NH7.2
Orals: Tue, 25 Apr | Room 1.31/32
Wildfires have reached an unprecedented scale in recent fire seasons of the Northern Hemisphere as demonstrated by the summers of 2021 and 2022. Severe fire seasons, characterized by heat, drought and windy conditions, might become even more frequent and will extend to more temperate regions in northern latitudes under global warming. Still, quantifying the effects of climate change on future fire danger is challenging because natural variability hides trends of increasing fire danger in climate model simulations in future potentially fire-prone areas. Single Model Initial-Condition Large Ensembles (SMILEs) help scientists to distinguish climate trends from natural variability. Here, we leverage the capabilities of SMILEs to assess future changes in fire weather conditions in a currently non-fire-prone area in Central Europe. The study area covers four heterogeneous landscapes, namely the Alps, the Alpine Foreland (southern parts), the lowlands of the Southern German Escarpment, and the eastern mountain ranges of the Bavarian Forest (northern parts). We use a SMILE of the Canadian regional climate model version 5 (CRCM5-LE) under the RCP 8.5 scenario from 1980 to 2099 to analyze trends in fire danger quantified by the globally applicable Canadian Fire Weather Index (FWI).
Our results show the strongest increases for the median (50th percentile) and extreme (90th percentile) FWI in the northern parts of the study area during the late summer months July, August and September. The southern, more alpine parts are affected less strongly and show high fire danger mostly in August by the end of the 21st century for the median FWI. Over the whole study area, we find that the extreme FWI in the present climate period will become much more frequent at the end of the century. In the South German Escarpment and Eastern Mountain Ranges, the climate change trend exceeds natural variability in the late 2040’s. Due to weaker variability, the time of emergence is reached in the Alps and Alpine Foreland in the early 2040's.
These results demonstrate that the CRCM5-LE is a suitable dataset to disentangle climate trends from natural variability in a multivariate fire danger metric. Our study emphasizes that regions with a low fire danger under current climate conditions will experience weather conditions facilitating the development of potentially uncontrollable wildfires in a warming climate.
How to cite: Miller, J., Böhnisch, A., Ludwig, R., and Brunner, M.: Impacts of climate variability and change on regional fire weather in heterogeneous landscapes of Central Europe, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-271, https://doi.org/10.5194/egusphere-egu23-271, 2023.
Forest fires strongly depend on local weather conditions. Weather conditions conducive for occurrence and growth of fires is known as “fire weather”. This work investigates how climate change can affect the future fire weather in Indian forests using the Canadian Forest Fire Danger Rating System – Fire Weather Index (CFFDRS-FWI), a well-known fire danger assessment system. To drive this model, we used a high-resolution dynamically downscaled climate projection DSCESM for a baseline (2006-2015) and an end-century (2091-2100) period to compute the metric ‘Fire Weather Index (FWI)’. We divided the forest areas of the country into 5 zones based on climate and forest types viz., Himalayan (HIM), Northeast (NE), Central India (CEN), Deccan (DEC) and Western Ghats (WG) zones. Then, we developed thresholds for five fire weather danger classes using the baseline FWI in conjunction with observed fire count from MODIS active fire data. The baseline and future FWI, fire weather danger, Seasonal Severity Ratings (SSR) and characteristics of the fire weather season were compared to estimate the effect of climate change on forest fire danger.
Results show that there is considerable heterogeneity in the baseline as well as future fire weather danger across, and even within, the different forest zones of India. Climate change is likely to have a strong effect on fire weather. Days exceeding the Very High FWI threshold are likely to increase by about 30-40 days by the end-century despite a modest increase of about 5% in annual FWI values. SSR analysis suggests a maximum increase in fire disturbances during the pre-monsoon months of March-April-May. About 55% of forest area over India will experience increased fire danger in this season. The least effect will be in the post monsoon season in September-October-November. The fire season is also expected to lengthen up to 59 days depending upon the forest type. The forests which are most likely to be affected by fire disturbances by end-century are moist deciduous and evergreen forests in the northern WG, mixed dry deciduous forests in central and southern CEN, Pine and Sal forests in the HIM and the scrub forests in the DEC zone. Climate change is unlikely to affect the fire weather danger in the NE.
This study is one of the first attempts to quantify the effects of climate change on forest fire hazard in India. It has significant policy implications and can be valuable for fire management authorities for designing appropriate fire suppression and mitigating measures.
How to cite: Barik, A. and Baidya Roy, S.: Impact of climate change on the fire weather in Indian forests, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-10618, https://doi.org/10.5194/egusphere-egu23-10618, 2023.
This work investigates the physical interactions and feedback between wildfires and the atmosphere using the coupled atmosphere-fire spread modelling system, WRF-SFIRE. The Figueira da Foz forest fire, occurred in Portugal in October 2017, which ocurred in association with hurricane Ophelia, was simulated under two different scenarios of fuel moisture settings, one static and one dynamic. Results show an underestimation of burnt area in the dynamic case, while static fuel moisture has shown a very high agreement. Pyrocumulus formed during late afternoon with a very dry base and more humid top, creating conditions favourable for the occurrence of downbursts, with very high Convective Available Potential Energy values. Lifted Condensation Level increased above the fire front as moisture was transported upwards, increasing surface temperature. Official reports show an overestimation of fuel moisture near the surface, leading to high CAPE values, compared to near zero values reported by vertical soundings. Relative Humidity values were higher by 30% when compared to weather station observations, and temperatures approximately 4ºC lower. Further model testing is needed to provide more accurate surface temperature and moisture simulations, to allow a more accurate fire progression representation and energy exchange, and improve the modelling of potential convective events.
How to cite: Vaz, R., Silva, R., Cardoso Pereira, S., Carvalho, A., Carvalho, D., and Rocha, A.: Modelling of a wildfire in Portugal using a fully coupled atmosphere-fire spread modelling system, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-1415, https://doi.org/10.5194/egusphere-egu23-1415, 2023.
Mega-fires are wildfires that burn an area greater than 10.000 hectares. Despite being a minority in relation to the total number of fires, they are the one with the greatest negative impact on society and the environment. Associated with this wildfire type, the phenomenon of pyro-convection has been reported in several cases. Strong pyro-convective activity can lead to the formation of clouds within the smoke plume, also known as pyro-cumulus (PyroCu) or pyro-cumulonimbus (PyroCb). In 2017, Portugal recorded 11 mega-fires, of which 8 occurred on the 15th October. Since the photographic evidence of the formation of a PyroCu cloud, the chosen case study was the Quiaios mega-fire. The study aims to simulate the impact of a fire in the atmosphere, as well as the large-scale meteorological conditions that were affecting Portugal during the mega-fires. For this purpose, two numerical simulations were performed using the MesoNH atmospheric model: a coupled simulation with the ForeFire fire propagation model, with 3 nested domains with resolution of 2000m, 400m and 80m (300 by 300 grid points), and a large-scale non-coupled simulation, with a 15km resolution (300 by 250 grid points) to study the large-scale conditions. The coupled simulation allowed identifying the formation of a PyroCu cloud composed by different species of hydrometeors, namely graupel and rain droplets. The pyro-cloud developed inside the plume due the vertical transport of water vapor to higher levels. In the context of large scale, the simulation well represented the evolution of hurricane Ophelia, showing the change in wind direction from Southeast to Southwest in Portuguese territory, which created a favourable condition to the intensification of the active fires and the development of PyroCb clouds during the late afternoon. This study was funded by national funds through FCT-Foundation for Science and Technology, I.P. under the PyroC.pt project (Ref. PCIF/MPG/0175/2019).
How to cite: Campos, C., Couto, F. T., Purificação, C., Filippi, J.-B., Baggio, R., and Salgado, R.: Modelling pyro-convective activity and the meteorological conditions leading to mega-fires, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-8967, https://doi.org/10.5194/egusphere-egu23-8967, 2023.
Over mountainous terrain, the atmospheric structure becomes much more complex than homogeneous terrain in terms of the Atmospheric Boundary Layer (ABL). In the context of interaction between fire and atmosphere, abrupt changes in the ABL wind often lead to erratic and turbulent flow in the fire environment and expose firefighters to dangerous conditions. The study aims to characterize the ABL conditions associated with the largest forest fire that occurred in Portugal in 2019. The fire event took place in Vila de Rei county, which is surrounded by hills and valleys with large differences in altitudes. In order to study the regional scale, a numerical simulation was performed using the Meso-NH atmospheric model, configured with 500 × 500 grid points at 2500 m horizontal resolution, between 19 July at 0000 UTC and 25 July 2019 at 0000 UTC. The simulation covered the Iberian Peninsula and corresponds to the period when the fire burned more than 9,000 hectares in Vila de Rei. Such a simulation helped to characterize the lower troposphere, which contributed to the evolution of the ABL height over the days. Results indicate that the simulated ABL evolution is characterized by the presence of a coastal low-level jet with a maximum wind speed of 10 meters per second at ~ 600 meters’ altitude (1800 UTC of 20 July). ABL height calculated from Richardson number method depicted a growing in the morning that reached a peak height by mid-afternoon. The ABL height ranged from 500 to 900 m throughout the afternoon and evening during the entire study period. Besides the identification of the fire weather conditions, this study also highlights the factors that contributed to the lower values of the ABL height in the wildfire event. This study was funded by national funds through FCT-Foundation for Science and Technology, I.P. under the PyroC.pt project (Ref. PCIF/MPG/0175/2019).
How to cite: Purificação, C., Campos, C., Henkes, A., and Couto, F. T.: Modelling the atmospheric factors determining the evolution of the boundary layer during a wildfire event, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-14223, https://doi.org/10.5194/egusphere-egu23-14223, 2023.
We will present approaches to modeling wildfire dynamics using the IIASA’s wildFire cLimate impacts and Adaptation Model (FLAM). FLAM operates with a daily time step and uses mechanistic algorithms to parametrize the impacts of climate, human activities, and fuel availability on wildfire probabilities, frequencies, and burned areas. Validation on historical data and future projections under climate change scenarios will be discussed at various scales and resolutions. We will present results for the following case-studies: (i) projections of global burned areas driven by climate change scenarios until 2100; (ii) modeling burned areas and adaptation options in Europe; (iii) modeling burned areas and their feedback to land-use change in Indonesia with a particular emphasis on extreme fires due the impacts of El Niño southern oscillation using historical data and the delta approach for future scenarios; (iv) regional variability and driving forces behind forest fires in Sweden. Our results support international analyses that, irrespective of changes in management, it is evident that climate change is very likely to increase the frequency and impact of wildland fires in the coming decades.
How to cite: Krasovskiy, A., Corning, S., Boere, E., Khabarov, N., Cimdins, R., and Kraxner, F.: Modeling wildfire dynamics and future projections under climate change scenarios: the FLAM approach , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-16190, https://doi.org/10.5194/egusphere-egu23-16190, 2023.
Wildfire events are driven by complex interactions of the climate and anthropogenic interventions. Predictions of future wildfire events, their extremity, and their impact on the environment and economy must account for the interactions between these drivers. Economic policy and land use decisions influence the susceptibility of an area to climate extremes, the probability of burning, and future decision making. To better understand how climate-driven drought events and adaptation efforts affect burned area, agricultural production losses, and land use decisions, we developed a storyline approach centered on Indonesia’s 2015 fire events, which saw significant production losses of palm oil – a product imported by the EU chiefly as a biofuel – surpassing 7%. We explored analogous events under three warming conditions and two palm oil sector adaptation scenarios using two storylines: ensemble mean climate and high aridity conditions. We employed a model chain consisting of IIASA's wildfire climate impacts and adaptation model (FLAM) and the partial equilibrium global biosphere management model (GLOBIOM) to predict burned area and assess resultant production losses in the oil palm sector in Indonesia. To quantify the changes in burned area, we applied a delta approach based on the different degrees of global warming that can be expected. To define fire-induced oil palm losses and associated economic impacts, we combined the burned areas from FLAM with land-use change and productivity estimates from GLOBIOM. We found that the total burned area and production loss increased across the projections and climate warming by up to 25%, with only minor differences between storylines. By varying characteristics of regional climate change features, we found that these results are spatially explicit and robust across projections. Our results highlight the importance of including future warming and drought conditions in predicting oil palm losses and land use decision making. They leave room to explore how climatic and economic impacts could be mitigated through economic and land use management policies affecting Indonesia and the EU.
How to cite: Corning, S., Boere, E., Krasovskiy, A., Lessa-Derci-Augustynczik, A., and Kraxner, F.: Flammable Futures – A storyline of climatic and land-use change impacts on wildfire extremes in Indonesia, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-10736, https://doi.org/10.5194/egusphere-egu23-10736, 2023.
Climate change has increased the vulnerability of boreal forests and grasslands to wildfires. An increase in high-latitude wildfires has resulted in the deterioration of air quality, particularly in Western Siberia, where PM2.5 levels have increased at >1 µg m-3 year-1 during 1998−2020. Arctic wildfire carbon emissions have doubled during the last 20 years, and in Siberia they have shifted northwards. Using fire air pollutant emissions data from the Quick Fire Emissions Dataset (QFED), we create two emissions scenarios for Arctic Council member nations, with and without wildfires. PM2.5 is simulated for the two scenarios using the Community Earth System Model, which we evaluate using in-situ measurement data, finding a large negative bias in wildfire plumes. To correct this underestimation we use a high resolution PM2.5 reanalysis dataset, improving agreement with observations. Bias-corrected scenarios are used to estimate air quality degradation and resulting health impacts due to Arctic Council nation wildfires across the Northern Hemisphere high- and mid-latitudes for the period 2001-2020. We use the Global Exposure Mortality Model to estimate the health impacts of chronic exposure to Arctic wildfire-attributed PM2.5. We find that health impacts are highly variable, with 25,000−55,000 premature deaths yearly, with most of the health burden falling on nations outside the Arctic Council, particularly China, due to transboundary transport of Siberian wildfire PM2.5. Health impacts have decreased during our study period partly due to the northwards shift in wildfires.
How to cite: Silver, B., Arnold, S., Emmons, L., Reddington, C., and Conibear, L.: Health impacts of wildfire smoke in the Arctic, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-9394, https://doi.org/10.5194/egusphere-egu23-9394, 2023.
Wildfires are a major source of atmospheric aerosols and can have significant impacts on air quality and radiative forcing. In our work, we have utilized the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to study the impact of wildfires on aerosol pollution and meteorological feedbacks, focusing on the geographical area of Greece as a test case. We focus on the summer season of 2021, during which intense wildfire activity occurred in the country. We have performed sensitivity experiments with and without emissions from fires as a way to quantify the impact of such emissions on atmospheric pollutants, AOD, radiative forcing and weather variables (temperature, humidity, winds). Our results show that wildfires can have a significant impact on AOD, with the magnitude of the effect depending on the size and intensity of the wildfire and the meteorological conditions. Our recent work has shown that fire prone areas determined using the FWI index seem to link closely with the areas in Greece with the highest burnt area. Since the emitted aerosols are an important parameter, we test how well the emissions correlate to the FWI. Overall, our work demonstrates the potential role of wildfires in the evolution of short-term weather conditions via fire pollution radiative forcing, and provides new insights into the mechanisms leading to such effects.
How to cite: Rovithakis, A. and Voulgarakis, A.: Studying air pollution and weather feedbacks from wildfires over Greece using WRF-Chem, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-11003, https://doi.org/10.5194/egusphere-egu23-11003, 2023.
The identification of areas susceptible to fire is critical for planners, managers, and decision makers in developing effective mitigation strategies. At Climate X we are producing risk estimates to help businesses and communities mitigate and adapt for climate change related losses. Climate X provides risk scores and expected financial losses from a range of physical hazards. The risks posed by wildfire are increasing in many regions and especially within the wildland–urban interface. We developed a machine learning model to predict changes in fire risk at 90m that can be applied globally. The approach combines meteorological drivers of fire weather utilising CORDEX regional climate models with local fire susceptibility modelling trained from Earth observation records of fire occurrence. By 2100, we find an average 7% increase in fire risk across the US and western Europe under the rcp8.5 scenario. Our results demonstrate how the combined application of machine learning, climate and Earth observation data can provide time sensitive assessments of fire risk at global scale.
How to cite: Brennan, J., Burke, C., Reveley, G., Woodhouse, S., Mitchell, H., Leach, N., and Ramsamy, L.: Towards global prediction of fire risk in a changing climate, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-8082, https://doi.org/10.5194/egusphere-egu23-8082, 2023.
Posters on site: Tue, 25 Apr, 16:15–18:00 | Hall X4
Wildfires are increasing in intensity, frequency, and occurring earlier and later than normal on the seasonal timeline. Coupled atmosphere-flame-fuel dynamics makes wildfire a difficult phenomenon to understand and predict across its temporal and spatial spectrum of scales. This is especially true at the turbulence scale where rapid fluctuations of near-surface wind velocity and temperature within the atmosphere-fire boundary layer can control fire spread rates and extreme fire behavior. Appropriate observations from wildfires suitable for process-based investigations of coupled atmosphere-fire boundary layer dynamics do not exist, instead experimentally controlled fire burns are usually carried out. These experiments rely on repeated short-term wind driven fires that are usually restricted to certain meteorological regimes. Experimental design remains a challenging endeavor, which still lacks spatially coherent ambient and fire-induced atmospheric observations for understanding coupled dynamics. We have carried out several experimental fire burns in New Zealand for short stubble wheat and more dense and higher gorse shrubs. Our observations covered fuel properties, atmospheric turbulence, and flaming zone behavior. We have used uncrewed aerial vehicles carrying high speed infrared and visible video cameras, along with in-situ eddy covariance towers for ambient and fire-induced turbulence heat and momentum measurements. Some methodological highlights include the combination of image processing techniques, fuel density maps from aerial Lidar, and atmospheric turbulence structure analysis. We present a synthesis of research findings over the last two observational campaigns and introduce our new objectives for the upcoming crown fire forest canopy fire experiments. In addition, we discuss large eddy simulations of carefully designed numerical experiments allowing for a better understanding of the fire-atmosphere energetics at the atmospheric boundary layer scales.
How to cite: Katurji, M., Zhang, J., Valencia, A., Lin, D., Strand, T., Pearce, G., Finney, M., Clements, C., and Gross, S.: Atmosphere and fire interactions from the New Zealand experimental burn campaigns, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-10286, https://doi.org/10.5194/egusphere-egu23-10286, 2023.
Human settlements in many regions have suffered great damage due to the escalating impacts of wildfires in recent decades. Most human activities have taken place over urban areas and/or Rural-Urban Interfaces (RUI). These areas have their unique vegetative and built fuels and structures, microclimates, and local wind flow dynamics. Despite the significant impacts of wildfires in RUI, only a small number of studies have been done to investigate fire-atmosphere dynamics and wildfire risk at RUI. The parallelized large eddy simulation model (PALM) system 6.0 was used to conduct simulations for a real RUI at Bottle Lake Forest, Christchurch, New Zealand. The simulations contain over 3000 residential buildings spreading around a large pine forest with an area of over 7 km2. Fine-scale simulations (Δx = 9 m and Δz = 2 m) were run for the complex rural-urban environment by using initial conditions obtained from larger-scale weather simulations using the Weather Research and Forecasting (WRF) model. A novel experimental-based method allowing for realisation of forest fire heat forcing was developed and implemented into PALM. Heat sources to simulate a forest fire were prescribed at two separate locations for the assessment of the impact of fire locations on wildfire risk on the RUI. In addition, the simulations were performed with two weather scenarios for daytime and night-time conditions, respectively. We aim to investigate the sensitivity of fire-atmosphere dynamic behaviour to different fire ignition locations and weather conditions. Our work specifically focuses on the resulting development of wind gusts and implications for potential firebrand transport paths within the surrounding urban canopy.
How to cite: Lin, D., Katurji, M., Valencia, A., and Gill, F.: Fire-atmosphere dynamics at a rural-urban interface using turbulence-resolving meteorological simulations, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-10923, https://doi.org/10.5194/egusphere-egu23-10923, 2023.
Forest fire is the main disturbance for the Himalayan ecosystems, which impacts the regional and global carbon cycle, climate, forest succession, and tree density. Forest fires can occur due to both natural processes and anthropogenic factors. The fires over the Himalayas are mostly observed in the summer and pre-monsoon season, with large interannual variability. The primary objective of the present study is to identify the main meteorological drivers controlling forest fires over the Himalayas from March to June. The study performed statistical analysis on the daily and monthly observed/reanalysis climate data between 2001-2016. We used precipitation (P), temperature (T), and soil moisture (SM) from the climate prediction center and Vapor Pressure Deficient (VPD) from ECMWF-ERA5. The three satellite-based datasets for the Burned Area (BA) are accessed from Global Fire Emissions Database version 4 (GFEDs), Collection 6 Moderate Resolution Imaging Spectroradiometer (MODIS C6), and the European Space Agency Fire Climate Change Initiative version 5.1 (FireCCI51 – CEDA archive). The preliminary results show that all three BA has significant spatial and temporal/interannual variability. Meteorological variables such as P, T, SM, and VPD indicate strong interannual variability with rising slopes throughout the study period. Among these, P and SM indicate a significant trend over the central and northeast parts of the Himalayas. The VPD has a maximum significant positive correlation with BA for all three datasets (highest for GFED). The daily climatology suggests that VPD drops with an increase in P and follows the peaks of increasing T. The VPD rises until the end of April and starts falling from May due to pre-monsoon showers. The study observed that the varying amount of BA follows the peaks of high VPD, high temperature, and dry days (PThreshold < 1mm). The northeast part of the Himalayas experiences major fires in March-April because of the substantial number of dry days and reduces in May-June due to pre-monsoon showers. In the northwest part, the amount of BA is high in May-June, despite having a smaller number of high VPD and dry days over the region. In the future, the study will focus on the impact of Himalayas forest fires on the atmospheric dust loading at a high temporal scale which can potentially trigger forest fires in adjacent regions.
How to cite: Khadke, L. and Ghosh, S.: Meteorological variables controlling the forest fire over the Himalayas, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-3274, https://doi.org/10.5194/egusphere-egu23-3274, 2023.
Forest fires are considered an important hazard in forested areas and a serious threat to forest ecosystem and buildings. The combination of drought, high temperatures, and wind increases the risk of forest fires. To better understand the fundamental causes and consequences of fire, we need to study the historical fire regimes. In this study, the meteorological conditions were simulated with the WRF model (Weather Research and Forecasting; Skamarock et al. 2008) for three historical forest fires, in the Canton of Bern, Switzerland (La Neuveville, April 1893, Simmenflueh, August 1911, Kirchberg, April 1915). In terms of area, these are the largest fires in the canton of Bern in the Swiss fire database. The "Twentieth Century Reanalysis" version 3 (20CRv3, Slivinski et al. 2019) was used as a boundary condition. 20CRv3 has a spatial resolution of about 75 km and a temporal resolution of three hours. Using WRF version 4.1.2 20CRv3 has now been gradually downscaled to a resolution of 1x1 km^2. Simulations suggest that the soil had dried out in the previous week and soil moisture had reached low values on the day the fire broke out. High-resolution fire weather indices are also calculated. A lack of precipitation and high temperatures led to high forest fire index values and a high to very high risk of forest fires.
References
[1] Slivinski, L. C.et al. (2019), Towards a more reliable historical reanalysis: Improvements to the
Twentieth Century Reanalysis system. , Q. J. Roy. Meteorol. Soc. 145, 2876-2908.
[2] Pfister, L. , S. Brönnimann, M. Schwander , FA Isotta , P. Horton, and C. Rohr, (2020) Statistical
Reconstruction of Daily Precipitation and Temperature Fields in Switzerland back to 1864, Clim.
past 16, 663-678.
[3] Skamarock, WC, et al. (2008) A Description of The Advanced Research WRF Version 3. NCAR
Technical Note.
[4] Van Wagner, C.E. (1987): Development and Structure of the Canadian Forest Fire Weather Index
System, Forestry Technical Report, Canadian Forestry Service Headquarters, Ottawa.
How to cite: Shastri, R. P., Brönniman, S., and steinfeld, D.: High-resolution modeling of historical forest fires in the Canton of Bern, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-4547, https://doi.org/10.5194/egusphere-egu23-4547, 2023.
Wildfires in carbon-rich northern high latitudes, especially Siberia, is an important phenomenon because it can worsen the air quality and accelerate warming over the Pan-Arctic regions. We investigate the shift of wildfire regimes in northern high latitudes over the recent decades using Moderate Resolution Imaging Spectroradiometer (MODIS) active fire data. Northeast Siberia has experienced a significant increase in the number of wildfires (+11.04 % year-1) and the mean period of events (+0.16 days year-1). Strengthened anomalous anti-cyclonic circulation from the surface to the upper troposphere over Northeast Siberia under the Pan-Arctic warming is responsible for more active wildfires over the last decades. This causes strong and long-lasting warm and dry conditions conducive to the ignition and persistence of wildfire. Additionally, extreme wildfire events in Northeast Siberia show that biomass-burning aerosols and gases are transported into the Arctic Ocean, contributing to the rapid melting of sea ice and snow by altering the surface radiation budget. These results suggest that extended wildfire activities in Northeast Siberia are critical to predicting the future Arctic climate.
How to cite: Kim, S.-W., Cho, Y., Yoon, J.-H., Kim, B.-M., and Jeong, J.-H.: Wildfires in Warming Siberia: Trends, Transportation and Implications on Arctic Climate, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-10866, https://doi.org/10.5194/egusphere-egu23-10866, 2023.
In March 2022, an unprecedented largest forest fire occurred in South Korea, burning 22,477 ha of forest for two weeks. In this study, we studied the causes of these fires based on an analysis of all meteorological data available over 100 years and also investigated their effects on air quality data obtained from ground-based observations (AirKorea and Asian Initiative for Clean Air Networks (AICAN)) and satellite data. Analysis results of meteorological data reveal changes in the climate regime from cold and wet winter conditions to hot and dry conditions. The temperature has been increased by 4 °C and precipitation has decreased by 17 mm over 100 years. The resistance level of forest fires is drastically reduced in the past few years and eventually lead to large-scale wildfires. These devastating wildfires emitted large amounts of ultrafine biomass-burning aerosols that were composed mainly of small particle sizes with diameters less than 1.0 mm. It elevated the air pollution level by more than 20 folds than usual condition. Carbon monoxide (CO) was also emitted from biomass burning that was detected as smoke paths (from 373 ppb to 1181 ppb) by the Tropospheric Monitoring Instrument (TROPOMI). This study highlights that climate change can make forests more vulnerable to fires and their effects on air quality could be more severe than expected.
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. RS-2022-00155875).
How to cite: Chang, D. Y. and Jeong, S.: Wildfire Effects on Air Quality: A Case Study of Wildfires in Korea in 2022, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-11045, https://doi.org/10.5194/egusphere-egu23-11045, 2023.
Over the summer of 2022, Europe experienced exceptional wildfire activity, with fires occurring more frequently and intensively, mainly in Spain, France, and Portugal. Together these countries registered more than 470 000 hectares of the total 786 000 burnt area in the European Union, accordingly to the estimates of the European Forest Fire Information System (EFFIS) for this fire season.
Southern Europe is a widely known climate change hotspot resulting in heatwaves, droughts, and wildfire activity (increase in the number and severity of fires, burnt area, and longer fire seasons) although severe droughts and heatwaves have been expanding and worsening in central and northern Europe, increasing fire risk.
This work aims to evaluate how extreme the 2022 fire season was when compared with the period 1979-2021 over Europe. The proposed methods comprise the analysis of fire-related products and atmospheric variables to evidence the fire-prone weather conditions. The European Centre for Medium-Range Weather Forecast (ECMWF) ERA5 reanalysis dataset of Fire Weather Index (FWI) and air temperature, relative humidity and wind products are used. FWI is part of a dataset from the Canadian Fire Weather Index System, and is defined as a numerical rating of the potential frontal fire intensity, that indicates fire intensity by combining the rate of fire spread with the amount of fuel being consumed. The Standardized Precipitation Evapotranspiration Index (SPEI) at time-scales of 1 to 6 months was used to assess drought conditions.
Results highlight the new fire dynamics in Europe since climate change effects are leading to new emergent hot spots (central and northern Europe), not so well known as the Mediterranean Basin. This is extremely important to allow the assessment of fire danger activity as well as the characteristics of wildfires and improve the monitoring, planning, and mitigation activities.
How to cite: Canelas da Silva, M., Durão, R., Russo, A., and Gouveia, C.: The 2022 fire season over Europe , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-13877, https://doi.org/10.5194/egusphere-egu23-13877, 2023.
Climate change and altered land use patterns have increased the risk and frequency of wildfires over the last decade. Today's estimates of the carbon impact of wildfires deploy a bottom-up approach to estimate the amount of carbon released into the atmosphere. Various parameters and variability in this approach make it difficult to make quick and accurate estimations of the carbon emissions from wildfires. We propose using satellite data from NASA’s OCO-2 and MODIS satellites to directly estimate the amount of CO2 released into the atmosphere from wildfires. A similar approach can be used to measure carbon emissions from crop-burning activities in the Gangetic plains- another significant source of carbon emissions. Direct measurements of carbon emissions can help policymakers and researchers make data-based decisions to prevent forests from becoming carbon sources instead of carbon sinks.
In our presentation, we will present a new data platform to estimate carbon emissions from localized wildfires and crop-burning instances using publicly available satellite data. The platform has pre-built functions and pipelines, allowing researchers to perform data analysis without the need to write cumbersome code. The underlying data lake combines NASA’s Orbiting Carbon Observatory (OCO-2 and OCO-3) data with other data sources (e.g., MODIS-based fire data) that facilitate more accurate and complete modeling of the dynamics of biomass burning and the impact they have on their immediate geography and the planet’s climate system at large.
How to cite: Jain, R., Odhiambo, M., Kaushal, N., Mishra, A., and Gorana, Y.: Measuring the Carbon Footprint from Wildfires and Crop Burning Using Satellite Data, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-15493, https://doi.org/10.5194/egusphere-egu23-15493, 2023.
Posters virtual: Tue, 25 Apr, 16:15–18:00 | vHall NH
Wildfires can affect the hydrological regime of a watershed until vegetation is reestablished and the hydrological cycle returns to its previous state. Wildfire induced changes can lead to increased high flows due to vegetation destruction that affects rainfall interception, evapotranspiration, but also fire induced soil imperviousness. Floods or water cycle changes after wildfire events have been extensively studied at a fire event and basin level, or at regional scale, yet changes at a global scale have not been studied systematically. Based on a wide discharge observation inventory from 651 basins globally and MODIS burned area data between 2001 and 2018, we show that the average annual discharge tends to increase in the first two years after the wildfire event, but gradually tends to return to its previous state. Furthermore, it is also found that high flow events tend to increase with wildfire size. This work focuses to a better understanding of the hydrological impacts of wildfires, and hence contribute to the improved modeling representation of fire – hydrology processes.
How to cite: Grillakis, M. and Voulgarakis, A.: Hydrological impacts of wildfires at a global scale, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-11112, https://doi.org/10.5194/egusphere-egu23-11112, 2023.
During the last decade, there has been a dramatic rise in Forest Fire incidents over the Indian Himalayan region, leading to a considerable loss of life and property. To mitigate and manage the impact of forest fires through a Forest Fire Early Warning System, a better understanding of both small and large-scale atmospheric processes conducive to the spread of forest fires is required. Although significant progress has been made in disseminating forest fire danger information, most of the operational methodologies in the Indian sub-continent still do not consider real-time weather forecasts from atmospheric numerical models as input to the fire module. The objective of this work is to systematically analyze the meteorological conditions during two major forest fire events that occurred over the Uttarakhand region in 2016 and 2020. Forest fire events in 2016 and 2020 coincide with El Nino, La-Nina and cycles of Indian Ocean Dipole (IOD). A detailed analysis of the 2016 and 2020 fire events shows an increased frequency of fire events and burnt areas in 2016, whereas the area burnt was considerably low in the 2020 event. A typical year without significant influences from ENSO and IOD shows relatively low spread of fires and burnt areas. Such an impenetrable correlation between atmospheric oscillations and fire events results in vast damage over the Indian Himalayan region. The inculcation of real-time weather forecasts with numerical weather prediction models could tackle this existing gap in the Forest Fire Early Warning System and possibly mitigate the further casualties caused by the increased acceleration of fire spread induced by atmospheric oscillation over the Indian Himalayan region.
How to cite: Prabhakaran, A., Srivastava, P., and Pai, A.: Atmospheric Conditions Conducive to Forest Fire Events in the Greater Himalayan Region, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-1004, https://doi.org/10.5194/egusphere-egu23-1004, 2023.
Wildland fires have been increasing in size, frequency and intensity during recent decades, affecting entire ecosystems and societies even in regions historically not considered fire prone. Some of those fires display dynamics of extreme fire behaviour, which chaotic and large-scale nature make them challenging to study. Thus, there is a need of new methodologies for wildland fire analysis, capable of capturing spatiotemporal characteristics suitable for this application. This work presents two applications of the image velocimetry technique applied to wildland fires, offering new details on the morphology and structure of large-scale medium-intensity prescribed shrubland fires, as well as an outlook on new applications in more complex scenarios. Fire flow displacement vectors and streamlines were calculated and mapped from a high-resolution overhead visible-spectrum (RGB) video acquired during a four-hectare prescribed gorse fire. This method allowed for identification of spatially interleaved flow convergence and divergence regions, providing insight on the high-level structure of the fire front and flaming zone. The method was further expanded to identify what we refer to as “fire sweeps”, via the application of a 2D convolution operation on the displacement vector based upon a kernel carefully designed to highlight the characteristics highly divergent fire flows.
How to cite: Valencia, A., Katurji, M., Lin, D., Gross, S., Zhang, J., Pearce, G., Finney, M., and Strand, T.: Unravelling wildland fire morphology and structure using image velocimetry, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-12974, https://doi.org/10.5194/egusphere-egu23-12974, 2023.
