Forecast Models
Lightning Data Assimilation
NSSL scientists are studying how including lightning observations in mesoscale forecast models could improve the forecasts of initial conditions. Lightning data could be important because it can pinpoint the location of current convection and may be a measure of its intensity. Using lightning data could also improve the effects of prior convection on the initial conditions of the forecast period.
Lightning Observations Assimilated into the COAMPS Mesoscale Model
Lightning observations have been assimilated into the COAMPS (Coupled Ocean/Atmosphere Mesoscale Prediction System) mesoscale model for improvement of forecast initial conditions. Data are used from the National Lightning Detection Network and a Lightning Mapping Array that was installed in western Kansas/eastern Colorado. Lightning assimilation was successful in generating the cold pool that was present in the surface observations at initialization of the forecast. The resulting forecast showed considerable more skill than the control forecast, especially in the first few hours as convection was triggered by the propagation of the cold pool boundary.
Lightning Data Assimilation Technique for Mesoscale Forecast Models
NSSL implemented an assimilation scheme that ingests lightning data directly, without additional analysis to estimate rainfall per flash as in the prior assimilation scheme. Direct ingest makes the scheme more appropriate for use in a rapid update cycle forecast. Assimilation is most effective with total lightning data, such as from the ground-based lightning mapping array or data that could be acquired by a satellite-based optical system.
