Abstract. Sea-ice biogeochemical models are key to understanding polar marine ecosystems. We present an intercomparison of six one-dimensional models, assessing their ability to simulate algal phenology and nutrient dynamics using physical-biogeochemical data from an Arctic drift expedition in spring 2015. While no model fully captured observed bloom dynamics with default settings, tuning improved biomass but had a limited impact on nutrients. The experiment revealed challenges in simulating short-lived, dynamic ice habitats, which are expected to become more common in a changing Arctic. Variability in tuning strategies underscores key knowledge gaps and highlights the need for coordinated future model developments to improve reliability and predictive capacity.
Tedesco et al. (Wed,) studied this question.