4 resultados para Scale Climate Variability

em Plymouth Marine Science Electronic Archive (PlyMSEA)


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Shifts in global climate resonate in plankton dynamics, biogeochemical cycles, and marine food webs. We studied these linkages in the North Atlantic subpolar gyre (NASG), which hosts extensive phytoplankton blooms. We show that phytoplankton abundance increased since the 1960s in parallel to a deepening of the mixed layer and a strengthening of winds and heat losses from the ocean, as driven by the low frequency of the North Atlantic Oscillation (NAO). In parallel to these bottom-up processes, the top-down control of phytoplankton by copepods decreased over the same time period in the western NASG, following sea surface temperature changes typical of the Atlantic Multi-decadal Oscillation (AMO). While previous studies have hypothesized that climate-driven warming would facilitate seasonal stratification of surface waters and long-term phytoplankton increase in subpolar regions, here we show that deeper mixed layers in the NASG can be warmer and host a higher phytoplankton biomass. These results emphasize that different modes of climate variability regulate bottom-up (NAO control) and top-down (AMO control) forcing on phytoplankton at decadal timescales. As a consequence, different relationships between phytoplankton, zooplankton, and their physical environment appear subject to the disparate temporal scale of the observations (seasonal, interannual, or decadal). The prediction of phytoplankton response to climate change should be built upon what is learnt from observations at the longest timescales.

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Shifts in global climate resonate in plankton dynamics, biogeochemical cycles, and marine food webs. We studied these linkages in the North Atlantic subpolar gyre (NASG), which hosts extensive phytoplankton blooms. We show that phytoplankton abundance increased since the 1960s in parallel to a deepening of the mixed layer and a strengthening of winds and heat losses from the ocean, as driven by the low frequency of the North Atlantic Oscillation (NAO). In parallel to these bottom-up processes, the top-down control of phytoplankton by copepods decreased over the same time period in the western NASG, following sea surface temperature changes typical of the Atlantic Multi-decadal Oscillation (AMO). While previous studies have hypothesized that climate-driven warming would facilitate seasonal stratification of surface waters and long-term phytoplankton increase in subpolar regions, here we show that deeper mixed layers in the NASG can be warmer and host a higher phytoplankton biomass. These results emphasize that different modes of climate variability regulate bottom-up (NAO control) and top-down (AMO control) forcing on phytoplankton at decadal timescales. As a consequence, different relationships between phytoplankton, zooplankton, and their physical environment appear subject to the disparate temporal scale of the observations (seasonal, interannual, or decadal). The prediction of phytoplankton response to climate change should be built upon what is learnt from observations at the longest timescales.

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Investigating the variability of Agulhas leakage, the volume transport of water from the Indian Ocean to the South Atlantic Ocean, is highly relevant due to its potential contribution to the Atlantic Meridional Overturning Circulation as well as the global circulation of heat and salt and hence global climate. Quantifying Agulhas leakage is challenging due to the non-linear nature of this process; current observations are insufficient to estimate its variability and ocean models all have biases in this region, even at high resolution . An Eulerian threshold integration method is developed to examine the mechanisms of Agulhas leakage variability in six ocean model simulations of varying resolution. This intercomparison, based on the circulation and thermo- haline structure at the Good Hope line, a transect to the south west of the southern tip of Africa, is used to identify features that are robust regardless of the model used and takes into account the thermohaline biases of each model. When determined by a passive tracer method, 60 % of the magnitude of Agulhas leakage is captured and more than 80 % of its temporal fluctuations, suggesting that the method is appropriate for investigating the variability of Agulhas leakage. In all simulations but one, the major driver of variability is associated with mesoscale features passing through the section. High resolution (<1/10 deg.) hindcast models agree on the temporal (2–4 cycles per year) and spatial (300–500 km) scales of these features corresponding to observed Agulhas Rings. Coarser resolution models (<1/4 deg.) reproduce similar time scale of variability of Agulhas leakage in spite of their difficulties in representing the Agulhas rings properties. A coarser resolution climate model (2 deg.) does not resolve the spatio-temporal mechanism of variability of Agulhas leakage. Hence it is expected to underestimate the contribution of Agulhas Current System to climate variability.

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Investigating the variability of Agulhas leakage, the volume transport of water from the Indian Ocean to the South Atlantic Ocean, is highly relevant due to its potential contribution to the Atlantic Meridional Overturning Circulation as well as the global circulation of heat and salt and hence global climate. Quantifying Agulhas leakage is challenging due to the non-linear nature of this process; current observations are insufficient to estimate its variability and ocean models all have biases in this region, even at high resolution . An Eulerian threshold integration method is developed to examine the mechanisms of Agulhas leakage variability in six ocean model simulations of varying resolution. This intercomparison, based on the circulation and thermo- haline structure at the Good Hope line, a transect to the south west of the southern tip of Africa, is used to identify features that are robust regardless of the model used and takes into account the thermohaline biases of each model. When determined by a passive tracer method, 60 % of the magnitude of Agulhas leakage is captured and more than 80 % of its temporal fluctuations, suggesting that the method is appropriate for investigating the variability of Agulhas leakage. In all simulations but one, the major driver of variability is associated with mesoscale features passing through the section. High resolution (<1/10 deg.) hindcast models agree on the temporal (2–4 cycles per year) and spatial (300–500 km) scales of these features corresponding to observed Agulhas Rings. Coarser resolution models (<1/4 deg.) reproduce similar time scale of variability of Agulhas leakage in spite of their difficulties in representing the Agulhas rings properties. A coarser resolution climate model (2 deg.) does not resolve the spatio-temporal mechanism of variability of Agulhas leakage. Hence it is expected to underestimate the contribution of Agulhas Current System to climate variability.