Found 10000 publications. Showing page 18 of 400:
2007
Aerosol Optical Properties and Type Retrieval via Machine Learning and an All-Sky Imager
This study investigates the applicability of using the sky information from an all-sky imager (ASI) to retrieve aerosol optical properties and type. Sky information from the ASI, in terms of Red-Green-Blue (RGB) channels and sun saturation area, are imported into a supervised machine learning algorithm for estimating five different aerosol optical properties related to aerosol burden (aerosol optical depth, AOD at 440, 500 and 675 nm) and size (Ångström Exponent at 440–675 nm, and Fine Mode Fraction at 500 nm). The retrieved aerosol optical properties are compared against reference measurements from the AERONET station, showing adequate agreement (R: 0.89–0.95). The AOD errors increased for higher AOD values, whereas for AE and FMF, the biases increased for coarse particles. Regarding aerosol type classification, the retrieved properties can capture 77.5% of the total aerosol type cases, with excellent results for dust identification (>95% of the cases). The results of this work promote ASI as a valuable tool for aerosol optical properties and type retrieval.
2023
Optical properties of surface aerosols at Dome C, Antarctica, in 2007–2013 and their potential source areas are presented. Scattering coefficients (σsp) were calculated from measured particle number size distributions with a Mie code and from filter samples using mass scattering efficiencies. Absorption coefficients (σap) were determined with a three-wavelength Particle Soot Absorption Photometer (PSAP) and corrected for scattering by using two different algorithms. The scattering coefficients were also compared with σsp measured with a nephelometer at the South Pole Station (SPO). The minimum σap was observed in the austral autumn and the maximum in the austral spring, similar to other Antarctic sites. The darkest aerosol, i.e., the lowest single-scattering albedo ωo≈0.91, was observed in September and October and the highest ωo≈0.99 in February and March. The uncertainty of the absorption Ångström exponent αap is high. The lowest αap monthly medians were observed in March and the highest in August–October. The equivalent black carbon (eBC) mass concentrations were compared with eBC measured at three other Antarctic sites: the SPO and two coastal sites, Neumayer and Syowa. The maximum monthly median eBC concentrations are almost the same ( ng m−3) at all these sites in October–November. This suggests that there is no significant difference in eBC concentrations between the coastal and plateau sites. The seasonal cycle of the eBC mass fraction exhibits a minimum f(eBC) ≈0.1 % in February–March and a maximum ∼4 %–5 % in August–October. Source areas were calculated using 50 d FLEXPART footprints. The highest eBC concentrations and the lowest ωo were associated with air masses coming from South America, Australia and Africa. Vertical simulations that take BC particle removal processes into account show that there would be essentially no BC particles arriving at Dome C from north of latitude 10∘ S at altitudes
2022
2007
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2014
2025
The Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS) officially became the 33rd European Research Infrastructure Consortium (ERIC) on April 25, 2023 with the support of 17 founding member and observer countries. As a pan-European legal organization, ACTRIS ERIC will coordinate the provision of data and data products on short-lived atmospheric constituents and clouds relevant to climate and air pollution over the next 15-20 years. ACTRIS was designed more than a decade ago, and its development was funded at national and European levels. It was included in the European Strategy Forum on Research Infrastructures (ESFRI) Roadmap in 2016 and subsequently, in the national infrastructure roadmaps of European countries. It became a landmark of the ESFRI roadmap in 2021. The purpose of this paper is to describe the mission of ACTRIS, its added value to the community of atmospheric scientists, providing services to academia as well as the public and private sectors, and to summarize its main achievements. The present publication serves as a reference document for ACTRIS, its users and the scientific community as a whole. It provides the reader with relevant information and an overview on ACTRIS governance and services, as well as a summary of the main scientific achievements of the last 20 years. The paper concludes with an outlook on the upcoming challenges for ACTRIS and the strategy for its future evolution.
2024
2023
2023
2022
2007
Aerosol-Cloud Interactions: Overcoming a Barrier to Projecting Near-Term Climate Evolution and Risk
Aerosol-cloud interactions (ACI) are a major source of uncertainty in climate science, critically affecting our ability to project near-term climate evolution and assess societal risks. These interactions influence effective radiative forcing, cloud dynamics, and precipitation patterns, yet remain insufficiently constrained due to limitations in observations, modeling, and process understanding. This uncertainty hampers robust policy advice across multiple domains—from estimating remaining carbon budgets and climate sensitivity, to anticipating regional extreme events and evaluating climate interventions such as solar radiation modification. In many cases, the influence of ACI is either underappreciated or excluded from decision-making frameworks due to its complexity and lack of quantification. This perspective outlines a path forward to overcome these barriers by leveraging emerging opportunities in satellite remote sensing, ground-based and airborne observations, high-resolution climate modeling, and machine learning. We identify key areas where rapid progress is feasible, including improved retrievals of cloud microphysical properties, better representation of natural aerosols in a warming world, and enhanced integration of observational and modeling communities. Even as anthropogenic aerosol and its impacts on clouds is reducing owing to emissions controls, addressing ACI uncertainties remains essential for refining climate projections, supporting effective mitigation and adaptation strategies, and delivering actionable science to policymakers in a rapidly changing climate system.
2026
2012