Application of a dual unscented Kalman filter for simultaneous state and parameter estimation in problems of surface-atmosphere exchange
Application of a dual unscented Kalman filter for simultaneous state and parameter estimation in problems of surface-atmosphere exchange
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DOI：
10.1029/2005jd006021
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发表时间：
2006-04-22
影响因子：
4.4
通讯作者：
Hollinger, DY
中科院分区：
文献类型：
--
作者：
Gove, JH;Hollinger, DY
[1] 双无味卡尔曼滤波器 (UKF) 用于将在美国缅因州 Howland AmeriFlux 站点的云杉铁杉森林中测量的净二氧化碳交换 (NEE) 数据吸收到一个简单的生理模型中，以填补涡流时间序列中的空白。除了填补测量记录中的空白之外，UKF 方法还提供模型参数和不确定性的连续估计。该过程明确识别测量数据和模型结构中的不确定性，提供近似、有效的最佳状态和参数估计，与许多以前的间隙填充方法相比，主观性更少。双 UKF 是一种递归预测校正器估计方法，其中噪声测量数据用于连续更新所需状态的非线性过程模型预测，在本例中为净生态系统交换等。在双方法中同时运行两个并行滤波器，一个用于状态，另一个用于参数估计。无味变换采用联合密度中“西格玛点”的确定性采样，捕获二阶分布的前两个矩。非线性过程模型应用于这些西格玛点，以在过滤器框架内传播联合密度。UKF 使用夜间数据对 2000 年豪兰森林的年度 NEE 估计总计为 296.4 +/- 2.4 g 碳 m(-2)（平均值 +/- 标准差）当动量通量 (u*) 的平方根超过 0.25 m s(-1) 时，该 NEE 值比之前的估计值高出约 9%，其中模型估计值对接受或拒绝夜间通量数据的阈值（“u* 阈值”）很敏感，而之前的估计值则由 u* 阈值的选择决定。
[ 1] A dual unscented Kalman filter (UKF) was used to assimilate net CO2 exchange ( NEE) data measured over a spruce-hemlock forest at the Howland AmeriFlux site in Maine, USA, into a simple physiological model for the purpose of filling gaps in an eddy flux time series. In addition to filling gaps in the measurement record, the UKF approach provides continuous estimates of model parameters and uncertainty. The process explicitly recognizes uncertainty in the measurement data and model structure, providing approximate, effectively optimal state and parameter estimates with less subjectivity than in many previous gap-filling methods. The dual UKF is a recursive predictor-corrector estimation method whereby noisy measurement data are used to continuously update nonlinear process model predictions of the desired states, in this case net ecosystem exchange, among others. Two parallel filters are run simultaneously in the dual approach, one for state and the other for parameter estimation. The unscented transformation employs a deterministic sampling of "sigma points'' from the joint density that captures the first two moments of the distribution to the second order. Nonlinear process models are applied to these sigma points to propagate the joint density within the filter framework. The UKF estimate of annual NEE in 2000 at the Howland Forest totaled - 296.4 +/- 2.4 g carbon m(-2) ( mean +/- standard deviation) using nocturnal data when the square root of the momentum flux (u*) exceeded 0.25 m s(-1). This NEE value is about 9% higher than a previous estimate where gaps were filled by physiological models fitted to monthly, seasonal, and annual data. Model estimates are sensitive to the threshold set for accepting or rejecting nocturnal flux data ("u* threshold''), and we show that uncertainty in annual estimates is dominated by the choice of u* threshold.