Session

11.09.2017     10:00–12:00

Title:
MS5
Ensemble-based data assimilation and optimization in geosciences • Part I
Type:
Atmosphere / climate / weather models
Room:

In the past decade, ensemble-based data assimilation and optimization methods have received great attention from researchers in various disciplines of geosciences, given their reliable performance, reasonable computational costs, the simplicity in implementations and the ability to quantify the uncertainties of the estimates. This minisymposium will bring together researchers in the field to communicate and discuss their recent developments and applications of the ensemble-based data assimilation and optimization methods. We encourage presentations on new methodologies, ideas or perspectives, numerical algorithm implementations, and open problems and challenges in real world applications.

11.09.2017
10:00–12:00

Title:
MS5
Ensemble-based data assimilation and optimization in geosciences • Part I
Type:
Atmosphere / climate / weather models
Room:

In the past decade, ensemble-based data assimilation and optimization methods have received great attention from researchers in various disciplines of geosciences, given their reliable performance, reasonable computational costs, the simplicity in implementations and the ability to quantify the uncertainties of the estimates. This minisymposium will bring together researchers in the field to communicate and discuss their recent developments and applications of the ensemble-based data assimilation and optimization methods. We encourage presentations on new methodologies, ideas or perspectives, numerical algorithm implementations, and open problems and challenges in real world applications.


10:00–10:20
O23 An efficient state-parameter filtering scheme combining ensemble Kalman and particle filters
Boujemaa Ait-El-Fquih (Thuwal/SA)


10:20–10:40
O24 Ensemble methods for combined state and parameter estimation
Arnold Heemink (Delft/NL)


10:40–11:00
O25 Assimilating all-sky SEVIRI infrared brightness temperatures using the KENDA ensemble data assimilation system
Axel Hutt (Offenbach am Main/DE)


11:00–11:20
O26 Use of correlation-based localization for history matching seismic data
Rolf Lorentzen (Bergen/NO)


11:20–11:40
O27 A spatiotemporal stochastic model for tropical precipitation and water vapor dynamics
Scott Hottovy (Annapolis/US)