Abstract
A four-dimensional variational (4DVAR) data assimilation technique, based on an anelastic model and its adjoint, is used to retrieve the wind, temperature, pressure and microphysical fields in moist convective systems from single or multiple-Doppler radar observation. The microphysical parameterization in this model incorporated the liquid phase physics. This model is applied to a severe thunderstorm observed during the MIST experiment. Observations have indicated that ice process played a significant role in the precipitation processes in its life-time period. To have a better microphysical retrieval, the differential reflectivity (ZDR) observation from the multi-parameter radar (CP2) is included.
| Original language | English (US) |
|---|---|
| Pages | 532-533 |
| Number of pages | 2 |
| State | Published - 1997 |
| Event | Proceedings of the 1997 28th Conference on Radar Meteorology - Austin, TX, USA Duration: Sep 7 1997 → Sep 12 1997 |
Other
| Other | Proceedings of the 1997 28th Conference on Radar Meteorology |
|---|---|
| City | Austin, TX, USA |
| Period | 9/7/97 → 9/12/97 |
All Science Journal Classification (ASJC) codes
- Atmospheric Science
- Electrical and Electronic Engineering
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Wu, B., Verlinde, J., & Sun, J. (1997). 4DVAR assimilation of multi-parameter radar observations in an explicit cloud model. 532-533. Paper presented at Proceedings of the 1997 28th Conference on Radar Meteorology, Austin, TX, USA, .