The Arctic is warming almost 4 times faster than the rest of the globe. Yet how Arctic climate change will evolve remains highly uncertain, as there are large discrepancies in the projections from different climate models. A significant contributor to this uncertainty is our poor understanding of aerosol-cloud interactions in the Arctic and thus their poor representation in the models. The cloud-aerosol puzzle is a rather complex problem, affected by several physical and chemical processes that span various scales.
An important focus of the workshop will be on the relative role of anthropogenic air pollution vs the role of marine aerosols in the Arctic cloud lifecycle. The climatic effects of increasing industrialization within the Arctic circle and transport from more polluted mid-latitude regions are not well understood. At the same time the relationships between decreasing sea-ice extent, increasing ocean temperatures, the resulting changes in marine aerosol emissions and cloud characteristics in the Arctic remains a major unknown.
To quantify these complex interactions, the QuIESCENT workshop aims to gather polar atmospheric and marine scientists, experimentalists and modellers, physicists and chemists, to exchange knowledge and work together to establish a coordinated plan on how to address these critical research questions. Apart from the Arctic scientific community, participation by Antarctic and Southern Ocean scientists is strongly encouraged to provide insights to the aerosol-cloud-precipitation processes that govern the Southern counterpart. In the spirit of the first two QuIESCENT workshops, participation by early career scientists is strongly encouraged.
Finally, in the context of the fourth International Conference on Arctic Research Planning (ICARP IV) and the ongoing planning for the International Polar Year 2032–2033 (IPY32), QuiESCENT aims to address two main objectives:
to hierarchise knowledge gaps in cloud-aerosol interactions and suggest research activities to address them in field and laboratory experiments
propose modelling strategies to improve the efficiency of the knowledge transfer from observations to atmospheric models.