Brief communication: Intercomparison study reveals pathways for improving the representation of sea-ice biogeochemistry in models

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.