| contributor author | Hodyss, Daniel;Anderson, Jeffrey L.;Collins, Nancy;Campbell, William F.;Reinecke, Patrick A. | |
| date accessioned | 2018-01-03T11:03:09Z | |
| date available | 2018-01-03T11:03:09Z | |
| date copyright | 8/22/2017 12:00:00 AM | |
| date issued | 2017 | |
| identifier other | mwr-d-17-0089.1.pdf | |
| identifier uri | http://138.201.223.254:8080/yetl1/handle/yetl/4246600 | |
| description abstract | AbstractIt 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. | |
| publisher | American Meteorological Society | |
| type | Journal Paper | |
| journal volume | 145 | |
| journal issue | 11 | |
| journal title | Monthly Weather Review | |
| identifier doi | 10.1175/MWR-D-17-0089.1 | |
| journal fristpage | 4467 | |
| journal lastpage | 4479 | |
| tree | Monthly Weather Review:;2017:;volume( 145 ):;issue: 011 | |
| contenttype | Fulltext | |
