Abstract

Abstract Using data from the 6 July 2015 PECAN case study, this paper provides the first objective assessment of how the assimilation of ground-based remote sensing profilers affects the forecasts of bore-driven convection. To account for the multiscale nature of the phenomenon, data impacts are examined separately with respect to (i) the bore environment, (ii) the explicitly resolved bore, and (iii) the bore-initiated convection. The findings from this work suggest that remote sensing profiling instruments provide considerable advantages over conventional in situ observations, especially when the retrieved data are assimilated at a high temporal frequency. The clearest forecast improvements are seen in terms of the predicted bore environment where the assimilation of kinematic profilers reduces a preexisting bias in the structure of the low-level jet. Data impacts with respect to the other two forecast components are mixed in nature. While the assimilation of thermodynamic retrievals from the Atmospheric Emitted Radiance Interferometer (AERI) results in the best convective forecast, it also creates a positive bias in the height of the convectively generated bore. Conversely, the assimilation of wind profiler data improves the characteristics of the explicitly resolved bore, but tends to further exacerbate the lack of convection in the control forecasts. Various dynamical diagnostics utilized throughout this study provide a physical insight into the data impact results and demonstrate that a successful prediction of bore-driven convection requires an accurate depiction of the internal bore structure as well as the ambient environment ahead of it.

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