3DVAR and cloud analysis with WSR-88D Level-II data for the prediction of tornadic thunderstorms.
| dc.contributor.advisor | Xue, Ming, | en_US |
| dc.contributor.author | Hu, Ming. | en_US |
| dc.date.accessioned | 2013-08-16T12:19:59Z | |
| dc.date.available | 2013-08-16T12:19:59Z | |
| dc.date.issued | 2005 | en_US |
| dc.description.abstract | Doppler weather radar observations play a key role in initializing convective storms within storm-scale numerical weather prediction (NWP) models. The radial velocity and reflectivity are the two main parameters measured by Doppler weather radars. Due to their indirect nature and incomplete spatial coverage, the optimal assimilation of these data remains a challenging task. | en_US |
| dc.description.abstract | For each of these three cases, the impact of full-volume WSR-88D radar reflectivity and radial velocity data, individually or in combination, on the assimilated initial condition and the subsequent forecast of the individual storm cells is analyzed in detail, usually through a comprehensive set of numerical experiments. | en_US |
| dc.description.abstract | For the Fort Worth case, the current cloud analysis procedure in the ARPS is compared with an earlier version that was used in a previous publication, and the effects of individual modifications that lead to an overall improvement are investigated. The best configuration in this case is able to predict the morphology of individual storm cells on the 3-km grid for up to two hours and the rotating supercell characteristics of the storm that spawned two tornadoes are well captured. (Abstract shortened by UMI.) | en_US |
| dc.description.abstract | In this dissertation, the Advanced Region Prediction System (ARPS), a multiscale NWP model, together with its three-dimensional variational (3DVAR) data analysis system and a complex cloud analysis procedure is used to perform high-frequency intermittent data assimilation that includes the radial velocity and reflectivity data. The radial velocity is analyzed using the 3DVAR system that includes a mass divergence constraint for coupling wind components together, while the reflectivity is assimilated through the cloud analysis that also adjusts in-cloud temperature and moisture fields. In the 3DVAR analysis, the background error covariance is modeled using recursive filters, and a multipass strategy is employed to deal with observations representing very different scales. | en_US |
| dc.description.abstract | The assimilation and forecast system is applied to three tornadic thunderstorm cases, specifically, the 28 March 2000 Fort Worth, Texas, tornadic thunderstorm case, the 8 May 2003 Oklahoma City, Oklahoma, tornadic thunderstorm case, and the 29 May 2004 central Oklahoma tornadic thunderstorm case. In general, two one-way nested grids are used, one at a 9-km and one at a 3-km horizontal resolution, and our focus is placed on the 3-km grid which directly assimilates the radar data. | en_US |
| dc.format.extent | xix, 216 leaves : | en_US |
| dc.identifier.uri | http://hdl.handle.net/11244/955 | |
| dc.note | Source: Dissertation Abstracts International, Volume: 66-12, Section: B, page: 6673. | en_US |
| dc.note | Adviser: Ming Xue. | en_US |
| dc.subject | Doppler radar. | en_US |
| dc.subject | Weather forecasting. | en_US |
| dc.subject | Physics, Atmospheric Science. | en_US |
| dc.subject | Tornadoes Texas Fort Worth. | en_US |
| dc.subject | Tornadoes Oklahoma Oklahoma City. | en_US |
| dc.thesis.degree | Ph.D. | en_US |
| dc.thesis.degreeDiscipline | School of Meteorology | en_US |
| dc.title | 3DVAR and cloud analysis with WSR-88D Level-II data for the prediction of tornadic thunderstorms. | en_US |
| dc.type | Thesis | en_US |
| ou.group | College of Atmospheric & Geographic Sciences::School of Meteorology | |
| ou.identifier | (UMI)AAI3203315 | en_US |
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