Technical note: Low meteorological influence found in 2019 Amazonia fires

Abstract. The sudden increase in Amazon fires early in the 2019 fire season made global headlines. While it has been heavily speculated that the fires were caused by deliberate human ignitions or human-induced landscape changes, there have also been suggestions that meteorological conditions could have played a role. Here, we ask two questions: were the 2019 fires in the Amazon unprecedented in the historical record, and did the meteorological conditions contribute to the increased burning? To answer this, we take advantage of a recently developed modelling framework which optimises a simple fire model against observations of burnt area and whose outputs are described as probability densities. This allowed us to test the probability of the 2019 fire season occurring due to meteorological conditions alone. The observations show that the burnt area was higher than in previous years in regions where there is already substantial deforestation activity in the Amazon. Overall, 11 % of the area recorded the highest early season (June–August) burnt area since the start of our observational record, with areas in Brazil's central arc of deforestation recording the highest ever monthly burnt area in August. However, areas outside of the regions of widespread deforestation show less burnt area than the historical average, and the optimised model shows that this low burnt area would have extended over much of the eastern Amazon region, including in Brazil's central arc of deforestation with high fire occurrence in 2019. We show that there is a 9 % likelihood of the observed August fires being caused by meteorological conditions alone, decreasing to 6 %–7 % along the agricultural–humid forest interface in Brazil's central states and 8 % in Paraguay and Bolivia dry forests. Our results suggest that changes in land use, cover or management are the likely drivers of the substantial increase in the 2019 early fire season burnt area, especially in Brazil. Burnt area for September in the arc of deforestation had a 14 %–26 % probability of being caused by meteorological conditions, potentially coinciding with a shift in fire-related policy from South American governments.

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Technical note: Low meteorological influence found in 2019 Amazonia fires

10.5194/bg-2020-123 ◽

2020 ◽

Cited By ~ 1

Author(s):

Douglas I. Kelley ◽

Chantelle Burton ◽

Chris Huntingford ◽

Megan A. J. Brown ◽

Rhys Whitley ◽

...

Keyword(s):

Historical Record ◽

Technical Note ◽

Meteorological Conditions ◽

Fire Season ◽

Burned Area ◽

Sudden Increase ◽

Burnt Area ◽

Modelling Framework ◽

Probability Densities ◽

Optimized Model

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Spatial distribution and temporal variability of open fire in China

International Journal of Wildland Fire ◽

10.1071/wf15213 ◽

2017 ◽

Vol 26 (2) ◽

pp. 122 ◽

Cited By ~ 7

Author(s):

Kunpeng Yi ◽

Yulong Bao ◽

Jiquan Zhang

Keyword(s):

Meteorological Data ◽

Fire Season ◽

Spatial And Temporal Patterns ◽

Burnt Area ◽

The North ◽

Temperature And Precipitation ◽

North Eastern ◽

Vegetation Fires ◽

Precipitation Variation ◽

Two Peaks

This study presents the spatial and temporal patterns of vegetation fires in China based on a combination of national fire records (1950–2010) and satellite fire data (2001–12). This analysis presents the first attempt to understand existing patterns of open fires and their consequences for the whole of China. We analysed inter- and intra-annual fire trends and variations in nine subregions of China as well as associated monthly meteorological data from 130 stations within a 50-year period. During the period 2001–12, an average area of 3.2 × 106 ha was consumed by fire per year in China. The Chinese fire season has two peaks occurring in the spring and autumn. The profiles of the burnt area for each subregion exhibit distinct seasonality. The majority of the vegetation fires occurred in the north-eastern and south-western provinces. We analysed quantitative relationships between climate (temperature and precipitation) and burnt area. The results indicate a synchronous relationship between precipitation variation and burnt area. The data in this paper reveal how climate and human activities interact to create China’s distinctive pyrogeography.

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Measured and predicted time-dependent stress-strain behaviour of Hong Kong marine deposits

Canadian Geotechnical Journal ◽

10.1139/t99-043 ◽

1999 ◽

Vol 36 (4) ◽

pp. 760-766 ◽

Cited By ~ 17

Author(s):

Jian-Hua Yin ◽

Jun-Gao Zhu

Keyword(s):

Hong Kong ◽

Technical Note ◽

Time Dependent ◽

Practical Significance ◽

Stress Strain ◽

Analysis And Design ◽

Marine Deposits ◽

Modelling Framework ◽

Strain Behaviour ◽

Dependent Behaviour

Hong Kong marine deposits (HKMD) are considered to be difficult (or weak) soils for civil projects because of low shear strength and time-dependent high compressibility. Understanding and modelling the time-dependent stress-strain behaviour of HKMD are of practical significance in the analysis and design of civil structures on and in HKMD. In this technical note, test data on the time-dependent behaviour of a remoulded HKMD are presented and analysed. An existing elastic viscoplastic (EVP) modelling framework is used to describe the time-dependent stress-strain behaviour of HKMD. The modelling results are compared with the measured results.Key words: stress-strain, time dependent, creep, viscoplastic, triaxial, soil.

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Wildfires and the Canadian Forest Fire Weather Index system for the Daxing'anling region of China

International Journal of Wildland Fire ◽

10.1071/wf09120 ◽

2011 ◽

Vol 20 (8) ◽

pp. 963 ◽

Cited By ~ 29

Author(s):

Xiaorui Tian ◽

Douglas J. McRae ◽

Jizhong Jin ◽

Lifu Shu ◽

Fengjun Zhao ◽

...

Keyword(s):

Forest Fire ◽

Forest Fires ◽

Coniferous Forest ◽

Northern China ◽

Fire Danger ◽

Fire Season ◽

Fire Weather ◽

Burnt Area ◽

Weather Index ◽

Fire Weather Index

The Canadian Forest Fire Weather Index (FWI) system was evaluated for the Daxing'anling region of northern China for the 1987–2006 fire seasons. The FWI system reflected the regional fire danger and could be effectively used there in wildfire management. The various FWI system components were classified into classes (i.e. low to extreme) for fire conditions found in the region. A total of 81.1% of the fires occurred in the high, very high and extreme fire danger classes, in which 73.9% of the fires occurred in the spring (0.1, 9.5, 33.3 and 33.1% in March, April, May and June). Large wildfires greater than 200 ha in area (16.7% of the total) burnt 99.2% of the total burnt area. Lightning was the main ignition source for 57.1% of the total fires. Result show that forest fires mainly occurred in deciduous coniferous forest (61.3%), grass (23.9%) and deciduous broad leaved forest (8.0%). A bimodal fire season was detected, with peaks in May and October. The components of FWI system were good indicators of fire danger in the Daxing'anling region of China and could be used to build a working fire danger rating system for the region.

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History and Data Records of the Automatic Weather Station on Denali Pass (5715 m), 1990–2007

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-20-0082.1 ◽

2020 ◽

Vol 59 (12) ◽

pp. 2113-2127

Author(s):

Lea Hartl ◽

Martin Stuefer ◽

Tohru Saito ◽

Yoshitomi Okura

Keyword(s):

Wind Speed ◽

Historical Record ◽

Reanalysis Data ◽

Meteorological Conditions ◽

Weather Station ◽

Automatic Weather Station ◽

Wind Speeds ◽

Air Temperatures ◽

History Of ◽

Summit Region

AbstractWe present the data records and station history of an automatic weather station (AWS) on Denali Pass (5715 m MSL), Alaska. The station was installed by a team of climbers from the Japanese Alpine Club after a fatal accident involving Japanese climbers in 1989 and was operational intermittently between 1990 and 2007, measuring primarily air temperature and wind speed. In later years, the AWS was operated by the International Arctic Research Center of the University of Alaska Fairbanks. Station history is reconstructed from available documentation as archived by the expedition teams. To extract and preserve data records, the original datalogger files were processed. We highlight numerous challenges and sources of uncertainty resulting from the location of the station and the circumstances of its operation. The data records exemplify the harsh meteorological conditions at the site: air temperatures down to approximately −60°C were recorded, and wind speeds reached values in excess of 60 m s−1. Measured temperatures correlate strongly with reanalysis data at the 500-hPa level. An approximation of critical wind speed thresholds and a reanalysis-based reconstruction of the meteorological conditions during the 1989 accident confirm that the climbers faced extremely hazardous wind speeds and very low temperatures. The data from the Denali Pass AWS represent a unique historical record that can, we hope, serve as a basis for further monitoring efforts in the summit region of Denali.

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Unveiling the Factors Responsible for Australia’s Black Summer Fires of 2019/2020

Fire ◽

10.3390/fire4030058 ◽

2021 ◽

Vol 4 (3) ◽

pp. 58

Author(s):

Noam Levin ◽

Marta Yebra ◽

Stuart Phinn

Keyword(s):

Forest Fires ◽

Prescribed Burning ◽

Fire Season ◽

Burnt Area ◽

Explanatory Variables ◽

Average Area ◽

Southeast Australia ◽

Large Fires ◽

Fire Area ◽

Response Variables

The summer season of 2019–2020 has been named Australia’s Black Summer because of the large forest fires that burnt for months in southeast Australia, affecting millions of Australia’s citizens and hundreds of millions of animals and capturing global media attention. This extensive fire season has been attributed to the global climate crisis, a long drought season and extreme fire weather conditions. Our aim in this study was to examine the factors that have led some of the wildfires to burn over larger areas for a longer duration and to cause more damage to vegetation. To this end, we studied all large forest and non-forest fires (>100 km2) that burnt in Australia between September 2019 and mid-February 2020 (Australia’s Black Summer fires), focusing on the forest fires in southeast Australia. We used a segmentation algorithm to define individual polygons of large fires based on the burn date from NASA’s Visible Infrared Imaging Radiometer Suite (VIIRS) active fires product and the Moderate Resolution Imaging Spectroradiometer (MODIS) burnt area product (MCD64A1). For each of the wildfires, we calculated the following 10 response variables, which served as proxies for the fires’ extent in space and time, spread and intensity: fire area, fire duration (days), the average spread of fire (area/days), fire radiative power (FRP; as detected by NASA’s MODIS Collection 6 active fires product (MCD14ML)), two burn severity products, and changes in vegetation as a result of the fire (as calculated using the vegetation health index (VHI) derived from AVHRR and VIIRS as well as live fuel moisture content (LFMC), photosynthetic vegetation (PV) and combined photosynthetic and non-photosynthetic vegetation (PV+NPV) derived from MODIS). We also computed more than 30 climatic, vegetation and anthropogenic variables based on remotely sensed derived variables, climatic time series and land cover datasets, which served as the explanatory variables. Altogether, 391 large fires were identified for Australia’s Black Summer. These included 205 forest fires with an average area of 584 km2 and 186 non-forest fires with an average area of 445 km2; 63 of the forest fires took place in southeast (SE) Australia (the area between Fraser Island, Queensland, and Kangaroo Island, South Australia), with an average area of 1097 km2. Australia’s Black Summer forest fires burnt for more days compared with non-forest fires. Overall, the stepwise regression models were most successful at explaining the response variables for the forest fires in SE Australia (n = 63; median-adjusted R2 of 64.3%), followed by all forest fires (n = 205; median-adjusted R2 of 55.8%) and all non-forest fires (n = 186; median-adjusted R2 of 48.2%). The two response variables that were best explained by the explanatory variables used as proxies for fires’ extent, spread and intensity across all models for the Black Summer forest and non-forest fires were the change in PV due to fire (median-adjusted R2 of 69.1%) and the change in VHI due to fire (median-adjusted R2 of 66.3%). Amongst the variables we examined, vegetation and fuel-related variables (such as previous frequency of fires and the conditions of the vegetation before the fire) were found to be more prevalent in the multivariate models for explaining the response variables in comparison with climatic and anthropogenic variables. This result suggests that better management of wildland–urban interfaces and natural vegetation using cultural and prescribed burning as well as planning landscapes with less flammable and more fire-tolerant ground cover plants may reduce fire risk to communities living near forests, but this is challenging given the sheer size and diversity of ecosystems in Australia.

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Quantifying the Importance of Antecedent Fuel-Related Vegetation Properties for Burnt Area using Random Forests

10.5194/bg-2020-409 ◽

2020 ◽

Author(s):

Alexander Kuhn-Régnier ◽

Apostolos Voulgarakis ◽

Peer Nowack ◽

Matthias Forkel ◽

I. Colin Prentice ◽

...

Keyword(s):

Vegetation Indices ◽

Fire Season ◽

Burnt Area ◽

Antecedent Conditions ◽

Antecedent Moisture ◽

Out Of Sample ◽

Fuel Accumulation ◽

Moisture Conditions ◽

The Impact ◽

Antecedent Moisture Conditions

Abstract. The seasonal and longer-term dynamics of fuel accumulation affect fire seasonality and the occurrence of extreme wildfires. Failure to account for their influence may help to explain why state-of-the-art fire models do not simulate the length and timing of the fire season or interannual variability in burnt area well. We investigated the impact of accounting for different timescales of fuel production and accumulation on burnt area using a suite of random forest regression models that included the immediate impact of climate, vegetation, and human influences in a given month, and tested the impact of various combinations of antecedent conditions in four productivity-related vegetation indices and in antecedent moisture conditions. Analyses were conducted for the period from 2010 to 2015 inclusive. We showed that the inclusion of antecedent vegetation conditions on timescales > 1 yr had no impact on burnt area, but inclusion of antecedent vegetation conditions representing fuel build-up led to an improvement of the global, climatological out-of-sample R2 from 0.567 to 0.686. The inclusion of antecedent moisture conditions also improved the simulation of burnt area through its influence on fuel build-up, which is additional to the influence of current moisture levels on fuel drying. The length of the period which needs to be considered to account for fuel build-up varies across biomes; fuel-limited regions are sensitive to antecedent conditions over longer time periods (~4 months) and moisture-limited regions are more sensitive to current conditions.

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Iberian Fire Regimes for Future Climate Scenarios using a Climate Ensemble

10.5194/egusphere-egu2020-11610 ◽

2020 ◽

Author(s):

Tomás Calheiros ◽

Mário Pereira ◽

João Nunes

Keyword(s):

Iberian Peninsula ◽

Fire Regimes ◽

Future Climate ◽

Fire Season ◽

Fire Weather ◽

Future Scenarios ◽

Climate Scenarios ◽

Burnt Area ◽

Weather Risk ◽

The Future

<div> Iberia Fire Regimes for Future Climate Scenarios using a Climate Ensemble &#160; T. Calheiros(1), M.G. Pereira(2,3), J.P. Nunes(1) (1) CE3C &#8211; Centre for Ecology, Evolution and Environmental Changes, Faculdade de Ci&#234;ncias, Universidade de Lisboa, 1749-016 Lisboa, Portugal (2)Centro de Investiga&#231;&#227;o e de Tecnologias Agro-Ambientais e Biol&#243;gicas (CITAB), Universidade de Tr&#225;s-os-Montes e Alto Douro, Vila Real, Portugal (3)Instituto Dom Luiz (IDL), Universidade de Lisboa, Lisboa, Portugal &#160; &#160; </div>&#160;Wildfires are generating higher concern worldwide, especially in the Mediterranean regions. Fire season severity and total annual burnt area strongly depend on weather conditions and climate variability.The first objective of this work was to analyse Fire Weather Indexes (FWI) in the Iberian Peninsula for the present-day conditions and future climate scenarios, using reanalysis data from ERA-Interim (for 1980-2014) and an ensemble of 11 models from EURO-CORDEX, with high spatial (12 km) and daily resolution. FWI were computed for historical (1976 &#8211; 2005) and three future periods (2011-2040, 2041 &#8211; 2070 and 2071-2100), using maximum temperature, precipitation, relative humidity and wind speed data simulated for two future scenarios (RCP4.5 and RCP8.5). The second objective was to use the Iberian Pyro-Regions and an analysis of the Number of Extreme Days (NED), using previously published methods, to apply on the future scenarios and assess the intra-annual pattern of NED; and, subsequently, to assess if the pyro-regions will change in a future climate, by taking into account the link between monthly burnt area and extreme days found in previous work.The results anticipate a progressive growth of the SW pyro-region throughout the NW pyro-region, and a shift of the present-day NW pyro-region to most of the provinces occupying the N pyro-region, with exception of those north of the Cantabrian Mountains, in effect moving the present-day pattern northwards. This is driven by the large increase of the NED in summer months and eventually a decrease in March and April. Projections alto point to FWI values increasing considerably when comparing the historical and the future scenarios, especially in late spring and early autumn. These results anticipate a higher fire weather risk in the future, with a larger and stronger fire season.&#160;&#160;References:&#160;Calheiros, T., Pereira, M. G and Nunes, J. P. (2020, in press) &#8216;Recent evolution of spatial and temporal patterns of burnt areas and fire weather risk in the Iberian Peninsula&#8217;, Agricultural and Forest Meteorology.&#160;

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A General Mathematical Framework for Modeling Two-Dimensional Wildland Fire Spread

International Journal of Wildland Fire ◽

10.1071/wf9950063 ◽

1995 ◽

Vol 5 (2) ◽

pp. 63 ◽

Cited By ~ 62

Author(s):

GD Richards

Keyword(s):

Differential Equations ◽

Wildland Fire ◽

Fire Spread ◽

Meteorological Conditions ◽

Mathematical Framework ◽

Two Dimensional ◽

Affecting Factors ◽

Modelling Framework ◽

Rate Of Spread ◽

The Relationship

This work considers the modelling of two dimensional fire spread for heterogeneous fuel and meteorological conditions. Differential equations are used as the modelling form, and a set of partial differential equations that describes fire growth in terms of the rate of spread at each point on the perimeter is derived. These equations require the specification of the rate of spread as a function of the variables affecting it, and form a general modelling framework into which such a function can be placed. To model the relationship between the rate of spread and its affecting factors an analysis of point source ignition fires for homogeneous fuel and meteorological conditions is made. Based on this analysis a spread rate model for heterogeneous conditions is proposed. The resulting differential equations require a sophisticated computer solution, however there are a number of nontrivial fire situations for which solutions can relatively easily be obtained, and example solutions are presented.

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The importance of antecedent vegetation and drought conditions as global drivers of burnt area

Biogeosciences ◽

10.5194/bg-18-3861-2021 ◽

2021 ◽

Vol 18 (12) ◽

pp. 3861-3879

Author(s):

Alexander Kuhn-Régnier ◽

Apostolos Voulgarakis ◽

Peer Nowack ◽

Matthias Forkel ◽

I. Colin Prentice ◽

...

Keyword(s):

Vegetation Indices ◽

Fire Season ◽

Random Forest Regression ◽

Burnt Area ◽

Antecedent Conditions ◽

Antecedent Moisture ◽

Out Of Sample ◽

Fuel Accumulation ◽

Moisture Conditions ◽

The Impact

Abstract. The seasonal and longer-term dynamics of fuel accumulation affect fire seasonality and the occurrence of extreme wildfires. Failure to account for their influence may help to explain why state-of-the-art fire models do not simulate the length and timing of the fire season or interannual variability in burnt area well. We investigated the impact of accounting for different timescales of fuel production and accumulation on burnt area using a suite of random forest regression models that included the immediate impact of climate, vegetation, and human influences in a given month and tested the impact of various combinations of antecedent conditions in four productivity-related vegetation indices and in antecedent moisture conditions. Analyses were conducted for the period from 2010 to 2015 inclusive. Inclusion of antecedent vegetation conditions representing fuel build-up led to an improvement of the global, climatological out-of-sample R2 from 0.579 to 0.701, but the inclusion of antecedent vegetation conditions on timescales ≥ 1 year had no impact on simulated burnt area. Current moisture levels were the dominant influence on fuel drying. Additionally, antecedent moisture levels were important for fuel build-up. The models also enabled the visualisation of interactions between variables, such as the importance of antecedent productivity coupled with instantaneous drying. The length of the period which needs to be considered varies across biomes; fuel-limited regions are sensitive to antecedent conditions that determine fuel build-up over longer time periods (∼ 4 months), while moisture-limited regions are more sensitive to current conditions that regulate fuel drying.

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