Special Issue "Mediterranean Atmospheric Composition, Aerosols, and Clouds under a Changing Climate"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmosphere Remote Sensing".

Deadline for manuscript submissions: closed (31 July 2021).

Special Issue Editors

Dr. Nikos Hatzianastassiou
E-Mail Website
Guest Editor
Laboratory of Meteorology, Department of Physics, University of Ioannina, 45110 Ioannina, Greece
Interests: aerosol physical properties; aerosol-cloud interactions; aerosol-radiation interactions; radiation and climate; shortwave and longwave radiation transfer and budgets
Dr. Alcide Giorgio di Sarra
E-Mail Website
Guest Editor
ENEA Centro Ricerche Casaccia, 00123 Santa Maria di Galeria RM, Italy
Interests: atmospheric science; satellite monitoring; climate observation; remote sensing
Special Issues and Collections in MDPI journals
Dr. Christos Matsoukas
E-Mail Website
Guest Editor
University of the Aegean
Interests: radiation transfer modeling in the atmosphere; heat and energy budgets; long-term memory in climate quantities
Dr. Giandomenico Pace
E-Mail Website
Guest Editor
Laboratory for Observations and Analyses of Earth and Climate, ENEA
Interests: impact of aerosol and clouds on energy balance; characterization of radiometers and spectrometers for atmospheric radiation measurements

Special Issue Information

Dear Colleagues,

The greater Mediterranean basin is a challenging study area encompassing a variety of contrasting natural environments and climates. Natural and anthropogenic sources of particulates and gases are non-uniformly distributed across the basin in which diversified cloud and precipitation regimes exist from south to north and west to east. Medium- and long-range transport of particulate and gaseous atmospheric constituents occurs not only within this area but also within three different continents, namely, Europe, Africa, and Asia. Moreover, as documented in the AR5 and AR4 IPCC reports, the Mediterranean is one of the hot-spot areas of the globe, being severely threatened by future climate changes, while indications of ongoing warming and drying conditions are increasingly evident. In this context, changing cloud and precipitation patterns, especially related to aerosol and other atmospheric quantities, are also of great interest and worth studying in the Mediterranean basin.

A better understanding of the complex atmospheric mechanisms contributing to Mediterranean climate change is necessary; special emphasis needs to be given to the identification of the role of aerosols, clouds, and gaseous air pollutants, which are crucial for various processes of the Earth–atmosphere system. In this context, the observation of spatio-temporal variability and changing patterns of aerosols, clouds, and air constituents over the Mediterranean and surrounding areas is very important and can be effectively achieved based on remote sensing techniques and tools. Assessments of these key agents with the attribution of their changes to anthropogenic and natural sources are of special importance and at the core of this Special Issue. Studies dealing with this topic and area, based on remotely sensed surface and satellite products, as well as every kind of similar analysis, are welcome to this Special Issue, to which authors are cordially invited to submit and publish their research findings.

Dr. Nikos Hatzianastassiou
Dr. Alcide Giorgio di Sarra
Dr. Christos Matsoukas
Dr. Giandomenico Pace
Guest Editors

Manuscript Submission Information

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Keywords

  • aerosols
  • clouds
  • air pollution
  • satellites
  • remote sensing
  • climate
  • climate change

Published Papers (4 papers)

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Research

Article
A Climatological Assessment of Intense Desert Dust Episodes over the Broader Mediterranean Basin Based on Satellite Data
Remote Sens. 2021, 13(15), 2895; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13152895 - 23 Jul 2021
Viewed by 548
Abstract
A satellite algorithm able to identify Dust Aerosols (DA) is applied for a climatological investigation of Dust Aerosol Episodes (DAEs) over the greater Mediterranean Basin (MB), one of the most climatologically sensitive regions of the globe. The algorithm first distinguishes DA among other [...] Read more.
A satellite algorithm able to identify Dust Aerosols (DA) is applied for a climatological investigation of Dust Aerosol Episodes (DAEs) over the greater Mediterranean Basin (MB), one of the most climatologically sensitive regions of the globe. The algorithm first distinguishes DA among other aerosol types (such as Sea Salt and Biomass Burning) by applying threshold values on key aerosol optical properties describing their loading, size and absorptivity, namely Aerosol Optical Depth (AOD), Aerosol Index (AI) and Ångström Exponent (α). The algorithm operates on a daily and 1° × 1° geographical cell basis over the 15-year period 2005–2019. Daily gridded spectral AOD data are taken from Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua Collection 6.1, and are used to calculate the α data, which are then introduced into the algorithm, while AI data are obtained by the Ozone Monitoring Instrument (OMI) -Aura- Near-UV aerosol product OMAERUV dataset. The algorithm determines the occurrence of Dust Aerosol Episode Days (DAEDs), whenever high loads of DA (higher than their climatological mean value plus two/four standard deviations for strong/extreme DAEDs) exist over extended areas (more than 30 pixels or 300,000 km2). The identified DAEDs are finally grouped into Dust Aerosol Episode Cases (DAECs), consisting of at least one DAED. According to the algorithm results, 166 (116 strong and 50 extreme) DAEDs occurred over the MB during the study period. DAEDs are observed mostly in spring (47%) and summer (38%), with strong DAEDs occurring primarily in spring and summer and extreme ones in spring. Decreasing, but not statistically significant, trends of the frequency, spatial extent and intensity of DAECs are revealed. Moreover, a total number of 98 DAECs was found, primarily in spring (46 DAECs) and secondarily in summer (36 DAECs). The seasonal distribution of the frequency of DAECs varies geographically, being highest in early spring over the eastern Mediterranean, in late spring over the central Mediterranean and in summer over the western MB. Full article
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Article
The Potential of GRASP/GARRLiC Retrievals for Dust Aerosol Model Evaluation: Case Study during the PreTECT Campaign
Remote Sens. 2021, 13(5), 873; https://0-doi-org.brum.beds.ac.uk/10.3390/rs13050873 - 26 Feb 2021
Cited by 1 | Viewed by 664
Abstract
We use the Generalized Retrieval of Aerosol Surface Properties algorithm (GRASP) to compare with dust concentration profiles derived from the NMME-DREAM model for a specific dust episode. The GRASP algorithm provides the possibility of deriving columnar and vertically-resolved aerosol properties from a combination [...] Read more.
We use the Generalized Retrieval of Aerosol Surface Properties algorithm (GRASP) to compare with dust concentration profiles derived from the NMME-DREAM model for a specific dust episode. The GRASP algorithm provides the possibility of deriving columnar and vertically-resolved aerosol properties from a combination of lidar and sun-photometer observations. Herein, we apply GRASP for analysis of a Saharan dust outburst observed during the “PREparatory: does dust TriboElectrification affect our ClimaTe” campaign (PreTECT) that took place at the North coast of Crete, at the Finokalia ACTRIS station. GRASP provides column-averaged and vertically resolved microphysical and optical properties of the particles. The retrieved dust concentration profiles are compared with modeled concentration profiles derived from the NMME-DREAM dust model. To strengthen the results, we use dust concentration profiles from the POlarization-LIdar PHOtometer Networking method (POLIPHON). A strong underestimation of the maximum dust concentration is observed from the NMME-DREAM model. The reported differences between the retrievals and the model indicate a high potential of the GRASP algorithm for future studies of dust model evaluation. Full article
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Article
Consistency of the Single Calculus Chain Optical Products with Archived Measurements from an EARLINET Lidar Station
Remote Sens. 2020, 12(23), 3969; https://0-doi-org.brum.beds.ac.uk/10.3390/rs12233969 - 04 Dec 2020
Viewed by 502
Abstract
A long-term analysis and climatology of aerosol backscatter and extinction coefficients profiles using a five-year study period lidar dataset derived from a multiwavelenth Raman lidar at Thessaloniki station is presented. All measurements have been processed with the latest version of the Single Calculus [...] Read more.
A long-term analysis and climatology of aerosol backscatter and extinction coefficients profiles using a five-year study period lidar dataset derived from a multiwavelenth Raman lidar at Thessaloniki station is presented. All measurements have been processed with the latest version of the Single Calculus Chain (SCCv5.1.6) fully automated algorithm, which has been developed to provide a common lidar processing tool, within EARLINET (European Aerosol Research Lidar NETwork) stations. The optical products delivered by the SCC tool have already been compared with the optical products derived from the operational algorithm of Thessaloniki (THessaloniki Aerosol LIdar Algorithm-THALIA) and discussed in terms of inhomogeneities. In this contribution, we analyze these products for climatological purposes, in order to investigate the aerosol columnar properties over Thessaloniki lidar station, drawing conclusions about the issues to be considered when switching from the current operational algorithm to the SCCv5. The SCCv5 algorithm is evaluated for the AOD both for 355 and 532 nm. The agreement with THALIA algorithm seems promising with correlations of 0.89 and 0.84, respectively, and absolute deviations within the range of the EARLINET quality requirements. Time series of the AOD at 355 nm denote a decrease of 0.017 per year in the free troposphere, a trend that is also shown in the AOD values derived from the operational algorithm (0.014). A decrease of 0.01 per year in the lower troposphere is also noted from the SCC, whereas the corresponding AOD values derived from the operational algorithm denote a decrease of 0.017. Full article
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Article
Quantitative Aerosol Optical Depth Detection during Dust Outbreaks from Meteosat Imagery Using an Artificial Neural Network Model
Remote Sens. 2019, 11(9), 1022; https://0-doi-org.brum.beds.ac.uk/10.3390/rs11091022 - 30 Apr 2019
Cited by 5 | Viewed by 1329
Abstract
This study presents the development of an artificial neural network (ANN) model to quantitatively estimate the atmospheric aerosol load (in terms of aerosol optical depth, AOD), with an emphasis on dust, over the Mediterranean basin using images from Meteosat satellites as initial information. [...] Read more.
This study presents the development of an artificial neural network (ANN) model to quantitatively estimate the atmospheric aerosol load (in terms of aerosol optical depth, AOD), with an emphasis on dust, over the Mediterranean basin using images from Meteosat satellites as initial information. More specifically, a back-propagation ANN model scheme was developed to estimate visible (at 550 nm) aerosol optical depth (AOD550 nm) values at equal temporal (15 min) and spatial (4 km) resolutions with Meteosat imagery. Accuracy of the ANN model was thoroughly tested by comparing model estimations with ground-based AOD550 nm measurements from 14 AERONET (Aerosol Robotic NETwork) stations over the Mediterranean for 34 selected days in which significant dust loads were recorded over the Mediterranean basin. Using a testbed of 3076 pairs of modeled and measured AOD550 nm values, a Pearson correlation coefficient (rP) equal to 0.91 and a mean absolute error (MAE) of 0.031 were found, proving the satisfactory accuracy of the developed model for estimating AOD550 nm values. Full article
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