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University of Cambridge > Talks.cam > Quantitative Climate and Environmental Science Seminars > Spatio-temporal characteristics of mixed-layer turbulence in an energetic oceanic zone
Spatio-temporal characteristics of mixed-layer turbulence in an energetic oceanic zoneAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact phh1. The mixed layer (ML) is the ocean surface buffer layer, through which all buoyancy, momentum and gas exchanges with the atmosphere pass. One of the key aspects of the ML for the global ocean circulation is that it hosts a turbulence redistributing energy across-scales, either up- or down-scales, and significantly contributing to the global ocean energy balance. Representation of ML turbulence, in numerical models and from observations, is therefore critical for investigating global ocean circulation and climate variability. We assess the characteristics of ML turbulence and its sensitivity to spatio-temporal resolution using a numerical simulation of the Drake Passage in winter — a region and period of intense meso and submesoscale turbulence. Here we show that the modeled winter ML turbulence is accurately inferred from hourly average numerical outputs. The ML is populated by geostrophic and ageostrophic submesoscale currents having a significant KE fraction in temporal scales of 1 day-6 hours up to 3 hours. The cross-scale KE fluxes shift from intensively upscale to more weakly downscale, where the KE becomes increasingly ageostrophic (KE_ageostrophic about 0.1-0.4 of KE_geostrophic, for spatial-scales O(>6) km)). This scale correspondance highlights the contribution to upscale (geostrophic currents) and downscale (coupled geostrophic-ageostrophic currents) KE fluxes. The characteristics of the ML turbulence are highly sensitive to temporal-scales. Daily-averaged outputs fail to represent the ML turbulence and 6 hourly-averaged outputs represent an intermediate turbulent regime, between interior quasi-geostrophy theory and ML turbulence. Our results show the need for high spatio-temporal resolution (O(1) km and O(1) h) to accurately infer the ML turbulence. Our results also call for further analysis on the role of ML turbulence on the larger-scale regional dynamics of the Drake Passage. This talk is part of the Quantitative Climate and Environmental Science Seminars series. This talk is included in these lists:
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