HR: 09:16h
AN: A11G-06    [Abstracts]
TI: Ensemble-based data assimilation for convective-resolvimg hurricane predictions: Impacts of assimilating ground-based and airborne radar observations during RAINEX
AU: * Zhang, F
EM: fzhang@tamu.edu
AF: Texas A&M University, Mail Stop 3150, College Station, TX 77843-3150,
AU: Weng, Y
EM: yhweng@ariel.met.tamu.edu
AF: Texas A&M University, Mail Stop 3150, College Station, TX 77843-3150,
AU: Meng, Z
EM: zmeng@tamu.edu
AF: Texas A&M University, Mail Stop 3150, College Station, TX 77843-3150,
AU: Chen, Y
EM: yochen@ucar.edu
AF: NCAR, P.O. Box 3000, Boulder, CO 80307-3000,
AB: The ensemble-based data assimilation, commonly known as ensemble-Kalman filter or EnKF, has recently been demonstrated to be an effective and maturing assimilation technique with simulated and real observations for NWP across a range of scales. The current study examines the impacts of assimilating both ground-based and airborne Doppler radar observations as well as other convential data in the initiation and prediction of Hurricane Katrina (2005) with an WRF-based EnKF with model grid spacing down to 1.5 km. Despite some sensitivities to the number of observations to be assimilated (after quality control and data thinning) and the radius of influence of a given observation, assimilation of both the ground-based and airborne radar observations from RAINEX is very beneficial for initializing the hurricane near its observed intensity with realistic asymmetry and for subsequent ensemble forecast (or forecast from ensemble mean analysis). For example, forecast from a mean EnKF analysis that assimilates both the KMAX and KBYX Doppler radar observations at 00Z on 26 August 2005 tracks the observed hurricane position very closely and brings the hurricane directly to New Orleans in 96 h. Moreover, assimilation of raw airborne Doppler wind observations from 15 to 18Z 27 August ensure the hot-start of a Category 3 hurricane in near observed intensity without commonly used bogussing or surgical relocation techniques. We are currently exploring the best configurations and formulations with the EnKF framework for cloud-resolving hurricane initiation and prediction thorugh assimilating both synthetic and real observations. Ultimately, we plan to explore the structure, dynamics and predictability of hurricanes through assimilating all available observations during RAINEX and to determine minimum sufficient observations for monitoring and predicting tropical cyclones before diminishing returns.
DE: 3315 Data assimilation
DE: 3329 Mesoscale meteorology
DE: 3374 Tropical meteorology
SC: Atmospheric Sciences [A]
MN: 2007 Fall Meeting