Abstract
Abstract. We develop a conceptual coupled atmosphere–phytoplankton model by combining the Lorenz'84 general circulation model and the logistic population growth model under the condition of a climate change due to a linear time dependence of the strength of anthropogenic atmospheric forcing. The following types of couplings are taken into account: (a) the temperature modifies the total biomass of phytoplankton via the carrying capacity; (b) the extraction of carbon dioxide by phytoplankton slows down the speed of climate change; (c) the strength of mixing/turbulence in the oceanic mixing layer is in correlation with phytoplankton productivity. We carry out an ensemble approach (in the spirit of the theory of snapshot attractors) and concentrate on the trends of the average phytoplankton concentration and average temperature contrast between the pole and Equator, forcing the atmospheric dynamics. The effect of turbulence is found to have the strongest influence on these trends. Our results show that when mixing has sufficiently strong coupling to production, mixing is able to force the typical phytoplankton concentration to always decay globally in time and the temperature contrast to decrease faster than what follows from direct anthropogenic influences. Simple relations found for the trends without this coupling do, however, remain valid; just the coefficients become dependent on the strength of coupling with oceanic mixing. In particular, the phytoplankton concentration and its coupling to climate are found to modify the trend of global warming and are able to make it stronger than what it would be without biomass.
Highlights
Large-scale general circulation models typically take into account the interaction of the atmosphere with land vegetation and marine biomass production in the form of a huge number of parametrized processes
There is, no internal variability in the concentration variable c, an extended, fractal snapshot attractor underlies the atmospheric variables exactly as in the model of Drótos et al (2015), where phytoplankton dynamics was not taken into account
At a fixed time instant, we looked for those values of, e.g., x, for which only 10 % of values can be found on the snapshot attractor below or above x
Summary
Large-scale general circulation models typically take into account the interaction of the atmosphere with land vegetation and marine biomass production in the form of a huge number of parametrized processes (see, e.g., Marinov et al, 2010; Zhong et al, 2011; Mongwe et al, 2018; Wilson et al, 2018). Increased atmospheric CO2 level increases ocean temperature, decreases pH, increases water stratification, and influences general oceanic circulation These can all modify the net productivity and the composition of phytoplankton and can have either a positive or negative net effect on the biological carbon pump (Basu and Mackey, 2018, and references therein). In a simple heuristic form, important feedbacks in the model: (a) the change in the atmospheric temperature that modifies phytoplankton concentration; (b) the extraction of CO2 by phytoplankton; and (c) wind energy that enhances the strength of turbulence in the oceanic mixing layer, which increases the phytoplankton production (Estrada and Berdalet, 1997; Peters and Marrasé, 2000; Jäger et al, 2010). S4 contains a sample of the C code applied during numerical simulations
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