Influence of the oceanic biology on the tropical Pacific climate in a coupled general circulation model

Lengaigne, Matthieu; Menkès, Christophe E.; Aumont, Olivier; Gorguès, Thomas; Bopp, Laurent; André, Jean-Michel; Madec, Gurvan

doi:10.1007/s00382-006-0200-2

Cited by 139 publications

(151 citation statements)

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“…On the other hand, surface cooling caused by an indirect dynamical response to the biologically enhanced heating has been also reported (Nakamoto et al 2001;Manizza et al 2005;Loptien et al 2009;Jochum et al 2010). Similar to these conflicting results on the mean state changes, biological impacts on ENSO found in previous studies also show that biophysical feedback can either amplify the ENSO response (Marzeion et al 2005;Lengaigne et al 2007;Loptien et al 2009), or dampen it (Timmermann and Jin 2002;Wetzel et al 2006;Jochum et al 2010).…”

Section: Introductionsupporting

confidence: 84%

“…The atmosphere-ocean coupled global circulation models (CGCMs) incorporating marine biology have also shown that biological feedback can significantly change the modeled climatology and variability (Marzeion et al 2005;Wetzel et al 2006;Anderson et al 2007;Ballabrera-Poy et al 2007;Lengaigne et al 2007;Jochum et al 2010;Lin et al 2011;Patara et al 2012). For example, Marzeion et al (2005) showed that the presence of chlorophyll leads to a deepening of the mixed layer in the eastern equatorial Pacific due to the biologically enhanced subsurface warming.…”

Section: Introductionmentioning

confidence: 99%

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Impact of bio-physical feedbacks on the tropical climate in coupled and uncoupled GCMs

et al. 2013

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The bio-physical feedback process between the marine ecosystem and the tropical climate system is investigated using both an ocean circulation model and a fully-coupled ocean-atmosphere circulation model, which interact with a biogeochemical model. We found that the presence of chlorophyll can have significant impact on the characteristics of the El Niño-Southern Oscillation (ENSO), including its amplitude and asymmetry, as well as on the mean state. That is, chlorophyll generally increases mean sea surface temperature (SST) due to the direct biological heating. However, SST in the eastern equatorial Pacific decreases due to the stronger indirect dynamical response to the biological effects outweighing the direct thermal response. It is demonstrated that this biologicallyinduced SST cooling is intensified and conveyed to other tropical-ocean basins when atmosphere-ocean coupling is taken into account. It is also found that the presence of chlorophyll affects the magnitude of ENSO by two different mechanisms; one is an amplifying effect by the mean chlorophyll, which is associated with shoaling of the mean thermocline depth, and the other is a damping effect derived from the interactively-varying chlorophyll coupled with the physical model. The atmosphere-ocean coupling reduces the biologically-induced ENSO amplifying effect through the weakening of atmospheric feedback. Lastly, there is also a biological impact on ENSO which enhances the positive skewness. This skewness change is presumably caused by the phase dependency of thermocline feedback which affects the ENSO magnitude.

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Section: Introductionsupporting

confidence: 84%

Section: Introductionmentioning

confidence: 99%

Impact of bio-physical feedbacks on the tropical climate in coupled and uncoupled GCMs

et al. 2013

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“…The uniform RGB scheme used here assumes a Chlorophyll concentration of 0.05 mg.Chl m −3 (Lengaigne et al, 2007).…”

Section: Seasonal Stratificationmentioning

confidence: 99%

AMM15: A new high resolution NEMO configuration for operational simulation of the European North West Shelf

Graham¹,

O’Dea²,

Holt³

et al. 2017

Preprint

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Abstract. This paper describes the next generation ocean forecast model for the European North West Shelf, which will become the basis of operational forecasts in 2018. This new system will provide a step change in resolution, and therefore our ability to represent small scale processes. The new model has a resolution of 1.5 km, compared with a grid spacing of 7 km in the current operational system. AMM15 (Atlantic Margin Model, 1.5 km) is introduced as a new regional configuration of NEMO v3.6. Here we describe the technical details behind this configuration, with modifications appropriate for the new high 5 resolution domain. Results from a 30 year non-assimilative run, using the AMM15 domain, demonstrate the ability of this model to represent the mean state and variability of the region.Overall, there is an improvement in the representation of the mean state across the region, suggesting similar improvements may be seen in the future operational system. However, the reduction in seasonal bias is greater off-shelf than on-shelf. In the North Sea, biases are largely unchanged. Since there has been no change to the vertical resolution or parameterisation 10 schemes, performance improvements are not expected in regions where stratification is dominated by vertical processes, rather than advection. This highlights the fact that increased horizontal resolution will not lead to domain-wide improvements. Further work is needed to target bias reduction across the North West Shelf region.

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“…This configuration includes an improved Turbulent Kinetic Energy (TKE) closure scheme based on Blanke and Delecluse [1993]. The ocean radiative scheme is represented by threewave-band scheme of Lengaigne et al [2007], which accounts for influence of phytoplankton chlorophyll. The sea ice model is GELATO5 [Salas Melia, 2002], which considers four ice thickness categories (0-0.3 m, 0.3-0.8 m, 0.8-3 m, and over 3 m).…”

Section: A16 Model 17mentioning

confidence: 99%

Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models

Lee

Matrai

Friedrichs

et al. 2016

J. Geophys. Res. Oceans

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The relative skill of 21 regional and global biogeochemical models was assessed in terms of how well the models reproduced observed net primary productivity (NPP) and environmental variables such as nitrate concentration (NO3), mixed layer depth (MLD), euphotic layer depth (Zeu), and sea ice concentration, by comparing results against a newly updated, quality‐controlled in situ NPP database for the Arctic Ocean (1959–2011). The models broadly captured the spatial features of integrated NPP (iNPP) on a pan‐Arctic scale. Most models underestimated iNPP by varying degrees in spite of overestimating surface NO3, MLD, and Zeu throughout the regions. Among the models, iNPP exhibited little difference over sea ice condition (ice‐free versus ice‐influenced) and bottom depth (shelf versus deep ocean). The models performed relatively well for the most recent decade and toward the end of Arctic summer. In the Barents and Greenland Seas, regional model skill of surface NO3 was best associated with how well MLD was reproduced. Regionally, iNPP was relatively well simulated in the Beaufort Sea and the central Arctic Basin, where in situ NPP is low and nutrients are mostly depleted. Models performed less well at simulating iNPP in the Greenland and Chukchi Seas, despite the higher model skill in MLD and sea ice concentration, respectively. iNPP model skill was constrained by different factors in different Arctic Ocean regions. Our study suggests that better parameterization of biological and ecological microbial rates (phytoplankton growth and zooplankton grazing) are needed for improved Arctic Ocean biogeochemical modeling.

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Influence of the oceanic biology on the tropical Pacific climate in a coupled general circulation model

Cited by 139 publications

References 40 publications

Impact of bio-physical feedbacks on the tropical climate in coupled and uncoupled GCMs

Impact of bio-physical feedbacks on the tropical climate in coupled and uncoupled GCMs

AMM15: A new high resolution NEMO configuration for operational simulation of the European North West Shelf

Net primary productivity estimates and environmental variables in the Arctic Ocean: An assessment of coupled physical-biogeochemical models

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