Abstract's details

Global mode water detection and its representation in heat transport

Yanxu Chen (Laboratoire de Météorologie Dynamique, Ecole Normale Supérieure, France)


Sabrina Speich (Laboratoire de Météorologie Dynamique, Ecole Normale Supérieure, France); Rémi Laxenaire (Center for Ocean‐Atmospheric Prediction Studies, Florida State University, United States)

Event: 2022 Ocean Surface Topography Science Team Meeting

Session: Science III: Mesoscale and sub-mesoscale oceanography

Presentation type: Type Forum only

Mode water, characterized as a thick water mass with homogeneous properties, is a distinctive feature of the upper ocean commonly resulting from surface convection. It thus serves as a heat reservoir and is often referred to as “climate memories” that can modulate sea surface temperatures and ventilate the thermoclines. In this study, we propose a new algorithm applied to the Argo global array to determine the mixed layer depth (MLD) and mode water thickness and volume in a more precise way by taking into account mode water characteristics and how they translate in vertical variations of properties. That is, to look for extreme values of the second derivatives of properties for each single profile and accordingly identify the depths of any sharp gradient change. Thereby, we reconstruct the global mode water pools of renewal near the surface and residence in the ocean interior. The spatial difference between these surface and subsurface pools also suggest possible mechanisms of subduction along isopycnals, which further lead to our understanding of heat content (anomalies) taken up and transported by mode waters. A recent study (Chen et al., 2021) has validated the algorithm by detecting the South Atlantic Subtropical Mode Water, in which a possible route of subduction is also inferred that is closely correlated with anticyclonic Agulhas Rings. Similarly, by co-locating mesoscale eddies derived from satellite altimetry (Laxenaire et al., 2018; 2019; 2020) and mode waters, this study further provides insights into the influence of mesoscale features on heat uptake and transport in a global picture.
Yanxu Chen
Laboratoire de Météorologie Dynamique, Ecole Normale Supérieure