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Real Challenge of Data Assimilation for Tornadogenesis

  • Yoshi K. Sasaki

Abstract

Successful recent numerical simulation of tornadogenesis with horizontal resolution of the order of 10 m, O(10 m), and associated temporal resolution of O (0.1 s and 0.01 s for a time-split scheme) requires a vast amount of computer time, impractical to use the simulation model for the model constraint of variational data assimilation and ensemble Kalman filter.

Also, recent advanced observations such as phased array radar have revealed spatial and temporal details of the similar high resolutions important for tornadogenesis, which should be properly reflected in the data assimilation.

To deal with them, data assimilation for operational uses requires special strategy. The author discusses, in this article, one promising strategy, especially use of the entropic balance model, which sounds computationally practical in variational data assimilation.

The entropic balance theory with entropic source and sink simplification is favorably compared to other historically proposed tornadogenesis theories and models. The theory explains the overshooting of hydrometeors against head-wind upper level westerlies and middle-level south-westerlies, mesocyclone, rear frank downdraft and tornado development. Furthermore, the theory suggests transition from dipole structure of early stage to monopole type mature stage, similar to an attractor of nonlinear system, of tornadogenesis, which explains of tilting of tornado vortex axis.

It is a real challenge to develop an operational data assimilation technology for accurate diagnosis and prediction of tornadogenesis.

Keywords

Data Assimilation Vortex Tube Convective Storm Variational Data Assimilation Environmental Wind 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Yoshi K. Sasaki
    • 1
  1. 1.School of Meteorology National Weather CenterThe University of OklahomaNormanUSA

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