Geostationary infrared methods for detecting lightning‐producing cumulonimbus clouds

Abstract

[1] This study documents the behavior of cloud top infrared (IR) fields known to describe physical processes associated with growing convective clouds, for 30 nonlightning and 33 cloud-to-ground (CG) lightning-producing convective storms. The goal is to define "critical" threshold values for up to 10 IR fields that delineate lightning from nonlightning convective storms. Meteosat Second Generation and United Kingdom Meteorological Office very low frequency arrival time difference satellite and lightning data, respectively, were used in this study. These were collected during the National Aeronautics and Space Administration (NASA) African Monsoon Multidisciplinary Analyses (NAMMA) field campaign in August-September 2006 in Equatorial Africa. The main conclusions show that eight of 10 IR fields that describe updraft strength, cloud depth, and glaciation (or ice at cloud top) are significantly different between the nonlightning and lightning-producing convective clouds. The lack of notch overlap in "box and whiskers" plots confirms a 95% confidence that the two data sets are different. Nonlightning-producing clouds are far less vertically developed and possess >50% weaker updrafts (as estimated from satellite trends), as well as little to no evidence of ice or glaciation at cloud top. Results from this study therefore can be used to nowcast and identify with high confidence convective clouds that are producing or are going to produce CG lightning using Meteosat data, assuming appropriate tracking of growing cumulus clouds is performed.

Polarimetric radar characteristics of storms with and without lightning activity

“…The authors documented that many of the flashes observed in thundersnow were associated with localized high‐ Z H and low‐ Z DR regions, suggesting regions with graupel production indicating that storms with lightning could have larger and more numerous graupel content than storms without lightning. Observations from ground‐based total lightning combined with Doppler and polarimetric radar [ Deierling and Petersen , ], numerical simulations with explicit microphysics [ Calhoun et al ., ], and satellite observations [ Mattos and Machado , ; Matthee and Mecikalski , ] also support this idea, and it is suggested that storms with lightning include better graupel growth conditions due the existence of stronger updrafts, higher supercooled water content, and ice particle mass.…”

A method for convective storm detection using satellite data

“…In order to better understand deep moist convection, some techniques of analysis have been used to identify or estimate different patterns in satellite images, such as initiation, cloud top glaciation, cold-U/V shape, and overshooting tops (Petersen et al, 1984;Guang and McFarlane, 1991;Morel and Senesi, 2002;Roberts and Rutledge, 2003;Setvak et al, 2003;Holloway and Neelin, 2007;Zinner et al, 2008;Bedka et al, 2010;Coning et al, 2010;Bedka, 2011;Mahovic and Mikus, 2011;Matthee and Mecikalski, 2013). Simple techniques, such as a nearest neighbor average or time trends, can show important information that highlight subtle features of severe weather.…”

Summertime Convective Initiation Nowcasting over Southeastern China Based on Advanced Himawari Imager Observations

“…For middle and high clouds, T b,6.2 , T b,6.9 , and T b,7.3 remain unchanged unless the cloud top reaches their peak weighting function levels. The BT difference (BTD) between channels 9 and 10 (i.e., T b,6.9 − T b,7.3 ) can be utilized for estimating whether a cloud has grown to a given altitude (Matthee and Mecikalski 2013). T b,6.9 − T b,7.3 is mostly negative (about −15 K) when the moist layer is at ~ 500 hPa, and meanwhile, the cloud top is lower than ~ 600 hPa.…”