pendix B). A particular challenge that we faced in our current work was latency in the reanalysis datasets used to drive our model for novel attribution of fire extent. Our working group will therefore engage with the ISIMIP project to promote the creation of low-latency reanalysis products to support re-spective attribution assessment in future State of Wildfires reports and in other near real-time applications. An addi-tional avenue for enhancement of future reports is to include a greater number of climate models in the attribution work by widening the participation of other groups working on at-tribution internationally.

## The State of Wildfires report will support the expansion of attribution methods that target a range of extreme fire metrics.

Extending attribution approaches to a broader range of ex-treme fire properties (e.g. aspects of the fire size or fire be-haviour distributions) is increasingly possible as observations of individual fire characteristics and behaviour avail (Ap-pendix B). Capacity to attribute individual fire properties can be built by coupling the ConFire model with process-based models within attribution frameworks, allowing attribution of specific extreme fire characteristics to climate change and other forms of global change.

### 8.2.5 Projection

#### The State of Wildfires report will harness projections from multi-model ensembles.

In the coming years, FireMIP and ISIMIP will provide ensembles of model projections of future BA for the first time (Appendix B). The State of Wildfires report will make use of these simulations as soon as they are available, thus improv-ing upon the single model (ConFire) employed in the current edition and improving characterisation of uncertainty in the projections.

#### The State of Wildfires report will support the expansion of projection methods to target a range of extreme fire metrics.

An ambition for the State of Wildfires report is to provide projections of future fire properties that are beyond burned area, such as the fire size and behaviour distribution (Ap-pendix B). This capacity can be built by combining the ConFire model with multiple process-based models from FireMIP and ISIMIP. Advances in this area have particu-lar societal relevance in resource planning, as changes in fire behaviour (not only fire extent) are likely to factor into decision-making around future suppression resource require-ments.

## Appendix A: Year in review by continent

This appendix includes the review completed by an expert panel to supplement our quantitative analyses of extremes in the 2023–2024 fire season (see Sect. 2.1). Details of the assembled panel are provided in Table A1.

### A1 Africa

South Africa and Botswana experienced higher-than-average BA and fire size (Figs. 2, 4) in 2023–2024, which some regional experts had expected following three consecutive years of above-average rainfall that increased grassy fuel loads in the fuel-limited savannas and grasslands. This has potentially been exacerbated by a lack of prescribed burn-ing and active fire suppression in the privately held land and conservancies in the region, which likewise would have re-sulted in fuel build-up (Atlas of Namibia, 2021). The socio-economic impacts of these large fires were minimal (exten-sive grassland fires linked to high rain years are expected due to periodic 7–20-year wet-dry cycles in these ecosystems).

In east Africa, the area burned was extremely low in 2023–2024. This was in line with the expectations of re-gional experts given the effects of a triple La Niña in this region, which causes droughts in east Africa (in contrast to southern Africa). This multi-year drought meant that there were limited grass fuels to burn, and it reduced the likeli-hood of spread of accidental ignitions in many of the east African rangelands. However, the extreme fire weather en-abled fires to burn through upland forests, which are not nor-mally flammable. This included a regionally significant fire in Aberdare Forest, Nyeri County, Kenya, which reportedly burned 160 km² on 17 February 2023 (Citizen Digital, 2023).

The 2023 heatwave in North Africa exacerbated fire be-haviour in the region (Al Jazeera, 2023a). Algeria recorded significant fires in the latter half of July, facilitated by high temperatures that reached upwards of 48 °C (Al Jazeera, 2023b). Over 8000 personnel, including firefighters and the military, were deployed to combat rapidly spreading fires across 15 provinces (South African Broadcasting Corpora-tion, 2023). These efforts were critical in managing fires that forced over 1500 people from their homes (euronews, 2023). Despite these efforts, the wildfires claimed the lives of at least 34 individuals, including 10 soldiers (Al Jazeera, 2023b).

Neighbouring Tunisia also faced wildfire outbreaks, exac-erbated by strong winds that carried fires across the national border from Algeria, leading to the closure of two border crossings (Reuters, 2023a). The Tunisian wildfires prompted evacuations in the northwestern region of Tabarka, affecting at least 300 people and extending firefighting efforts to Biz-erte, Siliana, and Beja (Sullivan and Tondo, The Guardian, 2023). Resources such as firefighting aircraft and personnel were sent from EU nations to help tackle the fires, despite the challenging conditions imposed by near-record temperatures
<table><caption>**Table A1.** Experts contributing to the identification of extreme events and characterisation of the global fire season during March 2023–February 2024.</caption><thead><tr><th>Region</th><th>Expert</th><th>Country of organisation/nationality</th><th>Professional background(s)</th><th>Others consulted</th></tr></thead><tbody><tr><td rowspan="4">Africa</td><td rowspan="4">Natasha Ribeiro</td><td rowspan="4">Mozambique</td><td rowspan="4">Research</td><td>Robert Ang'ila, Karatina University</td></tr><tr><td>Kebonyethata Dintwe, Botswana University</td></tr><tr><td>John Mendelsohn, Okavango Research Institute</td></tr><tr><td>Ronald Heath, Forestry South Africa</td></tr><tr><td rowspan="3">Asia</td><td>Sally Archibald</td><td>South Africa</td><td>Research</td><td>Helen De Klerk, Stellenbosch University</td></tr><tr><td>Bambang Saharjo</td><td>Indonesia</td><td>Research, litigation</td><td></td></tr><tr><td>Veerachai Tanpipat</td><td>Thailand</td><td>Research, fire control and management instructor and consultant</td><td></td></tr><tr><td rowspan="3">Europe</td><td>Paulo Fernandes</td><td>Portugal</td><td>Research</td><td>Davide Ascoli, University of Turin, Italy</td></tr><tr><td>Stefan Doerr</td><td>UK/Germany</td><td>Research</td><td>Hellenic Agricultural Organization “DIMITRA”</td></tr><tr><td>Gavriil Xanthopoulos</td><td>Greece</td><td>Research</td><td>Institute of Mediterranean Forest Ecosystems; Niall MacLennan, Scottish Fire and Rescue Service</td></tr><tr><td rowspan="3">North America</td><td>Crystal Kolden</td><td>United States</td><td>Research, firefighting</td><td></td></tr><tr><td>Jacquelyn Shuman</td><td>United States</td><td>Research</td><td></td></tr><tr><td>Piyush Jain</td><td>Canada</td><td>Research</td><td></td></tr><tr><td rowspan="6">Oceania</td><td rowspan="5">Hamish Clarke</td><td rowspan="5">Australia</td><td rowspan="5">Research, environmental management</td><td>Grant Pearce, Fire and Emergency New Zealand</td></tr><tr><td>Simeon Telfer, South Africa Country Fire Service</td></tr><tr><td>Agnes Kristina, Department of Fire and Emergency Services</td></tr><tr><td>Russell Stephens Peacock, Queensland Fire and Emergency Services</td></tr><tr><td>Chris Collins, Tasmania Fire Service</td></tr><tr><td>Sarah Harris</td><td>Australia</td><td>Research, emergency management</td><td>David Field, NSW Rural Fire Service</td></tr><tr><td rowspan="2">South America</td><td>Dolors Armenteras</td><td>Colombia</td><td>Research</td><td>The Chico Mendes Institute for Biodiversity Conservation (ICMBio), Brazil, Santarém Office</td></tr><tr><td>Liana Anderson</td><td>Brazil</td><td>Research, disaster risk reduction strategies</td><td></td></tr></tbody></table>

of 49 °C (Gauldie, *AirMedandRescue*, 2024). In August, forest fires in mountainous regions of Morocco were also fanned by strong winds and facilitated by protracted hot spring and summer temperatures (Erraji, *Morocco World News*, 2023; Copernicus Climate Change Service, 2024a).

During December 2023–January 2024, the Western Cape of South Africa experienced wildfires related to prolonged hot and windy conditions, causing substantial damage and prompting widespread evacuations. In the Overstrand Lo-

cal Municipality, which includes coastal towns like Pringle Bay and Betty's Bay, multiple fires necessitated evacuations and destroyed properties. The Hangklip area between Pringle Bay and Betty's Bay was particularly affected, with the fires destroying properties in the Sea Farm Private Nature Reserve. On 29 January, a “code red” status was declared, indicating a serious threat to residential areas, and evacuations were advised for communities including Silversands and Seafarms (*Crisis24*, 2024; *AfricaNews*, 2024). A wildfire
swept from Simonstown to Scarborough in Cape Town, ne-
cessitating large-scale evacuation (Hough, *IOL News*, 2023).
This fire was challenging due to its rapid spread fuelled
by strong southeasterly winds and high temperatures. The
firefighting efforts were supported by multiple helicopters
and ground teams (*South African Broadcasting Corporation*,
2023). The most extensive damage was reported from the
Kluitjieskraal fire near Wolseley, where over 220 km² was
burned, and more than 40 structures were destroyed. This
fire also prompted evacuations and remained uncontained for
several days due to its size and complex terrain that hindered
ground access (*Crisis24*, 2024). Despite these extreme wild-
fires, the plantation forestry industry was not affected, with
relatively low losses due to fire.

A2 Asia

The 2023–2024 fire season in Asia was generally not an ex-
treme one, with much of central Asia experiencing low BA.
Siberia, which has seen several record-breaking fire seasons
since 2020, resulting in globally significant fire emissions
(Zheng et al., 2021), also experienced a somewhat typical
year for BA and fire C emissions. Likewise, most provinces
of China and states of India experience a fairly typical fire
season.

Nonetheless, there were regional examples of high fire ac-
tivity in the 2023–2024 fire season. The Dornod Province of
eastern Mongolia, near the borders with Russia and China,
experienced several extreme fires during April 2023 that
are also visible as anomalies in the global fire observa-
tions (Figs. 2, 4). Over 15% of the area of Dornod Aimag
burned in 2023–2024 in contrast to the 23-year average of
below 5%. The province includes the Mongolian part of
the Daurian steppe, notable for being one of the last re-
maining undisturbed steppes in the world (UNESCO World
Heritage Centre, 2017). Unusually dry and warm conditions
in eastern Mongolia during spring led to severe wildfires.
A notable wildfire spread into Dornod from the neighbour-
ing Sükhbaatar Province, fanned by windy, dry conditions
(Borneo Bulletin, 2023). The National Emergency Manage-
ment Agency mobilised over 250 individuals, including fire-
fighters and local residents, and helicopters were deployed
to manage the fast-spreading fires (Borneo Bulletin, 2023).
The effects of these wildfires were on herder and nomadic
populations, and the Mongolian Red Cross has provided aid
to 4800 herder households (International Federation of Red
Cross and Red Crescent Societies, 2023).

Although BA extent and fire counts were overall below
the 2002–2023 average along the southern border regions of
Russia during 2023–2024 (Figs. 2, 4), a number of disrup-
tive wildfires fanned by strong winds broke out during April
and May and affected regions bordering Kazakhstan, such
as in the Tyumenskaya, Omskaya, and Amurskaya oblasts
and Mongolia, such as in Irkutsk and Krasny Yar, where at
least one fatality was recorded (*Le Monde*, 2023). As well as

detecting anomalies in fire size and rate of spread in these
areas, the Global Fire Atlas also identified regionally large
and fast-moving wildfires in the Russia–China border zone
of Manchuria (Fig. 4); however these were not widely re-
ported on by media outlets or local authorities.

Lao People's Democratic Republic (PDR) experienced a
notable fire season in 2023–2024, marked by record-setting
BA at national level since 2002 in the MODIS BA data
(Figs. 2, S6). The fires were widespread, affecting various
provinces from the south to the north, including Attapu,
Khammouan, Louangphabang, Xaignabouli, and Bokeo. In
Attapeu, BA in 2023–2024 was over 2 times the average of
prior fire seasons since 2002. The fires in 2023–2024 were
generally small in scale but anomalously numerous, consis-
tent with the widespread use of slash-and-burn agricultural
fires in these regions that have been problematic for regional
air quality in this region during recent years (Meadley, *Laotian Times*, 2024). The uptick in fire counts in 2023–2024 has
been attributed in part to economic factors such as the high
price of cassava and demand for greater corn supplies to sup-
ply animal feed, which act as incentives for farmers to clear
forests for additional planting (Bhandari, *Radio Free Asia*,
2024). On top of economic factors, a heatwave that spanned
south and southeast Asia in April 2023 was reported to have
been an enabling driver (Zachariah et al., 2023). The persis-
tent smoke from these fires worsened air quality significantly
in southeast Asia, where efforts to manage transboundary
haze have been challenging during regional droughts, despite
a new transboundary agreement being signed in 2023 (*An-tara News*, 2023). Differences in fire management between
Thailand and Lao PDR were evident during the 2023 event,
with authorities intensifying patrols and seeking to control
forest fires and agricultural burning for improved air qual-
ity in Thailand (Meadley, *Laotian Times*, 2024). Conversely,
deforestation remains a critical issue in Lao PDR, with the
Laotian government facing challenges in gaining local com-
munity support for the prevention of agricultural expansion
and logging.

Earth observation data showed high-ranking BA anoma-
lies and fires with a large size and rate of growth during
2023–2024 in several regions of Pakistan, Iran, and Iraq and
parts of the Levant region (Fig. 4), consistent with reports
of extreme drought-driven wildfires in some of these regions
(Reuters, 2023b).

A3 Europe

Overall, fires burned 8400 km² in Europe from March 2023 to February 2024 according to the European Forest Fire Information System (EFFIS, 2024), of which 64.5% was from July to September and 18.1% was in March and April. Large fires (> 5 km²) amounted to 53.4% of the total BA, and those particularly large (> 100 km², n = 5) accounted for 17.7% of the total burned area. More than half (52.6%) of the BA corresponded to transitional woodland, with forests, shrub-
lands and grasslands, and agriculture respectively amounting to 19.1 %, 13.2 %, and 14.4 %. At least 44 people died as a direct result of wildfires (Copernicus Climate Change Service, 2024a; Centre for Research on the Epidemiology of Disasters, 2024).

Most countries in the Mediterranean Basin experienced mild to typical fire seasons in general, with variable timing but affecting mostly non-forest (open) vegetation types (European Forest Fire Information System (EFFIS), 2024). In the Balkans, fire activity varied among countries but was mostly very low by historical patterns such as in Croatia; however, a major exception was Greece, described in more detail below (Figs. 2, 4, A1). The other exceptions were North Macedonia, with a typical fire year, and Bulgaria, the worst year in a decade, with fire activity extending into October in both countries, and Bosnia and Herzegovina and Serbia and Montenegro, where collectively ~270 km² burned in January–February 2024.

Greece's 2023 fire season was reviewed at length by Xanthopoulos et al. (2024). It was the second worst on record regarding total area burned (1727 km²), despite recent efforts to strengthen the firefighting mechanism of the country with more aerial resources and new personnel, after another challenging fire season in 2021. The situation was kept under control until mid-July, but in the period 13–27 July, maximum temperature in many parts of the country exceeded the average for the 2010–2019 period by as much as 10 °C, according to the records of the National Observatory of Athens. This resulted in multiple fire starts pushing the limits of firefighting, which relies heavily on the aerial resources. The fires starting 18 July on the tourist island of Rhodes grew rapidly on the second day, finally burning 207 km² and stopping at the sea. About 20 000 tourists had to be evacuated from hotels along the coast. While the fire on Rhodes was still burning, three forest fires started on 3 July near the city of Aigio, in the north Peloponnese; on the island of Corfu; and near the town of Karystos in the south of Evia island. On 25 July, a Canadair CL-215 crashed near the village of Platanistos while fighting this last fire. Then, on 26 July, the tail of a cold front that passed over Greece, with the characteristic wind direction change that accompanies it, created further challenges, as a number of fire starts in central Greece and Thessaly spread fast, burning mostly in light fuels, challenged firefighters and threatened inhabited areas. The fast-spreading fire in Thessaly entered an air force base and caused a powerful explosion, resulting in damage to the nearby town of Nea Anchialos. By the end of July, the BA across the country had reached 550 km².

The next wave of multiple challenging fires in Greece began on 19 August. A lightning-caused fire that started before dawn NE of Alexandroupolis in the prefecture of Evros received limited attention at first and was destined to become the largest fire in recent European history. The fact that firefighting resources were focused on evacuation of the villages in the path of the fire rather than fire suppression may have

contributed to its eventual size. On 21 August, a second fire started to the north of the first one, near the village of Dadia. Fanned by a strong NE wind, it spread quickly, and within a few hours it reached the rear of the first one. On that day fire behaviour in terms of both spread and intensity was extreme (Athanasiou, 2024). A total of 19 migrants were trapped by the flames and were found dead on the 22 August. Another group was saved by the firefighters at the last moment. The authorities emphasised safety and evacuated the hospital in the outskirts of Alexandroupolis.

On 22 August, while the Evros fire was the focus of attention, a fire originating at more than one point near the village of Phyli, south of mount Parnis in Attica, at the outskirts of Athens started growing against the strong NE wind. Once more, many settlements were evacuated, and firefighting attention focused on protecting homes, as the fire moved slowly up the mountain slopes, finally burning 62 km² in 3 d. The Evros fire kept growing at various rates for the next 15 d, finally reaching 938 km² and becoming the largest on record in recent history in Europe. The simultaneous spread of the Evros fire, the fire in Attica, and a number of smaller fires is likely to have increased the growth rate statistics (km d⁻¹) for fires in the region (Figs. 4 and A1).

The BA of the Evros fire included 258 km² of deciduous oak forest and 218 km² of oak forest mixed with other species (Konstantinos Kaoukis, personal communication, 2024). The usually most challenging forest types regarding fire behaviour contributed less to burned area: 128 km² forest and 152 km² of evergreen shrubs. The fire was mostly only brought into control when it reached agricultural areas and barren lands. The final size of the Evros fire may not be solely attributed to adverse meteorological conditions. One aggregating factor may have been the recent shift in directing firefighting personnel more strongly from suppression towards evacuation and another the emphasis on aerial firefighting resources (Xanthopoulos et al., 2024). The latter was not effective once the extreme fire behaviour commenced (21 to 23 August). Deep-forest litter layers further hampered fire suppression in some areas, although a group of local forest workers working with hand tools were credited by the local forest service officers with control of a large part of the fire perimeter to the north, saving an estimated 100 ha of forest (Athanasiou, 2024).

Italy was the second-most-affected country after Greece, with continuous fire activity from July to October. More than 1000 km² burned in the country, of which 69 % was in Sicily (including 17 fires > 10 km²), although the largest fire (31 km²) occurred in the nearby region of Calabria (Isituto Superiore per la Protezione e la Ricerca Ambientale, 2023). A defining characteristic of these large fires was the importance (42 % overall) of agricultural land in the BA composition. The outskirts of Palermo and the Madonie Natural Regional Park were impacted by multiple wildfires in late September, causing one fatality and affecting wildland–urban interfaces, farms, and tourism.
Fire activity was insignificant in France, except for benign mountain burning (175 km²) in March–April and then in January–February, mostly in the western Pyrenees. Like in France, the north of Spain (Asturias–Cantabria) experienced unusual Spring burning activity, amounting to 423 km² during late March and early April (Educación Forestal, 2023a). In particular, the Foyedo wildfire (27 March 2023) was the largest on record for Asturias, burning 101 km² across variable vegetation but with the predominance of conifer plantations, mostly *Pinus pinaster*. It was a wind- and spot-driven fire, but its soil and overstorey burn severity were respectively low and mostly moderate, as more slowly drying fuels were not available to burn (Cátedra Cambio Climático de la Universidad de Oviedo, 2023).

Only two other notable large wildfires occurred in 2023 in continental Spain and again were unusual in that they happened in spring rather than summer. The Villanueva de Viver wildfire (23 March 2023, Castellón and Teruel) burned around 50 km² and was driven by abnormal seasonally dry conditions, combined with a shift in wind direction. It mostly burned naturally regenerated continuous pine forest of *Pinus halepensis*. Canopy fire severity was heterogeneous, with 39 % of the wildfire area being classified as high to very high severity (Mediterranean Center for Environmental Studies, 2023). The cost of fire suppression was EUR 2 million, and 1800 people were evacuated (Las Provincias, 2023).

At over 100 km², the Pinofranqueado wildfire (17 May 2023, Cáceres) was the largest fire in the Iberian Peninsula in 2023 (Copernicus Emergency Management Service, 2023b). The BA was 90 % forest, mostly pine (*Pinus pinaster*; Juntaex.es, 2023). It was a wind-driven fire, and the Canadian FWI indicates that all fine fuel was available to burn and extreme fire behaviour (FWI > 50). The fire significantly impacted the nesting of protected bird species and rainfall shortly after the wildfire caused important runoff, erosion, and disruption of water supply to the local population (Armero, *Hoy*, 2023).

The two other significant fires in Spain happened in the Canary Islands, the Puntagorda wildfire (14 July 2023, La Palma, 32 km²) and the Arafo–Candelaria wildfire (15 August 2023, Tenerife, 123 km²; Copernicus Emergency Management Service, 2023c). The latter spread for 9 d, and 94 % of its area had the status of “forest under conservation”, mostly Canary pine (*Pinus canariensis*). The fire was exacerbated by local topography and mostly low to moderate severity (Educación Forestal, 2023b). Nonetheless, 26 000 people were evacuated, 364 farms and 246 buildings (none residential) were affected, smoke impacts were substantial, and damage was estimated at EUR 80.4 million.

Like in Spain, winter shrubland burning was relevant in continental Portugal (~50 km² in February), but subsequent significant wildfire activity was restricted to two fires. The Sarzedas (66 km² ha) and Baiona (75 km²) wildfires started on 5 August under extreme fire weather (FWI > 50) and burned mostly (~70 %) forest, respectively, of pine (*P*.

*pinaster*) and eucalypt (*Eucalyptus globulus*) stands (Direção Nacional de Gestão do Programa de Fogos Rurais, 2023). Prevailing burn severity was moderate, and damage to infrastructure and emergency restoration amounted to EUR 6.4 million cost for the Sarzedas fire and a forest value loss of EUR 1.4 million (Instituto da Conservação da Natureza e das Florestas, 2023). The major run of the Baiona wildfire was on 7 August, corresponding to 73 % of the total BA, when it threatened wildland–urban interfaces and damaged several buildings and one camping park, and 20 small villages were evacuated (*Economia Online*, 2023). Moderate- to high-burn severity classes were dominant, and costs were estimated at EUR 2.7 million (tourism) and EUR 7 million (houses), as well as EUR 1.4 million in forest value loss and EUR 2.9 million for emergency stabilisation (*Rádio e Televisão de Portugal*, 2023; SIC Notícias, 2023). Finally, on 12 October, and under anomalously extreme fire weather for the time of the year, the Ponta do Pargo wildfire burned 48 km² on the island of Madeira, with an estimated agriculture-related cost of EUR 3 million (*Rádio e Televisão de Portugal*, 2023).

The year was also mild in other European countries, where burned areas can be extensive, namely Romania, Hungary, and Poland, which collectively summed only ~210 km² burned. EFFIS recorded 2461 km² burned in Ukraine, the largest fire attaining 42 km², but these figures are far from those registered in recent years. In northern Europe, a notable fire occurred in Scotland near Cannich, during the spring, the primary fire season in the humid Atlantic climate of the UK (Belcher et al., 2021). It started on 19 April and burned ~33 km² of mainly moorland, making it one of the largest fires in the UK in recent history (Sabljak, *The Herald*, 2023; personal communication Niall MacLennan, Scottish Fire and Rescue Service, 2024).

## A4 North America

Wildfire across North America in 2023–2024 was characterised by record fire activity across Canada, lower-than-normal BA in the most flammable regions of the western United States, near-average fire activity across Mexico, and several extreme events that resulted in disastrous impacts to human communities (Kolden et al., 2024). Over 150 000 km² burned in Canada in 2023 according to national statistics, over twice the previous record and over 7 times the annual average (Jain et al., 2024). The United States burned 10 900 km² in 2023, well below the long-term annual average (National Interagency Fire Center (NIFC), 2024a). Mexico has a relatively short national wildfire recording system, but March 2023–February 2024 saw among the highest area burned in the last decade (10 000 km²), and this has been associated with ongoing drought conditions (Comisión Nacional Forestal, 2024).

The fire season began earlier than normal in Canada, which regional experts have linked to early snowmelt across much of the country and persistent drought conditions in the
<figure><img src="image_27.png" /><figcaption>**Figure A1.** Summary of the 2023–2024 fire season in Greece. Time series of annual fire count, BA, C emissions, PM<sub>2.5</sub> emissions, 95th percentile fire size, fastest daily rate of growth, and 95th percentile fire daily rate of growth. Black dots show annual values prior to the latest fire season, red dots show values during the latest fire season, and dashed blue lines show the average values across all fire seasons.</figcaption></figure>

west. Abnormally high temperatures and lack of rainfall also saw forested regions of eastern Canada, including Quebec, transition rapidly to drought conditions at the end of May. The province of British Columbia recorded its first wildfire evacuation in mid-April, and in late May, over 16000 people were evacuated from Halifax, the capital city of Nova Scotia, which saw its largest ever wildfire in 2023 (Jain et al., 2024). In June, two lightning outbreaks in Quebec initiated several hundred new fires in what would eventually become a record BA year for the province (4300 km²) (Boulanger et al., 2024). While the majority of the Quebec fires were in remote regions, the smoke they generated was carried to several major cities in eastern North America, including New York, which experienced its worst air quality in half a century as the observed daily mean PM<sub>2.5</sub> concentration rose to 148.3 µg m<sup>-3</sup>, over 4 times the recommended daily limit (Wang et al., 2024). In total, over 50 million people were exposed to high levels of PM<sub>2.5</sub> for several days (Yu et al., 2024). This situation was further exacerbated in New York City by several wildfires in the nearby New Jersey pine barrens, a fire-prone dry pine forest that sees large fires during periods of drought.

The year started with low fire activity across the United States. In the High Plains of the central United States, an

outbreak of large wildfires occurred coincident with dry conditions and strong winds in March–April 2023. One wind-driven wildfire started by power lines in Oklahoma destroyed several dozen homes (Oklahoma Department of Emergency Management, 2023). Outside of the High Plains, dry conditions also elevated fire activity across the southern, eastern, and New England regions of the United States. Mexico saw slightly above-average fire activity during spring, which is the peak period of the fire season as debris burning and field clearing activities provide ignitions for predominantly shrubland and grassland wildfires.

As summer arrived in Canada, the western and boreal provinces and territories saw extreme and widespread fire activity, even as Quebec continued to burn. By the end of the year, record area had burned in British Columbia (2300 km²), Alberta (2700 km²), and the Northwest Territories (3500 km²), accompanied by evacuations of 232 000 people in numerous rural villages and large cities such as Yellowknife, NT, and Kelowna and West Kelowna, BC, where a wildfire jumped the 2 km wide Okanagan Lake (Jain et al., 2024; CBC News, 2023). The extreme behaviour of these fires not only shrouded large swaths of North America in smoke but also generated an unprecedented 140 pyrocumulonimbus clouds (Jain et al., 2024). Eight firefighters were
killed during summer 2023 in Canada (Jain et al., 2024), but miraculously no civilians died directly in the fires. Canada was at the highest national preparedness level (i.e. 5) for an unprecedented 120 continuous days starting on 11 May, indicative of the significant resource sharing required by fire management; in all, over 5500 international personnel from 12 countries and the EU were deployed to Canada during the 2023 fire season (Canadian Interagency Forest Fire Centre, 2023).

In the United States, a relatively low activity fire season became deadly in August, owing to unusual weather conditions facilitating extreme fire behaviour in multiple areas around the country. On 8 August, a pressure-gradient-induced katabatic wind event fanned several small wildfires in Hawaii, and 101 civilians died as the town of Lahaina on the island of Maui was consumed in the worst wildfire disaster in the United States in a century (Pyne, 2017). Over 2000 homes were destroyed, and over 10000 people were displaced as a result. Fires with extreme behaviour killed five additional civilians in the US states of Washington (two fatalities), Louisiana (two fatalities), and California (Crystal Kolden, unpublished data). These extreme events stood in contrast to overall low fire activity and were notable for where they occurred. Washington does not typically see many extreme, wind-driven wildfires, and Louisiana is one of the wettest states in the United States. By the end of August, the US BA was only 40% of normal levels and was the lowest since at least 2000 (NIFC, 2023; National Oceanic and Atmospheric Administration (NOAA), 2023).

As North America transitioned to autumn and then winter, Canada continued to burn nearly a month longer than normal, with the last large fires not controlled until late October. On 22 September, remarkably late in the fire season, Canada saw its largest ever 1 d total for BA at approximately 4400 km² (Jain et al., 2024). While many of the Canadian fires were fully extinguished by winter, others simply smouldered into the deep peat layers, aided by a warmer-than-normal winter with a reduced snowpack. At the end of February 2024, spaceborne thermal sensors detected several dozen fires in northern Alberta and British Columbia that were overwintering fires, likely sustained by peat smouldering (Shingler, CBC News, 2024; Scholten et al., 2021).

US fire agencies recorded just over 10 900 km² burned in 2023, just over half of the 20-year mean of 29 000 km² (NIFC, 2024a). Notably, over half of the BA was associated with higher fire activity in the central plains grasslands and the southeastern United States, while below-normal fire activity characterised California and the western United States throughout 2023 as the region exited a multi-year drought. However, the number of fires recorded was only slightly lower than average. This quiet pattern broke in February 2024, however, when drought conditions from the High Plains region of the United States down into north central Mexico coupled with strong winds to produce massive, fast-moving wildfires across multiple states on both sides

of the US–Mexico border. The US state of Texas recorded its largest ever single fire at over 4000 km² (Smokehouse Creek fire) in late February and early March that destroyed 130 homes across the High Plains region of the central United States (NIFC, 2024b). Two civilians were killed by the flames in the relatively rural area dominated by ranching, over 10 000 head of cattle died, and damages are estimated to be at least USD 4.6 million (National Oceanic and Atmospheric Administration (NOAA), 2024).

The impact of North American fires on air quality is significant, with half of the PM₂.₅ in America suggested to originate from fires (O'Dell et al., 2019). An exceptional fire season, such as seen in Canada in 2023, therefore poses an elevated level of health risk. Canada's wildfires produced levels of PM₂.₅ across the country that were well in excess of the last 20 years (Fig. A2). Additionally, long-range transport of pollution from Canada affected the Pacific Northwest, northern Midwest, and many eastern states (Fig. A3). According to the National Ambient Air Quality Standards (NAAQS) in the United States, the threshold for PM₂.₅ exposure is not to exceed 35 µg m⁻³ on average within a single day. CAMS analysis suggests that people living within over half of US states experienced up to 2 weeks of exposure at or above this level. In Canada, the safe limit for PM₂.₅ exposure, as defined by the Canadian Ambient Air Quality Standards (CAAQS), is also 35 µg m⁻³ over a 24 h period. However, the situation was worse in Canada due to closer proximity to fires, with many territories along the border experiencing up to a month of degraded air quality that exceeded national recommended exposure limits, British Columbia possibly facing twice the number of days at up to 2 months, and the Northern Territories potentially with 3 to 4 months of exposure.

The scale of the impact becomes particularly evident when comparing the number of days at double the exceedance level (70 µg m⁻³) due to short-range versus long-range transport of pollutants. In Canada, where the pollution sources were more localised, the number of days above this higher level remains substantial, ranging from a week along the border to months still at the fire epicentres. In contrast, the United States, affected primarily by long-range transport from Canada, experienced approximately half the number of such high-pollution days. It is also important to consider the context of interannual variability in fire occurrence. Last year, the United States experienced its lowest number of fires in 2 decades (Fig. 4), so most of the pollution impact came from Canada.

## A5 Oceania

As is commonly the case, there was a marked latitudinal difference in wildfire patterns in Oceania in 2023–2024. Fire activity was above average in the savannahs, grasslands, and shrublands of tropical, subtropical, and arid northern Australia. In contrast, fire activity in the southern states of Australia was generally below average and well below the levels
<figure><img src="image_28.png" /></figure>

**Figure A2.** Summary of the 2023–2024 fire season in Canada. Time series of annual fire count, BA, C emissions, PM<sub>2.5</sub> daily concentration percentiles (95th, 97th, and 99th), 95th percentile fire size, fastest daily rate of growth, and 95th percentile fire daily rate of growth. Black dots show annual values prior to the latest fire season, red dots the values during the latest fire season, and dashed blue lines the average values across all fire seasons. The PM<sub>2.5</sub> daily concentration percentiles are based on area-weighted daily mean surface PM<sub>2.5</sub> concentrations within each year across Canada from the CAMS atmospheric reanalysis (Inness et al., 2019). The grey zone marks concentrations exceeding reference levels for 24 h mean PM<sub>2.5</sub> concentration in Canada (25 µg m<sup>-3</sup>) Canadian Environmental Protection Act Federal-Provincial Working Group on Air Quality, 1998).

seen during the high-impacting Black Summer fires of 2019–2020. In New Zealand and the Pacific Islands, fire activity was relatively low compared to the preceding 2 decades.

Given the vast scale of savannah fires, 2023–2024 ranked among the top 5 years in BA for Australia as a whole since 2002 (Fisher, 2024; Fig. 2). Fire in tropical and arid areas is tightly linked to rainfall in the preceding season (Alvarado et al., 2020). The above-average fire seasons in the Northern Territory and northern Western Australia were driven to a large extent by elevated fuel growth associated with the La Niña conditions of the previous 3 years. These fires represented the vast majority of areas burned across the country in 2023–2024 (Fig. S7).

In the monsoonal north, savannah fires follow a strong seasonal pattern, with regular summer rain predictably followed by fire in the dry winter and spring months. In arid regions further south, fire remains tightly coupled to rain, but the seasonality is less pronounced. Anomalously, large fires began as early as May and June in Western Australia and the Northern Territory respectively, continuing to as late as January.

The year was also marked by a series of early-season, high-impact fires in populated areas of southwestern Western Australia, southeast Queensland, New South Wales, Victoria, and Tasmania. Hot, dry, windy conditions and extended dry periods are a major driver of forest, woodland, and shrubland fires of the subtropical and temperate south of Australia (Collins et al., 2022). In addition to 2023 being the eighth-warmest year on record, the 3 months from August to October was the driest in over 100 years of records (Bureau of Meteorology, 2024).

From October to January a string of fire events led to loss of life and property and a range of other human and environmental impacts throughout the country's southeast and southwest. In some cases, significant fire activity was observed in areas impacted by the 2019–2020 fire season. Despite these impacts, average rain in southern and eastern parts of Australia tempered fire activity for the austral summer. In Queensland and NSW, large fires in remote areas pushed the total BA in line with the long term mean, but this figure was
<figure><img src="image_29.png" /><figcaption>**Figure A3.** Impact of Canadian wildfires visible in air quality metrics for North America. Panels show the number of days in 2023 with mean PM<sub>2.5</sub> concentration over a threshold of (a) 35 µg m<sup>-3</sup> and (b) 70 µg m<sup>-3</sup>. Both the National Ambient Air Quality Standards (NAAQS) in the United States and the Canadian Ambient Air Quality Standards (CAAQS) have exposure targets of 35 µg m<sup>-3</sup> on average within a single day.</figcaption></figure>

well below average in Victoria, the Australian Capital Territory, and Tasmania.

In the southwest of Australia, a volunteer firefighter was killed while responding to a fire near Esperance. The Kings Park fire in October occurred in a popular tourist area containing vulnerable flora and threatened Perth Children's Hospital. Perth was again affected by fires in December, with several injured and five homes lost. A further two homes were lost in the region in mid-January from fires that burned 60 km². A similar sized fire burned through rugged terrain in the Gammon Ranges 600 km north of Adelaide, threatening highly significant cultural and ecological values.

A large number of significant fires affected the eastern States of Australia in October. The Tara and Mount Isa fires in Queensland burned well over 400 km² combined, destroying 65 homes and claiming the lives of two people. International and interstate support teams were deployed from New Zealand and Victoria to respond to the fires. Further south in New South Wales, significant fires included the Coolagolite Rd fire in Bega (over 70 km², two houses destroyed), the Willi Willi Rd fire in Kempsey (over 290 km², eight houses destroyed, one person killed), and large fires around Tenterfield (approximately 300 km², four homes destroyed). In November the Hudson Fire burned 228 km²; destroyed four properties; and led to the death of a volunteer fire fighter, who was killed by a falling tree while fighting the fire. In December, the Duck Creek Pilliga Forest fire burned 1385 km²

and initiated three documented fire-generated thunderstorms, with smoke impacts extending 500 km away and reaching Sydney.

In neighbouring Victoria, the fire season was bookended by high-impact events in October and then in February and March. Fires in Gippsland during October totalled 120 km² and exhibited some overnight fire runs that were regarded as unusual (Mills et al., 2022). An extended dry period saw fires impacting towns in central and western parts of the state in late February and early March. Over 40 homes were lost, and five firefighters were injured fighting two fires that originated in the Grampians National Park and burned 60 km². Interactions with the atmosphere and topography were suggested to explain extreme behaviour that was reported. This fire was followed by another near Ballarat, affecting grass, forest, and a pine plantation. Despite several extreme fire weather days and evacuation advice, a significant suppression effort aided by interstate deployments minimised impacts. The fire burned over 200 km².

In the island state of Tasmania, the fire season began early with the Coles Bay bushfire burning 27 km² of both private land and national park in September and then fires on Flinders Island in October. Other impactful fires that occurred during the season include the Dolphin Sands fire on the east coast of Tasmania that destroyed two homes and burned 2.5 km² and the multiple fires in the Brady lake area (Tasmania's central highlands) in February that destroyed
two homes and burned up to 100 km² and a fire in the Waterhouse Conservation Area that required campers to evacuate.

New Zealand experienced a normal fire season after three prior seasons well below average under La Niña conditions. The fire season began early with a relatively large fire in September on the western side of Lake Pukaki in the central Te Waipounamu/South Island in wilding pines. This fire totalled 29 km², and this was the third major wildfire event in recent years in this area at an earlier-than-normal stage of the fire season, following the 2020 Pukaki (August) and Ohau (October) fires. New Zealand then experienced a spate of fires around Waitaha/Canterbury in the Te Waipounamu/South Island between late January and mid-February 2024, with several houses burned and farmlands affected.

## A6 South America

The 2023–2024 fire season in South America was characterised by a moderately below average fire activity but with positive wildfire anomalies in specific regions, which were reportedly exacerbated by extended periods of drought and heatwave across the continent (Clarke et al., 2024; Figs. 2, 3, 4). In the Brazilian State of Amazonas, which features the largest extent of preserved old growth forests in Amazonia, June and October 2023 saw the highest fire counts since records began in 1998 (National Institute for Space Research, 2024; see also Fig. A4). This continues a recent trend towards record-setting months for fire in the State of Amazonas, with new maxima being set in 7 months of the year since 2019 (National Institute for Space Research, 2024). Recent changes in deforestation and land-use patterns are contributing to elevated fire ignitions in the state, reportedly compounded in 2023 by a historic drought and heatwave driven by El Niño (Espinoza et al., 2024; Clarke et al., 2024). Due to emissions of wildfire smoke, many areas of Amazonas experienced poor air quality from September to December 2023, including in the state capital, Manaus, where over 2 million people were exposed to the second-worst air quality in the world in October (Ministério Público Federal, 2023). The event was so severe that, in November 2023, the Federal Public Ministry opened a civil action case against the State of Amazonas, demanding evidence that the state was investing in fire prevention and combat in line with the “Plan for the Prevention and Control of Deforestation and Fires” (Estado do Amazonas, 2020). This procedure evaluates whether Amazonas authorities are accountable for environmental damage causing severe air pollution, reflecting the Public Ministry’s growing involvement at both federal and state levels in monitoring environmental degradation and seeking to make authority figures accountable (Ministério Público Federal, 2023).

National fire monitoring systems in Brazil indicate that some areas of Amazonia experienced anomalies in BA at the sub-state level. For example, BA in the municipality of San-

tarém in the State of Pará rose from an average of 70 km² in 2019 to 2022 to over 1000 km² in 2023 and has already exceeded 250 km² in 2024 (MapBiomas Brasil, 2024). Similarly, in the neighbouring Belterra municipality, BA extent was more than 3 times greater during the year 2023 than in 2019–2022 (MapBiomas Brasil, 2024). In Floresta Nacional do Tapajós, one of the most studied forest sites in the Amazon, which spans Satarém and Belterra, forest fires accounted for more than 60 % of the burned areas (MapBiomas Brasil, 2024). A total of 4000 people live in 24 communities of Traditional and Indigenous populations in the region and depend on protected forest resources for their cultural heritage, food security, economy, and livelihood in Floresta Nacional do Tapajós and Reserva Extrativista Tapajós-Arapiuns (Instituto Chico Mendes de Conservação da Biodiversidade, 2019). Fires in 2023 compounded the challenges faced by these communities, who were already isolated by low river levels resulting from the drought that severely reduced their mobility and fishing, impacting food security and enhancing socio-economic vulnerabilities.

In Chile, the 2023–2024 fire season was marked by a significant escalation in both the number and size of wildfires, especially in the central and southern regions (Fig. 4). Chile experienced its second-highest BA in the past 20 years (> 4000 km²; Jones et al., 2024). The peaks in BA at national scale were accompanied by peaks in the 95th percentile of fire size and daily rate of growth in highly populated regions such as Valparaíso (Figs. 2, 4), indicating unusually large and fast-moving fires. These fires drew international attention due to their deadly impacts on society. In February 2024, severe wildfires struck the Valparaíso region in Chile, particularly affecting Viña del Mar and other surrounding areas (NASA Earth Observatory, 2024). These fires resulted in the deaths of at least 131 people and destroyed thousands of homes, leaving at least 1600 people homeless (UN Resident Coordinator in Chile, 2024; *Al Jazeera*, 2024; *El Disconcierto*, 2024). The fires impacted the Lago Peñuelas National Reserve, where more than 60 km² of forest was affected (Oberholtz, *Fox Weather*, 2024). The National System for Disaster Prevention, Mitigation and Attention (SENAPRED) issued a red alert and ordered the evacuation of over 18 nearby towns (Oberholtz, *Fox Weather*, 2024). The February 2024 wildfires in Valparaíso followed other major disruptive wildfires in February 2023, which affected nearby regions of central Chile including Maule, Nüble, Biobío, La Araucanía, and Los Rios.

Several countries with territory in the west of Amazonia experienced anomalies in BA and fire behaviour during the 2023–2024 fire season, which coincided with drought conditions. Peru’s Loreto region, which neighbours the Brazilian State of Amazonas, faced its highest BA on record in the 2023–2024 fire season, signalling the wider impacts of drought conditions in western Amazonia (Fig. 2). The timing of peak anomalies in BA also coincided with those in Amazonas, around September–October 2023 (Fig. S2). The
<figure><img src="image_30.png" /><figcaption>**Figure A4.** Summary of the 2023–2024 fire season in the Brazilian State of Amazonas. Time series of annual fire count, BA, C emissions, PM<sub>2.5</sub> emissions, 95th percentile fire size, fastest daily rate of growth, and 95th percentile fire daily rate of growth. Black dots show annual values prior to the latest fire season, red dots the values during the latest fire season, and dashed blue lines the average values across all fire seasons. The PM<sub>2.5</sub> daily concentration percentiles are based on area-weighted daily mean surface PM<sub>2.5</sub> concentrations within each year across Amazonas from the CAMS atmospheric reanalysis (Inness et al., 2019). The grey zone marks concentrations exceeding the reference level for 24 h mean PM<sub>2.5</sub> concentration in Brazil’s National Air Quality Guidelines (25 µg m<sup>-3</sup>; Siciliano et al., 2020).</figcaption></figure>

northern Bolivian departments of La Paz and Beni experi-
enced similarly timed anomalies in BA. Remote parts of the
Colombian Amazon also saw a significant uptick in BA since
November 2023, which peaked in January 2024 (Mongabay,
2024). As a result of months of record-high temperatures and
drought conditions since the beginning of El Niño, the re-
gion recorded higher C emissions, reflecting the severity of
the burning at the end of the studied fire season. While the di-
rect impacts on society throughout these regions was not as
pointed as in the case of fires in Chile, the events are likely to
have contributed to reductions in regional air quality and also
impacted forest ecosystems and raised C emissions from fires
in South America. At the end of January there was a wild-
fire in the mountains surrounding Bogotá that affected the air
quality that affected thousands of citizens of the capital of
Colombia (France-Presse, VOA News, 2024).

In 2023-2024, Venezuela experienced its highest level of
fire activity on record, particularly in January and February
2024 (ALER, 2024; *Tiempo*, 2024; Figs. 4, S2, S8), notably
affecting the states of Anzoátegui, Cojedes, Guárico, and
Monagas, areas of which dominant land cover primarily con-

sists of savannas and extensive grasslands. This surge in fires
during the dry season was intensified by unusually warm and
dry conditions in the preceding months. These conditions,
likely a result of global warming and changes in circulation
and rainfall patterns associated with El Niño, make the land-
scapes more vulnerable to fires.

Appendix B: Frontiers in observing and modelling extreme fire occurrence and impact

This appendix summarises current challenges in the obser-
vation and modelling of extreme fire events or seasons and
identifies new technological and methodological advances
that are raising opportunities to overcome such challenges.
The section begins with a review of the study of extreme
fire *occurrence* and then focuses on the study of extreme fire
*impacts* across seven impact sectors. Advances in the study
of both fire occurrence and fire impact are required because
the impacts of extreme fires on society and the environment
do not necessarily scale with observable fire properties (see
Sect. 6.2).
# B1 Occurrence

## B1.1 Definition of extreme fire events

Studying impactful fires or unusual fire seasons is crucial for understanding changes in exposure and vulnerability to fire. However, defining “extreme” events presents several challenges. These challenges can be categorised here.

Data-oriented challenges are as follows:

- *Lack of consensus on quantitative criteria.* Variability in measurable criteria, such as fire size, across different studies hinders consistent classification. No statistical threshold is universally established to define outliers.

- *Geographic variability.* Regional differences complicate universal definitions. Size thresholds vary widely, influenced by local fire regimes.

- *Evolving definitions.* The term “extreme fire” has expanded over time, encompassing more fire types and behaviours. Climate change increases fire severity, suggesting definitions need flexibility.

- *Context dependence.* Definitions vary with ecosystem types and fire histories, lacking standardisation on baselines such as fire return intervals or ecosystem damage.

Knowledge-oriented challenges are as follows:

- *Lack of consensus on qualitative criteria.* Variability in criteria-like fire behaviour and impacts reflects differing expert opinions. The subjective nature of significant impact complicates a clear definition.

- *Terminological overlap and redundancy.* Terms like “catastrophic fire” and “megafire” overlap, causing confusion due to unclear or interchangeable usage.

- *Influence of language and culture.* Interpretations differ across languages and cultures, affecting global reporting and definitions.

- *Societal influence on scientific terminology.* Scientific terminology evolves with societal context. Language in scientific communication must remain adaptable and relevant to non-scientific audiences.

- *Scientific rigour and clarity.* Clear, consistent, and scientifically rigorous definitions are needed for standardised measurements. Existing definitions often fall short.

Defining “extreme fire” requires a significant and inclusive effort across the fire science community. We avoided a strict definition here, instead adopting a broad and flexible definition as discussed in Sect. 2.1. To support a formal definition for future iterations of this report, standardised criteria and protocols should be developed through transdisciplinary approaches, such as through workshops involving in-

put from scientists, fire practitioners, legislators, and communities (Chu et al., 2023; Linley et al., 2022; Shuman et al., 2022).

## B1.2 Observation of extreme fire events

Global-scale data for characterising extreme fire events are primarily sourced from satellite observations, notably active fire detections, BA maps, and tracking of smoke plumes. However, to accurately define how extreme a fire event is, it is crucial to contextualise present-day observations within historical data. Unfortunately, the historical records of satellite-derived active fire and BA products are relatively short. The longest coherent observations on a global scale are derived from the MODIS instruments on board the Aqua and Terra satellites, launched in 1999 and 2002 respectively. Various global BA products, such as the MCD64 product family (Giglio et al., 2018) and FireCCI51 (Lizundia-Loiola et al., 2020), as well as active fire data like the MCD14 product family (Giglio et al., 2016), have been generated based on imagery acquired by MODIS. Although these time series now span more than 2 decades, they are still relatively short when compared to the decadal to centurial fire return intervals observed in many ecosystems.

Pre-MODIS satellite data, like those from the AVHRR programme, exist and provide a continuous imagery archive from 1982 onwards. Although efforts are ongoing to generate a coherent BA product from AVHRR data (Otón et al., 2021), there are limits to the global applicability of these products. For example, unresolved challenges stemming from coherence issues between imagery from different AVHRR sensors result in artefacts and spurious trends in various regions worldwide (Giglio and Roy, 2022), although this has been debated by other authors (Pullabhotla et al., 2023).

Efforts are ongoing to extend the MODIS time series by incorporating active fire data from ATSR and VIRS with BA data (e.g. Chen et al., 2023). However, due to the different characteristics of these data, creating a coherent, multi-satellite time series of active fire data and/or BA is not straightforward. Concerns also arise with the impending de-commissioning of MODIS-Terra, raising doubts about the continuity of existing long-term fire records. However, operational satellite sensors such as VIIRS on board NOAA's series of satellites and SLSTR on board the Sentinel-3 satellites offer promising capabilities for medium-resolution BA mapping (e.g. Román et al., 2024; Lizundia-Loiola et al., 2022). Urgent attention should be directed towards developing methodologies to integrate these new datasets into a coherent, long-term BA dataset. Furthermore, advancements in medium-resolution satellite data availability and revisit times, particularly from Landsat and Sentinel-2, now enable global BA mapping at spatial resolutions as fine as 20–30 m (e.g. Roteta et al., 2021; Chuvieco et al., 2022), suggesting a potential future direction for coherent long-term global BA monitoring.
While BA is a key variable to characterise extreme fire occurrence, multiple other aspects of extreme fires can be characterised using satellite data. BA products can be used to cluster burned pixels in burned patches to obtain the number and size of individual fires (Archibald and Roy, 2009). Furthermore, the daily fire rate of spread, length of the active fire line, and spread direction can be extracted from the daily fire expansion (Andela et al., 2019). These algorithms, such as the Global Fire Atlas used in this study, give global scale and coherent estimates of patterns and trends in fire number, fire size, and rate of spread. However, these algorithms are sensitive to the temporal accuracy of the per-pixel burned date detection, the spatial resolution of the BA product, and any errors within each product. Recent advances focussing on clustering VIIRS thermal anomalies and extracting fire rate of spread, fire expansion, and length of the active fire line show promising results (Andela et al., 2022; Hantson et al., 2022; Chen et al., 2022) but have so far not been developed globally. Future development towards a global product should allow for a more detailed characterisation of fire characteristics in near-real time, well-suited for detection and quantification of fire extremes.

Active fire detections also record the amount of radiation emitted by the fire at the moment of satellite overpass (fire radiative power, FRP), within the pixel detected by the satellite. While this information is related to the intensity of the fire, the usage of FRP has been difficult as a low-intensity fire burning a large extent of the pixel can have a higher FRP than a high-intensity fire burning a small fraction of a pixel. These complications have limited a more standardised and operational usage of FRP for quantifying fire extremes. Advances in active fire detection from higher-resolution sensors may allow for a more comprehensive estimate of fire intensity when combined with FRP estimates from coarse resolution sensors (Schroeder et al., 2014, 2016).

A natural starting point for this global assessment of the 2023–2024 fire season was global data provided by the MODIS BA dataset, though we note that various national-, state-, or regional-level systems exist and can add longer-term context to the extremity of fire seasons (e.g. Canadell et al., 2021; Short, 2014; Gincheva et al., 2024). Regional datasets generally depend on manual logging of fires via field approaches or desk-based identification with high-resolution imagery or alternatively harness different blends of satellite observation with fire detection algorithms that can be regionally optimised. These approaches carry their own uncertainties and are limited by design to targeted regions, however their major advantage is multidecadal coverage. Advances in compiling regional datasets into gridded records with global coverage are bringing these advantages to formats compatible with global-scale analysis (Gincheva et al., 2024) and will thus be explored in future efforts to characterise regional extremes at scale.

### B1.3 Prediction of extreme fire events

Since the 1970s, fire predictions have relied on empirical fire behaviour models tailored to specific ecosystems (Bradshaw et al., 1984; Noble et al., 1980; Stocks et al., 1989; van Wagner, 1987), becoming pivotal tools for fire management agencies (San-Miguel-Ayanz et al., 2013). The ease of implementation and the availability of weather data have contributed significantly to their widespread adoption. However, despite their utility, several studies have highlighted the limited effectiveness of the FWI and similar metrics in fuel-limited ecosystems, where fires are driven by the short-term superficial drying of intermittently available biomass (Yebra et al., 2013). The absence of consideration for actual fuel availability presents a constraint to the meaningful application of the FWI in savanna-type ecosystems. Likewise, the response of fuel moisture to meteorological factors can be influenced by external factors that are challenging to observe and model at scale, such as mortality triggered by insect infestation or disease (Canelles et al., 2021). Beyond weather conditions, the remaining prerequisites for fire activity – namely, fuel and ignitions – are intricately linked to vegetation state, lightning activity, and human behaviours. Improving fire forecasts beyond solely considering fire weather could be achievable by accurately describing these components. This has been widely recognised in the global vegetation–fire community for several decades (Hantson et al., 2016), and consequently great advances have been made to address this through the development of fire-enabled DGVMS, as used in this report. However, explicit representation of these processes introduces biases and instabilities that, when used in isolation, limits their utilisation for assessing climate and human drivers of BA extremes (Hantson et al., 2020; Burton et al., 2024).

The availability of remote observations for fuel, either independently (Yebra et al., 2018) or supported by modelling frameworks (McNorton and Di Giuseppe, 2024), has demonstrated potential in aiding the development of new fire models and indices that partially incorporate fuel considerations into their formulation (Di Giuseppe, 2023; Hantson et al., 2016). However, it is the emergence of the data-driven revolution that holds the promise of significantly enhancing our predictive capabilities for extreme fires (McNorton et al., 2024). This has driven the development of semi-empirical tools at regional and global scales that could improve fire predictions, and their effectiveness will be assessed in the next edition of the report. Not only can these tools enhance predictive capability for extreme fires, but they also present an opportunity to disentangle the drivers of the prediction, giving us the capability to address or at least understand the causes of the event, as demonstrated by the PoF and ConFire frameworks used here. The coupling of FireMIP models with observational data (Burton et al., 2024, and used here), also showcases the potential to bridge the advanced modelling
capabilities of FireMIP with application-specific approaches such as ConFire and PoF.

Despite these technological advancements, widespread adoption is unlikely to occur suddenly, as there typically exists a delay between the creation of new indices, their operationalisation, and operational implementation by those responsible for fire prevention and control. There are also likely to be some stubborn issues with the detail provided large-scale observational data available to predictive systems, particularly in the case of fuel loads and fuel state (e.g. living versus dead). New global biomass observations, such as those from airborne and spaceborne light detection and ranging (lidar) and synthetic aperture radar (SAR), provide insights into fuel loading, but they are not currently providing information regarding fuel state that would be useful for modelling fuel moisture response to meteorological conditions (Santoro et al., 2022; Hunka et al., 2023).

Another emerging element is the recent availability of fire danger predictive systems at the seasonal and subseasonal timescales (Di Giuseppe et al., 2024). Currently, there is limited evidence on how these longer-range tools could contribute to prevention planning and adaptation strategies. While they exhibit minimal skill beyond 2 months, they may offer valuable pre-seasonal warnings under specific conditions established during important atmospheric modes of variability.

The current report does not include hybrid models for seasonal fire risk, fire propagation models, or fire susceptibility/risk mapping tools. Incorporating these approaches could offer valuable insights and will be considered in future reports. These advanced models and tools, which account for both past and present weather conditions as well as other critical factors such as soil moisture and vegetation dryness, can enhance our understanding of fire dynamics and improve predictive capabilities. By exploring these methods, future editions of the report could provide a more comprehensive overview of fire risk assessment and management strategies.

## B1.4 Attribution extreme fires to global change

The prediction and management of extreme fire events have become increasingly complex due to the multifaceted impacts of global change. Climate change exacerbates fire risks through rising temperatures, altered precipitation patterns, and more frequent and severe droughts, as shown in Canada and western Amazonia in this report. These climatic shifts affect vegetation productivity, with elevated CO₂ levels potentially increasing biomass and thereby providing more fuel for fires. Nutrient deposition and other environmental changes influence ecosystem responses, further altering fire potential. Land use changes and management practices also significantly influence fire dynamics. For example, human activities such as deforestation, urban expansion, and agricultural practices can both mitigate and exacerbate fire risks, with socioeconomic factors shown to have a strong influence on over-

all extreme fire likelihood in western Amazonia, and potentially contributing to increases in BA in 2023 in some areas of Greece. Effective land management strategies, including prescribed burns and forest thinning, are crucial for reducing fuel loads and minimising fire impacts. While climate-driven estimates of extreme behaviour are plentiful, few modelling frameworks take into account most of these dynamic factors and their interactions (Rabin et al., 2017).

We have used model-data fusion techniques that account for these factors in this report and have been able to attribute some of their influences in certain places. This report utilises semi-empirical models that blend empirical data with process-based understanding to better predict fire behaviour. Quantifying uncertainty in these models is essential, especially when dealing with extremes. By generating probability distributions, researchers can better understand the likelihood of various fire scenarios, informing more effective management and policy decisions.

Through uncertainty quantification techniques, we have been able to ascertain where we are confident in our attributions. However, uncertainties still remain, many from not considering the complex interactions and feedback onto fire, some from fire itself as it consumes fuel and some from effects of weather. Coupled vegetation-fire models explicitly represent many of these feedbacks. However, current FireMIP models struggle to accurately simulate extreme fire events (Hantson et al., 2020). One key factor hampering improvements in model development is our limited understanding of factors driving fire extinguishers in a natural setting. While much process-based knowledge exists on the factors influencing fire start and fire spread, only limited knowledge exists on the myriad of factors that can stop a fire, from changes in fuel moisture, structure, and heterogeneity to landscape fragmentation and fire fighting and how these interact (e.g. Finney et al., 2012). Without a strong theoretical understanding of these factors, process-based modelling of extremes at a global scale might be limited in the near future. For the 2023 focal events, we have shown that low fuel loads and variations in human modification of the landscape can limit fuel spread (Figs. 11, 12, S13, S14). However, we only look at a handful of events, and further examples are required at larger scales to inform improvement of process-based rates of spread in fire models.

To move forward, we need to combine these concepts in attribution techniques and quantifying uncertainty with coupled vegetation fire models, such as in FireMIP. Early attempts of this are promising – ConFire (used in Sects. 3, 4 and 5) borrows many of the modelling concepts from FireMIP, though it still lacks many feedbacks from fire itself. We have also used the latest FireMIP models coupled to an uncertainty framework for broad-scale, uncertainty-based attribution (obtained from Burton et al., 2024). But they struggle at reproducing the tails of distributions where extreme events are found. Another way to develop these techniques is to move towards an integrated system that would inform
both attribution and future projections in a seamless way. We make some progress in this direction here using tools such as ConFire, using the information gained from fire drivers to build future projections; however there is more work to do to link statistical approaches for today's fires to future projections.

The human role in driving fire and extremes is hard to represent. Despite the often-reported influences people have on both increasing extreme burning and causing the observed decline in global BA, the role of humans in the landscape remains hard to capture and, on the whole, remains one of the most uncertain aspects of this report. Agent-based modelling (ABM) is trying to address this by simulating the behaviours and interactions of individual human entities (e.g. deforestation, crop residue burning, and suppression) within a given environment (Ford et al., 2021). This approach provides a dynamic representation of how different factors contribute to fire risk and links well with subsequent sections of the report. These approaches could be a major contributor to subsequent issues of this report. However, the integration of these advanced modelling techniques into operational use faces challenges, as there is often a delay between the development of new approaches and their widespread adoption by fire management agencies. This underscores the need for continuous improvement and adoption of innovative modelling approaches to address the growing threat of extreme fire events effectively.

In addition to Fire Weather Index (FWI) and BA projections, it is crucial to go beyond these metrics to consider wider impacts such as intensity and emissions. Understanding the intensity of fires helps in assessing their destructive potential and the severity of their ecological and societal impacts. Emissions from fires, including C dioxide and other greenhouse gases, contribute to climate change and air quality issues. Finally, evaluating the broader impacts of fires, such as on biodiversity, human health, and economic stability, is essential for developing comprehensive adaptation and mitigation strategies. Quantifying and understanding the uncertainty in these projections is crucial for developing adaptive strategies that can effectively respond to the evolving fire risks posed by global change.

## B1.5 Projection of fire extremes

Projections of extreme fire events under future climate scenarios indicate a significant increase in their frequency and intensity. Semi-empirical models used in this report project that extreme BA events, currently rare, are likely to become more common by the end of the century. These projections highlight the urgent need for robust fire management strategies and policies to mitigate the impacts of these increasingly severe fire events on ecosystems, communities, and global C dynamics. Quantifying and understanding the uncertainty in these projections is crucial for developing adaptive strategies that can effectively respond to the evolving fire risks posed by global change.

In our ConFire uncertainty quantification framework, we have been able to make some confident inferences about the potential state of wildfires in the coming decades. However, we have also identified that there is a significant amount of crucial information that is currently beyond our reach due to the uncertainties involved. Our ability to forecast for the upcoming season, as well as for the next 2–3 decades, requires further refinement as we are observing mixed and uncertain responses. Beyond that, we still show similar uncertainties in responses of Canada and western Amazonia under different scenarios as highlighted by UNEP (2022a), which uses the previous generation of climate models from CMIP5, which shows a large overlap in the potential range of changes in the occurrence of fire extremes between SSP370 and SSP585. This does not imply that mitigation efforts for one scenario will be ineffective compared to another but rather indicates a lack of understanding regarding the response of extremes to these scenarios. By narrowing down the uncertainty ranges, we can better target adaptation efforts and evaluate the effectiveness of mitigation strategies. The reduced likelihood of extreme event recurrence in our high mitigation, however, does show that we can start separating out how mitigation efforts might affect fire extremism, though not in the level of detail needed for policy.

There are three main ways we may be able to constrain uncertainties in the coming reports. The first is development of the underlying GCMs that project future change in the drivers of BA. For individual models, this is a slow process and, beyond informing CMIP model development, is outside what the State of Wildfires can contribute to. However, bringing in more models, including having another model to incorporate any remaining biases in simulated fire from the correct models into our uncertainty projection, will help us constrain uncertainties more (Kelley et al., 2023). The second is obtaining more information and understanding of how fire drivers relate to fire extremes as outlined in the previous section.

Better ways of describing the statistical relationship between observed and modelled climate, land surface and fire today is a third approach. Investigating the dynamical climatic drivers of extreme fire conditions in different regions can help to physically disentangle and potentially constrain sources of uncertainty in future climate projections, for example, by constructing physical storylines (Shepherd et al., 2018; Mindlin et al., 2023). These storylines of plausible future change, or other similar approaches to quantify and explain uncertainty in projections, provide critical information for communities to develop robust adaptation strategies (Lemos et al., 2012) and prepare for future losses and damage caused by evolving fire risks posed by global change. Next to understanding future uncertainty, further insights into these dynamical drivers can support the development of improved physics-informed bias adjustment of climate models (Maraun et al., 2017). Currently available methods to bias-adjust climate models for their use in fire models, such as the ISIMIP3BASD method, have been shown to modify the cli-
mate change trend, particularly in extreme threshold indices (Casanueva et al., 2020; Spuler et al., 2024a) or increase spread in climate model projections (Lafferty and Sriver, 2023). Bias adjustment methods should therefore be evaluated carefully and leave scope for future method development that physically links present-day biases to future uncertainty.

## B2 Impact

### B2.1 Direct exposure of people and the built environment

The direct exposure of people and the built environment could be studied at scale; however these analyses have not been performed routinely and have thus far tended to focus on specific regions. The wildland urban interface (WUI) has been the focus of direct fire exposure to populations, particularly in urban conflagrations like the Lahaina fire in August 2023. Efforts to reduce fire losses in the WUI through prevention, fuel reduction, and mitigation (Calkin et al., 2023) are crucial due to increased populations in these areas (Radloff et al., 2018) and rising fire potential, accelerating community impacts (Higuera et al., 2023). US studies showed a doubling of direct population exposure to large fires during 2000–2019, mainly due to fires encroaching on the WUI (Modaresi Rad et al., 2023). Similar increases were noted in wildfires, affecting roads and energy infrastructure and complicating transportation and energy reliability. Most structure losses in the United States occurred in grasslands and shrublands, not forests, highlighting the need to look beyond traditional forest-centric assessments. Global WUI mapping efforts (Schug et al., 2023) offer opportunities to identify vulnerable areas and characterise fire exposure trends (Chen et al., 2024; Tang et al., 2024).

Understanding fire characteristics that result in direct exposure, structure loss, and fatalities is essential. For instance, Abatzoglou et al. (2023) found that fires driven by strong downslope winds in the western United States caused most structure losses and fatalities from 1999–2020, despite being only 12% of all fires. These winds push fires downhill into WUI communities, overwhelming suppression efforts and fuel treatments. The 2023 fires in Hawaii, Greece, and Chile were driven by such conditions (Synolakis and Karagiannis, 2024). The diagnosis of characteristics of extreme fires, including meteorological conditions (Van Wagtendonk, 2006; Lareau et al., 2018) and pre-existing vegetation conditions (Stephens et al., 2022), provides insights into fires likely to cause significant impacts, helping prioritise mitigation efforts.

A significant gap in characterising extreme fires and their human impacts (fatalities; evacuations; structure loss; secondary morbidity; economic losses; and impacts on food, water, energy, and transportation) is the lack of comprehensive national-to-global data. Wildfire morbidity data are col-

lected in few countries due to the infrequency of fatal wildfires and unclear cataloguing responsibilities (Haynes et al., 2019). Smoke-induced morbidity estimates rely on spikes in hospital visits linked to specific events (Johnston et al., 2021). California pioneered systematic cataloguing of structure losses in 2013, yielding significant insights (Kolden and Henson, 2019; Syphard and Keeley, 2019), but this model has not been widely adopted. Canada now catalogues wildfire evacuations, but complexities remain in characterising these events (Beverly and Bothwell, 2011). Global insurance records document insured losses but do not represent broader losses due to high rates of uninsured property (Hazra and Gallagher, 2022).

Databases like EM-DAT have attempted to fill this gap but often overgeneralise wildfire impacts, relying on variable accuracy news reporting. Expanding and improving quantification of wildfire impacts on humans is critical to overcoming the “burned area fallacy” and developing effective mitigation models (Kolden, 2020). Remote sensing for documenting structure loss and fire incursion into the WUI, combined with high-resolution sensors and air quality monitors, can facilitate interdisciplinary research on wildfire smoke and medical morbidity (Liang et al., 2021).

### B2.2 Air quality and health impacts

The impacts of fire on air quality and health could be studied routinely at scale using atmospheric models; however these analyses face several challenges. Exposure to outdoor pollution is a major global health risk (GBD 2019 Risk Factors Collaborators, 2020). Fine particles with a diameter of less than 2.5 µm ($PM_{2.5}$) are particularly concerning due to their link to cardiovascular diseases. Fire smoke is increasingly impacting air quality and is considered more toxic per unit of PM exposure than other pollution sources (Aguilera et al., 2021). The World Health Organization (WHO) has reduced the annual mean exposure limit for $PM_{2.5}$ from 10 to $5 \mu g m^{-3}$. With 95% of the world's population exposed to $PM_{2.5}$ concentrations of at least $10 \mu g m^{-3}$ (Shaddick et al., 2018), the rise in severe wildfire pollution poses an elevated health risk.

Issues contributing to the challenge of quantifying the impact of fire pollution on human health are the same as those for other pollution sources, including, but not limited to, a lack of ground-based measurements in many regions of the world, a need for more pollution dispersion and transport studies, a deeper understanding of plume dynamics and chemistry, and a partial reliance on animal-based human exposure-response models (e.g. Fiore et al., 2012; Fuzzi et al., 2015). These issues contribute to three of the major challenges in quantifying the impact of extreme fire pollution on human health. The first is accurately measuring the amount of pollution that a wide variety of communities are exposed to and then attributing the contribution of a wildfire event, which could be hundreds or thousands of kilometres away,
to the measured concentration. The second is that PM₂.₅ is not the only pollutant of concern (the EPA regulates six pollutants of concern for American citizens, and a wildfire produces them all). The third is accurately linking exposure to a wide range of pollutants to their associated short-term and long-term health impacts.

Tools to assess air quality primarily consist of ground-based measurements and modelling. Ground-based observations provide an accurate measurement of pollution at their location. However, measurement locations are spatially sparse. Ongoing efforts to increase spatial coverage include deployment of small relatively affordable particulate matter sensors, such as the PurpleAir network, by a wide range of communities (not just scientists), and efforts to relate surface PM concentrations to measured aerosol optical depth from satellites (Y. Li et al., 2021). One additional constraint of observations is that they cannot differentiate pollution sources, but modelling can.

Dispersion modelling uses emission estimates, reanalysis meteorology, and topography to provide estimates of ambient pollutant concentrations at varying spatiotemporal scales. A challenge for models currently lies in the large uncertainty in fire emissions (Reddington et al., 2016; Carter et al., 2020; Pan et al., 2020). Emission data will therefore require calibration against observations and adjusting before the contribution of fire to pollution can be quantified. Improved emission datasets will increase confidence in these assessments.

Environmental and personal factors both influence cardiovascular health, making it challenging to isolate the effects of fire smoke. Impacts may also not be immediate; some effects can be acute, such as exacerbation of asthma, while others emerge over a longer period, like the development of cardiovascular disease, and are thus much more difficult to directly connect to a specific extreme fire event. Conducting epidemiological studies that link fire smoke exposure to specific health outcomes requires comprehensive data collection and follow-up. These studies are resource-intensive, time consuming, and subject to potential limitations in data.

## B2.3 Impacts on Indigenous and Traditional communities

The impacts of fire on Indigenous and Traditional communities are not studied routinely and at scale, typically focussing on isolated regions and specific communities. Indigenous peoples and local communities (IPandLC) are disproportionately exposed to extreme fire impacts because of their proximity to the land and resources from which their cultures, livelihoods, and often food and medicines derive. Once landscapes are degraded through fire, the access and abundance of various resources can be shifted. At the same time, these communities are often less supported by the state due to access and their political and economic marginalisation, linked to systemic socioeconomic disadvantages. These communities not only suffer post-fire impacts but can also

be disincentivised from particular land- and resource-use activities because of the increasing threat of forthcoming wildfires. Whilst the multiple important values (e.g. instrumental, intrinsic, and relational) associated with landscapes by IPandLCs are threatened by fire, there is a lack of systematic pre-and post-fire assessment of these impacts (van Leeuwen and Miller-Sabbioni, 2023).

Historically, fire governance has added an additional burden to IPandLC, often prohibiting cultural fire use and management to the detriment of local knowledge and values and in some cases also increasing the propensity of wildfire in tropical systems as well as savannahs (Carmenta et al., 2019; Daeli et al., 2021; Croker et al., 2023). In some contexts there is a shift towards correcting these issues and renewed interest in and support for cultural burning and Indigenous approaches to land management. For example, integrated fire management is gaining traction globally and sits at the heart of a number of interventions and international policy efforts (e.g. Fire Hub, 2023). The premise of integrated fire management (IFM) is to maximise the “good” fire and minimise the occurrence of wildfire often through an approach of connecting knowledge (i.e. expert and place-based or Indigenous). Whilst nations sit at different stages of development in respect to IFM, and many IPandLC feel there is a long way to go, the growing interest is promising (Bilbao et al., 2019; Luque et al., 2020; Rodríguez-Trejo et al., 2022). Research is needed to better understand the effectiveness of IFM and what mechanisms and processes work best for rebalancing the influence of various forms of knowledge on fire management. For instance, in North America, fire use is considered a form of medicine to the land and anointed to particular patches of the landscape for care (Palmer, 2021). These approaches are perceived as potentially more, just as they allow for the many meanings and uses of fire to exist and persist. For example, in Australia, the term “country” is used to convey the cultural and spiritual connection of Aboriginal peoples to the land and water in specific regions. This link profoundly colours Indigenous peoples’ experience of extreme fire events such as the Black Summer fires of 2019–2020 (Nolan et al., 2021b).

## B2.4 Economic impacts

The economic impacts of fire are generally not studied routinely and at scale but rather focus on individual regions and fire seasons and arrive some time after the event occurs. Extreme wildfires cause economic disturbances worldwide, with impacts varying across regions due to different economic structures, environmental conditions, and response strategies. These impacts include property and infrastructure loss, business downtime, supply chain disruptions, decreased tourism, health costs, reduced productivity, and damages to ecosystem services. While tangible costs (e.g. insured property losses) are easier to measure, intangible costs (e.g. lives lost, health impacts from smoke exposure, damage to species
and habitats) are harder to quantify due to data availability and varying temporal and spatial scales. Consequently, assessing the true economic costs of extreme wildfires is challenging. Additionally, some sectors may benefit economically from post-fire reconstruction and suppression efforts (Nielsen-Pincus et al., 2014; Meier et al., 2023a).

Research on the economic impacts of wildfires has mainly focused on developed economies in Europe, the United States, and Australia. For instance, Meier et al. (2023b) estimated economic losses from a 1-in-10-year extreme wildfire in Mediterranean Europe: EUR 162–439 million in Portugal, EUR 81–219 million in Spain, EUR 41–290 million in Greece, and EUR 18–78 million in Italy. California’s 2018 and 2020 wildfire seasons resulted in approximately USD 150 billion and USD 19 billion in economic damages, respectively (Wang et al., 2021; Safford et al., 2022). Australia’s 2019–2020 fire season was the costliest natural disaster in the country’s history, with an estimated GDP decrease of USD 10 billion (Wittwer and Waschik, 2021).

While satellite data can provide proxies for economic impact shortly after events, traditional economic indicators such as sectoral GDP, employment, hospitalisations, suppression spending, house prices, and tourism revenues are often not publicly available, not harmonised, or unable to capture long-term effects. Thus, the full economic costs may only become apparent years later.

Econometric analysis of wildfires is more challenging than for other natural hazards because wildfire occurrence is largely influenced by human activity, land-use choices, and socioeconomic factors. While earthquakes are non-human-induced, making causal analysis easier, wildfires correlate with many economic outcome variables. Despite these challenges, counterfactual analyses or econometric approaches like instrumental variables can provide reliable causal estimates of wildfire impacts. These methods promise to enhance understanding and mitigation of wildfire economic consequences through more accurate analyses, helping target suppression policies and allocate resources effectively.

## B2.5 Loss of biodiversity, ecosystem function, and carbon storage

Impacts of extreme fires on biodiversity and rates of post-fire recovery have tended to require field-based approaches and are therefore not conducted routinely and at scale. Climate change, altered ignition, and suppression patterns are reshaping fire regimes and ecosystem functions, impacting biodiversity, ecosystem services, and C storage. Reduced seed quality, resprouting exhaustion, organic soil burning, and misaligned reproductive processes hinder post-fire regeneration (Burrell et al., 2022; Nolan et al., 2021a; Johnstone et al., 2016). Other disturbances like drought and insect infestations compound these effects. For example, increased fire activity in boreal forests is reducing fire-adapted species like black spruce, favouring deciduous species, and altering for-

est structure and C dynamics (Baltzer et al., 2021). In western North America, high-severity fires and warmer, drier conditions lead to poor forest recovery and transitions to shrublands or grasslands, affecting habitat, water regulation, and C storage (Coop et al., 2020). Similarly, in tropical savannas and forests, fire frequency can cause ecosystem transitions that are detrimental for C storage and biodiversity (Staver et al., 2011). Furthermore, release of ozone and particulate matter from fires including PM₂.₅ negatively impacts plant and ecosystem health (Anand et al., 2022) and reduces leaf area index through drought induced by aerosol radiative effects, leading to reduced carbon uptake (Tian et al., 2023).

Observing and modelling shifting fire regimes face challenges due to variability, inconsistent historical data, and complex ecosystem responses. Short-term observations often miss long-term trends, and species-specific reactions are influenced by fire-adaptive traits and genetic variability (Grau-Andrés et al., 2024). Fire regimes respond to multiple disturbances, complicating analysis (Nolan et al., 2021a; Coop et al., 2020).

Researchers are using new technologies to address these challenges. Advanced remote sensing, including satellite imagery and drones, provides detailed data on fire extent and severity (Burrell et al., 2022; Baltzer et al., 2021). Improved modelling techniques, such as process-based simulation models and machine learning, enhance predictive capabilities (Coop et al., 2020; Nolan et al., 2021a). Long-term monitoring networks and citizen science initiatives contribute to comprehensive datasets (Baltzer et al., 2021; Coop et al., 2020). Advances in genomic tools, climate-adaptive management frameworks, and AI further improve fire impact predictions (Nolan et al., 2021a; Coop et al., 2020; Grau-Andrés et al., 2024). In all cases, efforts to harmonise local to regional-scale observations of impact are required, in a similar manner to emerging compilations of regional fire monitoring systems (e.g. Gincheva et al., 2024).

A good example of emerging opportunities stemming from the assemblage of large datasets and application of AI is the comprehensive meta-analysis by Grau-Andrés et al. (2024), which analysed data from published studies to find that intensified fire regimes reduce plant abundance, diversity, and health globally. Increased fire severity has stronger effects than frequency, with forests, especially conifer and mixed forests being more negatively impacted than open-canopy ecosystems. Woody plants are more susceptible than herbs due to slower growth and recovery rates. Arid and cold climates exacerbate these impacts, and transitions from surface to crown fires significantly reduce plant abundance, diversity, and health.

## B2.6 Nature-based solutions and net zero

The impacts of extreme fire on nature-based solutions such as reforestation projects are known to be of potential high importance, yet studies of these effects remain rare. Terres-
trial ecosystems remove about 30% of annual anthropogenic C emissions through enhanced growth and ecosystem recovery, but land-use change offsets this by increasing annual C emissions by about 12% (Friedlingstein et al., 2023). Nature-based solutions, including forestry projects for planting, restoration, or conservation, are prominent in net zero strategies (Seddon et al., 2020). However, these projects are at risk from fires, leading to inaccurate C accounting and reversal risks. The spatial clustering of C projects in specific areas can exacerbate risk due to climate variability, such as El Niño impacts. In C markets, projects often allocate a portion of their credits to a buffer pool to account for reversal risks, but this may not be sufficient in regions facing increasing wildfire extremes (Badgley et al., 2022; Anderegg et al., 2024).

Despite these challenges, C markets offer opportunities to fund improved management of fire-prone ecosystems like savannas (Russell-Smith et al., 2015) and temperate forests (Nikolakis et al., 2022), benefiting ecosystems, climate, and local communities. Effective and scalable C markets require accurate and transparent monitoring systems for science-based fire management, precise C loss accounting from fires, and assessment of reversal risks. Novel satellite-based monitoring can provide early warnings, response to wildfire activity, and better estimates of ecosystem C stocks. Field studies remain essential for understanding the immediate and long-term impacts of fire on ecosystems (Silva et al., 2020), and new models forecasting fire risk over decades are needed to improve management strategies and support credible C claims.

## B2.7 Water quality and other aquatic impacts

Impacts of extreme fires on water quality and other aquatic properties have tended to require field-based approaches and are therefore not conducted routinely and at scale. Fire impacts freshwater ecosystems mainly through (i) the loss of vegetation and litter cover and (ii) the enhanced input of soil, sediment, and ash. This leads to reduced rainfall interception; increased runoff; and greater rainfall reaching streams, lakes, and reservoirs (Smith et al., 2011). Increased runoff from burned hillslopes can cause erosion, debris flows, and localised flooding (Shakesby and Doerr, 2006).

Wildfire ash, enriched in nutrients and contaminants (e.g. metals, polycyclic aromatic hydrocarbons) compared to vegetation and soil (Bodí et al., 2014; Sánchez-García et al., 2023), affects water quality by increasing turbidity, temperature, nutrient, and toxin content and decreasing dissolved oxygen. These changes can cause increased mortality in freshwater ecosystems, algal blooms, and water quality issues for supply catchments (Smith et al., 2011). For example, the 2016 Horse River Fire in Canada led to USD 9 million in additional water treatment costs (Pomeroy et al., 2019). The impacts depend on the burned ecosystem type, fire size and

severity, vegetation recovery rate, and post-fire rainfall patterns (Shakesby and Doerr, 2006; Nunes et al., 2018).

Fire emissions to the atmosphere contain compounds that can enrich or toxify aquatic ecosystems (Hamilton et al., 2022; Perron et al., 2022). While 2023 fire impacts on marine ecosystems are not yet well-documented, past extreme fires have disturbed ocean productivity far from the fire source. For instance, large Siberian fires in 2014 boosted Arctic phytoplankton blooms by adding reactive nitrogen (Ardyna et al., 2022). Similarly, 2019–2020 Eurasian fires increased East Siberian Sea productivity by over 200% through nutrient deposition and ice melting (Seok et al., 2024). The 2017 Thomas fires in California and the 2019–2020 Black Summer fires in Australia also caused significant changes in marine productivity and coastal ecosystems (Kramer et al., 2020; Ladd et al., 2023; Tang et al., 2021). The latter fuelled a large phytoplankton bloom, temporarily offsetting the carbon emitted by the fires (Tang et al., 2021), though this effect fluctuates with each fire season (Hamilton et al., 2022; Wang et al., 2022).

**Supplement.** The supplement related to this article is available online at: https://doi.org/10.5194/essd-16-3601-2024-supplement.

**Author contributions.** Conceptualisation: MWJ, DIK, CAB, FDG.

Project administration: MWJ, DIK, CAB, FDG.

Data curation: MWJ, DIK, CAB, FDG, MLFB, EB, SL, GM, JM, FS, JW, MP.

Formal analysis/validation: MWJ, DIK, CAB, FDG, MLFB, EB, AH, SL, GM, JM, FS, JW, MP, DSH.

Resources/software: NA, LG, MP, GRvdW, MLFB, EB, AH, SL, JM, FS, JW, EB, JSMA, YQ.

Visualisation: MWJ, DIK, CAB, FDG, GM, JM, YQ, AL.

Writing (original draft preparation): MWJ, DIK, CAB, FDG, JM, LA, SA, DA, HC, SD PF, SaH, PJ, CK, NR, BS, JS, VT, GX, RC, DSH, StH, SM, MMGP, MP, AJH, FS, JBW.

Writing (review and editing): all authors.

**Competing interests.** At least one of the (co-)authors is a member of the editorial board of *Earth System Science Data*. The peer-review process was guided by an independent editor, and the authors also have no other competing interests to declare.

**Disclaimer.** Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors.
**Acknowledgements.** The authors thank the following people for their contributions to the identification and description of key events in the 2023–2024 fire season: Robert Ang’ila (Karatina University, Kenya), Miltiadis Athanasiou (Institute of Mediterranean Forest Ecosystems, Greece), Davide Ascoli (University of Turin), Chris Collins (Tasmania Fire Service, Australia), Abigail Croker (Imperial College, London), Helen De Klerk (Stellenbosch University), Kebonyethata Dintwe (University of Botswana), David Field (NSW Rural Fire Service, Australia), Ronald Heath (Forestry South Africa), Konstantinos Kaoukis (Institute of Mediterranean Forest Ecosystems, Greece), Agnes Kristina (Department of Fire and Emergency Services, Australia), Niall MacLennan (Scottish Fire and Rescue Service), John Mendelsohn (Okavango Research Institute), Grant Pearce (Fire and Emergency New Zealand, New Zealand), Galia Selaya (Ecosconsult, Bolivia), Russell Stephens Peacock (QLD Fire and Emergency Services, Australia), Simeon Telfer (SA Country Fire Service, Australia), Emmanuela Zevgoli (Agricultural University of Athens, Greece), the Hellenic Agricultural Organization “DIMITRA”, and The Chico Mendes Institute for Biodiversity Conservation (ICMBio, Brazil, Santarém Office). The authors thank Andrew Ciavarella (Met Office) for guidance on using the HadGEM3-A data for the Fire Weather Index. The authors thank Anna Bradley (UK Met Office) for JULES-ES-ISIMIP data processing and submission to the ISIMIP repository. The authors thank the working groups “FLARE: Fire science Learning AcRoss the Earth System” and “TerraFIRMA: Dummies Guide to using Fire Models” for contributing to defining the report scope and establishing contributor links.

**Financial support.** Matthew W. Jones was funded by the UK Research and Innovation (UKRI) Natural Environment Research Council (NERC) (NE/V01417X/1). Douglas I. Kelley was supported by UKRI NERC as part of the LTSM2 TerraFIRMA project and NC-International programme (NE/X006247/1) delivering National Capability. Chantelle A. Burton was funded by the Met Office Climate Science for Service Partnership (CSSP) Brazil project, which is supported by the Department for Science, Innovation and Technology (DSIT), and by the Met Office Hadley Centre Climate Programme funded by DSIT. Paulo M. Fernandes received support from National Funds by the Fundação para a Ciência e a Tecnologia (project UIDB/04033/2020, https://doi.org/10.54499/UIDB/04033/2020). Francesca Di Giuseppe and JMCTS70 were both funded by a service contract from the Joint Research Centre (no. 942604) issued by the Joint Research Centre on behalf of the European Commission. Liana O. Anderson was supported by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (projects: 2021/07660-2 and 2020/16457-3) and by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), productivity scholarship (process: 314473/2020-3). Guilherme Mataveli was supported by FAPESP (grants 2019/25701-8, 2020/15230-5 and 2023/03206-0). Seppe Lampe was supported by a PhD Fundamental Research Grant by Fonds Wetenschappelijk Onderzoek – Vlaanderen (11M7723N). Sarah Meier was supported by the Dragon Capital Chair on Biodiversity Economics. Emilio Chuvieco was supported by the European Space Agency’s Climate Change Initiative (ESA CCI) programme (FireCCI: contract no. 4000126706/19/I-NB). Crystal A. Kolden was supported by the USDA National Institute

of Food and Agriculture (award 2022-67019-36435). Yuquan Qu was supported by the China Scholarship Council (CSC) under grant number 201906040220. Morgane M. G. Perron was supported by a HORIZON EUROPE Marie Skłodowska-Curie Actions Postdoctoral Fellowship 2021, funding number 101064063. Hamish Clarke was funded by the Westpac Scholars Trust via a Westpac Research Fellowship (HamishClarkeFellowship). Stefan H. Doerr was supported by UKRI NERC (grant NE/X005143/1) and the FirEUrisk project, which has received funding from the European Union’s Horizon 2020 Research and Innovation programme under grant agreement no. 101003890. Esther Brambleby was supported by the UKRI NERC ARIES Doctoral Training Partnership (grant number NE/S007334/1). Jacquelyn K. Shuman was supported by the National Aeronautics and Space Administration (NASA) FireSense project. Niels Andela was supported by the Sense4Fire project as part of the European Space Agency C Cycle Cluster (ESA contract numbers: 4000134840/21/I-NB). Maria Lucia F. Barbosa was supported by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), FinanceCode001. The contribution of Sander Veraverbeke was funded by a Consolidator grant from the European Research Council (grant agreement no. 101000987). Rachel Carmenta was financially supported by the Tyndall Centre for Climate Change Research.

**Review statement.** This paper was edited by Francesco N. Tubiello and reviewed by David Carlson, Piers M. Forster, and Marco Turco.

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