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Compared to other types of data, the assimilation of lightning data into operational numerical models has received relatively little attention. However, NASA's upcoming launch of the GOES-R Lightning Mapper (GLM) that will provide continuous, full disc, high resolution detection of total lightning (IC + CG) is stimulating interest.
FSU will develop a new type of nudging technique to create convection in areas where lightning is observed but not simulated. This is accomplished by warming the lower troposphere to make the atmosphere less stable. In addition we are developing a more sophisticated approach involving 4-D VAR toward which both NCEP and NRL are moving. The technique has been denoted 1-D VAR + 4-D VAR. The early stages of our research will utilize existing ground-based lightning data that can be assimilated prior to the launch of GLM; later phases will utilize GLM proxy data that will mimic what GLM will detect.
The 1-D VAR + 4-D VAR technique will be tested against existing nudging approaches, our new nudging approach, and a control run without lightning assimilation. We will investigate several severe weather systems. We hypothesize that the forecasts will improve with the assimilation of lightning data. We will collaborate with agencies comprising the JCSDA to insure that our 1-D VAR + 4-D VAR approach can be transitioned to operational use. The overall goal is to effectively assimilate satellite-derived lightning data so that model forecasts are improved.
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last updated February 24, 2014