A method for improving the estimation of conditional instability from satellite retrievals
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A method for improving the estimation of conditional instability from satellite retrievals

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    A method is presented for improving the estimation of conditional instability from satellite retrievals in pre-convective environments. The study is accomplished with a set of radiances simulated for the VAS-D instrument from a data base comprised of 139 tornado proximity and precedent soundings. Basically, a guess moisture profile is modeled in two layers characteristic of pre-storm conditions. In addition, a stability index (termed the Parcel Energy or PE index) is introduced which optimizes satellite retrieval information for assessing conditional instability. Comparative statistics demonstrate a marked improvement in the retrieved moisture structure and conditional instability as compared to results obtained using other guess profiles. Parameters evaluated include total precipitable water and layer mean values of potential temperature and mixing ratio in the lowest 10 kPa. Also, when the modelled guess is used, the mean mixing ratio in the lowest 10 kPa layer has smaller error than those generated by various objective methods evaluated by the Techniques Development Laboratory. This study suggests that VAS retrievals obtained with the model guess will have sufficient quality for providing updated stability information to the field between synoptic time periods.
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