A statistical approach to fast nowcasting of lightning potential fields
Thunderstorms and associated hazards like lightning can pose a serious threat to people outside and infrastructure. Thus, very short-term prediction capabilities (called nowcasting) have been developed to capture this threat and aid in decision-making on when to bring people inside for safety reasons. The atmospheric research and operational communities have been developing and using nowcasting methods for decades, but most methods do not rely on formal statistical approaches. A novel and fast statistical approach to nowcasting of lightning threats is presented here that builds upon an integro-difference modeling framework. Inspiration from the heat equation is used to define a redistribution kernel, and a simple linear advection scheme is shown to work well for the lightning prediction example. The model takes only seconds to estimate and nowcast and is competitive with a more complex image deformation approach that is computationally infeasible for very short-term nowcasts.
document
http://n2t.net/ark:/85065/d7gt5rjx
eng
geoscientificInformation
Text
publication
2016-01-01T00:00:00Z
publication
2020-07-23T00:00:00Z
Copyright author(s). This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
None
OpenSky Support
UCAR/NCAR - Library
PO Box 3000
Boulder
80307-3000
name: homepage
pointOfContact
OpenSky Support
UCAR/NCAR - Library
PO Box 3000
Boulder
80307-3000
name: homepage
pointOfContact
2023-08-18T18:29:18.091754