Within the framework of the present work, an aerosol typing methodology applicable to both ground-based and spaceborne lidar systems has been developed. The novel aerosol typing scheme was developed based on the optimal estimation method (OEM) and allows the identification of up to four different aerosol components present in an aerosol mixture as well as the quantification of their contribution to the aerosol mixture in terms of relative volume. The four aerosol components considered in this typing scheme represent the most commonly observed aerosol particles in nature and are assumed to be physically separated from each other and, therefore, can create external mixtures. Two components represent fine-mode particles, absorbing (FSA) and less absorbing (FSNA), and the remaining two aerosol components represent coarse-mode particles, spherical (CS) and non-spherical
(CNS). These components can adequately represent the most frequently observed aerosol types in the atmosphere: combustion- and pollution-related aerosol, sea salt and desert dust, respectively.
The lidar-derived optical parameters used in this typing scheme are the lidar ratio and the particle linear depolarization ratio at two distinctive wavelengths (355 and 532 nm), the backscatter-related color ratio (for the wavelength pair of 532/1064 nm) and the extinction-related Ångström exponent (for the wavelength pair of 355/532 nm). These intensive optical properties can be combined in different ways making the methodology flexible, allowing thus its application to lidar systems with different configurations (e.g., single wavelength or multiwavelength).
The functionality of the typing scheme was demonstrated by its application to case
studies of known aerosol conditions as well as to cases of non-characterized aerosol load. The algorithm was also applied to a long-term dataset to provide a seasonal characterization of the aerosol situation over Haifa, Israel. It was shown that the OEM is an effective methodology that can be also applied for aerosol typing purposes, and that it can be used to support the ground-based validation efforts of EarthCARE's products and algorithms.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:81216 |
| Date | 10 October 2022 |
| Creators | Floutsi, Athina Avgousta |
| Contributors | Universität Leipzig |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/acceptedVersion, doc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
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