Impacts of 4D-VAR Assimilation of Airborne Doppler Radar Observations on Numerical Simulations of the Genesis of Typhoon Nuri (2008)
Abstract
The Weather Research and Forecasting model and its four-dimensional variational data assimilation system are employed to examine the impact of airborne Doppler radar observations on predicting the genesis of Typhoon Nuri (2008). The ELDORA airborne radar data, collected during the Office of Naval Research-sponsored Tropical Cyclone Structure 2008 field experiment, are used for data assimilation experiments. Two assimilation methods are evaluated and compared, namely, the direct assimilation of radar-measured radial velocity and the assimilation of three-dimensional wind analysis derived from the radar radial velocity. Results show that direct assimilation of radar radial velocity leads to better intensity forecasts, as it enhances the development of convective systems and improves the inner core structure of Nuri, whereas assimilation of the radar-retrieved wind analysis is more beneficial for tracking forecasts, as it results in improved environmental flows. The assimilation of both the radar-retrieved wind and the radial velocity can lead to better forecasts in both intensity and tracking, if the radial velocity observations are assimilated first and the retrieved winds are then assimilated in the same data assimilation window. In addition, experiments with and without radar data assimilation lead to developing and nondeveloping disturbances for Nuri's genesis in the numerical simulations. The improved initial conditions and forecasts from the data assimilation imply that the enhanced midlevel vortex and moisture conditions are favorable for the development of deep convection in the center of the pouch and eventually contribute to Nuri's genesis. The improved simulations of the convection and associated environmental conditions produce enhanced upper-level warming in the core region and lead to the drop in sea-level pressure.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2014
- Bibcode:
- 2014AGUFM.A33K3346P
- Keywords:
-
- 3315 Data assimilation;
- 3360 Remote sensing;
- 3372 Tropical cyclones;
- 4313 Extreme events