Suchergebnisse

Monitoring and describing the spatiotemporal variability in dust aerosols is crucial for understanding their multiple effects, related feedbacks, and impacts within the Earth system. This study describes the development of the ModIs Dust AeroSol (MIDAS) data set. MIDAS provides columnar daily dust optical depth (DOD) at 550 nm at a global scale and fine spatial resolution (0.1∘ × 0.1∘) over a 15-year period (2003–2017). This new data set combines quality filtered satellite aerosol optical depth (AOD) retrievals from MODIS-Aqua at swath level (Collection 6.1; Level 2), along with DOD-to-AOD ratios provided by the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) reanalysis to derive DOD on the MODIS native grid. The uncertainties of the MODIS AOD and MERRA-2 dust fraction, with respect to the AEronet RObotic NETwork (AERONET) and LIdar climatology of vertical Aerosol Structure for space-based lidar simulation (LIVAS), respectively, are taken into account for the estimation of the total DOD uncertainty. MERRA-2 dust fractions are in very good agreement with those of LIVAS across the dust belt in the tropical Atlantic Ocean and the Arabian Sea; the agreement degrades in North America and the Southern Hemisphere, where dust sources are smaller. MIDAS, MERRA-2, and LIVAS DODs strongly agree when it comes to annual and seasonal spatial patterns, with colocated global DOD averages of 0.033, 0.031, and 0.029, respectively; however, deviations in dust loading are evident and regionally dependent. Overall, MIDAS is well correlated with AERONET-derived DODs (R=0.89) and only shows a small positive bias (0.004 or 2.7 %). Among the major dust areas of the planet, the highest R values (>0.9) are found at sites of North Africa, the Middle East, and Asia. MIDAS expands, complements, and upgrades the existing observational capabilities of dust aerosols, and it is suitable for dust climatological studies, model evaluation, and data assimilation. ; Antonis Gkikas acknowledges support from the European Union's Horizon 2020 Research and Innovation programme under the Marie Skłodowska-Curie Actions (grant no. 749461; DUST-GLASS). We would like to thank the principal investigators maintaining the AERONET sites used in the present work. We thank the NASA CALIPSO team and NASA/LaRC/ASDC for making the CALIPSO products available, which have been used to build the LIVAS products, and ESA, who funded the LIVAS project (contract no. 4000104106/11/NL/FF/fk). We are grateful to the AERIS/ICARE Data and Services Center for providing access to the CALIPSO data and their computational center (http://www.icare.univ-lille1.fr/, last access: 8 August 2019). Vassilis Amiridis acknowledges support from the European Research Council (grant no. 725698; D-TECT). Eleni Marinou was funded by a DLR VO-Ryoung investigator group and the Deutscher Akademischer Austauschdienst (grant no. 57370121). Carlos Pérez García-Pando acknowledges support from the European Research Council (grant no. 773051; FRAGMENT), the AXA Research Fund, and the Spanish Ministry of Science, Innovation and Universities (grant nos. RYC-2015-18690 and CGL2017-88911-R). The authors acknowledge support from the DustClim project as part of ERA4CS, an ERA-NET project initiated by JPI Climate and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), and ANR (FR), with cofunding by the European Union (grant no. 690462). PRACE (Partnership for Advanced Computing in Europe) is acknowledged for awarding access to the MareNostrum Supercomputer in the Barcelona Supercomputing Center. We acknowledge support of this work by the PANhellenic infrastructure for Atmospheric Composition and climatE chAnge (PANACEA) project (grant no. MIS 5021516), which is implemented under the Horizon 2020 Action of "Reinforcement of the Research and Innovation Infrastructure", funded by the Operational Programme Competitiveness, Entrepreneurship, and Innovation (NSRF 2014–2020) and cofinanced by Greece and the European Union (under the European Regional Development Fund). NOA members acknowledge support from the Stavros Niarchos Foundation (SNF). The authors would like to thank Andrew Mark Sayer for his valuable and constructive comments. The authors would like also to thank Thanasis Georgiou for developing the ftp server on which the MIDAS data set is stored. We would like to thank the two anonymous reviewers, who were very helpful and who provided constructive comments that improved the paper. ; Peer Reviewed ; Postprint (published version)

Quantifying the dust optical depth (DOD) and its uncertainty across spatiotemporal scales is key to understanding and constraining the dust cycle and its interactions with the Earth System. This study quantifies the DOD along with its monthly and year-to-year variability between 2003 and 2017 at global and regional levels based on the MIDAS (ModIs Dust AeroSol) dataset, which combines Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua retrievals and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), reanalysis products. We also describe the annual and seasonal geographical distributions of DOD across the main dust source regions and transport pathways. MIDAS provides columnar mid-visible (550 nm) DOD at fine spatial resolution (), expanding the current observational capabilities for monitoring the highly variable spatiotemporal features of the dust burden. We obtain a global DOD of 0.032±0.003 – approximately a quarter (23.4 %±2.4 %) of the global aerosol optical depth (AOD) – with about 1 order of magnitude more DOD in the Northern Hemisphere (0.056±0.004; 31.8 %±2.7 %) than in the Southern Hemisphere (0.008±0.001; 8.2 %±1.1 %) and about 3.5 times more DOD over land (0.070±0.005) than over ocean (0.019±0.002). The Northern Hemisphere monthly DOD is highly correlated with the corresponding monthly AOD (R2=0.94) and contributes 20 % to 48 % of it, both indicating a dominant dust contribution. In contrast, the contribution of dust to the monthly AOD does not exceed 17 % in the Southern Hemisphere, although the uncertainty in this region is larger. Among the major dust sources of the planet, the maximum DODs (∼1.2) are recorded in the Bodélé Depression of the northern Lake Chad Basin, whereas moderate-to-high intensities are encountered in the Western Sahara (boreal summer), along the eastern parts of the Middle East (boreal summer) and in the Taklamakan Desert (spring). Over oceans, major long-range dust transport is observed primarily along the tropical Atlantic (intensified during boreal summer) and secondarily in the North Pacific (intensified during boreal spring). Our calculated global and regional averages and associated uncertainties are consistent with some but not all recent observation-based studies. Our work provides a simple yet flexible method to estimate consistent uncertainties across spatiotemporal scales, which will enhance the use of the MIDAS dataset in a variety of future studies. ; Antonis Gkikas acknowledges support by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the 2nd Call for H.F.R.I. Research Projects to support Post-Doctoral Researchers (ATLANTAS, project number 544), as well as support from the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie Actions (grant no. 749461; DUST-GLASS). Vassilis Amiridis acknowledges support from the European Research Council (grant no. 725698; D-TECT). Eleni Marinou was funded by a DLR VO-R young investigator group and the Deutscher Akademischer Austauschdienst (grant no. 57370121). Jasper F. Kok acknowledges support from National Science Foundation (NSF) grant 1552519. Carlos Pérez García-Pando acknowledges support from the European Research Council (grant no. 773051; FRAGMENT); the AXA Research Fund; and the Spanish Ministry of Science, Innovation and Universities (grant nos. RYC-2015-18690 and CGL2017-88911-R). The authors acknowledge support from the DustClim project as part of ERA4CS, an ERA-NET project initiated by JPI Climate and funded by FORMAS (SE), DLR (DE), BMWFW (AT), IFD (DK), MINECO (ES), and ANR (FR), with cofunding by the European Union (grant no. 690462). PRACE (Partnership for Advanced Computing in Europe) and RES (Red Española de Supercomputación) are acknowledged for awarding access to the MareNostrum Supercomputer in the Barcelona Supercomputing Center. We acknowledge support of this work by the PANhellenic infrastructure for Atmospheric Composition and climatE chAnge (PANACEA) project (grant no. MIS 5021516), which is implemented under the Horizon 2020 Action of Reinforcement of the Research and Innovation Infrastructure, funded by the Operational Programme Competitiveness, Entrepreneurship, and Innovation (NSRF 2014–2020) and cofinanced by Greece and the European Union (under the European Regional Development Fund). NOA members acknowledge support from the Stavros Niarchos Foundation (SNF). The authors acknowledge support by the COST Action InDust (grant no. CA16202), supported by COST (European Cooperation in Science and Technology). The authors would like to thank Andrew Mark Sayer for his valuable and constructive comments. The authors would like also to thank Thanasis Georgiou for developing the ftp server on which the MIDAS dataset is stored. ; Peer Reviewed ; Postprint (published version)

The main aim of the present study is to describe the vertical structure of the intense Mediterranean dust outbreaks, based on the use of satellite and surface-based retrievals/measurements. Strong and extreme desert dust (DD) episodes are identified at 1° × 1° spatial resolution, over the period March 2000–February 2013, through the implementation of an updated objective and dynamic algorithm. According to the algorithm, strong DD episodes occurring at a specific place correspond to cases in which the daily aerosol optical depth at 550 nm (AOD550 nm) exceeds or equals the long-term mean AOD550 nm (Mean) plus two standard deviations (SD), which is also smaller than Mean+4 × SD. Extreme DD episodes correspond to cases in which the daily AOD550 nm value equals or exceeds Mean+4 × SD. For the identification of DD episodes, additional optical properties (Ångström exponent, fine fraction, effective radius and aerosol index) derived by the MODIS-Terra & Aqua (also AOD retrievals), OMI-Aura and EP-TOMS databases are used as inputs. According to the algorithm using MODIS-Terra data, over the period March 2000–February 2013, strong DD episodes occur more frequently (up to 9.9 episodes year−1) over the western Mediterranean, while the corresponding frequencies for the extreme ones are smaller (up to 3.3 episodes year−1, central Mediterranean Sea). In contrast to their frequency, dust episodes are more intense (AODs up to 4.1), over the central and eastern Mediterranean Sea, off the northern African coasts. Slightly lower frequencies and higher intensities are found when the satellite algorithm operates based on MODIS-Aqua retrievals, for the period 2003–2012. The consistency of the algorithm is successfully tested through the application of an alternative methodology for the determination of DD episodes, which produced similar features of the episodes' frequency and intensity, with just slightly higher frequencies and lower intensities. The performance of the satellite algorithm is assessed against surface-based daily data from 109 sun-photometric (AERONET) and 22 PM10 stations. The agreement between AERONET and MODIS AOD is satisfactory (R = 0.505 − 0.750) and improves considerably when MODIS level 3 retrievals with higher sub-grid spatial representativeness and homogeneity are considered. Through the comparison against PM10 concentrations, it is found that the presence of dust is justified in all ground stations with success scores ranging from 68 to 97 %. However, poor agreement is evident between satellite and ground PM10 observations in the western parts of the Mediterranean, which is attributed to the desert dust outbreaks' vertical extension and the high altitude of dust presence. The CALIOP vertical profiles of pure and polluted dust observations and the associated total backscatter coefficient at 532 nm (β532 nm), indicate that dust particles are mainly detected between 0.5 and 6 km, though they can reach 8 km between the parallels 32 and 38° N in warm seasons. An increased number of CALIOP dust records at higher altitudes is observed with increased latitude, northwards to 40° N, revealing an ascending mode of the dust transport. However, the overall intensity of DD episodes is maximum (up to 0.006 km−1 sr−1) below 2 km and at the southern parts of the study region (30–34° N). Additionally, the average thickness of dust layers gradually decreases from 4 to 2 km, moving from south to north. In spring, dust layers of moderate-to-high β532 nm values ( ∼ 0.004 km−1 sr−1) are detected over the Mediterranean (35–42° N), extending from 2 to 4 km. Over the western Mediterranean, dust layers are observed between 2 and 6 km, while their base height is decreased down to 0.5 km for increasing longitudes underlying the role of topography and thermal convection. The vertical profiles of CALIOP β532 nm confirm the multilayered structure of the Mediterranean desert dust outbreaks on both annual and seasonal bases, with several dust layers of variable geometrical characteristics and intensities. A detailed analysis of the vertical structure of specific DD episodes using CALIOP profiles reveals that the consideration of the dust vertical structure is necessary when attempting comparisons between columnar MODIS AOD retrievals and ground PM10 concentrations. ; The MDRAF project has received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 622662. The Collection 051 MODIS-Terra and MODIS-Aqua data were obtained from NASA's level 1 and Atmosphere Archive and Distribution System (LAADS) website (ftp://ladsweb.nascom.nasa.gov/). The Earth Probe (TOMS) and OMI aerosol climatology is available from the Mirador ftp server (http://mirador.gsfc.nasa.gov/). The CALIPSO retrievals have been derived from NASA's Earth Observing System Data and Information System (http://reverb.echo.nasa.gov/). We would like to thank the principal investigators maintaining the AERONET sites used in the present work. We would like to acknowledge the EMEP Programme and the public European databases Airbase and ACTRIS, which supplied PM10 data used in this study. J. Pey benefits from a Ramón y Cajal Research Grant (RYC-2013-14159) from the Spanish Ministry of Economy and Competitiveness. S. Basart, O. Jorba, S. Gassó and J. M. Baldasano acknowledge the CICYT project CGL2013-46736 and Severo Ochoa (SEV-996 2011-00067) programme of the Spanish Government. The publication was supported by the European Union Seventh Framework Programme (FP-7-REGPOT-2012-2013-1), in the framework of the project BEYOND, under Grant Agreement No. 316210 (BEYOND – Building Capacity for a Centre of Excellence for EO-based monitoring of Natural Disasters. The Figs. 10, 11 and 12 have been produced with ccplot (http://ccplot.org/). This work contributes to the Chemistry-Aerosol Mediterranean Experiment (ChArMEx) coordinated effort for the long-term Mediterranean aerosol characterization using available remote sensing data sets. ; This paper was written under the framework of the International HYMEX project and the Spanish HOPE (CGL2014-52571-R) project. We would like to thank the "Agència Catalana de l'Aigua" and the "Real Academia de Ciencias y Artes de Barcelona" for the SAIH and Jardí data provided, respectively. This work was partially funded by the Project of Interest 'NextData' of the Italian Ministry for Education, University and Research. We thank the anonymous reviewers whose comments greatly helped us improve the presentation of the results. ; Peer Reviewed ; Postprint (published version)

The main aim of the present study is to describe the vertical structure of the intense Mediterranean dust outbreaks, based on the use of satellite and surface-based retrievals/measurements. Strong and extreme desert dust (DD) episodes are identified at 1° × 1° spatial resolution, over the period March 2000–February 2013, through the implementation of an updated objective and dynamic algorithm. According to the algorithm, strong DD episodes occurring at a specific place correspond to cases in which the daily aerosol optical depth at 550 nm (AOD550 nm) exceeds or equals the long-term mean AOD550 nm (Mean) plus two standard deviations (SD), which is also smaller than Mean+4 × SD. Extreme DD episodes correspond to cases in which the daily AOD550 nm value equals or exceeds Mean+4 × SD. For the identification of DD episodes, additional optical properties (Ångström exponent, fine fraction, effective radius and aerosol index) derived by the MODIS-Terra & Aqua (also AOD retrievals), OMI-Aura and EP-TOMS databases are used as inputs. According to the algorithm using MODIS-Terra data, over the period March 2000–February 2013, strong DD episodes occur more frequently (up to 9.9 episodes year−1) over the western Mediterranean, while the corresponding frequencies for the extreme ones are smaller (up to 3.3 episodes year−1, central Mediterranean Sea). In contrast to their frequency, dust episodes are more intense (AODs up to 4.1), over the central and eastern Mediterranean Sea, off the northern African coasts. Slightly lower frequencies and higher intensities are found when the satellite algorithm operates based on MODIS-Aqua retrievals, for the period 2003–2012. The consistency of the algorithm is successfully tested through the application of an alternative methodology for the determination of DD episodes, which produced similar features of the episodes' frequency and intensity, with just slightly higher frequencies and lower intensities. The performance of the satellite algorithm is assessed against surface-based daily data from 109 sun-photometric (AERONET) and 22 PM10 stations. The agreement between AERONET and MODIS AOD is satisfactory (R = 0.505 − 0.750) and improves considerably when MODIS level 3 retrievals with higher sub-grid spatial representativeness and homogeneity are considered. Through the comparison against PM10 concentrations, it is found that the presence of dust is justified in all ground stations with success scores ranging from 68 to 97 %. However, poor agreement is evident between satellite and ground PM10 observations in the western parts of the Mediterranean, which is attributed to the desert dust outbreaks' vertical extension and the high altitude of dust presence. The CALIOP vertical profiles of pure and polluted dust observations and the associated total backscatter coefficient at 532 nm (β532 nm), indicate that dust particles are mainly detected between 0.5 and 6 km, though they can reach 8 km between the parallels 32 and 38° N in warm seasons. An increased number of CALIOP dust records at higher altitudes is observed with increased latitude, northwards to 40° N, revealing an ascending mode of the dust transport. However, the overall intensity of DD episodes is maximum (up to 0.006 km−1 sr−1) below 2 km and at the southern parts of the study region (30–34° N). Additionally, the average thickness of dust layers gradually decreases from 4 to 2 km, moving from south to north. In spring, dust layers of moderate-to-high β532 nm values ( ∼ 0.004 km−1 sr−1) are detected over the Mediterranean (35–42° N), extending from 2 to 4 km. Over the western Mediterranean, dust layers are observed between 2 and 6 km, while their base height is decreased down to 0.5 km for increasing longitudes underlying the role of topography and thermal convection. The vertical profiles of CALIOP β532 nm confirm the multilayered structure of the Mediterranean desert dust outbreaks on both annual and seasonal bases, with several dust layers of variable geometrical characteristics and intensities. A detailed analysis of the vertical structure of specific DD episodes using CALIOP profiles reveals that the consideration of the dust vertical structure is necessary when attempting comparisons between columnar MODIS AOD retrievals and ground PM10 concentrations. ; The MDRAF project has received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 622662. The Collection 051 MODIS-Terra and MODIS-Aqua data were obtained from NASA's level 1 and Atmosphere Archive and Distribution System (LAADS) website (ftp://ladsweb.nascom.nasa.gov/). The Earth Probe (TOMS) and OMI aerosol climatology is available from the Mirador ftp server (http://mirador.gsfc.nasa.gov/). The CALIPSO retrievals have been derived from NASA's Earth Observing System Data and Information System (http://reverb.echo.nasa.gov/). We would like to thank the principal investigators maintaining the AERONET sites used in the present work. We would like to acknowledge the EMEP Programme and the public European databases Airbase and ACTRIS, which supplied PM10 data used in this study. J. Pey benefits from a Ramón y Cajal Research Grant (RYC-2013-14159) from the Spanish Ministry of Economy and Competitiveness. S. Basart, O. Jorba, S. Gassó and J. M. Baldasano acknowledge the CICYT project CGL2013-46736 and Severo Ochoa (SEV-996 2011-00067) programme of the Spanish Government. The publication was supported by the European Union Seventh Framework Programme (FP-7-REGPOT-2012-2013-1), in the framework of the project BEYOND, under Grant Agreement No. 316210 (BEYOND – Building Capacity for a Centre of Excellence for EO-based monitoring of Natural Disasters. The Figs. 10, 11 and 12 have been produced with ccplot (http://ccplot.org/). This work contributes to the Chemistry-Aerosol Mediterranean Experiment (ChArMEx) coordinated effort for the long-term Mediterranean aerosol characterization using available remote sensing data sets. ; This paper was written under the framework of the International HYMEX project and the Spanish HOPE (CGL2014-52571-R) project. We would like to thank the "Agència Catalana de l'Aigua" and the "Real Academia de Ciencias y Artes de Barcelona" for the SAIH and Jardí data provided, respectively. This work was partially funded by the Project of Interest 'NextData' of the Italian Ministry for Education, University and Research. We thank the anonymous reviewers whose comments greatly helped us improve the presentation of the results. ; Peer Reviewed ; Postprint (published version)

Abstract. Atmospheric mineral dust aerosol constitutes a threat to aircraft engines from deterioration of internal components. Here we fulfil an overdue need to quantify engine dust ingestion at airports worldwide. The vertical distribution of dust is of key importance since ascent/descent rates and engine power both vary with altitude and affect dust ingestion. We use representative jet engine power profile information combined with vertically and seasonally varying dust concentrations to calculate the "dust dose" ingested by an engine over a single ascent or descent. Using the Copernicus Atmosphere Monitoring Service (CAMS) model reanalysis, we calculate climatological and seasonal dust dose at 10 airports for 2003–2019. Dust doses are mostly largest in Northern Hemisphere summer for descent, with the largest at Delhi in June–August (JJA; 6.6 g) followed by Niamey in March–May (MAM; 4.7 g) and Dubai in JJA (4.3 g). Holding patterns at altitudes coincident with peak dust concentrations can lead to substantial quantities of dust ingestion, resulting in a larger dose than the take-off, climb, and taxi phases. We compare dust dose calculated from CAMS to spaceborne lidar observations from two dust datasets derived from the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP). In general, seasonal and spatial patterns are similar between CAMS and CALIOP, though large variations in dose magnitude are found, with CAMS producing lower doses by a factor of 1.9 to 2.8, particularly when peak dust concentration is very close to the surface. We show that mitigating action to reduce engine dust damage could be achieved, firstly by moving arrivals and departures to after sunset and secondly by altering the altitude of the holding pattern away from that of the local dust peak altitude, reducing dust dose by up to 44 % and 41 % respectively. We suggest that a likely low bias of dust concentration in the CAMS reanalysis should be considered by aviation stakeholders when estimating dust-induced engine wear.

Atmospheric mineral dust has a rich tri-dimensional spatial and temporal structure that is poorly constrained in forecasts and analyses when only column-integrated aerosol optical depth (AOD) is assimilated. At present, this is the case of most operational global aerosol assimilation products. Aerosol vertical distributions obtained from spaceborne lidars can be assimilated in aerosol models, but questions about the extent of their benefit upon analyses and forecasts along with their consistency with AOD assimilation remain unresolved. Our study thoroughly explores the added value of assimilating spaceborne vertical dust profiles, with and without the joint assimilation of dust optical depth (DOD). We also discuss the consistency in the assimilation of both sources of information and analyse the role of the smaller footprint of the spaceborne lidar profiles in the results. To that end, we have performed data assimilation experiments using dedicated dust observations for a period of 2 months over northern Africa, the Middle East, and Europe. We assimilate DOD derived from the Visible Infrared Imaging Radiometer Suite (VIIRS) on board Suomi National Polar-Orbiting Partnership (SUOMI-NPP) Deep Blue and for the first time Cloud-Aerosol Lidar with Orthogonal Polarisation (CALIOP)-based LIdar climatology of Vertical Aerosol Structure for space-based lidar simulation studies (LIVAS) pure-dust extinction coefficient profiles on an aerosol model. The evaluation is performed against independent ground-based DOD derived from AErosol RObotic NETwork (AERONET) Sun photometers and ground-based lidar dust extinction profiles from the Cyprus Clouds Aerosol and Rain Experiment (CyCARE) and PREparatory: does dust TriboElectrification affect our ClimaTe (Pre-TECT) field campaigns. Jointly assimilating LIVAS and Deep Blue data reduces the root mean square error (RMSE) in the DOD by 39 % and in the dust extinction coefficient by 65 % compared to a control simulation that excludes assimilation. We show that the assimilation of dust extinction coefficient profiles provides a strong added value to the analyses and forecasts. When only Deep Blue data are assimilated, the RMSE in the DOD is reduced further, by 42 %. However, when only LIVAS data are assimilated, the RMSE in the dust extinction coefficient decreases by 72 %, the largest improvement across experiments. We also show that the assimilation of dust extinction profiles yields better skill scores than the assimilation of DOD under an equivalent sensor footprint. Our results demonstrate the strong potential of future lidar space missions to improve desert dust forecasts, particularly if they foresee a depolarization lidar channel to allow discrimination of desert dust from other aerosol types. ; This work received funding from the European Union's Horizon 2020 research and innovation programme (Marie Skłodowska-Curie (grant no. 754433)), the European Research Council (FRAGMENT (grant no. 773051)), and the AXA Research Fund. We were also supported by the Ministerio de Ciencia, Innovación y Universidades (MICINN), as part of the BROWNING project RTI2018-099894-B-I00 and NUTRIENT project CGL2017-88911-R, along with PRACE and RES for awarding access to Marenostrum4 based in Spain at the Barcelona Supercomputing Center through the eFRAGMENT2 and AECT2020-1-0007 projects. Martina Klose received funding from the European Union's Horizon 2020 research and innovation programme (Marie Skłodowska-Curie (grant no. 789630)). Martina Klose was also supported by the Helmholtz Association's Initiative and Networking Fund (grant no. VH-NG-1533). Vassilis Amiridis and Eleni Marinou were supported by ERC Consolidator Grant 2016 D-TECT: "Does dust TriboElectrification affect our ClimaTe?" (grant no. 725698). Eleni Marinou was supported by a DLR VO-R young investigator group and the Deutscher Akademischer Austauschdienst (grant no. 57370121). Emmanouil Proestakis was supported by the project PANhellenic infrastructure for Atmospheric Composition and climatE change (grant no. MIS5021516), which is implemented under the Action Reinforcement of the Research and Innovation Infrastructure, funded by the Operational Programme "Competitiveness, Entrepreneurship and Innovation" (grant no. NSRF2014–2020) and co-financed by Greece and the European Union (European Regional Development Fund). This research was supported by the German–Israeli Foundation for Scientific Research and Development (GIF, grant no. I1262-401.10/2014), the European Union's Framework Programme for Research and Innovation, Horizon 2020 (ACTRIS-2, grant no. 654109), and the former European Commission Seventh Framework Programme FP7/2007–2013 (ACTRIS (grant no. 262254) and BACCHUS (grant no. 603445)). ; Peer Reviewed ; Objectius de Desenvolupament Sostenible::13 - Acció per al Clima ; Objectius de Desenvolupament Sostenible::13 - Acció per al Clima::13.3 - Millorar l'educació, la conscienciació i la capacitat humana i institucional en relació amb la mitigació del canvi climàtic, l'adaptació a aquest, la reducció dels efectes i l'alerta primerenca ; Postprint (published version)

The Generalized Aerosol Retrieval from Radiometer and Lidar Combined data algorithm (GARRLiC) and the LIdar-Radiometer Inversion Code (LIRIC) provide the opportunity to study the aerosol vertical distribution by combining ground-based lidar and sun-photometric measurements. Here, we utilize the capabilities of both algorithms for the characterization of Saharan dust and marine particles, along with their mixtures, in the south-eastern Mediterranean during the CHARacterization of Aerosol mixtures of Dust and Marine origin Experiment (CHARADMExp). Three case studies are presented, focusing on dust-dominated, marine-dominated and dust–marine mixing conditions. GARRLiC and LIRIC achieve a satisfactory characterization for the dust-dominated case in terms of particle microphysical properties and concentration profiles. The marine-dominated and the mixture cases are more challenging for both algorithms, although GARRLiC manages to provide more detailed microphysical retrievals compared to AERONET, while LIRIC effectively discriminates dust and marine particles in its concentration profile retrievals. The results are also compared with modelled dust and marine concentration profiles and surface in situ measurements. ; The research leading to these results has received funding from the European Union's Horizon 2020 Research and Innovation Programme ACTRIS-2 (grant agreement no. 654109). The work has been developed under the auspices of the ESA-ESTEC project "Characterization of Aerosol mixtures of Dust And Marine origin" contract no. IPL-PSO/FF/lf/14.489. The work was also supported by the European Research Council under the European Community's Horizon 2020 research and innovation framework programme/ERC grant agreement 725698 (D-TECT). The publication was supported by the European Union's Horizon 2020 Research and Innovation programme under grant agreement no. 602014, project ECARS (East European Centre for Atmospheric Remote Sensing). The authors acknowledge support through the Stavros Niarchos Foundation. BSC-DREAM8b simulations were performed on the Mare Nostrum supercomputer hosted by the Barcelona Supercomputing Center-Centro Nacional de Supercomputación (BSC). ; Peer Reviewed ; Postprint (published version)

The Generalized Aerosol Retrieval from Radiometer and Lidar Combined data algorithm (GARRLiC) and the LIdar-Radiometer Inversion Code (LIRIC) provide the opportunity to study the aerosol vertical distribution by combining ground-based lidar and sun-photometric measurements. Here, we utilize the capabilities of both algorithms for the characterization of Saharan dust and marine particles, along with their mixtures, in the south-eastern Mediterranean during the CHARacterization of Aerosol mixtures of Dust and Marine origin Experiment (CHARADMExp). Three case studies are presented, focusing on dust-dominated, marine-dominated and dust–marine mixing conditions. GARRLiC and LIRIC achieve a satisfactory characterization for the dust-dominated case in terms of particle microphysical properties and concentration profiles. The marine-dominated and the mixture cases are more challenging for both algorithms, although GARRLiC manages to provide more detailed microphysical retrievals compared to AERONET, while LIRIC effectively discriminates dust and marine particles in its concentration profile retrievals. The results are also compared with modelled dust and marine concentration profiles and surface in situ measurements. ; The research leading to these results has received funding from the European Union's Horizon 2020 Research and Innovation Programme ACTRIS-2 (grant agreement no. 654109). The work has been developed under the auspices of the ESA-ESTEC project "Characterization of Aerosol mixtures of Dust And Marine origin" contract no. IPL-PSO/FF/lf/14.489. The work was also supported by the European Research Council under the European Community's Horizon 2020 research and innovation framework programme/ERC grant agreement 725698 (D-TECT). The publication was supported by the European Union's Horizon 2020 Research and Innovation programme under grant agreement no. 602014, project ECARS (East European Centre for Atmospheric Remote Sensing). The authors acknowledge support through the Stavros Niarchos Foundation. BSC-DREAM8b simulations were performed on the Mare Nostrum supercomputer hosted by the Barcelona Supercomputing Center-Centro Nacional de Supercomputación (BSC). ; Peer Reviewed ; Postprint (published version)

The paper makes a convincing case that the Brewer network is capable of detecting enhanced SO2 columns, as observed, e.g., after volcanic eruptions. For this reason, large volcanic eruptions of the past decade have been used to detect and forecast SO2 plumes of volcanic origin using the Brewer and other ground-based networks, aided by satellite, trajectory analysis calculations and modelling. ; This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 654109.

The paper makes a convincing case that the Brewer network is capable of detecting enhanced SO2 columns, as observed, e.g., after volcanic eruptions. For this reason, large volcanic eruptions of the past decade have been used to detect and forecast SO2 plumes of volcanic origin using the Brewer and other ground-based networks, aided by satellite, trajectory analysis calculations and modelling. ; This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement no. 654109.

The aim of this paper is to present our strategy and vision to upgrade the existing ERATOSTHENES Research Centre (ERC), established within Cyprus University of Technology (CUT), into a sustainable, viable and autonomous Centre of Excellence (CoE) for Earth Surveillance and Space-Based Monitoring of the Environment (EXCELSIOR), which will provide the highest quality of related services both on the National, European and International levels. The 'EXCELSIOR' project is a Horizon 2020 Teaming project, addressing the reduction of substantial disparities in the European Union by supporting research and innovation activities and systems in low performing countries. It also aims at establishing long-term and strategic partnerships between the Teaming partners, thus reducing internal research and innovation disparities within European Research and Innovation landscape. The ERCis already an established player in the local community and has excellent active collaboration with actors from various sectors in (a) the government, (b) industry, (c) local organisations, and (d) society. In order to further engage users and citizens and to become more attractive to international research and education community, the Centre aims to be fully involved in strategic positioning on the national level, but also in Europe, the Middle East region and internationally. Some examples of how space technologies are integrated with other tools or techniques such as UAV, field spectroscopy, micro-sensors, EO space/in-situ sensors etc. for the systematic monitoring of the environment is shown. Indeed such examples fulfills the objectives of the COPERNICUS academy network (in which ERC is a member) for empowering the next generation of researchers, scientists, and entrepreneurs with suitable skill sets to use Copernicus data and information services to their full potential. Finally, opportunities for future collaboration and investments with the ERC in the Eastern Mediterranean Region are stated. Five partners have united to upgrade the existing ...

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 financial support of the ACTRIS Research Infrastructure Project supported by the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 262254 is gratefully acknowledged. This project has also received funding from the European Union's Seventh Framework Programme for research, technological development and demonstration under grant agreement no. 289923 – ITaRS. S. Basart and J. M. Baldasano acknowledge the CICYT project (CGL2010-19652 and CGL2013-46736) and Severo Ochoa (SEV- 2011-00067) programme of the Spanish Government. This program has received funding from the Ministry of Education and Science of the Republic of Serbia through project III43007.