Search NASA⌕ Search

SEARCH · Search NASA

Results for “lightning mapping”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Signatures in Lightning Activity during Tennessee Valley Severe Storms of 5-6 May 2003

During the first week of May 2003, the Tennessee Valley experienced 14 tornadoes. Those that moved across the Tennessee Valley Region of northern Alabama and southern Tennessee provided an opportunity for study us- ing the North Alabama Lightning Mapping Array (LMA). On 5 May a classic supercell trekked across southern Tennessee spawning several tornadoes producing FO-F3 damage; on 6 May a high precipitation supercell moved across northern Alabama producing several FO-F1 tornadoes. The life cycle of these supercells will be discussed by presenting their electrical and radar evolution.

Gatlin, Patrick N.↗
NASA NTRS2005

The NASA Short-term Prediction and Research Transition (SPoRT) Center: A Research to Operations Test Bed

Over the last three years, NASA/MSFC scientists have embarked on an effort to transition unique NASA EOS data/products and research technology to selected NWSEOs in the southeast U.S. This activity, called the Short-term Prediction and - Research Transition (SPoRT) program, supports the NASA Science Mission Directorate and its Earth-Sun System Mission to develop a scientific understanding of the Earth System and its response to natural or human-induced changes that will enable improved prediction capability for climate, weather, and natural hazards. The overarching question related to weather prediction is "How well can weather forecasting duration and reliability be improved by new space-based observations, data assimilation, and modeling?" The transition activity has included the real-time delivery of MODIS data and products to several NWS Forecast Offices. Local NWS FOs have used the MODIS data to complement the coarse resolution GOES data for a number of applications. Specialized products have also been developed and made available to local and remote offices for their weather applications. Data from &e Lightning Mapping Array (LMA) network has been used in severe storm forecasts at several offices in the region. At the regional scale and forecast horizons from 0-1 day, the next generation of high-resolution mesoscale forecast and data assimilation models have been used to provide local offices with unique weather forecasts not otherwise available. The continued use of near red-time infusion of NASA science products into high-resolution mesoscale forecast and decision-making models can be expected to improve the model initialization as well as short-term forecasts. A current focus of SPoRT is to expand collaborations to include contributions from the assimilation of AMSR-E data in the ADASIARPS forecast system (OU), inclusion of MODIS SSTs and AIRS thermodynamic profiles in the WRF, and to extend the distribution of real-time MODIS and AMSR-E data and products to the Florida coastal WFOs. A SPoRT Test bed, together with input from other interagency and university partners, will provide a means and a process to effectively transition ESE observations and technology to NWS operations and decision makers at both the globdnational and regional scales. The transition of emerging experimental products into operations through the SPoRT infrastructure will allow NASA to foster and accelerate the progress of this Science Mission Directorate research strategy over the coming years.

Jedlovec, Gary J.↗
NASA NTRS2006

Use of High-resolution WRF Simulations to Forecast Lightning Threat

Recent observational studies have confirmed the existence of a robust statistical relationship between lightning flash rates and the amount of large precipitating ice hydrometeors in storms. This relationship is exploited, in conjunction with the capabilities of recent forecast models such as WRF, to forecast the threat of lightning from convective storms using the output fields from the model forecasts. The simulated vertical flux of graupel at -15C is used in this study as a proxy for charge separation processes and their associated lightning risk. Six-h simulations are conducted for a number of case studies for which three-dimensional lightning validation data from the North Alabama Lightning Mapping Array are available. Experiments indicate that initialization of the WRF model on a 2 km grid using Eta boundary conditions, Doppler radar radial velocity and reflectivity fields, and METAR and ACARS data yield the most realistic simulations. An array of subjective and objective statistical metrics are employed to document the utility of the WRF forecasts. The simulation results are also compared to other more traditional means of forecasting convective storms, such as those based on inspection of the convective available potential energy field.

McCaul, William E.↗
NASA NTRS2007

High-Resolution WRF Forecasts of Lightning Threat

Tropical Rainfall Measuring Mission (TRMM)lightning and precipitation observations have confirmed the existence of a robust relationship between lightning flash rates and the amount of large precipitating ice hydrometeors in storms. This relationship is exploited, in conjunction with the capabilities of the Weather Research and Forecast (WRF) model, to forecast the threat of lightning from convective storms using the output fields from the model forecasts. The simulated vertical flux of graupel at -15C is used in this study as a proxy for charge separation processes and their associated lightning risk. Initial experiments using 6-h simulations are conducted for a number of case studies for which three-dimensional lightning validation data from the North Alabama Lightning Mapping Array are available. The WRF has been initialized on a 2 km grid using Eta boundary conditions, Doppler radar radial velocity and reflectivity fields, and METAR and ACARS data. An array of subjective and objective statistical metrics is employed to document the utility of the WRF forecasts. The simulation results are also compared to other more traditional means of forecasting convective storms, such as those based on inspection of the convective available potential energy field.

Goodman, S. J.↗
NASA NTRS2008

Pre-Launch Algorithms and Risk Reduction in Support of the Geostationary Lightning Mapper for GOES-R and Beyond

The Geostationary Lightning Mapper (GLM) is a single channel, near-IR imager/optical transient event detector, used to detect, locate and measure total lightning activity over the full-disk as part of a 3-axis stabilized, geostationary weather satellite system. The next generation NOAA Geostationary Operational Environmental Satellite (GOES-R) series with a planned launch in 2014 will carry a GLM that will provide continuous day and night observations of lightning from the west coast of Africa (GOES-E) to New Zealand (GOES-W) when the constellation is fUlly operational. The mission objectives for the GLM are to 1) provide continuous, full-disk lightning measurements for storm warning and nowcasting, 2) provide early warning of tornadic activity, and 3) accumulate a long-term database to track decadal changes of lightning. The GLM owes its heritage to the NASA Lightning Imaging Sensor (1997-Present) and the Optical Transient Detector (1995-2000), which were developed for the Earth Observing System and have produced a combined 13 year data record of global lightning activity. Instrument formulation studies were completed in March 2007 and the implementation phase to develop a prototype model and up to four flight models is expected to be underway in the latter part of 2007. In parallel with the instrument development, a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 ground processing algorithms and applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds (e.g., Lightning Mapping Arrays in North Alabama and the Washington DC Metropolitan area)

Goodman, Steven J.↗
NASA NTRS2008

GOES-R Geostationary Lightning Mapper Performance Specifications and Algorithms

The Geostationary Lightning Mapper (GLM) is a single channel, near-IR imager/optical transient event detector, used to detect, locate and measure total lightning activity over the full-disk. The next generation NOAA Geostationary Operational Environmental Satellite (GOES-R) series will carry a GLM that will provide continuous day and night observations of lightning. The mission objectives for the GLM are to: (1) Provide continuous, full-disk lightning measurements for storm warning and nowcasting, (2) Provide early warning of tornadic activity, and (2) Accumulate a long-term database to track decadal changes of lightning. The GLM owes its heritage to the NASA Lightning Imaging Sensor (1997- present) and the Optical Transient Detector (1995-2000), which were developed for the Earth Observing System and have produced a combined 13 year data record of global lightning activity. GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms and applications. The science data will consist of lightning "events", "groups", and "flashes". The algorithm is being designed to be an efficient user of the computational resources. This may include parallelization of the code and the concept of sub-dividing the GLM FOV into regions to be processed in parallel. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds (e.g., Lightning Mapping Arrays in North Alabama, Oklahoma, Central Florida, and the Washington DC Metropolitan area) are being used to develop the prelaunch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution.

Mach, Douglas M.↗
NASA NTRS2008

Use of Vertically Integrated Ice in WRF-Based Forecasts of Lightning Threat

Previously reported methods of forecasting lightning threat using fields of graupel flux from WRF simulations are extended to include the simulated field of vertically integrated ice within storms. Although the ice integral shows less temporal variability than graupel flux, it provides more areal coverage, and can thus be used to create a lightning forecast that better matches the areal coverage of the lightning threat found in observations of flash extent density. A blended lightning forecast threat can be constructed that retains much of the desirable temporal sensitivity of the graupel flux method, while also incorporating the coverage benefits of the ice integral method. The graupel flux and ice integral fields contributing to the blended forecast are calibrated against observed lightning flash origin density data, based on Lightning Mapping Array observations from a series of case studies chosen to cover a wide range of flash rate conditions. Linear curve fits that pass through the origin are found to be statistically robust for the calibration procedures.

McCaul, E. W., jr.↗
NASA NTRS2011

GOES-R Proving Ground Activities at the NASA Short-Term Prediction Research and Transition (SPoRT) Center

SPoRT is actively involved in GOES-R Proving Ground activities in a number of ways: (1) Applying the paradigm of product development, user training, and interaction to foster interaction with end users at NOAA forecast offices national centers. (2) Providing unique capabilities in collaboration with other GOES-R Proving Ground partners (a) Hybrid GOES-MODIS imagery (b) Pseudo-GLM via regional lightning mapping arrays (c) Developing new RGB imagery from EUMETSAT guidelines

Molthan, Andrew↗
NASA NTRS2014

Total Lightning as an Indicator of Mesocyclone Behavior

Apparent relationship between total lightning (in-cloud and cloud to ground) and severe weather suggests its operational utility. Goal of fusion of total lightning with proven tools (i.e., radar lightning algorithms. Preliminary work here investigates circulation from Weather Suveilance Radar- 1988 Doppler (WSR-88D) coupled with total lightning data from Lightning Mapping Arrays.

Stough, Sarah M.↗
NASA NTRS2014

Three Dimensional Lightning Launch Commit Criteria Visualization Tool

Lightning occurrence too close to a NASA LSP or future SLS program launch vehicle in flight would have disastrous results. The sensitive electronics on the vehicle could be damaged to the point of causing an anomalous flight path and ultimate destruction of the vehicle and payload.According to 45th Weather Squadron (45 WS) Lightning Launch Commit Criteria (LLCC), a vehicle cannot launch if lightning is within 10 NM of its pre-determined flight path. The 45 WS Launch Weather Officers (LWOs) evaluate this LLCC for their launch customers to ensure the safety of the vehicle in flight. Currently, the LWOs conduct a subjective analysis of the distance between lightning and the flight path using data from different display systems. A 3-D display in which the lightning data and flight path are together would greatly reduce the ambiguity in evaluating this LLCC. It would give the LWOs and launch directors more confidence in whether a GO or NO GO for launch should be issued. When lightning appears close to the path, the LWOs likely err on the side of conservatism and deem the lightning to be within 10 NM. This would cause a costly delay or scrub. If the LWOs can determine with a strong level of certainty that the lightning is beyond 10 NM, launch availability would increase without compromising safety of the vehicle, payload or, in the future, astronauts.The AMU was tasked to conduct a market research of commercial, government, and open source software that might be able to ingest and display the 3-D lightning data from the KSC Lightning Mapping Array (LMA), the 45th Space Wing Weather Surveillance Radar (WSR), the National Weather Service in Melbourne Weather Surveillance Radar 1988 Doppler (WSR-88D), and the vehicle flight path data so that all can be visualized together. To accomplish this, the AMU conducted Internet searches for potential software candidates and interviewed software developers.None of the available off-the-shelf software had a 3-D capability that could display all of the data in a single visualization. The AMU determined there are two viable software packages that could satisfy the 45 WS requirement with further development and recommends the KSC Weather Office follow-up with both organizations to request development costs.

weather↗
NASA NTRS2019

Use of Polarimetric Radar Measurements to Constrain Simulated Convective Cell Evolution: A Pilot Study with Lagrangian Tracking

To probe the potential value of a radar-driven field campaign to constrain simulation of isolated convection subject to a strong aerosol perturbation, convective cells observed by the operational KHGX weather radar in the vicinity of Houston, Texas, are examined individually and statistically. Cells observed in a single case study of onshore flow conditions during July 2013 are first examined and compared with cells in a regional model simulation. Observed and simulated cells are objectively identified and tracked from observed or calculated positive specific differential phase (K(sub DP)) above the melting level, which is related to the presence of supercooled liquid water. Several observed and simulated cells are subjectively selected for further examination. Below the melting level, we compare sequential cross sections of retrieved and simulated raindrop size distribution parameters. Above the melting level, we examine time series of KDP and radar differential reflectivity (Z(sub DR)) statistics from observations and calculated from simulated supercooled rain properties, alongside simulated vertical wind and supercooled rain mixing ratio statistics. Results indicate that the operational weather radar measurements offer multiple constraints on the properties of simulated convective cells, with substantial value added from derived K(sub DP) and retrieved rain properties. The value of collocated three-dimensional lightning mapping array measurements, which are relatively rare in the continental US, supports the choice of Houston as a suitable location for future field studies to improve the simulation and understanding of convective updraft physics. However, rapid evolution of cells between routine volume scans motivates consideration of adaptive scan strategies or radar imaging technologies to amend operational weather radar capabilities. A 3-year climatology of isolated cell tracks, prepared using a more efficient algorithm, yields additional relevant information. Isolated cells are found within the KHGX domain on roughly 40 % of days year-round, with greatest concentration in the northwest quadrant, but roughly 5-fold more cells occur during June through September. During this enhanced occurrence period, the cells initiate following a strong diurnal cycle that peaks in the early afternoon, typically follow a south-to-north flow, and dissipate within 1 h, consistent with the case study examples. Statistics indicate that ∼ 150 isolated cells initiate and dissipate within 70 km of the KHGX radar during the enhanced occurrence period annually, and roughly 10 times as many within 200 km, suitable for multi-instrument Lagrangian observation strategies. In addition to ancillary meteorological and aerosol measurements, robust vertical wind speed retrievals would add substantial value to a radar-driven field campaign.

Fridlind, Ann M.↗
NASA NTRSDate not supplied

Hail Storm Risk Assessment Using Space-Borne Remote Sensing Observations and Reanalyses

Much of the world is impacted by severe thunderstorms, but whether they become disasters depends upon resilience--our capacity to prepare, mitigate, respond, and recover. Hail is the costliest severe weather hazard for the insurance industry, generating ~70% of severe convective storm losses due to damage to assets such as homes, businesses, agriculture, and infrastructure. Most insurance companies do not reserve enough capital to cover catastrophes, so they acquire reinsurance. The reinsurance industry uses catastrophe models (CatModels) to statistically estimate risk to an insurer’s portfolio. Hail CatModels are developed with climatologies that define hailstorm frequency and severity. Hail-prone areas can be defined using hail reports from trained spotters, the media, and the general public. Extremely severe hail (2+ inch diameter) occurs nearly every day across the world. Weather radars can detect hail because hailstones strongly reflect microwave signals that they emit. However, hail climatologies are difficult to derive because hail covers small areas and there are neither hail reporting mechanisms (e.g. website or mobile app) nor radar networks in most places outside the US and Europe. This lack of ground truth on severe hail puts society and economies at risk. Hail is generated within storms by strong updrafts. These updrafts exhibit unique signatures in NASA and other agency satellite observations, offering new opportunities for hailstorm analysis. Geostationary (GEO) visible and infrared imagery has been collected for ~15-25 years across the world (region dependent) and methods have been developed at NASA Langley Research Center (LaRC) to detect hailstorm updrafts using GEO imagery. Climatological GEO updraft data has been used by Willis Towers Watson (WTW), a leader in catastrophe risk assessment for the insurance industry, and Karlsruhe Institute of Technology to develop CatModels over Europe and Australia. Hail can also be inferred with passive microwave imagery collected by low-Earth-orbiting sensors such as the GPM GMI, TRMM TMI, AMSR-E, AMSR-2, SSM/I, and SSMIS over the last 20+ years using methods developed at the Marshall Space Flight Center (MSFC). Hailstorms generate enhanced lightning flash rates that can be tracked using new GOES-R series GEO Lightning Mapping (GLM) imagery. Atmospheric reanalyses can be used to define favorable hailstorm environments for combination with the satellite-based storm detections. This presentation will describe a framework for developing continental to global hail climatologies and CatModels based on NASA satellite data and capabilities. This is a collaboration between LaRC and MSFC, WTW, and partners in Brazil, Argentina, and South Africa. This project seeks to mitigate hail disasters by aiding development of new satellite-based severe storm nowcasting tools by regional partners and developing climatologies to improve societal understanding of hail frequency. GEOO visible and infrared metrics of storm intensity, environmental conditions based on reanalyses, spotter hail reports and radar MESH observations are intercompared to quantify the detectability of hailstorms, and our ability to discriminate hailstorms from other severe storms. We are also maturing methods using land surface imaging satellite data (e.g. MODIS, Landsat, Sentinel 1 and 2) to identify hail damage to agriculture. Work with WTW will improve socioeconomic resilience through development of new CatModels. Southern Brazil, Uruguay, Paraguay, and Argentina feature some of the most intense thunderstorms on Earth. South America and South Africa are developing insurance markets of interest to WTW clients, and is similar to other regions routinely impacted by hail that do not have comprehensive hail reporting or radars to assess hailstorm frequency. Project datasets will be made available via online GIS-enabled tools developed at the LaRC Atmospheric Science Data Center (ASDC) which will visualize data and provide it in multiple formats for use in a wide range of open source and commercial tools.

Kristopher Michael Bedka↗
NASA NTRS2022

Global Assessment of the Capability of Satellite Precipitation Products to Retrieve Landslide-Triggering Extreme Rainfall Events

Rainfall-induced landsliding is a global and systemic hazard that is likely to increase with the projections of increased frequency of extreme precipitation with current climate change. However, our ability to understand and mitigate landslide risk is strongly limited by the availability of relevant rainfall measurements in many landslide prone areas. In the last decade, global satellite multisensor precipitation products (SMPP) have been proposed as a solution, but very few studies have assessed their ability to adequately characterize rainfall events triggering landsliding. Here, we address this issue by testing the rainfall pattern retrieved by two SMPPs (IMERG and GSMaP) and one hybrid product [Multi-Source Weighted-Ensemble Precipitation (MSWEP)] against a large, global database of 20 comprehensive landslide inventories associated with well-identified storm events. We found that, after converting total rainfall amounts to an anomaly relative to the 10-yr return rainfall R*, the three products do retrieve the largest anomaly (of the last 20 years) during the major landslide event for many cases. However, the degree of spatial collocation of R* and landsliding varies from case to case and across products, and we often retrieved R* > 1 in years without reported landsliding. In addition, the few (four) landslide events caused by short and localized storms are most often undetected. We also show that, in at least five cases, the SMPP’s spatial pattern of rainfall anomaly matches landsliding less well than does ground-based radar rainfall pattern or lightning maps, underlining the limited accuracy of the SMPPs. We conclude on some potential avenues to improve SMPPs’ retrieval and their relation to landsliding.

Extreme events↗
NASA NTRS2010

The Goes-R Geostationary Lightning Mapper (GLM): Algorithm and Instrument Status

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved capability for the Advanced Baseline Imager (ABI). The Geostationary Lighting Mapper (GLM) will map total lightning activity (in-cloud and cloud-to-ground lighting flashes) continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate 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. In parallel with the instrument development (a prototype and 4 flight models), a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms, cal/val performance monitoring tools, and new applications. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. A joint field campaign with Brazilian researchers in 2010-2011 will produce concurrent observations from a VHF lightning mapping array, Meteosat multi-band imagery, Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) overpasses, and related ground and in-situ lightning and meteorological measurements in the vicinity of Sao Paulo. These data will provide a new comprehensive proxy data set for algorithm and application development.

Goodman, Steven J.↗
NASA NTRS2011

The GOES-R GeoStationary Lightning Mapper (GLM)

The Geostationary Operational Environmental Satellite (GOES-R) is the next series to follow the existing GOES system currently operating over the Western Hemisphere. Superior spacecraft and instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES capabilities include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved capability for the Advanced Baseline Imager (ABI). The Geostationary Lighting Mapper (GLM) will map total lightning activity (in-cloud and cloud-to-ground lighting flashes) continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate 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. In parallel with the instrument development (a prototype and 4 flight models), a GOES-R Risk Reduction Team and Algorithm Working Group Lightning Applications Team have begun to develop the Level 2 algorithms (environmental data records), cal/val performance monitoring tools, and new applications using GLM alone, in combination with the ABI, merged with ground-based sensors, and decision aids augmented by numerical weather prediction model forecasts. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite and regional test beds are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. An international field campaign planned for 2011-2012 will produce concurrent observations from a VHF lightning mapping array, Meteosat multi-band imagery, Tropical Rainfall Measuring Mission (TRMM) Lightning Imaging Sensor (LIS) overpasses, and related ground and in-situ lightning and meteorological measurements in the vicinity of Sao Paulo. These data will provide a new comprehensive proxy data set for algorithm and application development.

Goodman, Steven J.↗
NASA NTRS2022

Chile Wildfires: Utilizing NASA and NOAA Earth Observations to Determine Lightning-ignited Wildfire Risks in Central Chile

In recent years, Central Chile has experienced wildfires of increasing frequency and intensity which threaten natural resources and communities. The Corporación Nacional Forestal (CONAF) responds to wildfires caused by a variety of ignitions, including lightning, but it is difficult to determine the prevalence of lightning-ignited wildfires based solely on ground observations. In collaboration with CONAF and the Embassy of Chile, Agricultural Office, the team used Earth observations to map coincidence of lightning strikes and wildfire ignitions. The Active Fire Product of Suomi NPP Visible Infrared Imaging Radiometer Suite (VIIRS) identified wildfires as thermal anomalies, which the team compared to the lightning events detected by NOAA’s GOES-16 Geostationary Lightning Mapper (GLM). Next, the team mapped lightning strike frequency and lightning related wildfires across the study area. Finally, the team calculated and mapped a relative estimate of lightning-ignited wildfire vulnerability across the year, fire season (December – March), and off-season (April – November) by summing the following factors: lightning frequency, the Normalized Difference Moisture Index (NDMI) and land surface temperature (LST). These risks were then weighted by fuel availability. Preliminary analysis of the lightning fire relationship showed a spatiotemporal coincidence, primarily in the South-central region of study, near Temuco, and isolated areas on the Andean front. The team identified areas at risk of lightning-induced wildfires, predominantly in the northern third of the study area and along the Andean front. Adjusting the relative weight of risk factors and improving the lightning and fire coincidence map by clustering VIIRS thermal anomalies into fire events could reduce discrepancies and improve risk assessments for future work.

Christopher Matechik↗
NASA NTRS2018

Examining Sub-Flash Properties of Lightning from GLM for Tracking and Intensification Characterization of Thunderstorms

Current methodologies for operational use of lightning are developed using ground-based networks. Lightning detectors measure different characteristics of the flash, thus they don't observe the same lightning event in the same manner: i.e., flash rates from NDLN (National Lightning Detection Network (R)) will typically not match flash rates from GLM (Geostationary Lightning Mapper) because each sensor is measuring different characteristics (EM (Electromagnetic) radiation vs. optical). Resolution/timeliness of space-based sensor data will change our "rules of thumb" for operational use: Lightning safety - how does the 2D mapping of lightning enhance lightning safety metrics; Is the super-fast input of data (20s) useful for decision-makers, including (non-AWIPS (Advanced Weather Interactive Processing System) -users) non-mets?

lightning jump↗
NASA NTRS2009

Forecasting Lightning Threat using Cloud-resolving Model Simulations

As numerical forecasts capable of resolving individual convective clouds become more common, it is of interest to see if quantitative forecasts of lightning flash rate density are possible, based on fields computed by the numerical model. Previous observational research has shown robust relationships between observed lightning flash rates and inferred updraft and large precipitation ice fields in the mixed phase regions of storms, and that these relationships might allow simulated fields to serve as proxies for lightning flash rate density. It is shown in this paper that two simple proxy fields do indeed provide reasonable and cost-effective bases for creating time-evolving maps of predicted lightning flash rate density, judging from a series of diverse simulation case study events in North Alabama for which Lightning Mapping Array data provide ground truth. One method is based on the product of upward velocity and the mixing ratio of precipitating ice hydrometeors, modeled as graupel only, in the mixed phase region of storms at the -15\dgc\ level, while the second method is based on the vertically integrated amounts of ice hydrometeors in each model grid column. Each method can be calibrated by comparing domainwide statistics of the peak values of simulated flash rate proxy fields against domainwide peak total lightning flash rate density data from observations. Tests show that the first method is able to capture much of the temporal variability of the lightning threat, while the second method does a better job of depicting the areal coverage of the threat. A blended solution is designed to retain most of the temporal sensitivity of the first method, while adding the improved spatial coverage of the second. Weather Research and Forecast Model simulations of selected North Alabama cases show that this model can distinguish the general character and intensity of most convective events, and that the proposed methods show promise as a means of generating quantitatively realistic fields of lightning threat. However, because models tend to have more difficulty in correctly predicting the instantaneous placement of storms, forecasts of the detailed location of the lightning threat based on single simulations can be in error. Although these model shortcomings presently limit the precision of lightning threat forecasts from individual runs of current generation models, the techniques proposed herein should continue to be applicable as newer and more accurate physically-based model versions, physical parameterizations, initialization techniques and ensembles of cloud-allowing forecasts become available.

McCaul, E. W., Jr.↗