Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.
AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.
Recent case studies highlight that warm and moist air intrusion events are significant sources of aerosol particles in the Arctic, influencing cloud properties and thus the resulting radiative forcing in the region. However, the contribution of these short-lived events to different aerosol size modes, cloud condensation nuclei (CCN), and droplet number concentrations remains unconstrained. Here, we investigate the multi-annual aspects of intrusion impacts on aerosol properties using data on aerosol number size distributions, CCN, total particle number concentrations, and optical properties from multiple Arctic stations, including Alert, Tiksi, Utqiaġvik, Villum, and Zeppelin, covering the period 2010-2020.Preliminary results suggest that particle concentrations change significantly during intrusion episodes, with variations across seasons and stations. For instance, contrary to previous studies, number size distribution data indicate a distinct decrease in accumulation mode concentrations during wintertime intrusion episodes relative to non-intrusion periods at several Arctic stations. In summer, this pattern reverses, although not uniformly across stations. Additionally, at Zeppelin, the average of the yearly mean CCN concentrations during intrusions is increased by 13% compared to non-intrusion periods, with some years showing increases exceeding 40%.We explore the potential drivers of these observed number size distribution patterns and derive potential source contribution function and removal mechanisms along the trajectories, employing the Lagrangian analysis tool LAGRANTO.