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A large stretch of the east coast of Australia experienced unprecedented rainfall and flooding over a two‐week period in early 2022. It is difficult to reliably estimate the likelihood of such a rare event from the relatively short observational record, so an alternative is to use data from an ensemble prediction system (e.g., a seasonal or decadal forecast system) to obtain a much larger sample of simulated weather events. This so‐called 'UNSEEN' method has been successfully applied in several scientific studies, but those studies typically rely on a single prediction system. In this study, we use data from the Decadal Climate Prediction Project to explore the model uncertainty associated with the UNSEEN method by assessing 10 different hindcast ensembles. Using the 15‐day rainfall total averaged over the river catchments impacted by the 2022 east coast event, we find that the models produce a wide range of likelihood estimates. Even after excluding a number of models that fail basic fidelity tests, estimates of the event return period ranged from 320 to 1814 years. The vast majority of models suggested the event is rarer than a standard extreme value assessment of the observational record (297 years). Such large model uncertainty suggests that multi‐model analysis should become part of the standard UNSEEN procedure. [ABSTRACT FROM AUTHOR]

We analyze an optimized model of the global silicon cycle embedded in a data-assimilated steady ocean circulation. Biological uptake is modeled by conditionally restoring silicic acid in the euphotic zone to observed concentrations where the modeled concentrations exceed the observational climatology. An equivalent linear model is formulated to which Green-function-based transport diagnostics are applied. We find that the models' opal export through 133 m depth is 166 ± 24 Tmol Si/yr, with the Southern Ocean (SO) providing ∼70% of this export, ∼50% of which dissolves above 2000 m depth. The global-scale gradients of the opal dissolution rate are primarily meridional, while the global-scale gradients of phosphate remineralization are primarily vertical. The mean depth of the temperature-dependent silicic-acid regeneration reaches 2300 m in the SO, compared to 600 m for phosphate remineralization. Silicic acid is stripped out of the euphotic zone far more efficiently than phosphate, with only (34 ± 5)% of the global silicic-acid inventory being preformed, compared to (61 ± 7)% for phosphate. Subantarctic and tropical waters contribute most of the ocean's regenerated silicic acid, while Antarctic waters provide most of the preformed silicic acid. About half of the global silicic-acid inventory is trapped in transport paths connecting successive SO utilizations, with silicic acid last utilized in the SO having only a (5 ± 2)% chance of being next utilized outside the SO. This trapping depletes subantarctic mode waters of silicic acid relative to phosphate, which has a (44 ± 2)% probability of escaping successive SO utilization.

One of the central objectives of the Joint Global Ocean Flux Study (JGOFS) is to use data from the extensive field programs to evaluate and improve numerical ocean carbon-cycle models. Substantial improvements are required if we are to achieve a better understanding of present-day biogeochemical properties and processes in the ocean and to predict potential future responses to perturbations resulting from human activities. We have made significant progress in this regard and expect even greater strides over the next decade as the synthesis of JGOFS data sets is completed and disseminated to the broader scientific community.

Accurate predictive modeling of the ocean's global carbon and oxygen cycles is challenging because of uncertainties in both biogeochemistry and ocean circulation. Advances over the last decade have made parameter optimization feasible, allowing models to better match observed biogeochemical fields. However, does fitting a biogeochemical model to observed tracers using a circulation with known biases robustly capture the inner workings of the biological pump? Here we embed a mechanistic model of the ocean's coupled nutrient, carbon, and oxygen cycles into two circulations for the current climate. To assess the effects of biases, one circulation (ACCESS-M) is derived from a climate model and the other from data assimilation of observations (OCIM2). We find that parameter optimization compensates for circulation biases at the expense of altering how the biological pump operates. Tracer observations constrain pump strength and regenerated inventories for both circulations, but ACCESS-M export production optimizes to twice that of OCIM2 to compensate for ACCESS-M having lower sequestration efficiencies driven by less efficient particle transfer and shorter residence times. Idealized simulations forcing complete Southern Ocean nutrient utilization show that the response of the optimized system is sensitive to the embedding circulation. In ACCESS-M, Southern Ocean nutrient and dissolved inorganic carbon (DIC) trapping is partially short circuited by unrealistically deep mixed layers. For both circulations, intense Southern Ocean production deoxygenates Southern-Ocean-sourced deep waters, muting the imprint of circulation biases on oxygen. Our findings highlight that the biological pump's plumbing needs careful assessment to predict the biogeochemical response to ecological changes, even when optimally matching observations. [ABSTRACT FROM AUTHOR]