International audienceIn the present study, interannual fluctuations of the mixed layer depth (MLD) in the tropical Indian Ocean are investigated from a long-term (1960-2007) eddy permitting numerical simulation and a new observational dataset built from hydrographic in situ data including Argo data (1969-2008). Both datasets show similar interannual variability patterns in relation with known climate modes and reasonable phase agreement in key regions. Due to the scarcity of the observational dataset, we then largely rely on the model to describe the interannual MLD variations in more detail. MLD interannual variability is two to four times smaller than the seasonal cycle. A large fraction of MLD interannual variations is linked to large-scale climate modes, with the exception of coastal and subtropical regions where interannual signature of small-scale structures dominates. The Indian Ocean Dipole is responsible for most variations in the 10°N-10°S band, with positive phases being associated with a shallow MLD in the equatorial and south-eastern Indian Ocean and a deepening in the south-central Indian Ocean. The El Niño signature is rather weak, with moderate MLD shoaling in autumn in the eastern Arabian Sea. Stronger than usual monsoon jets are only associated with a very modest MLD deepening in the southern Arabian Sea in summer. Finally, positive Indian Ocean Subtropical Dipoles are associated with a MLD deepening between 15 and 30°S. Buoyancy fluxes generally appear to dominate MLD interannual variations except for IOD-induced signals in the south-central Indian Ocean in autumn, where wind stirring and Ekman pumping dominate

International audienc

International audienc

Fine-scale currents, O(1–100 km, days–months), are actively involved in the transport and transformation of biogeochemical tracers in the ocean. However, their overall impact on large-scale biogeochemical cycling on the timescale of years remains poorly understood due to the multiscale nature of the problem. Here, we summarize these impacts and critically review current estimates. We examine how eddy fluxes and upscale connections enter into the large-scale balance of biogeochemical tracers. We show that the overall contribution of eddy fluxes to primary production and carbon export may not be as large as it is for oxygen ventilation. We highlight the importance of fine scales to low-frequency natural variability through upscale connections and show that they may also buffer the negative effects of climate change on the functioning of biogeochemical cycles. Significant interdisciplinary efforts are needed to properly account for the cross-scale effects of fine scales on biogeochemical cycles in climate projections. Expected final online publication date for the Annual Review of Marine Science, Volume 16 is January 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Phytoplankton biomass exhibits significant year-to-year changes and understanding these changes is crucial to fisheries management and projecting future climate. These annual changes result partly from low-frequency climate modes that also lead to variations in sea surface temperature (SST). Here we evaluate the contribution of small scales to annual fluctuations based on a global analysis of satellite observations of sea surface chlorophyll (SChl), an indicator of phytoplankton biomass, and of SST, from 1999 to 2018. We disentangle the spatio-temporal scales of variability in the timeseries, and find that besides the prominent seasonal cycle, SChl is dominated by high-frequency fluctuations (<3 months) at small spatial scales (<50 km) -which accumulates over annual scales, in contrast to SST.The results suggest that observations and models with high spatio-temporal resolutions are necessary to understand annual changes in SChl. The rapid response of SChl to small-scale physical processes, combined with intrinsic ecosystem interactions and air-sea interaction feedbacks, may explain the differences between annual variations in SST and SChl.Predicting the response of phytoplankton to climate change has important implications for biogeochemical cycling and ecosystem management 1-3 due to the key role phytoplankton play in marine food webs 4 . The continuous daily monitoring of surface chlorophyll-a (SChl), a proxy of phytoplankton biomass, from satellite radiometric measurements has been an invaluable tool to observe phytoplankton variability at the global scale over the past two decades [5][6][7][8][9][10][11][12] . As the satellite SChl timeseries grows, attempts have been made to detect climate change-driven trends [11][12][13][14][15][16] . However, this detection is made difficult by the large amplitude of natural variations, which overwhelm the long-term changes [16][17][18] . It is therefore essential to fully characterize natural SChl variability in order to attribute long-term changes to climate variability and/or anthropogenic forcing.