Numerical Simulations of Maritime Deep Convection using an Unstructured Adaptive Grid Model Initialized with Lightning Data

The emergence of long-range lightning detection networks heralds a growing, but currently under-utilized source of lightning information. Long-range lightning observations provide a means to identify both under-resolved mesoscale and unresolved storm-scale areas of deep, precipitating convection over the open oceans where surface and rawinsonde observations are very sparse.

Numerical models can be configured to exploit the multiscale quality of long-range lightning data to improve the simulation of convective storms and tropical weather systems. The density of lightning strikes over the open ocean can be used to specify the location and extent of convection-resolving grid spacing in numerical simulations. This application is ideal for an adaptive grid model in which the simulation can automatically adjust and maintain fine grid spacing over areas of enhanced lightning activity.

We will present results of numerical simulations from the TCS-08 and TCS-10 field experiments using the Operational Multiscale Environment model with Grid Adaptivity (OMEGA) initialized with lightning data from Vaisala's Long-range Lightning Detection Network (LLDN) and Global Lightning Dataset (GLD360). Although the lightning data are only used to add resolution to the model grid, this research presents a first step toward an efficient method for the assimilation of lightning data or a proxy for the lightning data, with the goal of advancing the numerical prediction of maritime severe weather.