Engineering topics

Chronis, T.

Publications and source records attributed to Chronis, T..

3 records

NASA NTRS2017

Terrestrial Gamma Ray Flashes due to Particle Acceleration in Tropical Storm Systems

Terrestrial gamma ray flashes (TGFs) are submillisecond flashes of energetic radiation that are believed to emanate from intracloud lightning inside thunderstorms. This emission can be detected hundreds of kilometers from the source by space-based observatories such as the Fermi Gamma-ray Space Telescope (Fermi). The location of the TGF-producing storms can be determined using very low frequency (VLF) radio measurements made simultaneously with the Fermi detection, allowing additional insight into the mechanisms which produce these phenomena. In this paper, we report 37 TGFs originating from tropical storm systems for the first time. Previous studies to gain insight into how tropical cyclones formed and how destructive they can be include the investigation of lightning flash rates and their dependence on storm evolution. We find TGFs to emanate from a broad range of distances from the storm centers. In hurricanes and severe tropical cyclones, the TGFs are observed to occur predominately from the outer rainbands. A majority of our sample also show TGFs occurring during the strengthening phase of the encompassing storm system. These results verify that TGF production closely follows when and where lightning predominately occurs in cyclones. The intrinsic characteristics of these TGFs were not found to differ from other TGFs reported in larger samples. We also find that some TGF-producing storm cells in tropical storm systems far removed from land have a low number of WWLLN sferics. Although not unique to tropical cyclones, this TGF/sferic ratio may imply a high efficiency for the lightning in these storms to generate TGFs.

Roberts, O. S.↗

NASA NTRS2014

The GOES-R Geostationary Lightning Mapper (GLM) and the Global Observing System for Total Lightning

for the existing GOES system currently operating over the Western Hemisphere. New and improved instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved temporal, spatial, and spectral resolution for the next generation Advanced Baseline Imager (ABI). The GLM will map total lightning continuously day and night with near-uniform spatial resolution of 8 km with a product latency of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency among a number of potential applications. The GLM will help address the National Weather Service requirement for total lightning observations globally to support warning decision-making and forecast services. Science and application development along with pre-operational product demonstrations and evaluations at NWS national centers, forecast offices, and NOAA testbeds will prepare the forecasters to use GLM as soon as possible after the planned launch and check-out of GOES-R in 2016. New applications will use GLM alone, in combination with the ABI, or integrated (fused) with other available tools (weather radar and ground strike networks, nowcasting systems, mesoscale analysis, and numerical weather prediction models) in the hands of the forecaster responsible for issuing more timely and accurate forecasts and warnings.

Goodman, Steven J.↗

NASA NTRS2014

Lightning Jump Algorithm Development for the GOES·R Geostationary Lightning Mapper

Current work on the lightning jump algorithm to be used in GOES‐R Geostationary Lightning Mapper (GLM)'s data stream is multifaceted due to the intricate interplay between the storm tracking, GLM proxy data, and the performance of the lightning jump itself. This work outlines the progress of the last year, where analysis and performance of the lightning jump algorithm with automated storm tracking and GLM proxy data were assessed using over 700 storms from North Alabama. The cases analyzed coincide with previous semi‐objective work performed using total lightning mapping array (LMA) measurements in Schultz et al. (2011). Analysis shows that key components of the algorithm (flash rate and sigma thresholds) have the greatest influence on the performance of the algorithm when validating using severe storm reports. Automated objective analysis using the GLM proxy data has shown probability of detection (POD) values around 60% with false alarm rates (FAR) around 73% using similar methodology to Schultz et al. (2011). However, when applying verification methods similar to those employed by the National Weather Service, POD values increase slightly (69%) and FAR values decrease (63%). The relationship between storm tracking and lightning jump has also been tested in a real‐time framework at NSSL. This system includes fully automated tracking by radar alone, real‐time LMA and radar observations and the lightning jump. Results indicate that the POD is strong at 65%. However, the FAR is significantly higher than in Schultz et al. (2011) (50‐80% depending on various tracking/lightning jump parameters) when using storm reports for verification. Given known issues with Storm Data, the performance of the real‐time jump algorithm is also being tested with high density radar and surface observations from the NSSL Severe Hazards Analysis & Verification Experiment (SHAVE).

Schultz. E.↗