Graduate School of Urban Innovation, Yokohama National University, Tokiwadai 79-5, Hodogaya, Yokohama 240-8501, Japan.
Faculty of Urban Innovation, Yokohama National University, Tokiwadai 79-5, Hodogaya, Yokohama 240-8501, Japan.
Sci Total Environ. 2021 Jun 1;771:145290. doi: 10.1016/j.scitotenv.2021.145290. Epub 2021 Jan 22.
Regional ocean models require accurate weather data for atmospheric boundary conditions such as air temperature, wind speed, and direction to simulate the coastal environment. In this study, a numerical modelling framework was developed to simulate different physical, chemical, and biological processes in a semi-enclosed coastal ecosystem by integrating the Weather Research and Forecasting (WRF) model with a 3D hydrodynamic and ecosystem model (Ise Bay Simulator). The final analytic data of the global forecast system released by the National Centers for Environmental Prediction with a 0.25° horizontal resolution was used as an atmospheric boundary condition for the WRF model to dynamically downscale the weather information to a spatial and temporal fine resolution. This modelling framework proved to be an effective tool to simulate the physical and biogeochemical processes in a semi-enclosed coastal embayment. The WRF-driven ecosystem simulation and recorded Automated Meteorological Data Acquisition System (AMeDAS)-driven ecosystem simulation results were further compared with the observed data. The performance of both the recorded AMeDAS and WRF generated weather datasets were equally good, and more than 80% of the variation in bottom dissolved oxygen for shallow water and more than 90% for deep water was reproduced.
区域海洋模式需要准确的天气数据作为大气边界条件，例如气温、风速和风向，以模拟沿海环境。在这项研究中，通过将天气研究和预报（WRF）模型与三维水动力和生态系统模型（海湾模拟器）集成，开发了一个数值建模框架，以模拟半封闭沿海生态系统中的不同物理、化学和生物过程。国家环境预报中心发布的全球预测系统的最终分析数据，水平分辨率为 0.25°，被用作 WRF 模型的大气边界条件，以便将天气信息动态下转换为时空精细分辨率。该建模框架被证明是模拟半封闭沿海海湾物理和生物地球化学过程的有效工具。WRF 驱动的生态系统模拟和记录的自动气象数据采集系统（AMeDAS）驱动的生态系统模拟结果与观测数据进行了进一步比较。记录的 AMeDAS 和 WRF 生成的天气数据集的性能同样良好，浅水底层溶解氧变化的 80%以上和深水底层溶解氧变化的 90%以上得到了再现。
