Abstract

The Arctic is warming two to three times faster than the global average. Arctic amplification has repercussions for the global climate, northern hemispheric weather, and local livelihoods. Current models have difficulties simulating Arctic change making future scenarios uncertain.

To improve model skills, the factors contributing to Arctic amplification need to be better represented. We focus on the role of aerosols. Aerosols can interact directly with solar radiation, and change cloud radiative properties. Considerable effort has gone into describing the role of anthropogenic aerosols in Arctic climate change. Much less focus has been on natural aerosols, which are gaining importance. This is partly because they are emitted in complex processes involving several environmental compartments, which is difficult to represent in models. To complicate things further, the natural state of the Arctic is changing rapidly thereby changing aerosol processes.

We propose to use an unprecedented combination of in-situ measurements, satellite-based observations, and numerical weather prediction data to reveal natural Arctic processes that drive climate-relevant aerosol properties. Aerosol data are available from eight Arctic observatories covering up to 30 years, and from two high Arctic drift expeditions. By developing a latent variable model, which accommodates the different data types, time series with gaps, and domain knowledge for constraints, we will explore relationships between environmental variables, such as sea ice extent, chlorophyll-a concentrations, or meteorological conditions, and the aerosol target variables.

After quantifying these relationships, we will test the output from 5 Earth System models (ESM) against the data-driven model results to identify where ESMs can be improved. We expect the project to have a high impact because results would be produced while several large Horizon 2020 polar research projects are carried out where our output can be used directly.