Alejandro Rodríguez-Gómez

Abstract: . Systematic measurements of dust concentration profiles at a continental scale were recently made possible by the development of synergistic retrieval algorithms using combined lidar and sun photometer data and the establishment of robust remote-sensing networks in the framework of Aerosols, Clouds, and Trace gases Research InfraStructure Network (ACTRIS)/European Aerosol Research Lidar Network (EARLINET). We present a methodology for using these capabilities as a tool for examining the performance of dust transport models. The methodology includes considerations for the selection of a suitable data set and appropriate metrics for the exploration of the results. The approach is demonstrated for four regional dust transport models (BSC-DREAM8b v2, NMMB/BSC-DUST, DREAMABOL, DREAM8-NMME-MACC) using dust observations performed at 10 ACTRIS/EARLINET stations. The observations, which include coincident multi-wavelength lidar and sun photometer measurements, were processed with the Lidar-Radiometer Inversion Code (LIRIC) to retrieve aerosol concentration profiles. The methodology proposed here shows advantages when compared to traditional evaluation techniques that utilize separately the available measurements such as separating the contribution of dust from other aerosol types on the lidar profiles and avoiding model assumptions related to the conversion of concentration fields to aerosol extinction values. When compared to LIRIC retrievals, the simulated dust vertical structures were found to be in good agreement for all models with correlation values between 0.5 and 0.7 in the 1–6 km range, where most dust is typically observed. The absolute dust concentration was typically underestimated with mean bias values of -40 to -20 μg m−3 at 2 km, the altitude of maximum mean concentration. The reported differences among the models found in this comparison indicate the benefit of the systematic use of the proposed approach in future dust model evaluation studies.

TL;DR: In this article, a review of the state-of-the-art lidar systems used to obtain aerosol information is presented, with a focus on structural (aerosol layers profiling), optical (backscatter and extinction coefficients) and microphysical (size, shape and type) properties.

TL;DR: In this article, an unprecedented extreme Saharan dust event was registered in winter time from 20 to 23 February 2017 over the Iberian Peninsula (IP) through passive and active remote sensing techniques.

TL;DR: The presented algorithm has proven to be highly versatile as it adapts to changes in the size of the training dataset and the number of aerosol classes and classifying parameters and is extremely suitable for the implementation within the single calculus chain (SCC), the EARLINET centralized processing suite.

TL;DR: An analytical model, based on the duality between beam wander and angle-of-arrival fluctuations, is proposed for the temporal statistics, and the expression of the probability density function of the log-amplitude fluctuations is obtained.