Frontiers
Browse
Table_1_The second-generation real-time ecological environment prediction system for the Guangdong–Hong Kong–Marco Greater Bay Area: Model setup, vali.docx (14.06 kB)

Table_1_The second-generation real-time ecological environment prediction system for the Guangdong–Hong Kong–Marco Greater Bay Area: Model setup, validation, improvements, and online visualization.docx

Download (14.06 kB)
dataset
posted on 2023-02-27, 04:13 authored by Lin Luo, Zhao Meng, Weiwei Ma, Jingwen Huang, Youchang Zheng, Yang Feng, Yineng Li, Yonglin Liu, Yuanguang Huang, Yuhang Zhu

With the rapidly growing population and socioeconomic development of the Guangdong–Hong Kong–Marco Greater Bay Area of China, inputs of diverse contaminants have rapidly increased. This poses threats to the water quality of the Pearl River Estuary (PRE) and adjacent seas. To provide valuable information to assist the governors, stakeholders, and decision-makers in tracking changes in environmental conditions, daily nowcasts and two-day forecasts from the ecological prediction system, namely the Coupled Great Bay Ecological Environmental Prediction System (CGEEPS), has been setup. These forecast systems have been built on the Coupled Ocean–Atmosphere–Wave–Sediment Transport modelling system. This comprises an atmospheric Weather Research Forecasting module and an oceanic Regional Ocean Modelling System module. Daily real-time nowcasts and 2-day forecasts of temperature, salinity, NO2 + NO3, chlorophyll, and pH are continuously available. Visualizations of the forecasts are available on a local website (http://www.gbaycarbontest.xyz:8008/). This paper describes the setup of the environmental forecasting system, evaluates model hindcast simulations from 2014 to 2018, and investigates downscaling and two-way coupling with the regional atmospheric model. The results shown that though CGEEPS lacks accuracy in predicting the absolute value for biological and biogeochemical environmental variables. It is quite informative to predict the spatio-temporal variability of ecological environmental changes associated with extreme weather events. Our study will benefit of developing real-time marine biogeochemical and ecosystem forecast tool for oceanic regions heavily impact by extreme weathers.

History