Influence of Convectively Driven Flows in the Course of a Large Fire in Portugal: The Case of Pedrógão Grande

Fire is a natural phenomenon that has played a critical role in transforming the environment and maintaining biodiversity at a global scale. However, the plants in some habitats have not developed strategies for recovery from fire or have not adapted to the changes taking place in their fire regimes. Maps showing ecological vulnerability to fires could contribute to environmental management policies in the face of global change scenarios. The main objective of this work is to characterize the ecological vulnerability to fires based on how fires occur on a global scale. For this purpose, we are going to create zonal statistics by biome and by vulnerability category, finding out the average data of the different fire variables. For this, we have taken two spatial databases previously developed by us, Ecological Vulnerability to Wildfires and Wildfires Characteristics. Ecological Vulnerability to Wildfires is a global database that categorizes spatial vulnerability by ecoregion. Wildfire Characteristics collects global spatial mean data on recurrence, seasonality, patch size, and interannual variability. The results show that in areas with High/Very High vulnerability of tropical and subtropical biomes, fires are not very intense, with a small patch size and low interannual variability, but are highly recurrent and with extensive seasonality. The most vulnerable areas of the Mediterranean biome have more intense fires, with a considerable patch size and, in addition, they present considerable interannual variability, little recurrence and limited seasonality. Temperate forest biomes present their most vulnerable areas with moderate intensity, patch size and recurrence fires, but with high interannual variability. The most vulnerable areas of the montane grasslands biome show highly recurrent fires, with extensive seasonality, with moderate patch size, intensity, and interannual variability.

Section: Introductionmentioning

confidence: 99%

Catastrophic Fire Behaviour in the June 2017 Pedrógão Grande Fire

Viegas¹,

Dias²,

Pinto³

et al. 2022

“…(2017) showed that fire particles exhibit ρhv values lower than those associated to hydrometeors. In accordance with Pinto et al (2022), this study assumes that atmospheric volumes with ρhv ≤ 0.7 are mainly filled in by pyrometeors without significant condensation, whereas larger values correspond to atmospheric volumes with significant condensation/glaciation of pyrometeors.…”

Section: Radar and Surface Observationsmentioning

confidence: 72%

“…The fire complex of Pedrogão Grande, during 17-22 June 2017, was considered as the worst on record in Portugal due to the large burnt area and related fatalities, as described in Viegas et al (2017). The influence of a mesoscale convective system over the fires was analyzed in Pinto et al (2022) for an event of 17 June.…”

Section: Introductionmentioning

confidence: 99%

Influence of a sea-breeze front over a fire plume, Pedrogão Grande wildfires (20 June 2017)

Pinto¹,

Silva²,

Viegas³

et al. 2022

During the afternoon of 20 June 2017, two massive wildfires were ongoing more than 30 km to the east-southeast of the city of Coimbra, central Portugal. There were no clouds over the location and surrounding areas. As these fires were progressing, smoke plumes were observed with their tops at around 6-7 km a.m.s.l. However, as a sea-breeze front arrived at the buoyancy sources it was observed an outstanding vertical growth of the plumes. One of these developments was particularly analyzed and it was found that the plume topped at nearly double that altitude in less than 60 min. As a result of this interaction, an impressive pyroCumulus cloud formed. This process was analyzed using weather radar with Dual polarization capabilities.

“…Thus, the magnitude of low-level reflectivity observed near the fire site is a good indicator of the overall intensity of strong convective processes caused by fire. A/PG radar was additionally used to verify if the suspected plume patterns were, in fact, originating from fire activity, based in the magnitude of the correlation coefficient that is processed in DP mode (Balakrishnan et al (1990), Pinto et al (2022)). Within the range of 100 km, the spatial resolution of the radar observations was 1 km or better.…”

Section: Methodsmentioning

confidence: 99%

Monitoring wildfire smoke dispersion using concentrations of PM10 and PM2.5

Bugalho¹,

Mendes²,

Monteiro³

et al. 2022

Portugal as a member of the European Union (EU) follows the air quality legislation regulated by Directive 2008/50/EC that states that â€œMember States shall ensure that timely information about actual or predicted exceedances of alert thresholds, and any information threshold is provided to the publicâ€. The southern European countries have biogenic contributions, mainly resulting from the long-distance transport of particulate matter, originated in arid regions, and from large forest fires, whose pollutants loads cannot be imposed limits. These sources lead to an additional contribution of atmospheric pollutants mainly during the spring and summer seasons. Climate change is increasing the vulnerability of the environment to extreme events, such as those that enhance the likelihood of forest fires. Due to the forecast increase in temperatures and decrease in precipitation and humidity it is likely there will be an increase in the frequency and intensity of forest fires in certain regions of the Mediterranean basin as is the case of Portugal. Monitoring the concentration of particles matters in the network of air quality stations can be a way of detecting the dispersion of smoke and giving possible alerts to affected populations. The analysis of PM10 and PM2.5 of the air quality network stations, from June to October, in the period 2010-2020, showed very high concentration values coincident with the years and periods of forest fires. This data was analysed for all stations by considering the average value of the concentration in the 2 days before the day of registration of fires with burned area, daily and by district, greater than 500ha, on the day of the fire occurrence and on two days later. Back trajectory analysis was performed using HYSPLIT Model to confirm the origin of the particles observed at the stations. It was observed that the percentage increase in the daily average value of PM10 concentration, between one day before and the day of the event, is variable but with 26% as an average value for the wildfire above 500ha district daily value, in the period 2010-2020 . This difference depends on the proximity of the forest fire, the area burned as an indication of its strength, the stability of the atmosphere and the height of the boundary layer. Dust episodes with origin in the deserts in Northern Africa often affect the southern regions of Portugal which leads to an increase the concentration of PM10 and PM2.5 particles. The days with high values of PM10 particles (and PM2.5), in the summer months, were studied in order to distinguish the days that could be related to dust particles, in general larger particles, from those which referred to smoke particles from forest fires, usually smaller particles. For this purpose, the relationship between the concentrations of PM2.5 in relation to PM10, in the data coincidence period, was considered. For the large fires of 2017, a more detailed assessment of these characteristics was made by studying the optical thickness of the aerosols and the Angstrom exponent of the VIIRS radiometer on board the Suomi NPP satellite.