Early Warning of Harmful Algal Bloom Risk Using Satellite Ocean Color and Lagrangian Particle Trajectories
Early Warning of Harmful Algal Bloom Risk Using Satellite Ocean Color and Lagrangian Particle Trajectories
复制标题
DOI：
10.3389/fmars.2021.736262
复制
发表时间：
2021-11
期刊：
影响因子：
--
通讯作者：
Junfang Lin;P. I. Miller;B. Jönsson;M. Bedington
中科院分区：
文献类型：
--
作者：
Junfang Lin;P. I. Miller;B. Jönsson;M. Bedington
结合拉格朗日轨迹和卫星观测提供了一个新的基础，监测水的属性变化与高的时间和空间分辨率。在这项研究中，一个预测方案，综合卫星观测和拉格朗日模式数据，以更好地解释有害藻华（HAB）的风险。该算法不仅可以预测叶绿素a浓度的变化，但也改变了光谱特性的水，这是重要的不同藻类物种的卫星海洋颜色的歧视。该预测方案被应用到英国沿海沿着地区，以验证其适用性。结果表明，拉格朗日方法可以显着提高卫星产品的覆盖范围，独特的动画是有效的解释赤潮的发展。叶绿素a的预测和卫星观测之间的比较进一步证明了这种方法的有效性：r2 = 0.81和36.9%的低平均绝对百分比误差。虽然建模和方法的不确定性影响预测的准确性，但这种方法为监测海洋生态系统和支持水产养殖业提供了一个强大的工具，改进了对潜在有害藻华的早期预警。
Combining Lagrangian trajectories and satellite observations provides a novel basis for monitoring changes in water properties with high temporal and spatial resolution. In this study, a prediction scheme was developed for synthesizing satellite observations and Lagrangian model data for better interpretation of harmful algal bloom (HAB) risk. The algorithm can not only predict variations in chlorophyll-a concentration but also changes in spectral properties of the water, which are important for discrimination of different algal species from satellite ocean color. The prediction scheme was applied to regions along the coast of England to verify its applicability. It was shown that the Lagrangian methodology can significantly improve the coverage of satellite products, and the unique animations are effective for interpretation of the development of HABs. A comparison between chlorophyll-a predictions and satellite observations further demonstrated the effectiveness of this approach: r2 = 0.81 and a low mean absolute percentage error of 36.9%. Although uncertainties from modeling and the methodology affect the accuracy of predictions, this approach offers a powerful tool for monitoring the marine ecosystem and for supporting the aquaculture industry with improved early warning of potential HABs.