RAIA.da · Data Assimilation in RAIA
7РП — „Хора“ (Действия „Мария Кюри“)
- Период
- 2012-05-01 → 2014-04-30
- Финансиране от ЕС
- 157 748 €
- Участници
- 1
- Схема
- MC-IEF
Линиите свързват координатора с партньорите.
Накратко на български
Хидродинамичните прогнози за северозападната част на Иберийския полуостров се подобряват чрез използването на група от различни модели вместо един единствен. Това помага за по-точното предвиждане на морските процеси чрез добавяне на реални наблюдения към изчисленията.
Кратко обяснение, генерирано от езиков модел по текста на CORDIS. Оригиналът е по-долу.
Резултати накратко
Data Assimilation in RAIA
The RAIA.da project concerned operational hydrodynamic forecasts in the north-western Iberian Peninsula. The objective was to improve forecasts of an implementation of the ROMS model, run by the CIIMAR group in Porto (Portugal) in the framework of the RAIA and RAIA.co projects. The original (deterministic) model needed to be replaced by an ensemble of models, each member of the ensemble being a different realization in the space of all possible models (i.e. different parameters, atmospheric forcing fields etc). Furthermore, the ensemble would be used to assimilate observations and improve the forecasts. Finally, a set of particular multi-model data assimilation techniques called “super-ensembles” would be further studied and implemented.
Текст от CORDIS, на английски · Данни: CORDIS, © Европейски съюз
Цел на проекта
The project aims at providing end-users with high-skill operational coastal ocean forecasts, for the (trans-frontier) northwestern part of the Iberian peninsula. This objective fits very well within the current needs of multiple communities (coastal and open sea management, ecosystem protection, fishing industry, maritime transport, catastrophe management, etc).The project will take place at CIMAR, Portugal, within the framework of the RAIA project (http://www.observatorioraia.org). RAIA partners provide different forecasts for the same geographical region. More specifically, different versions of the ROMS model are run concurrently. However, data is under-used: (remote-sensed and in situ observational) data assimilation is not implemented operationally, and no model fusion, ensemble modeling, or super-ensemble technique is implemented at all.The proposed project aims at replacing one of the models by an ensemble of models. Methods for generating random but physically consistent perturbations of the oceanographic variables will be researched and implemented. This will allow obtaining more reliable model error estimations; and furthermore an Ensemble Kalman filter with a realistic error covariance matrix will be implemented to assimilate observations.It has been shown that a super-ensemble (SE) of models (i.e. a weighted combination of individual models) provides forecasts with higher skill and reduced uncertainty. SE techniques are relatively new in the ocean modeling community, but their usage is expected to increase together with the number of seas covered by concurrent models. In the proposed project, SE techniques will be further developed, and new filters will be tried out to evolve the SE combination in time. SEs will be tried out on full 3D model fields.The project will be favorable to the fellow's scientific career, will provide new research results, and will also improve the operational forecasts of the studied region.
Оригинален текст от CORDIS (на английски).
Участници
- CENTRO INTERDISCIPLINAR DE INVESTIGACAO MARINHA E AMBIENTAL · MatosinhosКоординаторПортугалия
Връзки
Данни: CORDIS, © Европейски съюз