GLM is coming: Preparations

Creating demonstration data and products to train forecasters for GLM has presented unique challenges.  Aside from the Optical Transient Detector (OTD) and the Lightning Imaging Sensor (LIS), no other space-based platform had similar capabilities to the GLM.  Furthermore, the OTD and LIS were low-Earth orbiting instruments and would only view a small portion of the Earth for no more than a couple minutes at a time.  This prevented their use as a demonstration data set as forecasters would need to see how total lightning (the combination of intra-cloud and cloud-to-ground) evolved with time.  That put the focus on ground networks, which could observe the entire life cycle of a storm.  The ground networks, unfortunately, lacked the ability to observe total lightning (or the capability was not yet available).  The exception was the ground-based lightning mapping array.

The lightning mapping array (LMA) was developed by New Mexico Tech and evolved out of earlier systems, some of which were tested at Kennedy Space Center.  By operating in the very high frequency end of the electromagnetic spectrum (~80 GHz), the LMAs could observe the entire lightning channel within a cloud.  Primarily designed for lightning research, these would become instrumental in the training activities for the GOES-R Proving Ground and the GLM.  This is because the LMAs were capable of observing total lightning.  Their accuracy was extremely good and they have been used for ground verification for OTD and LIS and will do so again for GLM.  Their primary disadvantage is a very short range; generally no more than 200 km from the center of the network.  Figure 1 shows the physical relationship of total lightning to a storm updraft as well as the lightning jump concept.

total_lightning_physical_reasoning

Figure 1:  The top two panels show the total lightning density (left) and radar reflectivity at ~20 thousand feet (right) and 1442 UTC.  The radar elevation corresponds to the mixed phase region.  Total lightning is produced by a strong, voluminous updraft extending into the mixed phase region.  This is a non-linear relationship so the strongest updrafts will produce the most lightning.  This physical connection can be harnessed by forecasters as shown in the lower left (total lightning density at 1450 UTC) and right (radar reflectivity at 20 thousand feet at 1452 UTC).  The total lightning shows a “bull’s eye” feature indicating rapid intensification, or lightning jump.  This preceded the radar update at 1452 UTC showing the updraft now extending into the mixed phase region.  This allowed the total lightning to provide additional information on the intensification of this storm and the rapid increase indicates that severe weather is imminent.  Also, the total lightning information shows the spatial extent of the lightning that can be used for safety applications.

The Melbourne, Florida forecast office was the first office to use total lightning data from a local lightning detection and ranging network (very similar to an LMA) in the late 1990s.  This was a combined effort by the forecast office, Massachusetts Institute of Technology (MIT), MIT Lincoln Lab, and NASA Marshall Space Flight Center.  The data became extremely popular with the office and the Lightning Imaging Sensor Demonstration and Display (LISDAD) system was instrumental in investigating the uses of total lightning in real-time.

In 2002, NASA’s Marshall Space Flight Center had installed the research oriented North Alabama Lightning Mapping Array (NALMA).  By March 2003, the NASA SPoRT team, in collaboration with the Huntsville weather forecast office, had made NALMA data available in the National Weather Service display system; AWIPS.  The Huntsville forecast office would then go on to issue its first warning using total lightning data that May.  NASA SPoRT would extend collaborations with a handful of other forecast offices using NALMA as well as the NASA owned Washington D.C. LMA in the late 2000s.

By 2008, the GOES-R Proving Ground was accelerating its efforts with training and hands-on activities, such as the Hazardous Weather Testbed in Norman, Oklahoma.  This required a demonstration product for GLM that could be used in real-time.  The Marshall Space Flight Center had developed the GLM proxy that was derived from NALMA to test data processing algorithms for the GLM.  The drawback was that it could not be run in real-time.  However, in 2009 NASA SPoRT produced the pseudo-GLM (PGLM) product (Figure 2).  It was not an exact replica of future GLM observations, but it represented a reasonable facsimile that allowed for hands-on training that let forecasters better learn about total lightning and its relation to storms intensity and severe weather.

pglm_example

Figure 2:  An example of the pseudo-GLM flash extent density product derived from the Washington D.C. lightning mapping array during the derecho event of 2012.  The radar reflectivity (right) shows a strong line of storms approaching Washington D.C.  The greatest reflectivities (and likely strongest storms) are towards the northeast.  The pseudo-GLM (left) shows that it has update sooner than the radar, but also emphasizes the northeastern end of the line.  In fact, over 110 flashes are observed in two minutes at one location, highlighting the strongest overall storm.  The convection to the southwest is weaker as evidenced by the lack of pseudo-GLM observations.

NASA SPoRT, thanks to funding via the GOES-R visiting scientist program, was able to reach out to each of the other LMAs that were in operation across the country (and one in Canada!).  By 2014, almost a dozen LMAs were collaborating.  This allowed for the PGLM to be produced for numerous locations as well as expand partnerships to over a dozen forecast offices, three center weather service units, and the Aviation Weather Center.  Figure 3 shows the approximate domain and collaborating organization for each available LMA.  Combined, the collaborations between the forecasters, LMA owners, and the testbeds allowed for a wide variety of feedback discussing operational uses and visualization concepts.  Much of this has directly supported my own efforts as the GLM satellite liaison for the ongoing work in the Satellite Foundational Course for GOES-R, preparing for operational applications training, and the 2017 summer assessment.

lma_collaborators

Figure 3:  The approximate domain of the 11 collaborating lightning mapping arrays that have been used as part of the GLM preparations for the GOES-R Proving Ground.  The numbers correspond to the list at top showing the owners of the collaborative network.

Next up in the “GLM is coming” series is a post describing the GLM instrument itself as we await in initial release of GLM data.

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