Assessment of the total lightning flash rate density (FRD) in northeast Brazil (NEB) based on TRMM orbital data from 1998 to 2013

<p>Lightning activity over oceans is normally greatly suppressed in comparison with continents.&#160; The most conspicuous region of enhanced lightning activity over open ocean is found in the equatorial Pacific (150 W) in many global lightning climatologies (OTD, LIS, WWLLN, GLD360, RHESSI, Schumann resonance Q-bursts) and is associated with the South Pacific Convergence Zone (SPCZ).&#160; This oceanic lightning anomaly completes the zonal wavenumber-4 structure of continent-based lightning maxima (with nominal 90-degree longitudinal separation between sources), and so is appropriately named &#8220;the fourth chimney&#8221;.&#160; This region is now under continuous surveillance by the Geostationary Lightning Mapper (GLM) on the GOES-17 satellite (at 137 W).&#160; This total lightning activity is compared with Convective Available Potential Energy (CAPE) from ERA-5 reanalysis.&#160; These CAPE values are correlated with values extracted from thermodynamic soundings at proximal stations Atuona, Rikitea and Tahiti. &#160;The shape of the regional climatology of CAPE resembles that of the SPCZ and is oblique to the equator.&#160; The total lightning flash rate is positively correlated with CAPE, and lightning locations are found preferentially in regions of elevated CAPE on individual days.&#160; The diurnal variation of total lightning for January exceeds a factor-of-two and shows a phase at odds with the usual behavior of oceanic lightning near continents.</p>

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Sensitivities of the WRF Lightning Forecasting Algorithm to Parameterized Microphysics and Boundary Layer Schemes

Weather and Forecasting ◽

10.1175/waf-d-19-0101.1 ◽

2020 ◽

Vol 35 (4) ◽

pp. 1545-1560 ◽

Cited By ~ 1

Author(s):

Eugene W. McCaul ◽

Georgios Priftis ◽

Jonathan L. Case ◽

Themis Chronis ◽

Patrick N. Gatlin ◽

...

Keyword(s):

Boundary Layer ◽

Numerical Models ◽

The United States ◽

Lightning Flash ◽

Flash Rate ◽

Output Variability ◽

Empirical Procedure ◽

Forecast Models ◽

Total Lightning ◽

Insight Into

AbstractThe Lightning Forecasting Algorithm (LFA), a simple empirical procedure that transforms kinematic and microphysical fields from explicit-convection numerical models into mapped fields of estimated total lightning flash origin density, has been incorporated into operational forecast models in recent years. While several changes designed to improve LFA accuracy and reliability have been implemented, the basic linear relationship between model proxy amplitudes and diagnosed total lightning flash rate densities remains unchanged. The LFA has also been added to many models configured with microphysics and boundary layer parameterizations different from those used in the original study, suggesting the need for checks of the LFA calibration factors. To assist users, quantitative comparisons of LFA output for some commonly used model physics choices are performed. Results are reported here from a 12-member ensemble that combines four microphysics with three boundary layer schemes, to provide insight into the extent of LFA output variability. Data from spring 2018 in Nepal–Bangladesh–India show that across the ensemble of forecasts in the entire three-month period, the LFA peak flash rate densities all fell within a factor of 1.21 of well-calibrated LFA-equipped codes, with most schemes failing to show differences that are statistically significant. Sensitivities of threat areal coverage are, however, larger, suggesting substantial variation in the amounts of ice species produced in storm anvils by the various microphysics schemes. Current explicit-convection operational models in the United States employ schemes that are among those exhibiting the larger biases. For users seeking optimum performance, we present recommended methods for recalibrating the LFA.

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Lightning Clustering to Study Regional Variations in Thunderstorm Characteristics

10.5194/egusphere-egu2020-20611 ◽

2020 ◽

Author(s):

Jeff Lapierre ◽

Michael Stock

Keyword(s):

Clustering Algorithm ◽

Geographical Region ◽

Lightning Flash ◽

Peak Current ◽

Regional Variations ◽

Flash Rate ◽

The Earth ◽

Total Lightning

<p>Many studies have shown that the characteristics of lightning such as size and peak current differ by geographical region as well as between ocean and continental thunderstorms. For example, several studies have shown that the lightning in oceanic thunderstorms are generally larger and have lightning with higher peak currents than in continental thunderstorms. In this study, as opposed to individual lightning flash characteristics, we focus on how thunderstorm characteristics change for various regions. We develop a lightning clustering algorithm that takes individual lightning strokes and creates thunderstorms based on their spatiotemporal proximity. We use lightning data from the Earth Networks Total Lightning Network and compare storms throughout regions of the U.S.A. and Europe. Once these thunderstorms are obtained, we can regionally categorize them and compare various characteristics (size, duration, flash rate, polarity, IC/CG ratio, etc.) to determine if any differences stand out. In this presentation, we will discuss the clustering algorithm used, analyze the results of the study, and discuss implications.</p>

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Revisiting Lightning Activity and Parameterization Using Geostationary Satellite Observations

Remote Sensing ◽

10.3390/rs13193866 ◽

2021 ◽

Vol 13 (19) ◽

pp. 3866

Author(s):

Xin Zhang ◽

Yan Yin ◽

Julia Kukulies ◽

Yang Li ◽

Xiang Kuang ◽

...

Keyword(s):

Robust Statistics ◽

Detection Efficiency ◽

Lightning Activity ◽

Power Relationship ◽

Lightning Flash ◽

Flash Rate ◽

The Difference ◽

Total Lightning ◽

The Tropics ◽

The Relationship

The Geostationary Lightning Mapper (GLM) on the Geostationary Operational Environmental Satellite 16 (GOES-16) detects total lightning continuously, with a high spatial resolution and detection efficiency. Coincident data from the GLM and the Advanced Baseline Imager (ABI) are used to explore the correlation between the cloud top properties and flash activity across the continental United States (CONUS) sector from May to September 2020. A large number of collocated infrared (IR) brightness temperature (TBB), cloud top height (CTH) and lightning data provides robust statistics. Overall, the likelihood of lightning occurrence and high flash density is higher if the TBB is colder than 225 K. The higher CTH is observed to be correlated with a larger flash rate, a smaller flash size, stronger updraft, and larger optical energy. Furthermore, the cloud top updraft velocity (w) is estimated based on the decreasing rate of TBB, but it is smaller than the updraft velocity of the convective core. As a result, the relationship between CTH and lightning flash rate is investigated independently of w over the continental, oceanic and coastal regimes in the tropics and mid-latitudes. When the CTH is higher than 12 km, the flash rates of oceanic lightning are 38% smaller than those of both coastal and continental lightning. In addition, it should be noted that more studies are necessary to examine why the oceanic lightning with low clouds (CTH < 8 km) has higher flash rates than lightning over land and coast. Finally, the exponents of derived power relationship between CTH and lightning flash rate are smaller than four, which is underestimated due to the GLM detection efficiency and the difference between IR CTH and 20 dBZ CTH. The results from combining the ABI and GLM products suggest that merging multiple satellite datasets could benefit both lightning activity and parameterization studies, although the parallax corrections should be considered.

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TRMM LIS Climatology of Thunderstorm Occurrence and Conditional Lightning Flash Rates*

Journal of Climate ◽

10.1175/jcli-d-15-0124.1 ◽

2015 ◽

Vol 28 (16) ◽

pp. 6536-6547 ◽

Cited By ~ 33

Author(s):

Daniel J. Cecil ◽

Dennis E. Buechler ◽

Richard J. Blakeslee

Keyword(s):

East Coast ◽

Eastern China ◽

Central Africa ◽

Tropical Rainfall Measuring Mission ◽

Lightning Flash ◽

Conditional Mean ◽

Flash Rate ◽

Central United States ◽

Total Lightning ◽

Imaging Sensor

Abstract The Lightning Imaging Sensor (LIS) on the Tropical Rainfall Measuring Mission (TRMM) satellite has previously been used to build climatologies of mean lightning flash rate across the global tropics and subtropics. This new work explores climatologies of thunderstorm occurrence as seen by LIS and the conditional mean flash rates when thunderstorms do occur. The region where thunderstorms are seen most often by LIS extends slightly farther east in central Africa than the corresponding region with the highest total mean annual flash rates. Presumably this reflects a difference between more frequent thunderstorm initiation in the east and upscale growth as storms move westward. There are some differences between locations with the greatest total lightning flash counts and those where thunderstorms occur most often. The greatest conditional mean flash rates—considering only those TRMM orbits that do have lightning in a given grid box—are found in subtropical regions. The highest values are in Argentina, with the central United States, Pakistan, eastern China, and the east coast of Australia also having particularly high values.

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Exploring Lightning Jump Characteristics

Weather and Forecasting ◽

10.1175/waf-d-14-00064.1 ◽

2015 ◽

Vol 30 (1) ◽

pp. 23-37 ◽

Cited By ~ 30

Author(s):

T. Chronis ◽

Lawrence D. Carey ◽

Christopher J. Schultz ◽

Elise V. Schultz ◽

Kristin M. Calhoun ◽

...

Keyword(s):

Lightning Flash ◽

Autocorrelation Functions ◽

Tracking Method ◽

Flash Rate ◽

Detection Systems ◽

Storm Tracking ◽

Lightning Detection ◽

Random Behavior ◽

Temporal Occurrence ◽

Total Lightning

Abstract This study is concerned with the characteristics of storms exhibiting an abrupt temporal increase in the total lightning flash rate [i.e., lightning jump (LJ)]. An automated storm tracking method is used to identify storm “clusters” and total lightning activity from three different lightning detection systems over Oklahoma, northern Alabama, and Washington, D.C. On average and for different employed thresholds, the clusters that encompass at least one LJ (LJ1) last longer and relate to higher maximum expected size of hail, vertical integrated liquid, and lightning flash rates (area normalized) than do the clusters without an LJ (LJ0). The respective mean radar-derived and lightning values for LJ1 (LJ0) clusters are 80 min (35 min), 14 mm (8 mm), 25 kg m−2 (18 kg m−2), and 0.05 flash min−1 km−2 (0.01 flash min−1 km−2). Furthermore, the LJ1 clusters are also characterized by slower-decaying autocorrelation functions, a result that implies a less “random” behavior in the temporal flash rate evolution. In addition, the temporal occurrence of the last LJ provides an estimate of the time remaining to the storm’s dissipation. Depending on the LJ strength (i.e., varying thresholds), these values typically range between 20 and 60 min, with stronger jumps indicating more time until storm decay. This study’s results support the hypothesis that the LJ is a proxy for the storm’s kinematic and microphysical state rather than a coincidental value.

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Modeling the Flash Rate of Thunderstorms. Part II: Implementation

Monthly Weather Review ◽

10.1175/mwr-d-10-05032.1 ◽

2011 ◽

Vol 139 (10) ◽

pp. 3112-3124 ◽

Cited By ~ 9

Author(s):

Johannes M. L. Dahl ◽

Hartmut Höller ◽

Ulrich Schumann

Keyword(s):

Small Scale ◽

Lightning Flash ◽

New Approach ◽

Southern Germany ◽

Flash Rate ◽

Convective Clouds ◽

Direct Observations ◽

Scale Modeling ◽

Lightning Detection ◽

Total Lightning

Abstract In Part I of this two-part paper a new method of predicting the total lightning flash rate in thunderstorms was introduced. In this paper, the implementation of this method into the convection-permitting Consortium for Small Scale Modeling (COSMO) model is presented. The new approach is based on a simple theoretical model that consists of a dipole charge structure, which is maintained by a generator current and discharged by lightning and, to a small extent, by a leakage current. This approach yields a set of four predictor variables, which are not amenable to direct observations and consequently need to be parameterized (Part I). Using an algorithm that identifies thunderstorm cells and their properties, this approach is applied to determine the flash frequency of every thunderstorm cell in the model domain. With this information, the number of flashes that are accumulated by each cell and during the interval between the activation of the lightning scheme can be calculated. These flashes are then randomly distributed in time and beneath each cell. The output contains the longitude, the latitude, and the time of occurrence of each simulated discharge. Simulations of real-world scenarios are presented, which are compared to measurements with the lightning detection network, LINET. These comparisons are done on the cloud scale as well as in a mesoscale region composing southern Germany (two cases each). The flash rates of individual cumulonimbus clouds at the extreme ends of the intensity spectrum are realistically simulated. The simulated overall lightning activity over southern Germany is dominated by spatiotemporal displacements of the modeled convective clouds, although the scheme generally reproduces realistic patterns such as coherent lightning swaths.

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An Analysis of Total Lightning Flash Rates Over Florida

Journal of Geophysical Research Atmospheres ◽

10.1002/2017jd027579 ◽

2017 ◽

Vol 122 (23) ◽

Cited By ~ 1

Author(s):

Thomas O. Mazzetti ◽

Henry E. Fuelberg

Keyword(s):

Lightning Flash ◽

Total Lightning

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A Total Lightning Trending Algorithm to Identify Severe Thunderstorms

Journal of Atmospheric and Oceanic Technology ◽

10.1175/2009jtecha1286.1 ◽

2010 ◽

Vol 27 (1) ◽

pp. 3-22 ◽

Cited By ~ 68

Author(s):

Patrick N. Gatlin ◽

Steven J. Goodman

Keyword(s):

Severe Weather ◽

Lightning Flash ◽

Severe Thunderstorm ◽

Critical Success ◽

Severe Thunderstorms ◽

Weather Events ◽

Total Lightning ◽

Jump Algorithm ◽

Early Indication ◽

Critical Success Index

Abstract An algorithm that provides an early indication of impending severe weather from observed trends in thunderstorm total lightning flash rates has been developed. The algorithm framework has been tested on 20 thunderstorms, including 1 nonsevere storm, which occurred over the course of six separate days during the spring months of 2002 and 2003. The identified surges in lightning rate (or jumps) are compared against 110 documented severe weather events produced by these thunderstorms as they moved across portions of northern Alabama and southern Tennessee. Lightning jumps precede 90% of these severe weather events, with as much as a 27-min advance notification of impending severe weather on the ground. However, 37% of lightning jumps are not followed by severe weather reports. Various configurations of the algorithm are tested, and the highest critical success index attained is 0.49. Results suggest that this lightning jump algorithm may be a useful operational diagnostic tool for severe thunderstorm potential.

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Spatiotemporal Variability of Lightning Flash Distribution over Sri Lanka

International Letters of Chemistry Physics and Astronomy ◽

10.18052/www.scipress.com/ilcpa.82.1 ◽

2019 ◽

Vol 82 ◽

pp. 1-13

Author(s):

U.G.Dilaj Maduranga ◽

Mahesh Edirisinghe ◽

L. Vimukthi Gamage

Keyword(s):

Sri Lanka ◽

Monsoon Season ◽

Tropical Rainfall Measuring Mission ◽

Spatiotemporal Variability ◽

Spatial And Temporal Variation ◽

Lightning Flash ◽

Northeast Monsoon ◽

Time Period ◽

Total Lightning ◽

Imaging Sensor

The variation of the lightning activities over Sri Lanka and surrounded costal belt (5.750N-10.000N and 79.50E-89.000E) is studied using lightning flash data of Lightning Imaging Sensor (LIS) which was launched in November 1997 for NASA’s Tropical Rainfall Measuring Mission (TRMM). The LIS data for the period of 1998 to 2014 are considered for this study. The spatial and temporal variation of lightning activities is investigated and respective results are presented. The diurnal variation over the studied area presents that maximum and minimum flash count recorded at 1530-1630 Local Time (10-11UTC) and 0530-0630LT (00-01UTC) respectively. Maximum lightning activities over the observed area have occurred after the 1330LT (08UTC) in every year during the considered time period. The seasonal variation of the lightning activities shows that the maximum lightning activities happened in First inter monsoon season (March to April) with 30.90% total lightning flashes and minimum lightning activities recorded in Northeast monsoon season (December to February) with 8.51% of total lightning flashes. Maximum flash density of 14.37fl km-2year-1 was observed at 6.980N/80.160E in First inter monsoon season. These seasonal lighting activities are agree with seasonal convective activities and temperature variation base on propagation of Intra-Tropical Convection Zone over the studied particular area. Mean monthly flash count presents a maximum in the month of April with 29.12% of lightning flashes. Variation pattern of number of lightning activities in month of April shows a tiny increment during the time period of 1998 to 2014. Maximum annual flash density of 28.09fl km-2yr-1 was observed at 6.980N/80.170E. The latitudinal variation of the lightning flash density is depicted that extreme lightning activities have happened at the southern part of the county and results show that there is a noticeable lack of lightning activities over the surrounded costal belt relatively landmass.

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