Impacts of interdecadal climate variability and vertical mixing on biological production
Impacts of interdecadal climate variability and vertical mixing on biological production
Abstract:
Climate change has periodic variations with various time scales. In particular, many studies have been conducted on changes in marine ecosystems related to climate change with decadal scale climate variability, such as the Pacific Decadal Oscillation. To clarify variability of lower trophic level productivity and its controlling factor, we simulated changes in the marine ecosystem caused by interdecadal climate variability, using the JRA55-do (atmospheric dataset for driving ice-ocean model based on JRA-55) dataset from 1958 to 2018 to drive an ecosystem model, COCO-NEMURO. We compared and verified model results with time series mooring system (temperature, Chl-a, biogenic particles etc) by the Japan Agency for Marine-Earth Science and Technology (JAMSTEC) and observations of phytoplankton and zooplankton species composition data collected by the Japan Fisheries Research and Education Agency (FRA). According to our model results, sea surface temperature (SST) and productivity showed change according to PDO at the St. K2 (47N, 160E) and Oyashio region in the western sub-arctic North Pacific. In the eastern sub-arctic NP, SST trend has shown increase with decadal variations, but decrease in phytoplankton and zooplankton biomass after the mid-1970s. In the western Arctic, the simulated sea ice concentration (SST) showed negative (positive) trends on the decadal timescale. The phytoplankton biomass has also been increasing, but its trend was not so simple. We also focused on the role of internal tidal waves that contribute to the transport and mixing of nutrients supply. To examine the effect on the biogeochemical processes by the intensity of mixing and its distribution, we performed additional experiment named TED500. In TED500, vertical diffusion coefficient is parameterized based on a global map of tidal energy dissipation rate, which is estimated from a high-resolution three-dimensional tide model (Niwa and Hibiya, 2014).