Using Improved Background-Error Covariances from an Ensemble Kalman Filter for Adaptive Observations

نویسندگان

  • THOMAS M. HAMILL
  • CHRIS SNYDER
چکیده

A method for determining adaptive observation locations is demonstrated. This method is based on optimal estimation (Kalman filter) theory; it determines the observation location that will maximize the expected improvement, which can be measured in terms of the expected reduction in analysis or forecast variance. This technique requires an accurate model for background error statistics that vary both in space and in time. Here, these covariances are generated using an ensemble Kalman filter assimilation scheme. A variant is also developed that can estimate the analysis improvement in data assimilation schemes where background error statistics are

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تاریخ انتشار 2001