Nick Pedatella (NSF, NCAR/HAO, USA) wird auf unserem IAP-Kolloquium einen Vortrag zum Thema "Development and Applications of Data Assimilation for Whole Atmosphere Models" halten.

Zusammenfassung:

Data assimilation is the process of statistically combining observations with a background model to determine a best estimate of the current state. Data assimilation is widely used in the lower atmosphere for weather prediction and scientific research. However, it has yet to be widely adopted at higher altitudes, despite its potential for improving space weather specification and forecasting. In order to improve representation of variability in the middle and upper atmosphere, as well as provide initial conditions for studying predictability of the near-Earth space weather, the data assimilation capability was developed for the Whole Atmosphere Community Climate Model with thermosphere-ionosphere eXtension (WACCM-X) using the Data Assimilation Research Testbed (DART) ensemble Kalman filter. A brief overview of the development of WACCMX+DART will be provided, including how the application of data assimilation techniques differs between the lower and upper atmospheres. Drawing on several examples, it will be shown that using data assimilation can improve representation of the variability in the middle and upper atmospheres, including for chemical transport, dynamical variability, and thermosphere neutral density. The use of WACCMX+DART for providing initial conditions for forecasting the space environment will also be presented.