Controle de qualidade de dados de um sistema LIDAR troposférico pela análise de parâmetros ópticos atmosféricos e instrumentais via protocolos das redes LALINET E EARLINET

Abstract

Observational data acquisition related to atmospheric aerosols is relevant for the progress in research to investigate their influence on climate change related processes. Due to their optical properties, they can interfere with the radiative balance and with cloud microphysics changing their dimensions and lifetimes. The active remote sensing system Light Detection and Ranging (LIDAR), called DUSTER, located in Natal, capital of Rio Grande do Norte, Brazil, sends laser pulses to the atmosphere and detects aerosols optical characteristics through their interaction with light. This research had two main foci: the first one is the LIDAR DUSTER quality assurance during the operational acquisition campaigns. The assurance was made by the following instrumental tests: Dark Measurment, Zero Bin, Bin-Shift, Telecover and Rayleigh Fit according to the Latin America LIDAR Network (LALINET) and the European Aerosol Research LIDAR Network (EARLINET) standards. By means of these tests it was possible to detect noises, recorder delays and check de alignment in near and far range. A set of algorithms called DUSTER Quality Assurance (DQA), with modules which read the instrumental quality test data, pre-processed data, generate graphics and write the results in ASCII format were developed. The results point that the errors relative to the alignment testes, Telecover and Rayleigh Fit, are less than 0.1 in most of the channels. The second focus was to compare tropospheric aerosol backscatter profiles by the Klett-Fernald-Sasano inversion method in two different tools: The Single Calculus Chain and the LALINET Inversion Algorithm. Two days of data acquisition with 1064 nm wavelength were selected to acquire the profiles. The computation happened by means of the relative error among the profiles. The relative error profiles varied among 0 and 10% on the two days. In the context of this work, a cloud filter was developed, the DUSTER Cloud Free filter, which removes cloud contaminated files automatically.