ABSTRACT: How might lightning measurements be used to improve short-term (0-24 hr) weather forecasting? We examine this question under two different prediction strategies. These include integration of lightning data into short-term forecasts (nowcasts) of convective (including severe) weather hazards and the assimilation of lightning data into cloud-resolving numerical weather prediction models. In each strategy we define specific metrics of forecast improvement and a progress assessment. We also address the conventional observing system deficiencies and potential gap-filling information that can be addressed through the use of the lightning measurement. PRESENT STATE OF KNOWLEDGE In simplest terms, lightning is an electrical manifestation of thermodynamic and mechanical work performed by storm updrafts. Updrafts determine the supply, growth and transport of water condensate to the upper regions of storms, and directly control the dynamics of charge separation that lead to lightning. While there is considerable complexity in the microphysical charge separation process itself, the larger-scale physics involved are reasonably well understood and straightforward. This was exemplified by early theoretical work by Vonnegut , who expressed the electrical power available for lightning generation in scaling-law form, dependent upon storm updraft velocity, charge density, area and electric dipole separation (height). This simple scalin
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