos Santos; Duarte, Ediclê de Souza Fernandes; Silva, Marcos Paulo Araújo da; Santos, Renata Sammara da Silva

doi:10.5772/intechopen.95451

Remote Sensing 2021

DOI: 10.5772/intechopen.95451

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Lidar Observations in South America. Part II - Troposphere

Eduardo Landulfo¹,

Alexandre Cacheffo²,

Alexandre Calzavara Yoshida³

et al.

Abstract: In Part II of this chapter, we intend to show the significant advances and results concerning aerosols’ tropospheric monitoring in South America. The tropospheric lidar monitoring is also supported by the Latin American Lidar Network (LALINET). It is concerned about aerosols originating from urban pollution, biomass burning, desert dust, sea spray, and other primary sources. Cloud studies and their impact on radiative transfer using tropospheric lidar measurements are also presented.

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Collaborative development of the Lidar Processing Pipeline (LPP) for retrievals of atmospheric aerosols and clouds

Pallotta,

de Carvalho,

Lopes

et al. 2023

Geosci. Instrum. Method. Data Syst.

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Abstract. 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.

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Collaborative development of the Lidar Processing Pipeline (LPP) for retrievals of atmospheric aerosols and clouds

Pallotta,

de Carvalho,

Lopes

et al. 2023

Geosci. Instrum. Method. Data Syst.

View full text Add to dashboard Cite

show abstract

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Lidar Observations in South America. Part II - Troposphere

Cited by 1 publication

References 71 publications

Collaborative development of the Lidar Processing Pipeline (LPP) for retrievals of atmospheric aerosols and clouds

Collaborative development of the Lidar Processing Pipeline (LPP) for retrievals of atmospheric aerosols and clouds

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