Comment on gmd-2022-255

Abstract

<strong class="journal-contentHeaderColor">Abstract.</strong> Meteorological fronts are important for their associated surface impacts, including extreme precipitation and extreme winds. Objective identification of fronts is therefore of interest in both operational and research settings. We have implemented a number of changes in a widely used objective front identification algorithm, and present the improvements associated with these changes. First, we show that a change to the order of operations from applying a mask then joining frontal points to contouring the thermal field then applying the mask, yields smoother fronts with fewer breaks. Next we address the selection of the identification parameters, including the thresholds and number of smoothing passes. This allows a comparison between datasets of differing resolutions. Finally, we have made a number of numerical improvements in the implementation of the algorithm, such as more accurate finite differencing, direct calculation of the wet-bulb potential temperature, and better handling of short fronts, which yield further benefits in smoothness and number of breaks. This updated version of the algorithm has been made fully portable and scalable to different datasets in order to enable future climatological studies of fronts and their impacts.