The FireCCI project, as part of the ESA Climate Change Initiative (CCI), has developed and validated burned area (BA) algorithms and products with the objective to meet, as far as possible, GCOS (Global Climate Observing System) Essential Climate Variable requirements for global satellite data products from multi-sensor data archives.

The current suite of global products include FireCCI51, whose algorithm uses as input MODIS NIR surface reflectance at 250 m and 1-km-resolution active fires, and currently covers a 20-year time series. An evolution of this algorithm uses the SWIR bands of the Sentinel-3 SLSTR sensor, provided at 300 m resolution by the Synergy products developed by ESA. This input is complemented by VIIRS active fire information at 375 m resolution. The resulting BA product, called FireCCIS310, takes advantage of the improved BA detection capacity of the SWIR bands and the higher resolution of the VIIRS thermal information, apart from upgrades in the algorithm itself. This product is currently available for 2019, and it is being further processed for the subsequent years. FireCCIS310 is capable of detecting 28% more BA than FireCCI51 for the same year.

Complementary, a specific dataset has been created for sub-Saharan Africa, where more than 70% of the total global burned area occurs. This product, called FireCCISFD (SFD standing for Small Fire Dataset), uses surface reflectance from the Sentinel-2 MSI sensor at 20 m spatial resolution, supplemented by active fire information. Version 1.1 of this dataset (FireCCISFD11) covers the year 2016 and is based on Sentinel-2A data plus MODIS active fires, while the newer version (FireCCISFD20) has been processed for the year 2019, and takes advantage of the additional data provided by Sentinel-2B, duplicating the input data amount and temporal resolution, and the improved spatial resolution of VIIRS active fires. Due to the much higher spatial resolution of the input data, this product detected 58% more BA than FireCCI51 in 2016, and 82% more in 2019, mostly due to the enhanced detection of small burned patches, not detectable with coarser resolution sensors.

All these datasets provide very valuable information regarding land cover change dynamics due to fires, and their associated aerosol and greenhouse gasses emitted to the atmosphere. Particularly, the SFD datasets show that current estimations of fire emissions have been underestimated, and that they should be re-assessed taking into account the capabilities of the information provided by medium to high-resolution sensors.

How to cite: Pettinari, M. L., Lizundia-Loiola, J., Khairoun, A., Roteta, E., Storm, T., Boettcher, M., Danne, O., Brockmann, C., and Chuvieco, E.: Global and continental burned area detection from remote sensing: the FireCCI products, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1317, https://doi.org/10.5194/egusphere-egu23-1317, 2023.

Previous studies have found that global burned area products based on coarse resolution sensors tend to miss small fires (<100 ha), particularly in those regions where burnings tend to be human-controlled.

We aimed to analyse the accuracy of small fire detection of current global burned area products in China. Most regions in China tend to have small fires due to strict forest and grassland fire suppression policies, as well as straw burning ban policies. According to Chinese government statistics from 2010 to 2019, there are more than 2000 forest fires every year, with an average size of 10.9 ha per fire. However, most of the studies on fire regimes and fire impacts in China used global burned area products with relatively coarser spatial resolutions, most likely leading to considerable uncertainty in the results.

Our assessment included burned area products with coarse spatial resolution sensors (MODIS, Sentinel-3) with relatively high temporal resolution (1 day) and those with medium resolution sensors (Landsat, Sentinel-2) with relatively low temporal resolution (> 5 days). A burned area reference dataset from Sentinel-2 (S2) images was built to validate those burned area products in China. The extent to which the difference in the spatial and temporal resolutions affecting the total burned area was measured based on the spatial and temporal intercomparison of burned area products.

Accuracy metrics, including both omission (undetected burned pixels) and commission errors (unburned pixels classified as burned), were used in this study. The preliminary results indicate that the ability of global burned area products to detect small fires needs to be improved. This work imposes the essential requirement of relatively high spatial and temporal resolution burned area products for small fires.

How to cite: Lou, S., Franquesa, M., Bai, Y., and Chuvieco, E.: Preliminary assessment of burned area products in the detection of small fires: A case study of China, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8373, https://doi.org/10.5194/egusphere-egu23-8373, 2023.

How to cite: Johnsy, A. C., Cardenal, R. L., Kourkouli, P., and Zhang, Q.: Wildfire mapping with Interferometric ICEYE SAR data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11914, https://doi.org/10.5194/egusphere-egu23-11914, 2023.

Forest fires in Poland are a serious disturbance of forest ecosystems, generating large natural, social and economic losses. For this reason, it is very important to identify and quantify the factors that may affect the occurrence of fires in the forest environment.

In this paper, it was hypothesized that the structure of the forest landscape significantly affects the occurrence of forest fire. In order to verify this thesis, basic landscape metrics were calculated, reflecting the features of the structure of forest areas in Poland (number of patches, average and median area of patches, length and density of patch edges, patch shape) in relation to three characteristics of forest stands: age class, moisture type and trophic type (data from Poland National State Forest). The analyzes were carried out both at the landscape level and at the level of selected classes. Two approaches were tested to statistically test the impact of landscape structure on forest fires:

1. The metrics were calculated with reference to the test set (A), which was the areas of buffer zones with a radius of 1000 m established around the occurrences of fires from 2015 in one of the Polish voivodeships (Lubelskie voivodeship), registered by the National Forest Fire Information System (NFFIS). The control sets were buffer zones of the same radius, established around randomly placed points: allowing (set B) and not allowing (set C) the overlapping of buffer zones. It was assumed that finding a statistically significant difference between set A and sets B or C allows the acceptance of a research hypothesis in relation to the features of the landscape structure expressed by the analyzed metrics. Therefore, statistical analysis was performed using the Kruskal-Wallis test and the Wilcoxon test for paired observations.

2. The indicators were calculated in relation to the test set (A), which was the areas of buffer zones with a radius of 1000 m established around the occurrences of fires from 2007-2017 in Poland registered by the National Forest Fire Information System (NFFIS). The control set consisted of buffer zones of identical radius established around randomly selected points (selected by stratified random sampling). It was assumed that finding a statistically significant difference between the two groups allows for the positive verification of a research hypothesis in relation to the feature of the landscape structure expressed by the analyzed indicator. For this purpose, statistical analysis was performed using the Mann-Whitney U test.

Preliminary results allowed to identify statistically significant differences between the features of the forest structure in the vicinity of fire sites and the surroundings of control groups, regardless of the method of selection of control groups. This may indicate the important role of the forest structure in shaping the fire risk. Further studies are planned to confirm this conclusion. The research is carried out as part of the PRELUDIUM project no. 2019/35/N/ST10/00279, funding by the National Science Centre Poland.

How to cite: Kolanek, A. and Szymanowski, M.: The structure of the forest landscape - a potential determinant of forest fires?, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11882, https://doi.org/10.5194/egusphere-egu23-11882, 2023.

Heat waves (HWs) and wildfires are potentially considered highly correlated hazards with dramatic impacts on ecosystems and society. However, previous studies focused only on one single hazard leaving out potential compounding and cascading effects. The aim of this work is thus to investigate spatio-temporal patterns for both hazards in Mediterranean Europe and assess the potential influence of HWs on fire regime.

The historical wildfire dataset was derived from the Global Wildfire Information System (GWIS). This dataset corresponds to georeferenced polygons detected between 2000 and 2021 by MODIS. To understand the relationship between fires and HWs, we extracted several fire regime metrics accounting for density, seasonality and severity. All the metrics were computed at the scale of 12 km square grid.

Then, we characterised the HWs in terms of frequency, duration, seasonality and intensity for the same period based on a high resolution meteorological dataset (ERA5-land from Copernicus Climate Data Store). A HW was defined as a period of at least 6 days with temperatures greater than the 90^th percentile whereas intensity was calculated as the total amount of degrees exceeding that percentile during the HW. Finally, we compared HWs occurrence with information about fire events. Compound and cascading events were analysed through hazard maps to identify simultaneous occurrences of the two hazards and look at different combinations of hazard sequences. Finally, multiple linear regression models were applied to explore the complex influence of HWs characteristics on fire metrics.

The results highlighted the hotspot areas in Mediterranean countries where the common hazard occurrences were identified, and the role of HWs in the compound and cascading fire hazard events. The findings of this study could support the assessment of hazard patterns and, in turn, prevention and monitoring activities to support disaster risk reduction.

How to cite: Costa-Saura, J. M., Bacciu, V., Spano, D., Duce, P., Sanesi, G., and Elia, M.: Exploring the influence of heat waves on wildfire occurrence in Mediterranean countries of southern Europe, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15247, https://doi.org/10.5194/egusphere-egu23-15247, 2023.

The occurrence of large bushfires in southeastern Australia has been linked to the occurrence of extreme climate conditions, such as droughts and extreme temperatures. Several extreme bushfires have occurred following or during severe droughts and heatwaves, namely the Black Saturday bushfires in 2009 and the Black Summer of 2019-2020. Fire-prone weather conditions have become more severe in this region during the past years and are expected to worsen as the frequency of compound drought and extreme temperature events is expected to increase in the future, even under lower emission scenarios. This is particularly important as the impacts of compound climate events are usually larger when compared to the impacts resulting from an individual event. Therefore, compound drought and temperature extremes are likely to increase the probability of large bushfires, compared to the occurrence of an individual event.

In this work, the trivariate relationship between burned area in the months of December to February, drought conditions, and temperature extremes was analyzed using copulas for the period 2001-2020. Burned area across forests were computed using the GlobFire dataset. Drought conditions were assessed using the Standardized Precipitation Evapotranspiration Index (SPEI), computed with monthly precipitation and temperature data from the CRU TS4.05 dataset. The indices Number of Hot Days (NHD) and Number of Hot Nights (NHN) were used to identify conditions of extreme temperature and were computed using hourly temperature data from ERA5. The influence of concurrent and previous climate conditions on the burned area was assessed, for up to 3 months before the beginning of the fire event.

The results show a clear influence on the probability of occurrence of large fires under conditions of drought and extreme temperature. Drought conditions in the months before the fire event had a larger effect than temperature extremes. Moreover, the probability of occurrence of large fires is higher when compound drought and hot events are present than given only one individual extreme event.

Acknowledgements: This study was supported by the H2020 FirEUrisk project (EU H2020, Grant Agreement 101003890) and by FCT (Fundação para a Ciência e Tecnologia, Portugal) through national funds (PIDDAC) – UIDB/50019/2020 and project Floresta Limpa (PCIF/MOG/0161/2019).

How to cite: Páscoa, P., Gouveia, C., Russo, A., and Ribeiro, A.: Large bushfires under drought and extreme temperature conditions in southeastern Australia: a probabilistic assessment using copulas, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-405, https://doi.org/10.5194/egusphere-egu23-405, 2023.

Wildfires occur unevenly in the territory, driven by different biophysical and social factors. Understanding the spatial and temporal distribution of wildfires can help identifying common characteristics and/or dissimilarities between regions. In this research, we use specific fire metrics, from historical fire data, to explore the possibility to identify groups of municipalities based on their pyrosimilarities. We apply a clustering model based on the method k means to identify and compare groups of municipalities (defining pyroregions) of mainland Portugal (n=277), using fire data from the last 22 years (between 2000 and 2021). The fire metrics used were: (a) cumulative percentage of total burned area, (b) cumulative percentage of burned area in the summer months, (c) mean annual number of fires and (d) GINI index applied for burned area over time. We used tools available in Geographic Information Systems (ArcGIS Pro) linked with python programming, to apply the cluster method and map the results. Our preliminary results divided the mainland in 5 clusters. CL1 (n=66) is seen in the west coast and is characterised by a burned area concentrated in a few years (high Gini index), but the fires occur mainly outside the summer months; CL2 (n=50) cover municipalities in the northeast and is characterised by a high mean number of fires dispersed over the years (low GINI index); CL3 (n=26) located in the central Portugal has a high percentage of cumulative burned area throughout the years, but with low number of fires, concentrated in time; CL4 (n=63) covers the municipalities in the southwest and south and shows a low mean number of fires but  these occur mainly in the summer season and, CL5 (n=55) appears throughout the country, but is more concentrated in the west and is characterised by intermediate values in all analysed metrics. The extreme wildfires that occurred in 2017 in Portugal influence the clustering; for example, CL1 occurs on the west central coast, where the consolidated maritime pine forest has burned in October 2017, outside the summer months. The next steps of this analysis are: (i) apply other clustering methods to compare with these clusters identified with k means and their characteristics and (ii) analyse the explanatory variables that influence these fire patterns.

This work was funded by FCT, I.P.: BB and AG in the scope of PhD projects [2022.12095.BD], [2020.07651.BD], SO under the contract ‘2020.03873.CEECIND′, Centre for Geographical Studies—University of Lisbon and FCT under Grant number [UIDB/00295/2020 + UIDP/ 00295/2020].

How to cite: Barbosa, B., Gonçalves, A., Oliveira, S., Rocha, J., and Caetano, M.: Identifying pyroregions in mainland Portugal with clustering methods using GIS, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-16160, https://doi.org/10.5194/egusphere-egu23-16160, 2023.

Forest fires are a global phenomenon with severe and destructive impacts at the ecological, environmental, socio-economic and health levels. Portugal, like all Mediterranean Europe, is recurrently affected by large wildfires, particularly intensive during the summers of 2003, 2005 and 2017. The latter is remembered because of the 500 000 hectares of burned area and the at least 116 deaths in the fire season.

CeaseFire is a website that aims at converting the scientific knowledge produced at universities and research institutes into useful and user-friendly tools that provide information on fire activity and meteorological fire danger tailored to the needs of the fire community in Portugal and assist in decision making on fire management and combat and on fire damage mitigation. The website, relying on information from the LSA SAF project, provides maps and data of (1) components of the Fire Weather Index System;(2) Fire Radiative Power (FRP) released by wildfires (3) classes of meteorological fire danger, ignition potential and aftermath; (4) outlooks of the fire season severity; and (5) prescribed burned classes. The site has been sponsored by The Navigator Company, a leading force in the global pulp and paper market since the operational start of the website in 2016. The number of registered users has increased up to more than 1 600 within the fire community, comprising firemen, civil protection officers, municipalities, academic researchers and private owners. In recent years E-Redes, a national electricity distribution utility service, has also been supporting the development of the website.

CeaseFire is sufficiently flexible to include other tools and be implemented in other regions. In this context, the feedback provided by users and companies has been decisive to improve the tools and products, and extend the site to other geographical areas, namely the Zambezia province in Mozambique and, more recently, the Brazilian Pantanal.

Research work was funded by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) IDL (UIDB/50019/2020), project FIRECAST (PCIF/GRF/0204/2017) and by EUMETSAT Satellite Application Facility on Land Surface Analysis (LSA SAF).

How to cite: Nunes, S. A., DaCamara, C. C., Trigo, R. M., Trigo, I. F., Gouveia, C. M., Libonati, R., and Belém, L. B. C.: CeaseFire: from scientific knowledge to operational tools for fire combat and management, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14472, https://doi.org/10.5194/egusphere-egu23-14472, 2023.

Wildfires can be dangerous phenomena, creating risks for communities that are likely to be exposed to wildfire. The likelihood of community exposure to a wildfire is influenced by the interaction of fire behaviour factors (weather, fuel and topography) across multiple spatial scales.

Our objective is to develop an index that measures the connectivity of our communities to the multi-scaled interactions of fire behaviour factors in a computationally efficient manner. The index serves as a proxy for relative wildfire likelihood and represents temporally and spatially variable patterns in wildfire likelihood. The index will support wildfire risk assessments, including exploring problems such as optimising landscape treatment placements.

Here, we introduce the connectivity index as a multi-scaled, process-informed spatial aggregation of wildfire hazard properties across a landscape. We use a case study landscape to compare the connectivity index against simulated burn probability and historical burnt areas. Using a historically-informed parameterisation, we find a high correlation (0.83) to simulated burn probability with a fraction of the computational effort (0.3% of the runtime). The connectivity index also demonstrates an improved ability to explain historical burnt areas. We identify opportunities to further improve performance by incorporating the index into data-driven model structures.

Our findings demonstrate that the connectivity index captures structural patterns in wildfire likelihood, as influenced by the interaction of fire behaviour factors across multiple scales. By achieving this in a computationally efficient manner, we believe that the connectivity index can work alongside other measures of wildfire likelihood to inform and plan wildfire risk reduction activities, including in large-scale analysis.

How to cite: Radford, D., Maier, H., van Delden, H., Zecchin, A., and Jeanneau, A.: Efficiently Estimating Patterns in Wildfire Burn Probability, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4619, https://doi.org/10.5194/egusphere-egu23-4619, 2023.

This contribution seeks to better understand recent changes in synchronous fire danger across Europe that can overwhelm fire suppression capacity. We analyze the spatio-temporal synchronicity of fire danger in Europe over the period 1979-2021 based on the Canadian Fire Weather Index, one of the most commonly used fire indices globally (FWI; Vitolo et al. 2020). The daily synchronicity index indicates the total area with a level of FWI above 50, that represents the extreme fire danger threshold as classified by the European Forest Fire Information System (EFFIS). The annual mean surface affected by synchronicity extreme fire danger increased by about 100000 km² over the 42-year-long study period (i.e. 57% of the mean historical value). The expansion of synchronized fire potential can compromise fire management efforts.

References

Vitolo, C., Di Giuseppe, F., Barnard, C., Coughlan, R., San-Miguel-Ayanz, J., Libertá, G., & Krzeminski, B. (2020). ERA5-based global meteorological wildfire danger maps. Scientific data, 7(1), 1-11.

Acknowledgments

We acknowledge funding through the project ONFIRE, grant PID2021-123193OB-I00, funded by MCIN/AEI/ 10.13039/501100011033. A.G. thanks the Ministerio de Ciencia, Innovación y Universidades of Spain for PhD contract FPU19/06536.

How to cite: Gincheva, A., Moreno, A., Jerez, S., Montávez, J. P., and Turco, M.: Assessing fire danger synchronicity in Europe, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9310, https://doi.org/10.5194/egusphere-egu23-9310, 2023.

How to cite: Zotta, R., Schlaffer, S., Hollaus, M., Dostalova, A., Vacik, H., Müller, M., Atzberger, C., Immitzer, M., Dioszegi, G., and Dorigo, W.: Using satellite, airborne laser scanning and socio-economic data in a machine learning framework for improved fire danger modelling in the Alps, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8876, https://doi.org/10.5194/egusphere-egu23-8876, 2023.

As societal exposure to large fires increases, there is a growing concern about possible shifts in the fire regimes due to climate change. Understanding the response of fires to climatic variations is essential to adapt fire management systems and to design future prevention strategies. However, many aspects on this topic remain to be revealed.

ONFIRE, a Spanish national research project supported by the State Investigation Agency and by Ministry of Ministry of Science and Innovation, aims to push the state-of-the-art knowledge of climate impacts on fires beyond its current limitations and applications. Moreover, this project is open to any contributions. Specifically, we encourage any researcher/fire agency to joint this initiative.

In this contribution we show some preliminary results related to the main objectives of the ONFIRE project:

• The creation of a first-of-its-kind unified, open-access and user-friendly database comprised of all available burned area records from national inventories.
• A better understanding of past trends in fire series and their attribution to the anthropogenic component of climate change.
• An assessment of the spatio-temporal synchronicity of fire danger.
• The design and implementation of a public operational prototype system to perform global seasonal predictions of climate-driven fire risk for decision-making applications.

Acknowledgments
We acknowledge funding through the project ONFIRE, grant PID2021-123193OB-I00, funded by MCIN/AEI/ 10.13039/501100011033. A.G. thanks the Ministerio de Ciencia, Innovación y Universidades of Spain for PhD contract FPU19/06536.

How to cite: Turco, M., Gincheva-Norcheva, A., Torres-Vázquez, M. Á., and Jerez, S.: The ONFIRE project - on the response of fires to climate variability and change, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9137, https://doi.org/10.5194/egusphere-egu23-9137, 2023.

For the past decade, Twitter has become a robust platform for distributing messages (tweets) among numerous subscribers worldwide. During and around the occurrence of natural hazards, tweet volumes increase significantly. While Twitter is used for near real-time alerts, processes for extracting reported damage from tweets and resolving their geographical spread in high resolution are still under development. In this study we examine the spatio-temporal distribution of tweets associated with the November 2016 fire, which lasted in Haifa (Isreal) for nearly two days. The acquired tweets were classified and filtered using topic modeling procedure, a portion of them were accurately georeferenced by the Open Street Map and GeoNames gazetteers, and their hyperlocal spatio-temporal patterns were examined. It was found that the tweets’ sentiment (peaks and lows) corresponds to the fire’s occurring cascading events while their spatial distribution can be aligned with most of the actual (true) reports. Despite large uncertainties in the process, results show Twitter can serve in the future as another layer of information to assist decision makers and emergency agencies during and after cascading catastrophes.

How to cite: Zohar, M., Gennosar, B., Avny, R., Tessler, N., and Gal, A.: Spatio-temporal analysis in high resolution of curated tweets associated with the November 2016 wildfire in Haifa (Israel), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1758, https://doi.org/10.5194/egusphere-egu23-1758, 2023.

Wildfires can have significant impacts on the Earth's surface albedo, with effects that can be long-lasting. In Africa, the frequency and severity of wildfires are changing due to a combination of factors including drought, land use change, and human activity. However, the impact of wildfires on surface albedo in Africa is not well understood and previous research has produced conflicting results.

In this study, we are using Moderate Resolution Imaging Spectroradiometer (MODIS) data to investigate the potential changes in surface albedo following wildfires in Africa. Our preliminary results suggest that wildfires may have a complex and variable impact on albedo, with some regions potentially experiencing a decrease in albedo and others an increase or no significant change following a wildfire.

We are also exploring the use of different approaches to analyse the MODIS data to better understand how the choice of method may impact the results and looking how the effect varies for different land cover types. In addition, we are using Fire Radiative Power data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) to examine the role of fire intensity in driving albedo changes.

This research aims to provide new insights into the impact of wildfires on surface albedo in Africa, the underlying mechanisms driving these changes and how different analysis methods affect the conclusions. These results may have important implications for land management strategies in the region, and for understanding the impact of wildfires on local climate and ecosystem processes.

How to cite: Flegrova, M. and Brindley, H.: Investigating the Impact of Wildfires on Surface Albedo in Africa Using MODIS Data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7392, https://doi.org/10.5194/egusphere-egu23-7392, 2023.

Deforestation represents one of the major challenges of the current era as it constitutes an imminent threat to the forest carbon sink offsetting the different sources of greenhouse gas (GHG) emissions. Fire is highly contributing to forest loss and degradation as a driver (i.e. wildfires) and a clearing tool (e.g. slash-and-burn agriculture). However, fire impacts were mainly analysed at coarse spatial resolutions, and therefore estimations are deemed to be very conservative because of the high omission errors in global BA products. In this study, we focus on sub-Saharan Africa (SSA), which represents the region most affected by fires globally. We analysed fire-related forest loss at 20 m resolution based on FireCCISFD datasets available for 2016 and 2019, in combination with the Global Forest Cover (GFC) maps derived from medium-resolution sensors (Sentinel 2 and Landsat, respectively). These estimations were compared to the ones of two global BA products derived from the MODIS sensor, namely MCD64A1 (Collection 6) and FireCCI51. We found that fires are a precursor of forest loss, as burned areas had more than twice the chance to be lost than unburned ones during the two study years, and that on average, fires were directly involved in almost half of forest losses in SSA (46 ± 3.80% in 2019 and 47 ± 4.21% in 2016). Depending on biomes and the year of study, fire-related forest cover loss ranged from 32 ± 1.83% to 75 ± 3.65%. In general, the subtropics dominated by Tropical Savanna and Dry Tropical Forest exhibit the highest contributions of fire, whereas the tropical zone, where Moist Tropical Forest is prevailing, showed lower contributions due to the lower fire activity. Fragmentation, as well as fire season, were found to be drivers of forest loss as the majority of these losses occur in fragmented areas close to forest edge (< 320 m) and in late fire season. We conclude that the use of medium-resolution BA products to assess fire impacts in tropical ecosystems is crucial.

How to cite: Khairoun, A., Mouillot, F., Chen, W., Ciais, P., and Chuvieco, E.: Assessment of fire contribution to forest loss in sub-Saharan Africa using medium-resolution BA, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8151, https://doi.org/10.5194/egusphere-egu23-8151, 2023.

The 2020 worldwide bushfire activity was the most intense and widespread since the existence of satellite-based observational capabilities. The economic, societal, and ecological consequences have been immense: in Australia alone, the 2019-2020 Black Summer bushfires resulted in an economic cost of more than $100 billion, a burnt area of more than 18 M ha, 10,000 destroyed buildings, 34 direct deaths and more than 400 deaths due to smoke exposure. On the Australian East Coast, these intense wildfires lasting for almost two months produced very large smoke plumes and often fire-triggered thunderstorms - pyrocumulonimbus. These plumes and storms were predominantly within the range of operational weather radars, enabling observations of the plume thermodynamics, kinetics, and their composition. Here, we present two months of observations from a dual pol weather radar located near Sydney: a newly developed texture- and machine learning-based method enables us to extract smoke plumes and associated clouds from complex weather radar scenes including clear air and sea clutter. The characteristics of these smoke plumes are quantified including cloud top heights, volumes, projected areas, horizontal extends and daily dynamics. Using dual polarisation data, in-depth insights can be gained on the plumes’ microphysics and the transition zone from smoke to pyrocumulus and pyrocumulonimbus. These high-resolution observations contribute to a better understanding of smoke plume dynamics and provide the foundations to develop nowcasting tools to predict associated hazards such as fire-triggered storms such as downbursts, plume collapse, and ember transport.

How to cite: Guyot, A., Turner, K., Brook, J., Soderholm, J., Protat, A., and McGowan, H.: Properties of smoke plumes and associated clouds from the Australian 2019/2022 wildfiresidentified using dual polarisation weather radar observations, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17073, https://doi.org/10.5194/egusphere-egu23-17073, 2023.

After the extreme wildfire events occurred in Portugal in 2017, which burned about 500.000 hectares of land and killed more than 100 people, several initiatives were established aiming to improve the resilience and safety of communities, among which the programs "Safe Villages” (SV) and “Safe People" (SP), coordinated by the Portuguese Civil Protection (ANEPC). The present study aimed to identify the territorial and social characteristics of the villages where the SV program is being implemented. For this study, a database was built with the location of the SV already implemented in three different regions: i) Algarve, the municipalities of Alcoutim, Monchique, São Brás de Alportel; ii) Pinhal Interior, the municipalities of Alvaiázere, Figueiró dos Vinhos and Oliveira do Hospital; iii) Caramulo mountain region, the municipalities of Tondela and Mortágua. The location of the villages where the SV program is implemented was obtained via the overlap of a point representing each SV with the corresponding built-up area. The analysis was focused on the surrounding area of each village and a buffer of 100 m was drawn, as defined by law (DL 82/2021). For each protective buffer, the following parameters were calculated: percentage of critical area (high and very high structural hazard); percentage of wildland area (forest-shrubland-herbaceous); percentage of slopes above 20°; the number of times burned between 1975 and 2021; and the population density within the built-up area. Preliminary results show that, in total, 166 SV were implemented in 6 municipalities, while 2 municipalities do not have any SV implemented, showing that the implementation of the program differs largely between municipalities and regions. The characteristics of the surrounding area of the SV also vary; in Algarve, 97% of SV have 75% of the buffer with critical area, whereas in Pinhal Interior and Caramulo, there are 89% and 78%, respectively. The SV with the highest population density is in the Caramulo region with 58.6 hab/ha, then the Pinhal Interior with 56.9 hab/ha and lastly the Algarve region with 44.9 hab/ha. The municipality of Alcoutim has the highest implementation of SV (84 villages), although the maximum critical area found in their surroundings is only 18%, in one village, and in 19% of the villages, no critical area is found. These results indicate that the implementation of the SV program does not depend only on the physical factors of the territory, but also on the involvement of the population, namely the existence of a volunteer Safety Officer. This person must know the local context, existing structures at the local level and the actions required in case a wildfire is expected. The efficiency of this program and the protection of local communities can be improved by combining different criteria in selecting the villages, such as the proportion of critical area and population density.

This work was funded by FCT, I.P.: JLZ in the framework of the project People&Fire [PCIF/AGT/0136/2017], AG and BB in the scope of PhD projects [2020.07651.BD], [2022.12095.BD], SO under the contract ‘2020.03873.CEECIND′. 

How to cite: Gonçalves, A., Barbosa, B., Oliveira, S., and Zêzere, J. L.: Assessing the implementation of the “Safe Villages” program for wildfire mitigation, in three regions of Portugal, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15418, https://doi.org/10.5194/egusphere-egu23-15418, 2023.