Reconstructing the subsurface ocean decadal variability using surface nudging in a perfect model framework
SERVONNAT, Jérôme
Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
Modelling the Earth Response to Multiple Anthropogenic Interactions and Dynamics [MERMAID]
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Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
Modelling the Earth Response to Multiple Anthropogenic Interactions and Dynamics [MERMAID]
SERVONNAT, Jérôme
Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
Modelling the Earth Response to Multiple Anthropogenic Interactions and Dynamics [MERMAID]
Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
Modelling the Earth Response to Multiple Anthropogenic Interactions and Dynamics [MERMAID]
SWINGEDOUW, Didier
Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
Environnements et Paléoenvironnements OCéaniques [EPOC]
Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
Environnements et Paléoenvironnements OCéaniques [EPOC]
SÉFÉRIAN, Roland
Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
Centre national de recherches météorologiques [CNRM]
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Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] [LSCE]
Centre national de recherches météorologiques [CNRM]
Langue
EN
Article de revue
Ce document a été publié dans
Climate Dynamics. 2015-01, vol. 44, n° 1-2, p. 315-338
Résumé en anglais
Initialising the ocean internal variability for decadal predictability studies is a new area of research and a variety of ad hoc methods are currently proposed. In this study, we explore how nudging with sea surface ...Lire la suite >
Initialising the ocean internal variability for decadal predictability studies is a new area of research and a variety of ad hoc methods are currently proposed. In this study, we explore how nudging with sea surface temperature (SST) and salinity (SSS) can reconstruct the three-dimensional variability of the ocean in a perfect model framework. This approach builds on the hypothesis that oceanic processes themselves will transport the surface information into the ocean interior as seen in ocean-only simulations. Five nudged simulations are designed to reconstruct a 150 years “target” simulation, defined as a portion of a long control simulation. The nudged simulations differ by the variables restored to, SST or SST + SSS, and by the area where the nudging is applied. The strength of the heat flux feedback is diagnosed from observations and the restoring coefficients for SSS use the same time-scale. We observed that this choice prevents spurious convection at high latitudes and near sea-ice border when nudging both SST and SSS. In the tropics, nudging the SST is enough to reconstruct the tropical atmosphere circulation and the associated dynamical and thermodynamical impacts on the underlying ocean. In the tropical Pacific Ocean, the profiles for temperature show a significant correlation from the surface down to 2,000 m, due to dynamical adjustment of the isopycnals. At mid-to-high latitudes, SSS nudging is required to reconstruct both the temperature and the salinity below the seasonal thermocline. This is particularly true in the North Atlantic where adding SSS nudging enables to reconstruct the deep convection regions of the target. By initiating a previously documented 20-year cycle of the model, the SST + SSS nudging is also able to reproduce most of the AMOC variations, a key source of decadal predictability. Reconstruction at depth does not significantly improve with amount of time spent nudging and the efficiency of the surface nudging rather depends on the period/events considered. The joint SST + SSS nudging applied everywhere is the most efficient approach. It ensures that the right water masses are formed at the right surface density, the subsequent circulation, subduction and deep convection further transporting them at depth. The results of this study underline the potential key role of SSS for decadal predictability and further make the case for sustained large-scale observations of this field.< Réduire