Sparse observations induce large biases in estimates of the global ocean CO₂ sink: an ocean model subsampling...

Estimates of ocean [Formula: see text] uptake from global ocean biogeochemistry models and [Formula: see text]-based data products differ substantially, especially in high latitudes and in the trend of the [Formula: see text] uptake since 2000. Here, we assess the effect of data sparsity on two [Formula: see text]-based estimates by subsampling output from a global ocean biogeochemistry model. The estimates of the ocean [Formula: see text] uptake are improved from a sampling scheme that mimics present-day sampling to an ideal sampling scheme with 1000 evenly distributed sites. In particular, insufficient sampling has given rise to strong biases in the trend of the ocean carbon sink in the [Formula: see text] products. The overestimation of the [Formula: see text] flux trend by 20-35% globally and 50-130% in the Southern Ocean with the present-day sampling is reduced to less than [Formula: see text] with the ideal sampling scheme. A substantial overestimation of the decadal variability of the Southern Ocean carbon sink occurs in one product and appears related to a skewed data distribution in [Formula: see text] space. With the ideal sampling, the bias in the mean [Formula: see text] flux is reduced from 9-12% to 2-9% globally and from 14-26% to 5-17% in the Southern Ocean. On top of that, discrepancies of about [Formula: see text] (15%) persist due to uncertainties in the gas-exchange calculation. This article is part of a discussion meeting issue 'Heat and carbon uptake in the Southern Ocean: the state of the art and future priorities'.