Abstract. The North Atlantic spring bloom is one of the main events that lead to carbon export to the deep ocean and drive oceanic uptake of CO 2 from the atmosphere. Here we use a suite of physical, bio-optical and chemical measurements made during the 2008 spring bloom to optimize and compare three different models of biological carbon export. The observations are from a Lagrangian float that operated south of Iceland from early April to late June, and were calibrated with ship-based measurements. The simplest model is representative of typical NPZD models used for the North Atlantic, while the most complex model explicitly includes diatoms and the formation of fast sinking diatom aggregates and cysts under silicate limitation. We carried out a variational optimization and error analysis for the biological parameters of all three models, and compared their ability to replicate the observations. The observations were sufficient to constrain most phytoplankton-related model parameters to accuracies of better than 15 %. However, the lack of zooplankton observations leads to large uncertainties in model parameters for grazing. The simulated vertical carbon flux at 100 m depth is similar between models and agrees well with available observations, but at 600 m the simulated flux is larger by a factor of 2.5 to 4.5 for the model with diatom aggregation. While none of the models can be formally rejected based on their misfit with the available observations, the model that includes export by diatom aggregation has a statistically significant better fit to the observations and more accurately represents the mechanisms and timing of carbon export based on observations not included in the optimization. Thus models that accurately simulate the upper 100 m do not necessarily accurately simulate export to deeper depths.
Bifurcations and tipping points (TPs) are an important part of the Earth system’s behavior. These critical points represent thresholds at which small changes in the system’s parameters or in the forcing abruptly switch it from one state or type of behavior to another. Current concern with TPs is largely due to the potential of slow anthropogenic forcing to bring about abrupt, and possibly irreversible, change to the physical climate system and impacted ecosystems. Paleoclimate proxy records have been shown to contain abrupt transitions, or “jumps,” which may represent former instances of such dramatic climate change events. These transitions can provide valuable information for identifying critical TPs in current and future climate evolution. Here, we present a robust methodology for detecting abrupt transitions in proxy records that is applied to ice core and speleothem records of the last climate cycle. This methodology is based on the nonparametric Kolmogorov–Smirnov (KS) test for the equality, or not, of the probability distributions associated with two samples drawn from a time series, before and after any potential jump. To improve the detection of abrupt transitions in proxy records, the KS test is augmented by several other criteria and it is compared with recurrence analysis. The augmented KS test results show substantial skill when compared with more subjective criteria for jump detection. This test can also usefully complement recurrence analysis and improve upon certain aspects of its results.
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