A Correlation between Lightning Flash Frequencies and the Statistical Characteristics of Convective Activity in the Atmosphere

2019 ◽  
Vol 485 (1) ◽  
pp. 273-278 ◽  
Author(s):  
A. V. Eliseev ◽  
A. N. Ploskov ◽  
A. V. Chernokulsky ◽  
I. I. Mokhov
2019 ◽  
Vol 485 (1) ◽  
pp. 76-82
Author(s):  
A. V. Eliseev ◽  
A. N. Ploskov ◽  
А. V. Chernokulsky ◽  
I. I. Mokhov

A modification of the commonly used Price-Rind scheme for lightning flashes frequency (LFF), which can be used for calculations with large spatial and time steps, is developed. With such steps, the exponent in the relationship of LFF on convective cloud heights appears to be smaller by a factor of two over land and by one fourth over ocean in comparison to that in the original Price-Rind scheme. The modified version is implemented into the IAP RAS climate model (CM). The results of the lightning flash frequency simulations with the modified scheme agree better with the satellite data than those with the original one. In the IAP RAS CM, global warming (cooling) leads to LFF increase (decrease) in all seasons. The sensitivity of lightning flashes frequency to the surface air temperature change at the global level is estimated equal to 10%/K.


2011 ◽  
Vol 139 (1) ◽  
pp. 175-191 ◽  
Author(s):  
Sergio F. Abarca ◽  
Kristen L. Corbosiero ◽  
David Vollaro

Abstract Lightning flash density in tropical cyclones (TCs) is investigated to identify whether lightning flashes provide information on TC intensity and/or intensity change, to provide further insight into TC asymmetric convective structure induced by vertical shear and storm motion, and to assess how well the World Wide Lightning Location Network (WWLLN) is suited for the observation of TCs. The 24 Atlantic basin TCs that came within 400 km of the United States from 2004 to 2007 are studied. The National Lightning Detection Network is used to analyze flash density as a function of peak current and to evaluate the WWLLN. Flash density is shown to be smaller for hurricanes than for tropical depressions and storms, with this reduction being gradually more pronounced as flash peak current increases. The results suggest that flash density in the inner core is a parameter with potential for distinguishing intensifying versus nonintensifying TCs, particularly in the weaker storm stages where flash densities are largest. Vertical wind shear produces a strong downshear left (right) asymmetry in the inner core (outer rainbands), whereas motion asymmetries are less clear. The unprecedented azimuthal resolution used in this study suggests that as shear strengthens, the azimuthal region of convection in the inner core is sharpened from a width of ∼130° to a width of ∼60°. The radial distribution of flash density is shown to exhibit a relatively narrow region of little activity (between 60 and 120 km from the eye), with increased activity in both regions closer to, and more distant from, the center (i.e., the eyewall and outer rainbands, respectively). Finally, it is shown that the WWLLN captures the convective activity in Atlantic basin TCs remarkably well, despite its low detection efficiency.


2009 ◽  
Vol 137 (10) ◽  
pp. 3456-3470 ◽  
Author(s):  
Lesley A. Leary ◽  
Elizabeth A. Ritchie

Abstract Lightning flashes in convective tropical clusters of the eastern North Pacific Ocean are detected by the Long-Range Lightning Detection Network and are analyzed for temporal patterns in electrical activity. The rates of lightning flash discharge in the 2006 season are analyzed for both tropical cyclones and nondeveloping cloud clusters to 1) determine if there is a difference in the convective activity of these two populations and 2) find a level of electrical activity that constitutes development in a particular system. Convective activity is associated with tropical cyclogenesis and thus we use the rate of electrical discharge as a proxy for convection associated with the likelihood of organization of individual cloud clusters into a tropical depression strength system. On the basis of the rates of lightning flashes in the cloud clusters, four levels of development are defined, ranging from non- and partially developing to fully developing cloud clusters. The levels of development are further supported by the analysis of other remotely sensed observations, such as surface scatterometer winds, that allow for the description of the mesoscale and large-scale circulation patterns in which the cloud clusters are embedded. It is found that lightning flash rates distinguish those cloud clusters that do not fully develop into tropical depressions from those that do. Receiver operating characteristic curves for these groupings are calculated, and a level of flash rate can be chosen that gives a probability of detection of 67% for a false-alarm rate of 24%.


2005 ◽  
Vol 10 (2) ◽  
pp. 151-160 ◽  
Author(s):  
J. Kala ◽  
Z. Kala

Authors of article analysed influence of variability of yield strength over cross-section of hot rolled steel member to its load-carrying capacity. In calculation models, the yield strength is usually taken as constant. But yield strength of a steel hot-rolled beam is generally a random quantity. Not only the whole beam but also its parts have slightly different material characteristics. According to the results of more accurate measurements, the statistical characteristics of the material taken from various cross-section points (e.g. from a web and a flange) are, however, more or less different. This variation is described by one dimensional random field. The load-carrying capacity of the beam IPE300 under bending moment at its ends with the lateral buckling influence included is analysed, nondimensional slenderness according to EC3 is λ¯ = 0.6. For this relatively low slender beam the influence of the yield strength on the load-carrying capacity is large. Also the influence of all the other imperfections as accurately as possible, the load-carrying capacity was determined by geometrically and materially nonlinear solution of very accurate FEM model by the ANSYS programme.


2003 ◽  
Vol 59 (3-4) ◽  
pp. 10
Author(s):  
Ye. V. Tarnavsky ◽  
G. P. Kulemin

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