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In an effort led by the University Centre in Svalbard (UNIS), with support from the Norwegian Meteorological Institute (MET Norway), the Isfjorden Weather Information Network (IWIN) is under development in the Isfjorden region in central Svalbard. The network substantially expands upon the relatively sparse existing operational network of weather stations and consists of compact and cost-efficient all-in-one weather stations permanently installed at lighthouses around Isfjorden and on board small tourist cruise ships trafficking the fjord from spring to autumn. All data from the network until June 2023, as presented in this paper, can be found at https://doi.org/10.5281/zenodo.8137588 (Frank et al., 2023b). New data become freely available in near-real time via MET Norway's data portals (https://doi.org/10.21343/ebrw-w846, Frank et al., 2023a). The IWIN data are highly valuable for scientific purposes such as atmospheric boundary layer research, the validation and development of numerical weather prediction models, and assimilation in these, as well as the planning and safe conduction of outdoor activities in the region.

This study evaluates the simulation of wintertime (15 October, 2019, to 15 March, 2020) statistics of the central Arctic near -surface atmosphere and surface energy budget observed during the MOSAiC campaign with short-term forecasts from 7 state-of-the-art operational and experimental forecast systems. Five of these systems are fully coupled ocean -sea ice -atmosphere models. Forecast systems need to simultaneously simulate the impact of radiative effects, turbulence, and precipitation processes on the surface energy budget and nearsurface atmospheric conditions in order to produce useful forecasts of the Arctic system.This study focuses on processes unique to the Arctic, such as, the representation of liquid -bearing clouds at cold temperatures and the representation of a persistent stable boundary layer. It is found that contemporary models still struggle to maintain liquid water in clouds at cold temperatures. Given the simple balance between net longwave radiation, sensible heat flux, and conductive ground flux in the wintertime Arctic surface energy balance, a bias in one of these components manifests as a compensating bias in other terms. This study highlights the different manifestations of model bias and the potential implications on other terms. Three general types of challenges are found within the models evaluated: representing the radiative impact of clouds, representing the interaction of atmospheric heat fluxes with sub -surface fluxes (i.e., snow and ice properties), and representing the relationship between stability and turbulent heat fluxes.