Abstract
An analysis of the GOES measurements of a severe thunderstorm anvil on 2 May 1979 presented in Part I (Heymsfield et al.) showed a “V” shaped region of low infrared temperatures (TBB) and an internal region of high TBB. Several hypotheses have been given in the literature (e.g., dynamical and above-anvil cirrus) concerning the formation of the “V” pattern. In this paper, the radiative characteristics of the cirrus are examined as a partial explanation for the IR observations. Calculations are made relevant to the radiative properties using a plane parallel radiative transfer model which shows the sensitivity of TBB to ice water content (IWC), and an ice particle trajectory model which simulates the horizontal ice particle distribution. A variation in the horizontal distribution of IWC is postulated as an explanation for the “V” shaped area and internal warm region. The radiative model calculations support the hypothesis that the higher TBB values in the internal warm region may result from the radiometer seeing down into the anvil layer. The ice particle trajectory model results indicate that the “V” shape can be produced by the ice particle number distribution, where a higher concentration of particles is found in the arms of the “V". Asymmetry of the “V” results from the inclusion of storm motion in the trajectory calculations. Further, the calculated anvil is oriented along the storm relative wind vector in good agreement with the observations. Based on the results of the models, a variation in horizontal distribution of IWC is postulated as a partial explanation for the “V” shaped area and internal warm region. That is, the lower TBB values in the “V” arms are suggested to result in part from the IWC being higher there than that in the internal warm region in the top few kilometers of the anvil. The proposed mechanism may act together with other plausible mechanisms to produce the observed IR pattern. The relative importance of the proposed mechanism cannot be assessed however, given the uncertainties in the observations and models.
