1Dept. of Atmospheric Sciences, IAG/USP/Brazil, Rua do Matão 1226, 05508090, São Paulo, SP, Brazil
2Universidade Tecnológica Federal do Paraná, 86036-370, Londrina, PR, Brazil
3DSA/CPTEC, Instituto Nacional de Pesquisas Espaciais, Cachoeira Paulista, SP, Brazil
4INRA, UR407 Pathologie Végétale, 84140 Montfavet, France
Abstract. Many studies from the last decades have shown that airborne microorganisms can be intrinsically linked to atmospheric processes. Certain bacteria may constitute the most active ice nuclei found in the atmosphere and might have some influence on the formation of ice crystals in clouds. This study deals with the ice nucleation activity of Pseudomonas syringae inside of thunderstorms through numerical simulations using BRAMS (Brazilian Regional Atmospheric Model System). The numerical simulations were developed in order to investigate the effect on the total amount of rainwater as a function of ice nuclei (IN) P. syringae concentrations with different scenarios (classified as S2 to S4 scenarios) corresponding to a maximum of 102 to 104 IN bacteria per liter of cloud water plus the BRAMS default (classified as S5 scenario). Additionally, two other scenarios were included without any IN (S1) and the sum of RAMS default and S4 scenario (classified as S6). The chosen radiosonde data is for 3 March 2003, typical summertime in São Paulo City which presents a strong convective cell. The objective of the simulations was to analyze the effect of the IN concentrations on the BRAMS modeled cloud properties and precipitation. The simulated electrification of the cloud permitted analysis of the total flashes estimated from precipitable and non-precipitable ice mass fluxes in two different lightning frequencies. Among all scenarios, only S4 and S6 presented a tendency to decrease the total cloud water, and all bacteria scenarios presented a tendency to decrease the total amount of rain (−8%), corroborating other reports in the literature. All bacteria scenarios also present higher precipitable ice concentrations compared to S5 scenario, the RAMS default. The main results present the total flash number per simulation as well. From the results, the total flash numbers, from both lightning frequencies, in S4 and S6 scenarios, are from 3.1 to 3.7 higher than the BRAMS default. Even the lower bacterial concentrations (scenarios S2 and S3) produced 3 time higher number of flashes, compared to S5 scenario. This result is a function of the hydrometeors in each simulation. In conclusion, IN bacteria could affect directly the thunderstorm structure and lightning formation with many other microphysical implications.