Accounting for Correlated Observation Error in a Dual-Formulation 4D Variational Data Assimilation System
Abstract
Appropriate specification of the error statistics for both observational data and short-term forecasts is necessary to produce an optimal analysis. Observation error stems from instrument error, forward model error, and error of representation. All sources of observation error, particularly error of representation, can lead to nonzero correlations. While correlated forecast error has been accounted for since the early days of atmospheric data assimilation, observation error has typically been treated as uncorrelated until relatively recently. Thinning, averaging, and/or inflation of the assigned observation error variance have been employed to compensate for unaccounted error correlations, especially for high-resolution satellite data.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Mar 01, 2017
- Source ID
- 10.1175/mwr-d-16-0240.1
Entities
People
- Benjamin Ruston
- Elizabeth A. Satterfield
- Nancy L. Baker
- William F. Campbell
Organizations
- Office of Naval Research
- United States Naval Research Laboratory