 |
| Titel |
Physically-based data assimilation |
| VerfasserIn |
G. Levy, M. Coon, G. Nguyen, D. Sulsky |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1991-959X
|
| Digitales Dokument |
URL |
| Erschienen |
In: Geoscientific Model Development ; 3, no. 2 ; Nr. 3, no. 2 (2010-11-29), S.669-677 |
| Datensatznummer |
250000962
|
| Publikation (Nr.) |
 copernicus.org/gmd-3-669-2010.pdf |
|
|
|
|
|
| Zusammenfassung |
| Ideally, a validation and assimilation scheme should maintain the physical
principles embodied in the model and be able to evaluate and assimilate lower
dimensional features (e.g., discontinuities) contained within a bulk
simulation, even when these features are not directly observed or represented
by model variables. We present such a scheme and suggest its potential to
resolve or alleviate some outstanding problems that stem from making and
applying required, yet often non-physical, assumptions and procedures in
common operational data assimilation. As proof of concept, we use a sea-ice
model with remotely sensed observations of leads in a one-step assimilation
cycle. Using the new scheme in a sixteen day simulation experiment introduces
model skill (against persistence) several days earlier than in the control
run, improves the overall model skill and delays its drop off at later stages
of the simulation. The potential and requirements to extend
this scheme to different applications, and to both empirical and statistical
multivariate and full cycle data assimilation schemes, are discussed. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|