Error Covariance Estimation of Mesoscale Data Assimilation
Abstract
The goal of this project is to explore and develop new methods of error covariance estimation that will provide necessary statistical descriptions of prediction and observation errors for mesoscale data assimilation. To this end, two research objectives were fulfilled: (i) The previous method of innovation (observation minus forecast) vector analysis was extended to estimate horizontal variations of prediction and observational error variances. The extended method was successfully tested with newly collected innovation data from the Navy Operational Global Atmospheric Prediction System. (ii) A non-isotropic form of error correlation function was derived for radar radial-wind analysis and was used to estimate background wind error covariance and radar radial-wind observation error covariance from radar radial-wind innovation data.
Document Details
- Document Type
- Technical Report
- Publication Date
- Apr 20, 2005
- Accession Number
- ADA433478
Entities
People
- Qin Xu
Organizations
- University of Oklahoma