STAR GOES-R Algorithm Working Group website National Oceanographic & Atmospheric Administration website NOAA Center for Satellite Applications and Research website

Lightning Cluster Filter Algorithm

Background

Currently weather forecasters can use lightning data provided by a surface-based network to help "nowcast" severe weather. This is a valuable tool; however, it only has the capability of detecting cloud-to-ground flashes. The GOES-R satellites will have the capability to detect both cloud-to-ground and inter-cloud lightning, through use of the Geostationary Lightning Mapper (GLM). This will help severe weather forecasters identify thunderstorms which are rapidly intensifying, and enable them to issue accurate and timely severe thunderstorm and tornado warnings.

Product Description

The Lightning Cluster Filter Algorithm (LCFA) that generates Level 2 lightning products (flashes, groups, events) from Level 1b Geostationary Lightning Mapper (GLM) geo-located, time-tagged lightning event data. The LCFA builds a parent-child tree-structure that identifies the clustering of optical events into groups, and groups into flashes.

Improvements and Benefits

GOES-R will contain a Geostationary Lightning Mapper that will provide continuous lightning observations across a large portion of the full disk. This will allow for the monitoring of convective storms and other lightning occurrence on a global scale.

How does it work? - Algorithm

The concept of the LCFA is closely based on the (only predecessor) heritage OTD/LIS data processing algorithm. Consequently, there are no competing pre-existing algorithms to compare or contrast with, or to detail in a long overview. However, this ATBD does invoke modifications to the heritage algorithm that are needed when one moves from the Low Earth Orbiting (LEO) OTD/LIS application to the geostationary application associated with GLM.

There is one major product produced by the GLM software: a lightning dataset. To obtain this dataset, the satellite data stream needs to be decoded, filtered, clustered, and output to the appropriate file. The LCFA only generates the lightning dataset. Specifically, the LCFA receives as input the Level 1b pixel-level optical "event" data and processes this data into more convenient lightning data products that are easily utilized by the scientific research and broader operational user communities. Therefore, the LCFA must take the event data and assemble the higher level clustered lightning data products (events, groups and flashes), and in so doing, it will generate derived lightning characteristics associated with these higher level products.

Example display of GLM proxy lightning data

Example display of GLM proxy lightning data centered over the Sterling, Virginia NWS office at 21:04 UTC on 07 December 2006.

It will also interrogate individual flashes, groups, and events on a statistical basis to see if they are associated with lightning or noise [i.e., the Lightning AWG Team does not assume that the noise filtering performed by the Instrument Vendor is perfect]. Definitions of the basic data storage classes (events, groups, flashes) that drive the LCFA are provided below.

See the GOES-R ATBD page for all ATBDs.

How are the results compared to existing data? - Calibration and Validation

The goal of GLM validation is to ensure that GLM products (events, groups, flashes) are adequately detected, accurately located in space and time, and with proper latency.

GLM lightning product validation will involve space-based observations from the Lightning Imaging Sensor (LIS) and ground-based lightning detection technologies including: (1) VHF time-of-arrival systems for detection of total lightning [e.g., Lightning Mapping Array (LMA), Lightning Detection And Ranging (LDAR)], (2) combined magnetic direction finding and time-of-arrival technologies for the detection of ground flashes [e.g., VLF long range National Lightning Detection Network (NLDN) for detection over the Atlantic and Pacific oceans, GLD360, and (3) electric-field change measurement networks (currently planned for north Alabama, central Oklahoma, and KSC, Florida).

A more technical validation presentation, (PDF, 15.44 MB) are also available