Comparison of the dynamics of hot spots and claimed forest fires with the dynamics of lightning discharges over the Baikal natural territory
Authors: Васильев Р.В. , Тащилин М.А. , Татарников А.В. 
Published: December 2023

Грозы являются опасным природным явлением, наносящим значительный ущерб энергетическим сетям, системам связи, коммунальным структурам, лесному фонду и пр. Глобальное изменение климата сопровождается сменой типа общей, глобальной циркуляции атмосферы, вследствие чего увеличиваются факторы, способствующие возникновению гроз. Исследования гроз наиболее удобно вести при помощи сетей синхронизированных радиоприемников принимающих радиоволны сверхдлинного диапазона, которые регистрируют радиосигналы молниевых разрядов и по ним определяют местоположение разряда и его мощность. Поскольку грозы — один из основных факторов возникновения пожаров в лесах, исследование динамики пожаров и гроз актуально как для фундаментальных исследований пожарогенных факторов и их связи с окружающей средой, так и для формирования методов предсказания лесных пожаров. В работе исследованы динамика статистических характеристик и корреляций параметров гроз, термальных точек, ассоциированных с пожарами, и фактически зарегистрированных пожаров на Байкальской природной территории.
Purpose. Study of the timing of lightning discharges relative to a forest fire, to determine the likelihood of fire as a result of a lightning discharge. Methodology. The dynamics of thunderstorms were assessed using information on the lightning discharges recorded on the Vereya-MR VHF range receiver network. The Vereya-MR database contains information regarding the coordinates and time of occurrence of a lightning discharge on the territory of the Russian Federation from 2012 to 2018. The dynamics of fires was assessed from data on the coordinates and time of fires of the Regional Dispatch Service of the OSAU “Irkutsk Base of Aviation and Ground Forest Protection”, covering the territory of the Irkutsk region for the period 2012–1018 and the database of thermal spots obtained from satellite observations by the AVHRR (POES) instrument. A statistical analysis of the histogram of time intervals between the date of the fire and the dates of lightning discharges that occurred in a circle with a radius of 10 km centered at the fire location was carried out. The dates of lightning discharges within the specified area were chosen in the interval of ±14 days from the date of the fire. Testing the possible influence of the structure of the data set on the result of the statistical sample was carried out using numerical experiments in which the coordinates of the fire were shifted within a circle with a radius of 20 km, and its time was shifted by an interval of ±14 days, randomly relative to the registered fire. Findings. The fire is caused by discharges that occurred 2–4 days before it was detected on satellite data. The estimate of the probability of a fire from a lightning discharge is about 10 %, but in this case the estimate may be underestimated, since it is quite difficult to assess the effectiveness of recording an individual lightning discharge by a lightning direction network. The second maximum of lightning discharges after a fire may occur due to the initiation of showers over fires by increased temperature and emanation of combustion products. The second reason may be atmospheric aerosol, which reduces conductivity and increases the likelihood of discharges. Finally, it is necessary to comprehensively study the autocorrelation properties of weather variability, which can also shape the shown temporal dynamics of thunderstorms. Value. The maximum for the distribution of time intervals, delayed relative to the fire, may be an indicator of negative feedback in the “fire source – atmosphere” system, which could hypothetically lead to the extinguishing of summer forest fires by the rainstorms they induced. This is quite interesting information that can significantly influence the parameterization of thunderstorms and forest fires in climate models. However, the preliminary conclusions obtained need to be developed on other data sets, involving modelling of atmospheric parameters.