Assimilating a synthetic Kalman filter leaf area index series into the WOFOST model to improve regional winter wheat yield estimation
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- 作者：Jianxi Huanga ; b ; jxhuang@cau.edu.cn" class="auth_mail" title="E-mail the corresponding author ; Fernando Sedanoc ; Yanbo Huangd ; Hongyuan Maa ; Xinlu Lia ; Shunlin Liange ; c ; Liyan Tianf ; Xiaodong Zhanga ; Jinlong Fang ; Wenbin Wuh
- 关键词：WOFOST ; Leaf area index ; Kalman filter ; Ensemble Kalman filter ; Winter wheat ; Yield estimation
- 刊名：Agricultural and Forest Meteorology
- 出版年：2016
- 出版时间：15 January 2016
- 年：2016
- 卷：216
- 期：Complete
- 页码：188-202
- 全文大小：5129 K
文摘
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We estimated regional wheat yields by assimilating satellite LAI datasets.
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We generated a synthetic LAI time series using a Kalman filter (KF) algorithm.
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We assimilated the synthetic LAI series into the WOFOST crop model.
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Assimilating the synthetic KF LAI series reduced the estimation error.
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Accurately assessing LAI is the key to successful data assimilation.