4DVAR assimilation of multi-parameter radar observations in an explicit cloud model

Bing Wu, Johannes Verlinde, Juanzhen Sun

Research output: Contribution to conferencePaper

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 languageEnglish (US)
Pages532-533
Number of pages2
StatePublished - 1997
EventProceedings of the 1997 28th Conference on Radar Meteorology - Austin, TX, USA
Duration: Sep 7 1997Sep 12 1997

Other

OtherProceedings of the 1997 28th Conference on Radar Meteorology
CityAustin, TX, USA
Period9/7/979/12/97

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, .