Assessments and analysis on simulation of high-resolution sea ice leads in the Arctic
Sea ice leads in the Arctic,accounting for only 1%-10%area of the whole ice area,play a crucial role in the exchange of energy and moisture between the ocean and the atmosphere.Currently,the analysis of the numeric-al simulation of the leads mainly focuses on the spatial distribution of the occurrence frequency and the spatio-tem-poral variations of the lead area proportion within the cell,while few analysis concerns the simulated lead morpho-logy(length,width and orientation).This article is based on the high-resolution(2 km)ice sea coupling model us-ing visual plastic rheologies to simulate sea ice thickness to extract leads,and the lead morphology is compared to three MODIS lead products respectly.The results show that the spatial distribution of simulated leads occurrence frequency in Beaufort Sea is basically consistent with WH2015 and H2019 products.The number density and total length of leads with a width greater than 6 km follow the power law distribution as presented in remote sensing products,while that of the narrow(2-4 km)leads are underestimated due to limited model's resolution.The correla-tion between the total length of simulated leads and remote sensed products is high in January and March,but the model fails to reproduce the trends in February and April shown in the remote sensing products.The overall orienta-tion of the simulated leads aligns with the remote sensing products,both show that leads along the north of the Ca-nadian archipelago and the southeast of Beaufort sea are almost parallel to the coastline and the ice drift direction,while the orientation of the simulated leads is more restricted by the continent than that of remote sensing products,and the location of the lead and ice speed turning is not consistent in the middle of the Beaufort Sea.This study highlights the capability of the state-of-the-art high-resolution sea ice-ocean coupled models in simulating various morphological characteristics of sea ice lead,and provides insights for further model improvements.