EARLINET Single Calculus Chain - technical - Part 1: Pre-processing of raw lidar data

In this paper we describe an automatic tool for the pre-processing of aerosol lidar data called ELPP (EAR-LINET Lidar Pre-Processor). It is one of two calculus modules of the EARLINET Single Calculus Chain (SCC), the automatic tool for the analysis of EARLINET data. ELPP is an open source module that executes instrumental corrections and data handling of the raw lidar signals, making the lidar data ready to be processed by the optical retrieval algorithms. According to the specific lidar configuration, ELPP automatically performs dead-time correction, atmospheric and electronic background subtraction, gluing of lidar signals, and trigger-delay correction. Moreover, the signal-to-noise ratio of the pre-processed signals can be improved by means of configurable time integration of the raw signals and/or spatial smoothing. ELPP delivers the statistical uncertainties of the final products by means of error propagation or Monte Carlo simulations. During the development of ELPP, particular attention has been payed to make the tool flexible enough to handle all lidar configurations currently used within the EARLINET community. Moreover, it has been designed in a modular way to allow an easy extension to lidar configurations not yet implemented. The primary goal of ELPP is to enable the application of quality-assured procedures in the lidar data analysis starting from the raw lidar data. This provides the added value of full traceability of each delivered lidar product. Several tests have been performed to check the proper functioning of ELPP. The whole SCC has been tested with the same synthetic data sets, which were used for the EARLINET algorithm inter-comparison exercise. ELPP has been successfully employed for the automatic near-real-time preprocessing of the raw lidar data measured during several EARLINET inter-comparison campaigns as well as during intense field campaigns

EARLINET Single Calculus Chain – technical – Part 1: Pre-processing of raw lidar data

In this paper we describe an automatic tool for the pre-processing of aerosol lidar data called ELPP (EARLINET Lidar Pre-Processor). It is one of two calculus modules of the EARLINET Single Calculus Chain (SCC), the automatic tool for the analysis of EARLINET data. ELPP is an open source module that executes instrumental corrections and data handling of the raw lidar signals, making the lidar data ready to be processed by the optical retrieval algorithms. According to the specific lidar configuration, ELPP automatically performs dead-time correction, atmospheric and electronic background subtraction, gluing of lidar signals, and trigger-delay correction. Moreover, the signal-to-noise ratio of the pre-processed signals can be improved by means of configurable time integration of the raw signals and/or spatial smoothing. ELPP delivers the statistical uncertainties of the final products by means of error propagation or Monte Carlo simulations. During the development of ELPP, particular attention has been payed to make the tool flexible enough to handle all lidar configurations currently used within the EARLINET community. Moreover, it has been designed in a modular way to allow an easy extension to lidar configurations not yet implemented. The primary goal of ELPP is to enable the application of quality-assured procedures in the lidar data analysis starting from the raw lidar data. This provides the added value of full traceability of each delivered lidar product. Several tests have been performed to check the proper functioning of ELPP. The whole SCC has been tested with the same synthetic data sets, which were used for the EARLINET algorithm inter-comparison exercise. ELPP has been successfully employed for the automatic near-real-time pre-processing of the raw lidar data measured during several EARLINET inter-comparison campaigns as well as during intense field campaigns

CEOS Intercalibration of Ground-Based Spectrometers and Lidars: First Progress Report

This document reports on activities and achievements obtained during the first part of the ESA CEOS Intercalibration project. The period covered extends from March 2009 until December 2009.This document is the first progress report of the CEOS Intercalibration of Ground-Based Spectrometers and Lidars project. It summarizes activities performed and results achieved within each team

Lidar Calibration Centre

This paper presents the newly established Lidar Calibration Centre, a distributed infrastructure in Europe, whose goal is to offer services for complete characterization and calibration of lidars and ceilometers. Mobile reference lidars, laboratories for testing and characterization of optics and electronics, facilities for inspection and debugging of instruments, as well as for training in good practices are open to users from the scientific community, operational services and private sector. The Lidar Calibration Centre offers support for trans-national access through the EC HORIZON2020 project ACTRIS-2

Atmospheric boundary layer height estimation from aerosol lidar: A new approach based on morphological image processing techniques

The atmospheric boundary layer (ABL) represents the lowermost part of the atmosphere directly in contact with the Earth's surface. The estimation of its depth is of crucial importance in meteorology and for anthropogenic pollution studies. ABL height (ABLH) measurements are usually far from being adequate, both spatially and temporally. Thus, different remote sensing sources can be of great help in growing both the spatial and temporal ABLH measurement capabilities. To this aim, aerosol backscatter profiles are widely used as a proxy to retrieve the ABLH. Hence, the scientific community is making remarkable efforts in developing automatic ABLH retrieval algorithms applied to lidar observations. In this paper, we propose a ABLH estimation algorithm based on image processing techniques applied to the composite image of the total attenuated backscatter coefficient. A pre-processing step is applied to the composite total backscatter image based on morphological filters to properly set-up and adjust the image to detect edges. As final step, the detected edges are post-processed through both mathematical morphology and an object-based analysis. The performance of the proposed approach is assessed on real data acquired by two different lidar systems, deployed in Potenza (Italy) and Évora (Portugal), belonging to the European Aerosol Research Lidar Network (EARLINET). The proposed approach has shown higher performance than the benchmark consisting of some state-of-The-Art ABLH estimation methods. © 2021 Copernicus GmbH. All rights reserved.ACTRIS (https://www.actris.eu/, last access: 15 March 2021) has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement nos. 654109 (ACTRIS-2), 759530 (ACTRIS-PPP), 871115 (ACTRIS-IMP) and 824068 (ENVRI-FAIR), and previously from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 262254. The Portuguese lidar station is also supported by national funds through FCT – Foundation for Science and Technology, I. P., within the scope of projects UIDB/04683/2020 and UIDP/04683/2020, and also through project TOMAQAPA (PTDC/CTAMET/29678/2017). Moreover, the authors gratefully acknowledge CloudNET for providing ECMWF and GDAS atmospheric forecasts for all the measurement cases included in this study

EARLINET Single Calculus Chain – technical – Part 1: Pre-processing of raw lidar data

In this paper we describe an automatic tool for the pre-processing of aerosol lidar data called ELPP (EAR-LINET Lidar Pre-Processor). It is one of two calculus modules of the EARLINET Single Calculus Chain (SCC), the automatic tool for the analysis of EARLINET data. ELPP is an open source module that executes instrumental corrections and data handling of the raw lidar signals, making the lidar data ready to be processed by the optical retrieval algorithms. According to the specific lidar configuration, ELPP automatically performs dead-time correction, atmospheric and electronic background subtraction, gluing of lidar signals, and trigger-delay correction. Moreover, the signal-to-noise ratio of the pre-processed signals can be improved by means of configurable time integration of the raw signals and/or spatial smoothing. ELPP delivers the statistical uncertainties of the final products by means of error propagation or Monte Carlo simulations. During the development of ELPP, particular attention has been payed to make the tool flexible enough to handle all lidar configurations currently used within the EARLINET community. Moreover, it has been designed in a modular way to allow an easy extension to lidar configurations not yet implemented. The primary goal of ELPP is to enable the application of quality-assured procedures in the lidar data analysis starting from the raw lidar data. This provides the added value of full traceability of each delivered lidar product. Several tests have been performed to check the proper functioning of ELPP. The whole SCC has been tested with the same synthetic data sets, which were used for the EARLINET algorithm inter-comparison exercise. ELPP has been successfully employed for the automatic near-real-time preprocessing of the raw lidar data measured during several EARLINET inter-comparison campaigns as well as during intense field campaigns

CEOS Intercalibration of Ground-Based Spectrometers and Lidars: Final Report

The ESA CEOS Intercalibration project concentrated on important calibration activities addressing three key components of the ground-based network ground-truthing capacity in Europe, namely the Dobson/Brewer network of ozone spectrophotometers, the aerosol lidar EARLINET network and the UV-Vis MAXDOAS technique for air quality remote-sensing. This document summarizes activities and achievements during the third part of the ESA CEOS Intercalibration project. The period covered by this report extends from February 2012 until October 2012

CEOS Intercalibration of Ground-Based Spectrometers and Lidars: Second Progress Report

This document summarizes activities and achievements during the second part of the ESA CEOS Intercalibration project. The period covered by this report extends from February 2011 until January 2012

First validation of GOME-2/MetOp Absorbing Aerosol Height using EARLINET lidar observations

he aim of this study is to investigate the potential of the Global Ozone Monitoring Experiment-2 (GOME-2) instruments, aboard the Meteorological Operational (MetOp)-A, MetOp-B and MetOp-C satellite programme platforms, to deliver accurate geometrical features of lofted aerosol layers. For this purpose, we use archived ground-based lidar data from stations available from the European Aerosol Research Lidar Network (EARLINET) database. The data are post-processed using the wavelet covariance transform (WCT) method in order to extract geometrical features such as the planetary boundary layer (PBL) height and the cloud boundaries. To obtain a significant number of collocated and coincident GOME-2 - EARLINET cases for the period between January 2007 and September 2019, 13 lidar stations, distributed over different European latitudes, contributed to this validation. For the 172 carefully screened collocations, the mean bias was found to be -0.18 ± 1.68 km, with a near-Gaussian distribution. On a station basis, and with a couple of exceptions where very few collocations were found, their mean biases fall in the ± 1 km range with an associated standard deviation between 0.5 and 1.5 km. Considering the differences, mainly due to the temporal collocation and the difference, between the satellite pixel size and the point view of the ground-based observations, these results can be quite promising and demonstrate that stable and extended aerosol layers as captured by the satellite sensors are verified by the ground-based data. We further present an in-depth analysis of a strong and long-lasting Saharan dust intrusion over the Iberian Peninsula. We show that, for this well-developed and spatially well-spread aerosol layer, most GOME-2 retrievals fall within 1 km of the exact temporally collocated lidar observation for the entire range of 0 to 150 km radii. This finding further testifies for the capabilities of the MetOp-borne instruments to sense the atmospheric aerosol layer heights.Horizon 2020 Framework Programme 654109, 87111

One year of tropospheri clidar measurements of aerosol extinction and backscatter

The aerosol lidar system operational at IMAA-CNR in Tito Scalo (PZ) (Southern Italy, 40°36'N, 15°44'E, 820 m above sea level) is part of the EARLINET project. Systematic lidar measurements of aerosol backscatter and extinction in the troposphere have been performed since May 2000. Aerosol backscatter measurements were performed at both 355 nm and 532 nm, while aerosol extinction coeffi cient were retrieved from simultaneous N2 Raman backscatter signals at 386.6 nm. The observations were performed on a regular schedule of two night time measurements per week (around sunset) and one daytime measurement per week (around 13:00 UTC). Furthermore, special observations concerning Saharan dust outbreaks have been carried out. Starting in May 2000 the lidar measurements performed in Tito Scalo have been collected and analysed. Preliminary results regarding the fi rst year of measurements are reported. In particular, the evolution of the aerosol integrated backscatter and extinction as well as of the mean value of the lidar ratio in the whole aerosol layer is reported. Results show clear evidence of seasonal variation of the observed parameters, with higher values and greater variability during summertime