Lightning data provide valuable information on the existence of thunderstorms and can be used to augment radar reflectivity data for the purpose of initializing ongoing precipitation systems within numerical weather prediction models. Radar data are generally not available over oceanic areas and terrain-blocked areas, regions where lightning data can provide additional information. Lightning data provide conditional convection information: existence of strokes implies that convective clouds are present, but absence of strokes does not imply that convective clouds are not present.

Within the Rapid Update Cycle (RUC) model, we have recently developed a new assimilation procedure that utilizes radar and lightning data to initialize ongoing precipitation systems. The new procedure uses elements of the RUC cloud analysis and diabatic digital filter initialization (DFI) to force latent heating consistent with the hydrometeor fields derived from the radar and lightning data. Within the cloud analysis, a simple heuristic relationship is used to convert lightning ground stroke densities into an equivalent radar reflectivity. The merged reflectivity/lightning data are then used to compute a latent heat based temperature tendency. This tendency is then applied during the forward-model integration portion of the diabatic DFI. Application of this latent heat derived temperature tendency induces an associated vertical circulation, with low-level convergence and upper-level divergence.

In this presentation, we will describe the procedure and present results to illustrate the impact of the lightning data. In addition the planned transition of the RUC to the Rapid-Refresh (RR), with an expanded domain covering all of North America and adjacent waters will be discussed. Associated with this domain expansion will be an increase in the utility of lightning data for initializing convection over areas not covered by radar networks (portions of Canada, Pacific, Atlantic and Caribbean waters).