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\textit{Oh, an empty article!}   You To identify U.S. ES events, Colman(1990a) and Horgan et. al. 2007 used observer reports of thunderstorms, as well as upper air soundings, and surface and upper pressure analyses to identify where surface stable layers were located. Unfortunately, Australia does not have a dense spatial and temporal surface, and upper air observing network, and there is a concern too few Australian ES would be identified to create a climatology.  Rather than using observer reports of thunderstorms, the location and timing of observed lightning strokes from the Global Position and Tracking System (GPATS)  can get started be used as a proxy for thunderstorm locations. GPATS has 40 ground-based sensors in Australia, separated  by \textbf{double clicking} this text block and begin editing. You average distances of ~600km (at most 1200km separation for a few sites in central Australia), and fairly even coverage except for a lack of sensors in eastern WA. The sensors accurately detect the time of a lightning stroke event in the very low frequency radio band. When a lightning stroke is detected at more than 2 sensors, time difference of arrival mathematics  can also click calculate a location. Whilst GPATS location accuracies have not been published, the European ADTNET (with similar ground radio frequency sensor separation and  the \textbf{Insert} button below same location calculation methods as GPATS), has published location accuracies of 5-6km (Cummins and Murphy 2009).  Kumar et al (\textbf{2013- add ref  to bib}) identified radar-dervied convective cells near Darwin over two wet seasons \textbf{(get years from paper)}, for various monsoon wind flow regimes (\textbf{Pope et al XXXX -  add new block elements. Or you ref to bib}). To assess lightning flash density per wind flow regime over the two wet seasons, Kumar et al used a subset of GPATS strokes which had one or more convective cells within a 10km radius and +-10 minute window of the lightning stroke. Of the 153125 GPATS strokes occurred during the 2 wet seasons, the convective cell criteria rejected only 6\% of strokes. This gives confidence to GPATS strokes occurring close (in space and time) to convective cells not only in the Australian tropics in summer, but \textbf{nationally and seasonally (rewrite this?)}.  Total lightning consists of intra-cloud strokes (IC) and cloud to ground (CG) or ground to cloud (GC) strokes. In a comparison of GPATS stroke types to stroke types from a high-quality research lightning flash counter (CGR4) in Brisbane, GPATS grossly under reports IC strokes, (Kuleshov 2012), with the majority of detected strokes being either CG or GC types. (\textbf{get percentages of IC and CG/GC to total lightning}). After a software upgrade in 2006 however, the number of GPATS ground strokes detected from 2007 onwards seem to be comparable to ground stroke numbers from the high quality CGR4 sensor at Brisbane. This means that whilst GPATS detected ground stroke numbers  can \textbf{drag and drop an image} right onto this text. Happy writing! be trusted after 2007 (a dataset from 2008-2014 is readily available), GPATS will does not detect IC strokes.   Of concern is the spatial distributions of IC strokes, compared to CG or GC strokes over Australia. Lightning detected from the Lightning Image Sensor (LIS) on the TRMM polar orbiting satellite is considered very accurate in detecting total lightning (Cummins and Murphy 2009). GPATS CG/GC stroke locations have been compared to LIS total stroke locations for 3 summer and 3 winter days within the 2008-2014 period.  \textbf{(para re LIS VIEWTIMES and GPATS selection per viewtime space/time window)}