# Monitoring and Forecasting Green Tide in the Yellow Sea Using Satellite Imagery
## 4 Results
### Green Tide Growth Curve
We found that the start percentile \((P_{start})\) and dissipation percentile \(\left(P_{dissipation}\right)\) were related to the flatness of the Gaussian fit curve \(y^{\prime}\) of the first-order derivative of the growth curve; therefore, we established the relationship between the start and dissipation percentiles and the kurtosis coefficient \(g_{2}\) of \(y^{\prime}\) to better infer the start and dissipation times of the green tide. First, the kurtosis coefficient of the first derivative \(y^{\prime}\) of the growth curve was calculated as in Equation, and the input data were the growth curve. The relationships between the kurtosis coefficient of Gaussian fit curve \(y^{\prime}\) of the first derivative of the growth curve and the start and dissipation percentiles were established separately and found to be roughly exponential. According to the principle of the least squares method, the curves of the start and dissipation percentiles and the kurtosis coefficients were fitted, as shown in Figure 12. By combining these relationships with the growth curve fitted using the approximate nonlinear method, it was possible to predict the start and dissipation times of the Yellow Sea green tide and the extent of the green tide bloom based on the predicted ACA of the green tide. These predictions provide a reference basis for future work on green tide management. Figure 12: Curvilinear relationships between the start and dissipation percentiles and the kurtosis coefficients ((**a**) is curvilinear relationships between the start percentiles and the kurtosis coefficients and (**b**) is curvilinear relationships between the dissipation percentiles and the kurtosis coefficients). \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Year**} & \multirow{2}{*}{**Start Time**} & **Starting** & **Dissipation Time** & **Dissipation** \\  & & **Percentile** & & **Percentile** \\ \hline
2008 & May \(\bigstar\) & 0.832\% & August \(\bigstar\) & 97.64\% \\
2009 & 24 March \(\bigstar\) & 0.000\% & Late August \(\bigstar\) & 90.38\% \\
2010 & 20 April \(\bigstar\) & 0.000\% & Mid-August \(\bigstar\) & 100.0\% \\
2011 & 27 May \(\bigstar\) & 0.000\% & 21 August \(\bigstar\) & 100.0\% \\
2012 & Late March \(\bigstar\) & 0.000\% & 30 August \(\bigstar\) & 100.0\% \\
2013 & Mid to late March \(\bigstar\) & 0.000\% & Mid-August \(\bigstar\) & 99.98\% \\
2014 & 30 April \(\bigstar\) & 0.115\% & 8 September \(\bigstar\) & 99.60\% \\
2015 & Mid-April \(\bigstar\) & 3.934\% & 14 August \(\bigstar\) & 99.99\% \\
2016 & Mid-April \(\bigstar\) & 1.773\% & 25 August \(\bigstar\) & 100.0\% \\
2017 & Mid-April \(\bigstar\) & 0.000\% & 24 July \(\bigstar\) & 100.0\% \\
2018 & 4 May \(\bigstar\) & 0.000\% & 1 August \(\bigstar\) & 100.0\% \\
2019 & Mid to late April \(\bigstar\) & 0.000\% & 1 August \(\bigstar\) & 100.0\% \\
2020 & 19 March \(\bigstar\) & 4.767\% & 20 July \(\bigstar\) & 88.92\% \\
2021 & Mid-April \(\bigstar\) & 1.085\% & Late August \(\bigstar\) & 97.28\% \\ \hline \hline \end{tabular} Note. \(\bigstar\) indicates data from the China Marine Disaster Bulletin; \(\bigstar\) indicates data from the Jiangsu Provincial Marine Disaster Bulletin.  
\end{table} 
Table 8: Start and dissipation times of the green tide event.