Integration of Weather Research and Forecasting (WRF) model with regional coastal ecosystem model to simulate the hypoxic conditions
| Autor: | Takayuki Suzuki, Muhammad Ali Hafeez, Yoshitaka Matsuzaki, Abdul Moiz, Yoshiyuki Nakamura, Kangnian Wang, Tetsunori Inoue |
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| Rok vydání: | 2020 |
| Předmět: |
Global Forecast System
Biogeochemical cycle Environmental Engineering 010504 meteorology & atmospheric sciences Meteorology 010501 environmental sciences 01 natural sciences Pollution Wind speed Waves and shallow water Automated Meteorological Data Acquisition System Ecosystem model Weather Research and Forecasting Model Environmental Chemistry Environmental science Ecosystem Waste Management and Disposal Physics::Atmospheric and Oceanic Physics 0105 earth and related environmental sciences |
| Zdroj: | The Science of the total environment. 771 |
| ISSN: | 1879-1026 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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