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Schultz, Christopher J.

Publications and source records attributed to Schultz, Christopher J..

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2020

Using GLM Flash Density, Flash Area, and Flash Energy to Diagnose Tropical Cyclone Structure and Intensification

Increased lightning in tropical cyclones (TCs) is typically associated with intensification, but significant lightning outbreaks are also observed in weakening storms. The total number of lightning flashes in a TC is not always a reliable indicator of TC intensity evolution. Issues with the range and detection efficiency of ground-based networks, particularly for intracloud lightning. Physical processes such as vertical wind shear can intensify asymmetric convection while also weakening the TC. The commissioning of the Geostationary Lightning Mapper (GLM) aboard GOES-16 and GOES-17 marked, for the first time, the presence of an operational lightning detector in geostationary orbit. In addition to flash density (the number of flashes per unit area per unit time), GLM also provides continuous observations of flash area and total optical energy.

Duran, Patrick↗
NASA NTRS2019

Using Machine Learning to Develop a Predictive Model for Future Fire Seasons

The deep learning model shows promise for predicting areas of high wildfire potential. Full evaluation of the model performance is ongoing. Currently, the developed deep learning model is better overall at predicting the number of fires over the acres burned. Acres burned is dependent on location, suppression plan, and current conditions. Antecedent conditions are only one piece of the equation. In-season changes are not accounted for. An ignition source is required, which further complicates the model training and prediction.

White, Andrew T.↗
NASA NTRS2019

Spatial, Temporal, and Electrical Characteristics of Lightning in Reported Lightning-Initiated Wildfire Events

Analysis was performed to determine whether a lightning flash could be associated with every reported lightning-initiated wildfire that grew to at least 4 km(exp 2). In total, 905 lightning-initiated wildfires within the Continental United States (CONUS) between 2012 and 2015 were analyzed. Fixed and fire radius search methods showed that 81–88% of wildfires had a corresponding lightning flash within a 14 day period prior to the report date. The two methods showed that 52–60% of lightning-initiated wildfires were reported on the same day as the closest lightning flash. The fire radius method indicated the most promising spatial results, where the median distance between the closest lightning and the wildfire start location was 0.83 km, followed by a 75th percentile of 1.6 km and a 95th percentile of 5.86 km. Ninety percent of the closest lightning flashes to wildfires were negative polarity. Maximum flash densities were less than 0.41 flashes km(exp 2) for the 24 h period at the fire start location. The majority of lightning-initiated holdover events were observed in the Western CONUS, with a peak density in north-central Idaho. A twelve day holdover event in New Mexico was also discussed, outlining the opportunities and limitations of using lightning data to characterize wildfires.

Flash density↗
NASA NTRS2019

Utilizing the Geostationary Lightning Mapper for Lightning Safety

Outline: Collaborative Partners; What is the Geostationary Lightning Mapper (GLM)?; Initial observations (Density Products); Lightning safety with GLM; The 30-minute lightning hazard product; Goal - Basic understanding of and how to use the lightning hazard product.

Geostationary Lightning Mapper↗
NASA NTRS2019

A Radar Investigation of Precipitation Properties During Discrepancies Between GOES-16 GLM and LMA Observed Flash Rates in the Skyline Alabama Supercell of 22 April 2017

Conclusions: GLM (Geostationary Lightning Mapper) flash rates were 2 to 5 times lower than LMA (Lightning Mapping Array) in an Alabama supercell that was tracked using a combination of GLM flash initiation density and VIL (Vertically Integrated Liquid); Since most lightning was initiating at 8-9 kilometers (and not at low levels) according to LMA, flash height does not appear to be a primary factor in low GLM flash rates; When (LMA-GLM) flash rate differences were largest, the LMA observed flash areas were relatively small (and vice versa); Flash size may be a primary factor in low GLM flash rates due to detectability and/or flash clustering issues with small flashes within the coarse 8 kilometers by 8 kilometers resolution; High cloud liquid water droplet concentrations were inferred indirectly from riming necessary for large radar MESH (Maximum Expected Size of Hail), VIL and hail/graupel volumes. High cloud water droplet concentrations in supercells may decrease GLM detection efficiency due to optical extinction of near IR (near Infrared) emitted by lightning as it moves through cloud; Despite large flash rate differences, GLM & LMA lightning jumps during robust supercell generally agreed with each other and radar trends in HID (Radar Reflectivity and Hydrometeor Identification), MESH and VIL.However, more LMA jumps (than GLM) in developing supercell and more GLM jumps (than LMA) in weak to decaying supercell. Future work: improve GLM tracking.

GLM↗