Quadratic Polynomial Regression Using Serial Observation Processing: Implementation within DART
Abstract
It is well known that the ensemble-based variants of the Kalman filter may be thought of as producing a state estimate that is consistent with linear regression. Here, it is shown how quadratic polynomial regression can be performed within a serial data assimilation framework. The addition of quadratic polynomial regression to the Data Assimilation Research Testbed (DART) is also discussed and its performance is illustrated using a hierarchy of models from simple scalar systems to a GCM.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Nov 01, 2017
- Source ID
- 10.1175/mwr-d-17-0089.1
Entities
People
- Daniel Hodyss
- Jeffrey L. Anderson
- Nancy Collins
- Patrick A. Reinecke
- William F. Campbell
Organizations
- National Center for Atmospheric Research
- Office of Naval Research Global
- United States Naval Research Laboratory