Alistair Duffey

and 6 more

The Arctic winter-time atmospheric boundary layer often features strong and persistent low-level stability which arises from longwave radiative cooling of the surface during the polar night. This stable stratification results in a positive lapse rate feedback, which is a major contributor to Arctic amplification. A second state, associated with cloudy conditions, with weaker stability and near-zero net surface longwave flux is also observed. Previous work has shown that many CMIP5 climate models fail to realistically represent the cloudy state. In this study, we assess the representation of the Arctic atmospheric boundary layer over sea ice during the winter months in global climate models contributing to the latest phase of the Coupled Model Intercomparison Project (CMIP6). We compare boundary layer process relationships seen in these models to those in surface-based and radiosonde observations collected during the recent MOSAiC (2019-2020) field campaign, alongside the earlier SHEBA (1997-1998) expedition, and from North Pole drifting stations (1955-1991). Here, we show that a majority of CMIP6 models fail to realistically represent the cloudy state over winter Arctic sea ice. Despite this, CMIP6 models have a multi-model mean low-level stability which falls within the range recorded by observational campaigns, and are mostly able to capture the observed dependence of low-level stability on near-surface air temperature and wind speed. As the Arctic warms, CMIP6 models predict a decline of winter low-level stability, with the Central Arctic’s mean stability falling below zero in the multi-model mean state by the end of the century under the SSP2-4.5 emissions scenario.
Extreme weather events are triggered by atmospheric circulation patterns and shaped by slower components, including soil moisture and sea-surface temperature, and by the background climate. This separation of factors is exploited by the storyline approach where an atmosphere model is nudged toward the observed dynamics using different climate boundary conditions to explore their influence. The storyline approach disregards rather uncertain climatic changes in the frequency and intensity of dynamical conditions, but focuses on the thermodynamic influence of climate on extreme events. Here we demonstrate an advanced storyline approach that employs a coupled climate model (AWI-CM-1-1-MR) where the large-scale free-troposphere dynamics are nudged toward ERA5 data. Five-member ensembles are run for present-day (2017–2019), pre-industrial, +2K, and +4K climates branching off from CMIP6 historical and scenario simulations of the same model. In contrast to previous studies, which employed atmosphere-only models, feedbacks between extreme events and the ocean and sea-ice state, and the dependence of such feedbacks on the climate, are consistently simulated. Our setup is capable of reproducing observed anomalies of relevant unconstrained parameters, including near-surface temperature, cloud cover, soil moisture, sea-surface temperature, and sea-ice concentration. Focusing on the July 2019 European heatwave, we find that the strongest warming amplification expands from southern to central Europe over the course of the 21st century. The warming reaches up to 10 K in the 4K warmer climate, suggesting that an analogous event would entail peak temperatures around 50 ºC in central Europe.