The cost function is clearly not of a quadratic form in general and the conjugate gradient method minimization could be trapped into a local minimum. To enhance the ability to find the global minimum, a cycle of assimilation is performed with one additional radar volume scan introduced in each successive cycle. The analysis from the previous cycle is used as the background field and first guesses of the minimization algorithm for the next cycle. The benefit of a forward-backward feedback loop from consecutive cycles is examined. Preliminary results, performed by two successive assimilation cycles with four volume scans of radar data of a shallow hailstorm on 26 May 1997, show that after two feedback looping more realistic dynamic features of convective cells are observed in the retrieval fields at the same time as both, observation and model residuals are reduced in the cost function. In further research, a number of cycle assimilation experiments will be conducted to examine the sensitivity of the minimization algorithm to the background term and the first guess as well as to tuning of the weight in the smoothness constraint. The results of a 30-min forecast of the MC2 model will be shown initialized with the analysis of these experiments to evaluate the quality of the retrieval fields.

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