加速包络卡尔曼滤波的自旋启动
Accelerating the spin-up of Ensemble Kalman Filtering
摘要：
提出了一种改进基于集合的卡尔曼滤波器在初始启动阶段性能的方案。通过应用无成本的集合卡尔曼平滑器，该方案允许集合的模型解与由一些观测提供的真实动态“原地运行”。该方案的结果进行了研究与本地包络变换卡尔曼滤波器（LETKF）实现准地转模式，其原始框架需要一个很长的自旋时，从冷启动初始化。结果表明，它是可能的旋转LETKF和有一个快速收敛到最佳水平的误差。额外的计算只需要在初始自旋，因为该计划恢复到原来的LETKF后，“运行到位”实现。
英文摘要：
A scheme is proposed to improve the performance of the ensemble-based Kalman Filters during the initial spin-up period. By applying the no-cost ensemble Kalman Smoother, this scheme allows the model solutions for the ensemble to be "running in place" with the true dynamics, provided by a few observations. Results of this scheme are investigated with the Local Ensemble Transform Kalman Filter (LETKF) implemented in a Quasi-geostrophic model, whose original framework requires a very long spin-up time when initialized from a cold start. Results show that it is possible to spin up the LETKF and have a fast convergence to the optimal level of error. The extra computation is only required during the initial spin-up since this scheme resumes to the original LETKF after the "running in place" is achieved.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
