Ocean initialization for seasonal forecasts

Link:
Autor/in:
Erscheinungsjahr:
2009
Medientyp:
Text
Schlagworte:
  • Data assimilation
  • Kalman filter
  • Four-dimensional variational
  • Climate Models
  • Model
  • Rainfall
  • Data assimilation
  • Kalman filter
  • Four-dimensional variational
  • Climate Models
  • Model
  • Rainfall
Beschreibung:
  • Several operational centers routinely issue seasonal forecasts of Earth's climate using coupled ocean-atmosphere models, which require near-realtime knowledge of the state of the global ocean. This paper reviews existing ocean analysis efforts aimed at initializing seasonal forecasts. We show that ocean data assimilation improves the skill of seasonal forecasts in many cases, although its impact can be overshadowed by errors in the coupled models. The current practice, known as "uncoupled" initialization, has the advantage of better knowledge of atmospheric forcing fluxes, but it has the shortcoming of potential initialization shock. In recent years, the idea of obtaining truly "coupled" initialization, where the different components of the coupled system are well balanced, has stimulated several research activities that will be reviewed in light of their application to seasonal forecasts. © 2009 by The Oceanography Society. All rights reserved.
Lizenz:
  • info:eu-repo/semantics/openAccess
Quellsystem:
Forschungsinformationssystem der UHH
Interne Metadaten
Quelldatensatz
oai:www.edit.fis.uni-hamburg.de:publications/efe8af2c-e872-4525-b6c4-79442eb714af