78 research outputs found
Global Electric Circuit Implications of Combined Aircraft Storm Electric Current Measurements and Satellite-Based Diurnal Lightning Statistics
Using rotating vane electric field mills and Gerdien capacitors, we measured the electric field profile and conductivity during 850 overflights of thunderstorms and electrified shower clouds (ESCs) spanning regions including the Southeastern United States, the Western Atlantic Ocean, the Gulf of Mexico, Central America and adjacent oceans, Central Brazil, and the South Pacific. The overflights include storms over land and ocean, and with positive and negative fields above the storms. Over three-quarters (78%) of the land storms had detectable lightning, while less than half (43%) of the oceanic storms had lightning. Integrating our electric field and conductivity data, we determined total conduction currents and flash rates for each overpass. With knowledge of the storm location (land or ocean) and type (with or without lightning), we determine the mean currents by location and type. The mean current for ocean thunderstorms is 1.7 A while the mean current for land thunderstorms is 1.0 A. The mean current for ocean ESCs 0.41 A and the mean current for land ESCs is 0.13 A. We did not find any significant regional or latitudinal based patterns in our total conduction currents. By combining the aircraft derived storm currents and flash rates with diurnal flash rate statistics derived from the Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) low Earth orbiting satellites, we reproduce the diurnal variation in the global electric circuit (i.e., the Carnegie curve) to within 4% for all but two short periods of time. The agreement with the Carnegie curve was obtained without any tuning or adjustment of the satellite or aircraft data. Given our data and assumptions, mean contributions to the global electric circuit are 1.1 kA (land) and 0.7 kA (ocean) from thunderstorms, and 0.22 kA (ocean) and 0.04 (land) from ESCs, resulting in a mean total conduction current estimate for the global electric circuit of 2.0 kA. Mean storm counts are 1100 for land thunderstorms, 530 for ocean ESCs, 390 for ocean thunderstorms, and 330 for land ESCs
Electric Field Measurements During the Genesis and Rapid Intensification Processes (GRIP) Field Program
During the Genesis and Rapid Intensification Processes (GRIP) field program, a system of 6 electric field mills was flown on one of NASA's Global Hawk aircraft. We placed several mills on the aircraft to enable us to measure the vector electric field. We created a distributed, ethernet-connected system so that each sensor has its own embedded Linux system, complete with web server. This makes our current generation system fully "sensor web enabled." The Global Hawk has several unique qualities, but relevant to quality storm electric field measurements are high altitude (20 km) and long duration (20-30 hours) flights. There are several aircraft participating in the GRIP program, and coordinated measurements are happening. Lightning and electric field measurements will be used to study the relationships between lightning and other storm characteristics. It has been long understood that lightning can be used as a marker for strong convective activity. Past research and field programs suggest that lightning flash rate may serve as an indicator and precursor for rapid intensification change in tropical cyclones and hurricanes. We have the opportunity to sample hurricanes for many hours at a time and observe intensification (or de-intensification) periods. The electrical properties of hurricanes during such periods are not well known. America
Flash Detection Efficiencies of Long Range Lightning Detection Networks During GRIP
We flew our Lightning Instrument Package (LIP) on the NASA Global Hawk as a part of the Genesis and Rapid Intensification Processes (GRIP) field program. The GRIP program was a NASA Earth science field experiment during the months of August and September, 2010. During the program, the LIP detected lighting from 48 of the 213 of the storms overflown by the Global Hawk. The time and location of tagged LIP flashes can be used as a "ground truth" dataset for checking the detection efficiency of the various long or extended range ground-based lightning detection systems available during the GRIP program. The systems analyzed included Vaisala Long Range (LR), Vaisala GLD360, the World Wide Lightning Location Network (WWLLN), and the Earth Networks Total Lightning Network (ENTLN). The long term goal of our research is to help understand the advantages and limitations of these systems so that we can utilize them for both proxy data applications and cross sensor validation of the GOES-R Geostationary Lightning Mapper (GLM) sensor when it is launched in the 2015 timeframe
Combined Aircraft and Satellite-Derived Storm Electric Current and Lightning Rates Measurements and Implications for the Global Electric Circuit
Using rotating vane electric field mills and Gerdien capacitors, we measured the electric field profile and conductivity during 850 overflights of electrified shower clouds and thunderstorms spanning regions including the Southeastern United States, the Western Atlantic Ocean, the Gulf of Mexico, Central America and adjacent oceans, Central Brazil, and the South Pacific. The overflights include storms over land and ocean, with and without lightning, and with positive and negative fields above the storms. The measurements were made with the NASA ER-2 and the Altus-II high altitude aircrafts. Peak electric fields, with lightning transients removed, ranged from -1.0 kV/m to 16 kV/m, with a mean value of 0.9 kV/m. The median peak field was 0.29 kV/m. Integrating our electric field and conductivity data, we determined total conduction currents and flash rates for each overpass. With knowledge of the storm location (land or ocean) and type (with or without lightning), we determine the mean currents by location and type. The mean current for ocean storms with lightning is 1.6 A while the mean current for land storms with lightning is 1.0 A. The mean current for oceanic storms without lightning (i.e., electrified shower clouds) is 0.39 A and the mean current for land storms without lightning is 0.13 A. Thus, on average, land storms with or without lightning have about half the mean current as their corresponding oceanic storm counterparts. Over three-quarters (78%) of the land storms had detectable lightning, while less than half (43%) of the oceanic storms had lightning. We did not find any significant regional or latitudinal based patterns in our total conduction currents. By combining the aircraft derived storm currents and flash rates with diurnal lightning statistics derived from the Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) low Earth orbiting satellites, we reproduce the diurnal variation in the global electric circuit (i.e., the Carnegie curve) to within 4% for all but two short periods of time. This excellent agreement with the Carnegie curve was obtained without any tuning or adjustment of the satellite or aircraft data. Given our data and assumptions, mean contributions to the global electric circuit are 0.7 kA (ocean) and 1.1 kA (land) from lightning-producing storms, and 0.22 kA (ocean) and 0.04 (land) from electrified shower clouds, resulting in a mean total conduction current estimate for the global electric circuit of 2.0 kA. Breaking the results down into mean storm counts reveals 1100 for land storms with lightning, 530 for ocean storms without lightning, 390 for ocean storms with lightning, and 330 for land storms without lightning
GOES-R AWG GLM Val Tool Development
We are developing tools needed to enable the validation of the Geostationary Lightning Mapper (GLM). In order to develop and test these tools, we have need of a robust, high-fidelity set of GLM proxy data. Many steps have been taken to ensure that the proxy data are high quality. LIS is the closest analog that exists for GLM, so it has been used extensively in developing the GLM proxy. We have verified the proxy data both statistically and algorithmically. The proxy data are pixel (event) data, called Level 1B. These data were then clustered into flashes by the Lightning Cluster-Filter Algorithm (LCFA), generating proxy Level 2 data. These were then compared with the data used to generate the proxy, and both the proxy data and the LCFA were validated. We have developed tools to allow us to visualize and compare the GLM proxy data with several other sources of lightning and other meteorological data (the so-called shallow-dive tool). The shallow-dive tool shows storm-level data and can ingest many different ground-based lightning detection networks, including: NLDN, LMA, WWLLN, and ENTLN. These are presented in a way such that it can be seen if the GLM is properly detecting the lightning in location and time comparable to the ground-based networks. Currently in development is the deep-dive tool, which will allow us to dive into the GLM data, down to flash, group and event level. This will allow us to assess performance in comparison with other data sources, and tell us if there are detection, timing, or geolocation problems. These tools will be compatible with the GLM Level-2 data format, so they can be used beginning on Day 0
Preliminary Assessment of Detection Efficiency for the Geostationary Lightning Mapper Using Intercomparisons with Ground-Based Systems
As part of the calibration/validation (cal/val) effort for the Geostationary Lightning Mapper (GLM) on GOES-16, we need to assess instrument performance (detection efficiency and accuracy). One major effort is to calculate the detection efficiency of GLM by comparing to multiple ground-based systems. These comparisons will be done pair-wise between GLM and each other source. A complication in this process is that the ground-based systems sense different properties of the lightning signal than does GLM (e.g., RF vs. optical). Also, each system has a different time and space resolution and accuracy. Preliminary results indicate that GLM is performing at or above its specification
Lightning Jump Algorithm and Relation to Thunderstorm Cell Tracking, GLM Proxy and Other Meteorological Measurements
The lightning jump algorithm has a robust history in correlating upward trends in lightning to severe and hazardous weather occurrence. The algorithm uses the correlation between the physical principles that govern an updraft's ability to produce microphysical and kinematic conditions conducive for electrification and its role in the development of severe weather conditions. Recent work has demonstrated that the lightning jump algorithm concept holds significant promise in the operational realm, aiding in the identification of thunderstorms that have potential to produce severe or hazardous weather. However, a large amount of work still needs to be completed in spite of these positive results. The total lightning jump algorithm is not a stand-alone concept that can be used independent of other meteorological measurements, parameters, and techniques. For example, the algorithm is highly dependent upon thunderstorm tracking to build lightning histories on convective cells. Current tracking methods show that thunderstorm cell tracking is most reliable and cell histories are most accurate when radar information is incorporated with lightning data. In the absence of radar data, the cell tracking is a bit less reliable but the value added by the lightning information is much greater. For optimal application, the algorithm should be integrated with other measurements that assess storm scale properties (e.g., satellite, radar). Therefore, the recent focus of this research effort has been assessing the lightning jump's relation to thunderstorm tracking, meteorological parameters, and its potential uses in operational meteorology. Furthermore, the algorithm must be tailored for the optically-based GOES-R Geostationary Lightning Mapper (GLM), as what has been observed using Very High Frequency Lightning Mapping Array (VHF LMA) measurements will not exactly translate to what will be observed by GLM due to resolution and other instrument differences. Herein, we present some of the promising aspects and challenges encountered in utilizing objective tracking and GLM proxy data, as well as recent results that demonstrate the value added information gained by combining the lightning jump concept with traditional meteorological measurements
Summary of Almost 20 Years of Storm Overflight Electric Field, Conductivity, Flash Rate, and Current Statistics
We present total conduction (Wilson) currents for more than 1000 high-altitude aircraft overflights of electrified clouds acquired over nearly two decades. The overflights include a wide geographical sample of storms over land and ocean, with and without lightning, and with positive (i.e., upward-directed) and negative current. Peak electric field, with lightning transients removed, ranged from -1.0 kV/m to 16. kV/m, with mean (median) of 0.9 kV/m (0.29 kV/m). Total conductivity at flight altitude ranged from 0.6 pS/m to 3.6 pS/m, with mean and median of 2.2 pS/m. Peak current densities ranged from -2.0 nA m(exp -2) to 33.0 nA m(exp -2) with mean (median) of 1.9 nA m(exp -2) (0.6 nA m(exp -2)). Total upward current flow from storms in our dataset ranged from -1.3 to 9.4 A. The mean current for storms with lightning is 1.7 A over ocean and 1.0 A over land. The mean current for electrified shower clouds (i.e. electrified storms without lightning) is 0.41 A for ocean and 0.13 A for land. About 78% (43%) of the land (ocean) storms have detectable lightning. Land storms have 2.8 times the mean flash rate as ocean storms (2.2 versus 0.8 flashes min-1, respectively). Approximately 7% of the overflights had negative current. The mean and median currents for positive (negative) polarity storms are 1.0 and 0.35 A (-0.30 and -0.26 A). We found no regional or latitudinal-based patterns in our storm currents, nor support for simple scaling laws between cloud top height and lightning flash rate
Summary of Almost 20 Years of Storm Overflight Electric Field, Conductivity, Flash Rates, and Electric Current Statistics
We determined total conduction currents and flash rates for around 900 high-altitude aircraft overflights of electrified clouds over 17 years. The overflights include a wide geographical sample of storms over land and ocean, with and without lightning, and with positive (i.e., upward-directed) and negative current. Peak electric field, with lightning transients removed, ranged from -1.0 kV m(sup -1) to 16. kV m(sup -1), with mean (median) of 0.9 kV m(sup -1) (0.29 kV m(sup -1)). Total conductivity at flight altitude ranged from 0.6 pS m(sup -1) to 3.6 pS m(sup -1), with mean and median of 2.2 pS m(sup -1). Peak current densities ranged from -2.0 nA m(sup -2) to 33.0 nA m(sup -2) with mean (median) of 1.9 nA m(sup -2) (0.6 nA m(sup -2)). Total upward current flow from storms in our dataset ranged from -1.3 to 9.4 A. The mean current for storms with lightning is 1.6 A over ocean and 1.0 A over land. The mean current for electrified shower clouds (i.e. electrified storms without lightning) is 0.39 A for ocean and 0.13 A for land. About 78% (43%) of the land (ocean) storms have detectable lightning. Land storms have 2.8 times the mean flash rate as ocean storms (2.2 versus 0.8 flashes min(sup -1), respectively). Approximately 7% of the overflights had negative current. The mean and median currents for positive (negative) polarity storms are 1.0 and 0.35 A (-0.30 and -0.26 A). We found no regional or latitudinal-based patterns in our storm currents, nor support for simple scaling laws between cloud top height and lightning flash rate
Further Research on the Electrification of Pyrocumulus Clouds
Past research on pyrocumulus electrification has demonstrated that a variety of lightning types can occur, including cloudtoground (CG) flashes, sometimes of dominant positive polarity, as well as small intracloud (IC) discharges in the upper levels of the pyrocloud. In Colorado during summer 2012, the first combined polarimetric radar, multiDoppler radar, and threedimensional lightning mapping array (LMA) observations of lightningproducing pyrocumulus were obtained. These observations suggested that the National Lightning Detection Network (NLDN) was not sensitive enough to detect the small IC flashes that appear to be the dominant mode of lightning in these clouds. However, after an upgrade to the network in late 2012, the NLDN began detecting some of this pyrocumulus lightning. Multiple pyrocumulus clouds documented by the University of Wisconsin for various fires in 2013 and 2014 (including over the Rim, West Fork Complex, Yarnell Hill, Hardluck, and several other incidents) are examined and reported on here. This study exploits the increasedsensitivity NLDN as well as the new nationwide U.S. network of polarimetric Nextgeneration Radars (NEXRADs). These observations document the common occurrence of a polarimetric "dirty ice" signature modest reflectivities (2040+ dBZ), nearzero differential reflectivity, and reduced correlation coefficient (less than 0.9) prior to the production of lightning. This signature is indicative of a mixture of ash and ice particles in the upper levels of the pyrocloud (less than 20 C), with the ice interpreted as being necessary for pyrocloud electrification. PseudoGeostationary Lightning Mapper (GLM) data will be produced from the 2012 LMA observations, and the ability of GLM to detect small pyrocumulus ICs will be assessed. The utility of lightning and polarimetric radar for documenting rapid wildfire growth, as well as for documenting pyrocumulus impacts on the composition of the upper troposphere/lower stratosphere (UTLS), will be discussed
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