The oxygen deficiency index blueprint allows an economic and quick scan via baseline assessment for forecasting the risk of seasonal oxygen deficiency in the North and Baltic Seas
Abstract. Oxygen deficiency zones (ODZs) in coastal seas can become hazardous to organisms and may have severe ecological and economic consequences for the environment, the fisheries, and the tourism industries. A tight interaction between ventilation and respiration governs marine oxygen levels. Regions with high primary production and a thin water column below the seasonal mixed layer are particularly prone to the formation of oxygen deficiency. In the study of Große et al. (2016) the critical parameters of the oxygen deficiency index (ODI) were identified as stratification and primary production during the formation of oxygen deficiency in the seasonally stratified regions of the North Sea. In order to approach realistic spatio-temporal distributions of ODZs, Große et al. (2016) formulated a depth index serving as a proxy for the thickness of the water column below the mixed layer depth (MLD). Here we propose the further developed ODI to represent two differing hydrographic regimes, the North and the Baltic Seas, by using a density-based criterion of the MLD and the vertical extension of the water column between the seafloor and the bottom layer of the MLD. Moreover, we define the stratification status of the water column using continuous stratification periods of 30 days as our reference period for higher risks of developing ODZs. Different to Große et al. (2016), net primary production is not cumulated over the entire growing season but only over this reference period. With these modifications, the revised ODI offers intuitive, short-term forecasts on the areas at risk of developing oxygen deficiency in high spatio-temporal resolution for the coastal zone of the North and Baltic Seas. This allows an operational forecasting of ODZs to inform responsible authorities and civil services in advance. We propose an economic solution to assess oxygen conditions of the past, the present and test for the risk to developing ODZs in the near future. We are able to run all necessary simulations and calculations for this research on a simple laptop. We mostly used free and open software products and Open Data products. Our data set up consists of: a) Free available netCDF output files of the operational HBM-ERGOM model and b) free available data from the MARNET monitoring network, both operated by the Federal Maritime and Hydrographic Agency (BSH).
operational HBM-ERGOM model data https://www.bsh.de/DE/THEMEN/Modelle/modelle_node.html
Oceanographic data from North West Shelf and from the Baltic Sea https://www.bsh.de/EN/DATA/Climate-and-Sea/Marine_environment_monitoring_network/marine_environment_monitoring_network_node.html
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