| 基于集合卡尔曼滤波的太湖叶绿素a浓度同化试验系统设计及实现 |
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| 作者姓名： | 王泽人 马荣华 段洪涛 张玉超 齐琳 |
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| 作者单位： | 1. 中国科学院南京地理与湖泊研究所湖泊与环境国家重点实验室, 南京 210008;
2. 中国科学院大学, 北京 100049 |
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| 基金项目： | 中国科学院知识创新重要方向性项目(KZCX2-XY-QN311,KZCX2-EW-QN308);国家自然科学基金(41171271,41171273)资助 |
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| 摘 要： | 以太湖作为研究区,把数据同化技术引入蓝藻水华预测研究,设计并实现了太湖叶绿素a质量浓度同化试验系统,该系统结合基于WASP原理的二维水动力水质耦合模型,采用集合卡尔曼滤波方法同化空间分辨率为250 m的MODIS叶绿素a质量浓度反演数据. 结果表明,利用同化技术将衡量模型预报值、分析值和观测值之间的偏差指标RMSE减小了15.5%,可以有效地提高叶绿素a质量浓度的预测精度.
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| 关 键 词： | 数据同化 集合卡尔曼滤波 叶绿素a 藻华预测 |
| 收稿时间： | 2012-11-05 |
| 修稿时间： | 2013-02-25 |
Design and implementation of an experimental data assimilation system for chlorophyll-a in Lake Taihu based on the ensemble Kalman filter |
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| Authors: | WANG Ze-Ren MA Rong-Hua DUAN Hong-Tao ZHANG Yu-Chao QI Lin |
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| Institution: | 1. State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China;
2. University of Chinese Academy of Sciences, Beijing 100049, China |
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| Abstract: | We develop a novel data assimilation approach for the prediction of algal blooms in Lake Taihu. Our approach is based on a 2D ecological model which combines a physical model, 250 m MODIS inversion chlorophyll-a data, and an ensemble Kalman filter (EnKF) analysis scheme. Our results indicate that the data assimilation approach is reliable for predicting algal blooms in these complex waters. |
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| Keywords: | data assimilation EnKF Chlorophyll-a algal bloom forecast |
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