The Representation of Sea Salt Aerosols and Their Role in Polar Climate Within CMIP6

Abstract

Natural aerosols and their interactions with clouds remain an important uncertainty within climate models, especially at the poles. Here, we study the behavior of sea salt aerosols (SSaer) in the Arctic and Antarctic within 12 climate models from CMIP6. We investigate the driving factors that control SSaer abundances and show large differences based on the choice of the source function, and the representation of aerosol processes in the atmosphere. Close to the poles, the CMIP6 models do not match observed seasonal cycles of surface concentrations, likely due to the absence of wintertime SSaer sources such as blowing snow. Further away from the poles, simulated concentrations have the correct seasonality, but have a positive mean bias of up to one order of magnitude. SSaer optical depth is derived from the MODIS data and compared to modeled values, revealing good agreement, except for winter months. Better agreement for aerosol optical depth than surface concentration may indicate a need for improving the vertical distribution, the size distribution and/or hygroscopicity of modeled polar SSaer. Source functions used in CMIP6 emit very different numbers of small SSaer, potentially exacerbating cloud‐aerosol interaction uncertainties in these remote regions. For future climate scenarios SSP126 and SSP585, we show that SSaer concentrations increase at both poles at the end of the 21st century, with more than two times mid‐20th century values in the Arctic. The pre‐industrial climate CMIP6 experiments suggest there is a large uncertainty in the polar radiative budget due to SSaer.

Polar Aerosol Atmospheric Rivers: Detection, Characteristics, and Potential Applications

“…SS emissions have been increasing globally over the course of the 20th century (Figure A4), driven by increases in wind speed and decline of sea‐ice cover (Lapere et al., 2023). As a result of the increasing emissions, the historical threshold is more and more likely to be exceeded, and therefore an increase in SS p‐AAR would be expected over the last decades under unchanged transport dynamics.…”

“…In addition, the AR response to future climate change is highly dependent on the chosen detection tool (O'Brien et al, 2022;Shields et al, 2023). For natural aerosols, the emission sources are not expected to feature strong trends in future scenarios, although more sea salt (Lapere et al, 2023) and possibly slightly more dust (Zhou et al, 2023) can be expected under a changing climate. Local sources of anthropogenic aerosols such as BC are also expected to change moderately, particularly in the Arctic with increased shipping traffic (Corbett et al, 2010).…”

“…Emissions, transport and deposition are diversely represented. In particular, DU and SS mass concentrations are usually overestimated at high latitudes, including in MERRA‐2, and differ depending on the model/reanalysis considered (Böö et al., 2023; Lapere et al., 2023). Because we only evaluate extreme events here, defined based on a relative threshold, this should not be a problem for p‐AAR detection, but for impact studies this may be a limitation.…”

Ocean-sourced snow: An unaccounted process on Arctic sea ice

“…Adding a sublimating sea ice surface as an additional vapor source contributes mass to the base of the snowpack and counteracts the SNOWPACK modeled density reductions [11]. Additionally, including vapor fluxes through the snow is necessary for modeling gas exchanges through the Arctic sea ice and snow and has a detrimental effect on our understanding of sea salt aerosol sources and their role in polar climate [24].…”

A Dissection of the Inter‐Model Spread of the Aerosol Direct Radiative Effect in CMIP6 Models

“…To better constrain ADRE uncertainty and its impact on climate projection, it is crucial to identify the primary causes of the uncertainty in the global climate models (GCM).The inter-model spread of ADRE arises from many factors, including aerosol and atmospheric states as well as radiative transfer calculations. The representation of aerosols in CMIP6 models remains discrepant, especially in heavily polluted areas, desert and polar regions (Cherian & Quaas, 2020;Lapere et al, 2023). The discrepancies can result from various factors, including aerosol emissions and deposition, the representation of microphysics (such as size distribution and hygroscopicity) as well as the vertical distribution of aerosols (…”