Abstract
Recent wildfire outbreaks around the world have prompted concern that climate change is increasing fire incidence, threatening human livelihood and biodiversity, and perpetuating climate change. Here, we review current understanding of the impacts of climate change on fire weather (weather conditions conducive to the ignition and spread of wildfires) and the consequences for regional fire activity as mediated by a range of other bioclimatic factors (including vegetation biogeography, productivity and lightning) and human factors (including ignition, suppression, and land use). Through supplemental analyses, we present a stocktake of regional trends in fire weather and burned area (BA) during recent decades, and we examine how fire activity relates to its bioclimatic and human drivers. Fire weather controls the annual timing of fires in most world regions and also drives inter-annual variability in BA in the Mediterranean, the Pacific US and high latitude forests. Increases in the frequency and extremity of fire weather have been globally pervasive due to climate change during 1979–2019, meaning that landscapes are primed to burn more frequently. Correspondingly, increases in BA of ∼50% or higher have been seen in some extratropical forest ecoregions including in the Pacific US and high-latitude forests during 2001–2019, though interannual variability remains large in these regions. Nonetheless, other bioclimatic and human factors can override the relationship between BA and fire weather. For example, BA in savannahs relates more strongly to patterns of fuel production or to the fragmentation of naturally fire-prone landscapes by agriculture. Similarly, BA trends in tropical forests relate more strongly to deforestation rates and forest degradation than to changing fire weather. Overall, BA has reduced by 27% globally in the past two decades, due in large part to a decline in BA in African savannahs. According to climate models, the prevalence and extremity of fire weather has already emerged beyond its pre-industrial variability in the Mediterranean due to climate change, and emergence will become increasingly widespread at additional levels of warming. Moreover, several of the major wildfires experienced in recent years, including the Australian bushfires of 2019/2020, have occurred amidst fire weather conditions that were considerably more likely due to climate change. Current fire models incompletely reproduce the observed spatial patterns of BA based on their existing representations of the relationships between fire and its bioclimatic and human controls, and historical trends in BA also vary considerably across models. Advances in the observation of fire and understanding of its controlling factors are supporting the addition or optimization of a range of processes in models. Overall, climate change is exerting a pervasive upwards pressure on fire globally by increasing the frequency and intensity of fire weather, and this upwards pressure will escalate with each increment of global warming. Improvements to fire models and a better understanding of the interactions between climate, climate extremes, humans and fire are required to predict future fire activity and to mitigate against its consequences.
| Original language | English |
|---|---|
| Article number | e2020RG000726 |
| Pages (from-to) | 1-76 |
| Number of pages | 76 |
| Journal | Reviews of Geophysics |
| Volume | 60 |
| Issue number | 3 |
| Early online date | 11 Apr 2022 |
| DOIs | |
| Publication status | Published - Sept 2022 |
Bibliographical note
Funding Information:This work was principally funded by the European Research Council under the European Union's Horizon 2020 (H2020) VERIFY project (no. 776810) and builds upon a ScienceBrief Review (A. J. P. Smith et al., 2020 ; Jones et al., 2020 ) supported by the H2020 CRESCENDO (no. 641816) and H2020 4C (no. 821003) projects. The authors thank Anthony J. De‐Gol for developing the ScienceBrief platform. The authors thank the Fire Model Intercomparison Project (FireMIP) and the modeling groups who contribute to it, for making available the data from model simulations of BA. M. W. Jones was funded by the H2020 VERIFY project (no. 776810), the H2020 CHE project (no. 776186) and the UK Natural Environment Research council (NE/V01417X/1). A. J. P. Smith was funded by the H2020 CRESCENDO project (no. 641816) and the H2020 VERIFY project (no. 776810). S. Veraverbeke was funded by a Vidi grant from the Dutch Research Council (NWO; no. 016.Vidi.189.070) and a European Research Council consolidator grant from the H2020 research and innovation programme (no. 101000987). C. Burton was supported by the Newton Fund through the Met Office Climate Science for Service Partnership Brazil (CSSP Brazil). Richard Betts was supported by the Met Office Hadley Centre Climate Progamme (GA01101), funded by the UK department of Business, Energy and Industrial Strategy (BEIS). J. G. Canadell was funded by the Australian National Environmental Science Program (Climate Systems Hub). C. Santín was supported by the UK Natural Environment Research Council (no. NE/T001194/1) and the Spanish “Ramon y Cajal” programme (no. RYC2018‐025797‐I). S. H. Doerr was supported by the UK's Natural Environment Research Council (no. NE/T003553/1). M. Forkel and S. H. Doerr were supported by the H2020 FirEUrisk project (no. 101003890). C. Le Quéré was funded by the Royal Society (no. RP\R1\191063).
Publisher Copyright:
© 2022. The Authors.
Funding
This work was principally funded by the European Research Council under the European Union's Horizon 2020 (H2020) VERIFY project (no. 776810) and builds upon a ScienceBrief Review (A. J. P. Smith et al., 2020 ; Jones et al., 2020 ) supported by the H2020 CRESCENDO (no. 641816) and H2020 4C (no. 821003) projects. The authors thank Anthony J. De‐Gol for developing the ScienceBrief platform. The authors thank the Fire Model Intercomparison Project (FireMIP) and the modeling groups who contribute to it, for making available the data from model simulations of BA. M. W. Jones was funded by the H2020 VERIFY project (no. 776810), the H2020 CHE project (no. 776186) and the UK Natural Environment Research council (NE/V01417X/1). A. J. P. Smith was funded by the H2020 CRESCENDO project (no. 641816) and the H2020 VERIFY project (no. 776810). S. Veraverbeke was funded by a Vidi grant from the Dutch Research Council (NWO; no. 016.Vidi.189.070) and a European Research Council consolidator grant from the H2020 research and innovation programme (no. 101000987). C. Burton was supported by the Newton Fund through the Met Office Climate Science for Service Partnership Brazil (CSSP Brazil). Richard Betts was supported by the Met Office Hadley Centre Climate Progamme (GA01101), funded by the UK department of Business, Energy and Industrial Strategy (BEIS). J. G. Canadell was funded by the Australian National Environmental Science Program (Climate Systems Hub). C. Santín was supported by the UK Natural Environment Research Council (no. NE/T001194/1) and the Spanish “Ramon y Cajal” programme (no. RYC2018‐025797‐I). S. H. Doerr was supported by the UK's Natural Environment Research Council (no. NE/T003553/1). M. Forkel and S. H. Doerr were supported by the H2020 FirEUrisk project (no. 101003890). C. Le Quéré was funded by the Royal Society (no. RP\R1\191063).
| Funders | Funder number |
|---|---|
| H2020 4C | |
| Newton Fund | |
| Nederlandse Organisatie voor Wetenschappelijk Onderzoek | |
| European Commission | |
| Department for Business, Energy and Industrial Strategy, UK Government | |
| European Research Council | |
| UK Research and Innovation | |
| Royal Society | RP\R1\191063 |
| Horizon 2020 Framework Programme | 641816, 821003, 776810 |
| Natural Environment Research Council | NE/T001194/1, NE/T003553/1, NE/V01417X/1 |
| H2020 research and innovation programme | 101000987 |
| H2020 FirEUrisk | 101003890 |
| Met Office Hadley Centre Climate Progamme | GA01101 |
| Australian National Environmental Science Program | RYC2018-025797-I |
| H2020 CHE | 776186 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 13 Climate Action
Keywords
- burned area
- climate change
- fire weather
- land use
- lightning
- vegetation
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