Merging bio-optical data from Biogeochemical-Argo floats and models in marine biogeochemistry

In numerical models for marine biogeochemistry, bio-optical data, such as measurements of the light field, may be important descriptors of the dynamics of primary producers and ultimately of oceanic carbon fluxes. However, the paucity of field observations has limited the integration of bio-optical data in such models so far. New autonomous robotic platforms for observing the ocean, i.e., Biogeochemical-Argo floats, have drastically increased the number of vertical profiles of irradiance, photosynthetically available radiation (PAR) and algal chlorophyll concentrations around the globe independently of the season. Such data may be therefore a fruitful resource to improve performances of numerical models for marine biogeochemistry. Here we present a work that integrates into a 1-dimensional model 1314 vertical profiles of PAR acquired by 31 BGC-Argo floats operated in the Mediterranean Sea between 2012 and 2016 to simulate the vertical and temporal variability of algal chlorophyll concentrations. In addition to PAR as input, alternative light and vertical mixing models were considered. We evaluated the models’ skill to reproduce the spatial and temporal variability of deep chlorophyll maxima as observed by BGC-Argo floats. The assumptions used to set up the 1-D model are validated by the high number of co-located in-situ measurements. Our results illustrate the key role of PAR and vertical mixing in shaping the vertical dynamics of primary produces in the Mediterranean Sea. Moreover, we demonstrate the importance of modeling the diel cycle to simulate chlorophyll concentrations in stratified waters at the surface.

Abstract. New autonomous robotic platforms for observing the ocean, i.e. Biogeochemical-Argo (BGC-Argo) floats, have drastically increased the number of vertical profiles of irradiance, photosynthetically available radiation (PAR), and algal chlorophyll concentrations around the globe independent of the season. Such data may therefore be a fruitful resource to improve performances of numerical models for marine biogeochemistry. Here we present a work that integrates 1314 vertical profiles of PAR acquired by 31 BGC-Argo floats operated in the Mediterranean Sea between 2012 and 2016 into a one-dimensional model to simulate the vertical and temporal variability of algal chlorophyll concentrations. The model was initially forced with PAR measurements to assess its skill when using quality-controlled light profiles, and subsequently with a number of alternative bio-optical models to analyse the model capability when light observations are not available. Model outputs were evaluated against co-located chlorophyll profiles measured by BGC-Argo floats. Results highlight that the data-driven model is able to reproduce the spatial and temporal variability of deep chlorophyll maxima depth observed at a number of Mediterranean sites well. Further, we illustrate the key role of PAR and vertical mixing in shaping the vertical dynamics of primary producers in the Mediterranean Sea. The comparison of alternative bio-optical models identifies the best simple one to be used, and suggests that model simulations benefit from considering the diel cycle.