Resolving the Arctic winter radiative multimodality: a large eddy simulation study at the north slope of Alaska

The Arctic winter climate is characterised by multimodal radiative regimes. Two major regimes are well-documented in observational datasets across diverse Arctic regions. One is a radiatively clear regime with optically thin clouds with strong surface cooling, and another is a radiatively opaque regime characterized by optically thick, mixed-phase clouds and deep ice clouds that maintain a warm surface. The radiative opaque regime is largely driven by the presence of supercooled liquid water in mixed-phase clouds and optically thick ice in ice clouds.

Accurately capturing these regimes is essential for understanding Arctic climate and its future change; however, current reanalysis datasets, struggle to reproduce the multimodality. Analyses reveal that reanalysis often exhibits unimodal or skewed distributions of surface downward longwave radiation, failing to distinguish between the distinct clear and opaque regimes. These biases are from a systematic underestimation of the cloud liquid water path and warm temperature biases in the boundary layer, which obscure the radiative frequency peaks observed in nature.

Recent long-term analyses of in-situ data from the Atmospheric Radiation Management (ARM) North Slope of Alaska (NSA) have identified a rapid deterioration of the transmissive atmospheric radiative regime in the Western Arctic. This decline is particularly pronounced in autumn, where the frequency of clear regimes has dropped significantly over the past 25 years. It is unclear whether reanalysis dataset can capture such regime shift.

To address these discrepancies, we employ Dutch Atmospheric Large Eddy Simulation (DALES) capable of explicitly resolving small-scale turbulence and parameterising cloud with a 2-moment bulk mixed-phase microphysics. In this study, the LES is forced by large-scale reanalysis datasets and compared against long-term in-situ observations from the ARM NSA site.