Standardized daily high-resolution large-eddy simulations of the Arctic boundary layer and clouds during the complete MOSAiC drift

• Main Authors: Schnierstein, Niklas, Chylik, Jan, Shupe, Matthew D., Neggers, Roel
• Format: Other/Unknown Material
• Language: unknown
• Published: Authorea, Inc. 2024
• Subjects: Arctic; Climate change
• Online Access: http://dx.doi.org/10.22541/essoar.171033230.00246941/v1

This study utilizes the wealth of observational data collected during the recent MOSAiC drift experiment to constrain and evaluate 190 daily Large-Eddy Simulations (LES) of Arctic boundary layers and clouds at turbulence-resolving resolutions. A standardized approach is adopted to tightly integrate field measurements into the experimental configuration. Covering the full drift represents a step forward from single-case LES studies, and allows for a robust assessment of model performance against independent data under a broad range of atmospheric conditions. A homogeneously forced Eulerian domain is simulated, initialized with radiosonde and value-added cloud profiles. Prescribed boundary conditions include various measured surface characteristics. Time-constant composite forcing is applied, primarily consisting of subsidence rates sampled from reanalysis data. The simulations run for multiple hours, allowing turbulence and mixed-phase clouds to spin up while still facilitating direct comparison to MOSAiC data. Key aspects such as the vertical thermodynamic structure, cloud properties, and surface energy fluxes are satisfactorily reproduced and maintained. Specifically, the model captures the bimodal distribution of atmospheric states that is typical of Arctic climate. Selected days are investigated more closely to assess the model’s skill in maintaining the observed boundary layer structure. The sensitivity to various aspects of the experimental configuration and model physics is tested. The model input and output are available to the scientific community, supplementing the MOSAiC data archive. The close agreement with observed meteorology justifies the use of LES data for gaining further insight into Arctic processes and their role in Arctic climate change.