Modelling the marine ecosystem of Iberia–Biscay–Ireland (IBI) European waters for CMEMS operational applications

Abstract

Abstract. As part of the Copernicus Marine Environment Monitoring Service (CMEMS), a physical–biogeochemical coupled model system has been developed to monitor and forecast the ocean dynamics and marine ecosystem of the European waters and more specifically on the Iberia–Biscay–Ireland (IBI) area. The CMEMS IBI coupled model covers the north-east Atlantic Ocean from the Canary Islands to Iceland, including the North Sea and the western Mediterranean, with a NEMO-PISCES 1∕36∘ model application. The coupled system has been providing 7 d weekly ocean forecasts for CMEMS since April 2018. Prior to its operational launch, a pre-operational qualification simulation (2010–2016) has allowed assessing the model's capacity to reproduce the main biogeochemical and ecosystem features of the IBI area. The objective of this paper is then to describe the consistency and skill assessment of the PISCES biogeochemical model using this 7-year qualification simulation. The model results are compared with available satellite estimates as well as in situ observations (ICES, EMODnet and BGC-Argo). The simulation successfully reproduces the spatial distribution and seasonal cycles of oxygen, nutrients, chlorophyll a and net primary production, and confirms that PISCES is suitable at such a resolution and can be used for operational analysis and forecast applications. This model system can be a useful tool to better understand the current state and changes in the marine biogeochemistry of European waters and can also provide key variables for developing indicators to monitor the health of marine ecosystems. These indicators may be of interest to scientists, policy makers, environmental agencies and the general public.

Comment on bg-2021-2

“…Thanks to machine learning based methods (Bittig et al, 2018;Sauzède et al, 2017), floats equipped with O 2 sensors can be additionally used to derive, vertical profiles of NO 3 , phosphate (PO 4 ), silicate (Si), alkalinity (Alk), dissolved inorganic carbon (DIC), pH and pCO 2 . All these specificities overcome the limitations of previous data sets from now and open new perspectives for the validation of BGC models (Gutknecht et al, 2019;Terzić et al, 2019).…”

“…O 2 level lower than 80 µmol kg -1 are used to characterize OMZs (Schmidtko et al, 2017). Based upon the existing literature (e.g., Aumont et al, 2015;Cossarini et al, 2019;Doney et al, 2009;Dutkiewicz et al, 2015;Gutknecht et al, 2019;Séférian et al, 2013;Terzić et al, 2019), we propose 4 graphical representations that can be used to display the novel validation metrics and to assess the skill of a model in reproducing a particular process or variable: Taylor diagrams, scatterplots, spatial maps, and time series.…”

“…PISCES has been successfully used in a variety of biogeochemical studies, both at regional and global scale (Bopp et al, 2005;Gehlen et al, 2006Gehlen et al, , 2007Gutknecht et al, 2019;Lefèvre et al, 2019;Schneider et al, 2008;Séférian et al, 2013;Steinacher et al, 2010;Tagliabue et al, 2010).…”

“…We aim to demonstrate the use of the BGC-Argo global array for the validation of BGC models at the global scale. In regional seas or enclosed basins, where a limited number of floats have been so far deployed, point-by-point model-observation comparison is possible (Gutknecht et al, 2019;. However, at the global scale, the BGC-Argo dataset provides a massive and ever-growing amount of data, and it can be difficult to manipulate this large data set, especially when it comes to evaluate a 3-D time-varying model simulation for about ten variables.…”

Middle Miocene Temperature and Productivity Evolution at a Northeast Atlantic Shelf Site (IODP U1318, Porcupine Basin): Global and Regional Changes

“…At greater depths, Labrador Sea water and Norwegian Sea Deep Water are observed (Raddatz et al., 2011). Waters are moderately productive and productivity peaks occur in spring when seasonal stratification begins and the mixed layer depth becomes shallower (Gutknecht et al., 2019; UNEP LME Report, 2008).…”