Assessment of 1-dimensional marine ecosystem model in reproducing the seasonal patterns in the Yellow Sea Large Marine Ecosystem
- Korea Institute of Ocean Science and Technology (kwon@kiost.ac.kr)
The large marine ecosystems (LMEs) are described as regional units for the marine research, monitoring, and management. The Yellow Sea (YS), located between Korean Peninsula and continental North China, is known as one of the most important LMEs in the world due to its high biodiversity and complex food web dynamics. Yellow Sea Cold Water Mass (also called YSCWM) formed by the remnant of winter cold water (<~11 °C) in the central Yellow Sea remains throughout the summer, which is a striking hydrological phenomenon in the Yellow Sea and has important effects on the marine ecosystem. Against this background, we undertook a modelling study as a part of a research program of Korea Institute of Ocean Science and Technology (KIOST) to improve the understanding of the ecosystem structure and function and the physical-biological processes in the YS and to predict changes in the the fishery resources under future climate change scenarios. First of all, we applied the 1-dimensional marine ecosystem model (ERSEM-GOTM) to the station (35°N, 124°E) near the central YS affected by the YSCWM. Some inconsistencies between the model and the observations were founded: For examples, while primary production and bacteria carbon mass were overestimated in the model, the zooplankton carbon mass remaining high even after summer season were not represented, which shows clearly the need for model improvements to better capture the cycling of the YS biogeochemistry. Here we present the evaluation of the main aspects of the model behavior and discuss how we optimize the model performance for proper representation of the YS system.
How to cite: Kwon, Y. S., Kang, H., Choi, D. H., Noh, J. H., Lee, Y., and Seo, O. H.: Assessment of 1-dimensional marine ecosystem model in reproducing the seasonal patterns in the Yellow Sea Large Marine Ecosystem, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-10388, https://doi.org/10.5194/egusphere-egu23-10388, 2023.