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The potential of a synergestic lidar and sunphotometer retrieval for the characterization of a dust event over Finokalia and for aerosol model evaluation

Authors :
Dimitra Konsta
Alexandra Tsekeri
Stavros Solomos
Anton Lopatin
Philippe Goloub
Oleg Dubovik
Vassilis Amiridis
Panagiotis Nastos
Publication Year :
2020
Publisher :
Copernicus GmbH, 2020.

Abstract

The ability of three-dimensional dust models to accurately represent the dust life cycle is crucial for describing dust effects on radiation and clouds and for reducing the uncertainties on these processes. To improve the reliabilty of dust models, it is therefore imperative to carry out thorough evaluations of the dust properties. Dust optical and microphysical properties are accurately accessed through groundbased observations: multiwavelength lidars and sunphotometers. In this study we use the Generalized Retrieval of Atmospheric and Surface Properties (GRASP) data algorithm that combines the lidar and sunphotometer data to retrieve dust properties. GRASP is applied on a Saharan dust episode over Finokalia, Crete in Greece, on 14 May 2017. More precisely the measurements from PollyXT lidar participating in the European Aerosol Research Network (EARLINET) and the CIMEL sunphotometer participating in Aerosol Robotic Network (AERONET) are synergetically combined using the GRASP algorithm. The dust event is fully characterised through the retrieval of dust optical and microphysical properties. The retrieved properties are found to be in good agreement with the initial measurements from the AERONET sunphotometer and the lidar. Then the aforementioned tools are used to evaluate the performance of the regional dust model NMME-DREAM that has been developed to simulate and predict the atmospheric cycle of mineral dust aerosols. It is shown that the model has problems in simulating the high dust concentration values at low levels, probably due to the low spatial resolution of the model that causes difficulties in capturing the orography and the downdrafts winds.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........ae8f73ed225d6bb24dcf8f493e5da3e7
Full Text :
https://doi.org/10.5194/egusphere-egu2020-17111