Effect of climate change on wildfires in Fennoscandia

2021 ◽  
Author(s):  
Leif Backman ◽  
Tuula Aalto ◽  
Juha Aalto ◽  
Tiina Markkanen ◽  
Laura Thölix ◽  
...  
Keyword(s):  
Climate Change ◽  
Forest Fires ◽  
Gross Primary Production ◽  
Fire Risk ◽  
Shortwave Radiation ◽  
Fuel Load ◽  
Burned Area ◽  
Temperature And Precipitation ◽  
Model Domain ◽  
Projected Change

<p>The climate in the Boreal area is warming at a pace that is exceeding the global average. Both temperature and precipitation is projected to increase due to climate change. The gross primary production in the forested area is also projected to increase, as well as the soil respiration. The burned area is sensitive to the meteorological forcing and the risk of ignition depends on the amount and properties of the litter. Overall climate change has a potential to increase the fire risk in the Boreal forests.</p><p>The effects of projected climate change on forest fires in Fennoscandia, and in parts of Russia adjacent to Finland, were simulated with the JSBACH-SPITFIRE. JSBACH is the land model in the Earth system models of the Max-Planck Institute for Meteorology. SPITFIRE is a mechanistic fire model, driven by meteorology, vegetation cover, fuel load and fuel properties. The model simulates fire risk, number of fires and burned area fraction. SPITFIRE uses ignition rates and distinguishes between ignition events caused by lightning and humans. Ignition events result in fire only when enough fuel is present, and the fuel is sufficiently dry. The JSBACH-SPITFIRE model was driven by downscaled and bias corrected meteorological data from the EURO-CORDEX initiative, for the period from 1951 to 2100. The model domain was the land area within 55-71°N and 5-38°E. A subset of the EUR-44 domain was regridded to 0.5° resolution for our model domain. The global driving models used for producing the EURO-CORDEX data used here were CanESM2, CNRM-CM5, MIROC5. We selected driver models that represent mid-range regarding the projected change in temperature and precipitation for Finland under RCP4.5 and RCP8.5. We used daily bias corrected data of precipitation and temperature from 1951 to 2100 for both RCP4.5 and RCP8.5 climate change projections. In addition, daily data of relative humidity, wind speed, longwave and shortwave radiation were used for the historical (1951-2005) and scenario period (2006-2100).</p><p>Preliminary results indicate that the increase in temperature, which affects the drying rate of the fuel, is the major factor for driving the changes in forest fires in the simulations.</p>

scholarly journals The effect of climate anomalies and human ignition factor on wildfires in Russian boreal forests

2007 ◽  
Vol 363 (1501) ◽  
pp. 2329-2337 ◽  
Author(s):  
Frédéric Achard ◽  
Hugh D Eva ◽  
Danilo Mollicone ◽  
René Beuchle
Keyword(s):  
Climate Change ◽  
Forest Fires ◽  
Boreal Forests ◽  
Buffer Zone ◽  
Burned Area ◽  
Areal Extent ◽  
Human Disturbances ◽  
Fire Event ◽  
Climate Anomalies ◽  
Temperature And Precipitation

Over the last few years anomalies in temperature and precipitation in northern Russia have been regarded as manifestations of climate change. During the same period exceptional forest fire seasons have been reported, prompting many authors to suggest that these in turn are due to climate change. In this paper, we examine the number and areal extent of forest fires across boreal Russia for the period 2002–2005 within two forest categories: ‘intact forests’ and ‘non-intact forests’. Results show a far lower density of fire events in intact forests (5–14 times less) and that those events tend to be in the first 10 km buffer zone inside intact forest areas. Results also show that, during exceptional climatic years (2002 and 2003), fire event density is twice that found during normal years (2004 and 2005) and average areal extent of fire events (burned area) in intact forests is 2.5 times larger than normal. These results suggest that a majority of the fire events in boreal Russia are of human origin and a maximum of one-third of their impact (areal extension) can be attributed to climate anomalies alone, the rest being due to the combined effect of human disturbances and climate anomalies.

scholarly journals Evolution of Burned Area in Forest Fires under Climate Change Conditions in Southern Spain Using ANN

2019 ◽  
Vol 9 (19) ◽  
pp. 4155
Author(s):  
Pérez-Sánchez ◽  
Jimeno-Sáez ◽  
Senent-Aparicio ◽  
Díaz-Palmero ◽  
de Dios Cabezas-Cerezo
Keyword(s):  
Climate Change ◽  
Forest Fires ◽  
Southern Spain ◽  
Burned Area ◽  
Change Scenario ◽  
Absolute Deviation ◽  
Average Temperature ◽  
Mediterranean Regions ◽  
Artificial Neural Network Ann ◽  
Absolute Percent Error

Wildfires in Mediterranean regions have become a serious problem, and it is currently the main cause of forest loss. Numerous prediction methods have been applied worldwide to estimate future fire activity and area burned in order to provide a stable basis for future allocation of fire-fighting resources. The present study investigated the performance of an artificial neural network (ANN) in burned area size prediction and to assess the evolution of future wildfires and the area concerned under climate change in southern Spain. The study area comprised 39.41 km2 of land burned from 2000 to 2014. ANNs were used in two subsequential phases: classifying the size of the wildfires and predicting the burned surface for fires larger than 30,000 m2. Matrix of confusion and 10-fold cross-validations were used to evaluate ANN classification and mean absolute deviation, root mean square error, mean absolute percent error and bias, which were the metrics used for burned area prediction. The success rate achieved was above 60–70% depending on the zone. An average temperature increase of 3 °C and a 20% increase in wind speed during 2071–2100 results in a significant increase of the number of fires, up to triple the current figure, resulting in seven times the average yearly burned surface depending on the zone and the climate change scenario.

scholarly journals MULTICRITERIA ANALYSIS FOR IDENTIFYING FOREST FIRE RISK ZONES IN THE BIOLOGICAL RESERVE OF THE SAMA CORDILLERA, BOLIVIA

2020 ◽  
Vol XLII-3/W12-2020 ◽  
pp. 113-118
Author(s):  
S. Mariscal ◽  
M. Ríos ◽  
F. Soria
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Risk Model ◽  
Multicriteria Analysis ◽  
Fire Risk ◽  
Temperature And Precipitation ◽  
Spatial Risk ◽  
Forest Fire Risk ◽  
Very High ◽  
Biological Reserve

Abstract. Forest fires have negative effects on biodiversity, the atmosphere and human health. The paper presents a spatial risk model as a tool to assess them. Risk areas refer to sectors prone to the spread of fire, in addition to the influence of human activity through remote sensing and multi-criteria analysis. The analysis includes information on land cover, land use, topography (aspect, slope and elevation), climate (temperature and precipitation) and socio-economic factors (proximity to settlements and roads). Weights were assigned to each in order to generate the forest fire risk map. The investigation was carried for a Biological Reserve in Bolivia because of the continuous occurrence of forest fires. Five risk categories for forest fires were derived: very high, high, moderate, low and very low. In summary, results suggest that approximately 67% of the protected area presents a moderate to very high risk; in the latter, populated areas are not dense which reduces the actual risk to the type of events analyzed.

scholarly journals Influência de Mudanças Climáticas no Balanço Hídrico da Amazônia Ocidental (Influence of Climate Change on Water Budget of Western Amazonia)

2011 ◽  
Vol 3 (3) ◽  
pp. 170 ◽  
Author(s):  
Ailton Marcolino Liberato ◽  
José Ivaldo B. De Brito
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Air Temperature ◽  
Water Budget ◽  
Fire Risk ◽  
Climate Index ◽  
Climate Trends ◽  
Climatological Data ◽  
Temperature And Precipitation

A presente pesquisa teve por objetivo investigar possíveis alterações em componentes do balanço hídrico climático, associadas a diferentes cenários (A2 e B2) das mudanças climáticas do IPCC, para a Amazônia Ocidental (Acre, Amazonas, Rondônia e Roraima). Os dados climatológicos de temperatura do ar e totais de precipitação pluvial usados como referência neste estudo, são oriundos do INMET (1961-2005), da CEPLAC (1983-1999) e da reanálise do NCEP/NCAR (1983-1995). O método utilizado na elaboração do balanço hídrico é o de Thornthwaite e Mather (1957) modificado por Krishan (1980). Os resultados das projeções mostram tendência de clima mais seco, diminuição na umidade do solo, redução na vazão dos rios, aumento no risco de incêndio e diminuição no escoamento superficial e sub-superficial para a Amazônia Ocidental até 2100.Palavras-chave: cenários, índices climáticos, Amazônia. Influence of Climate Change on Water Budget of Western Amazonia ABSTRACTThe main objective of this study was investigate possible alterations in the climatic water budget components associated with different scenarios (A2 and B2) of the IPCC to Amazonian Western (Acre, Amazonas, Rondônia and Roraima). The climatological data of air temperature and precipitation from the INMET (1961-2005), CEPLAC (1983-1999) and NCEP/NCAR reanalysis (1983-1995) were used in the present study. The Thornthwaite and Mather (1955) method was used in the elaboration of the climatic water budget modified by Krishan (1980). The results of the projections show drier climate trends and decrease of the soil moisture, reduction in the rivers discharge, increase in the fire risk and decrease in the runoff for the Amazonian Western up to 2100. Keywords: scenarios, climate index, Amazonian.

scholarly journals Climate change and forest management affect forest fire risk in Fennoscandia

2021 ◽  
Author(s):  
Keyword(s):  
Climate Change ◽  
Forest Management ◽  
Black Carbon ◽  
Forest Fire ◽  
Forest Fires ◽  
Fire Risk ◽  
The Arctic ◽  
Large Fires ◽  
Forest Fire Risk ◽  
Fire Ignition

Forest and wildland fires are a natural part of ecosystems worldwide, but large fires in particular can cause societal, economic and ecological disruption. Fires are an important source of greenhouse gases and black carbon that can further amplify and accelerate climate change. In recent years, large forest fires in Sweden demonstrate that the issue should also be considered in other parts of Fennoscandia. This final report of the project “Forest fires in Fennoscandia under changing climate and forest cover (IBA ForestFires)” funded by the Ministry for Foreign Affairs of Finland, synthesises current knowledge of the occurrence, monitoring, modelling and suppression of forest fires in Fennoscandia. The report also focuses on elaborating the role of forest fires as a source of black carbon (BC) emissions over the Arctic and discussing the importance of international collaboration in tackling forest fires. The report explains the factors regulating fire ignition, spread and intensity in Fennoscandian conditions. It highlights that the climate in Fennoscandia is characterised by large inter-annual variability, which is reflected in forest fire risk. Here, the majority of forest fires are caused by human activities such as careless handling of fire and ignitions related to forest harvesting. In addition to weather and climate, fuel characteristics in forests influence fire ignition, intensity and spread. In the report, long-term fire statistics are presented for Finland, Sweden and the Republic of Karelia. The statistics indicate that the amount of annually burnt forest has decreased in Fennoscandia. However, with the exception of recent large fires in Sweden, during the past 25 years the annually burnt area and number of fires have been fairly stable, which is mainly due to effective fire mitigation. Land surface models were used to investigate how climate change and forest management can influence forest fires in the future. The simulations were conducted using different regional climate models and greenhouse gas emission scenarios. Simulations, extending to 2100, indicate that forest fire risk is likely to increase over the coming decades. The report also highlights that globally, forest fires are a significant source of BC in the Arctic, having adverse health effects and further amplifying climate warming. However, simulations made using an atmospheric dispersion model indicate that the impact of forest fires in Fennoscandia on the environment and air quality is relatively minor and highly seasonal. Efficient forest fire mitigation requires the development of forest fire detection tools including satellites and drones, high spatial resolution modelling of fire risk and fire spreading that account for detailed terrain and weather information. Moreover, increasing the general preparedness and operational efficiency of firefighting is highly important. Forest fires are a large challenge requiring multidisciplinary research and close cooperation between the various administrative operators, e.g. rescue services, weather services, forest organisations and forest owners is required at both the national and international level.

scholarly journals Risk of large-scale fires in boreal forests of Finland under changing climate

2016 ◽  
Vol 16 (1) ◽  
pp. 239-253 ◽  
Author(s):  
I. Lehtonen ◽  
A. Venäläinen ◽  
M. Kämäräinen ◽  
H. Peltola ◽  
H. Gregow
Keyword(s):  
Climate Change ◽  
Forest Fire ◽  
Forest Fires ◽  
Large Scale ◽  
Fire Danger ◽  
Short Period ◽  
Projected Change ◽  
Fire Activity ◽  
Model Variability ◽  
The Impact

Abstract. The target of this work was to assess the impact of projected climate change on forest-fire activity in Finland with special emphasis on large-scale fires. In addition, we were particularly interested to examine the inter-model variability of the projected change of fire danger. For this purpose, we utilized fire statistics covering the period 1996–2014 and consisting of almost 20 000 forest fires, as well as daily meteorological data from five global climate models under representative concentration pathway RCP4.5 and RCP8.5 scenarios. The model data were statistically downscaled onto a high-resolution grid using the quantile-mapping method before performing the analysis. In examining the relationship between weather and fire danger, we applied the Canadian fire weather index (FWI) system. Our results suggest that the number of large forest fires may double or even triple during the present century. This would increase the risk that some of the fires could develop into real conflagrations which have become almost extinct in Finland due to active and efficient fire suppression. However, the results reveal substantial inter-model variability in the rate of the projected increase of forest-fire danger, emphasizing the large uncertainty related to the climate change signal in fire activity. We moreover showed that the majority of large fires in Finland occur within a relatively short period in May and June due to human activities and that FWI correlates poorer with the fire activity during this time of year than later in summer when lightning is a more important cause of fires.

Potential changes in monthly fire risk in the eastern Canadian boreal forest under future climate change

2009 ◽  
Vol 39 (12) ◽  
pp. 2369-2380 ◽  
Author(s):  
Héloïse Le Goff ◽  
Mike D. Flannigan ◽  
Yves Bergeron
Keyword(s):  
Climate Change ◽  
Forest Fires ◽  
Fire Risk ◽  
Weather Conditions ◽  
Future Climate ◽  
Fire Season ◽  
Future Climate Change ◽  
Change Scenario ◽  
Fire Weather Index ◽  
Fire Activity

The main objective of this paper is to evaluate whether future climate change would trigger an increase in the fire activity of the Waswanipi area, central Quebec. First, we used regression analyses to model the historical (1973–2002) link between weather conditions and fire activity. Then, we calculated Fire Weather Index system components using 1961–2100 daily weather variables from the Canadian Regional Climate Model for the A2 climate change scenario. We tested linear trends in 1961–2100 fire activity and calculated rates of change in fire activity between 1975–2005, 2030–2060, and 2070–2100. Our results suggest that the August fire risk would double (+110%) for 2100, while the May fire risk would slightly decrease (–20%), moving the fire season peak later in the season. Future climate change would trigger weather conditions more favourable to forest fires and a slight increase in regional fire activity (+7%). While considering this long-term increase, interannual variations of fire activity remain a major challenge for the development of sustainable forest management.

Prediction for Burned Area of Forest Fires Based on SVM Model

2014 ◽  
Vol 513-517 ◽  
pp. 4084-4089 ◽  
Author(s):  
Dao Wen Xie ◽  
Shi Liang Shi
Keyword(s):  
Forest Fires ◽  
Fuel Load ◽  
Burned Area ◽  
Support Vector ◽  
Machine Model ◽  
Guangzhou City ◽  
Svm Model ◽  
Forest Fuel ◽  
Using Data ◽  
Fuel Moisture Content

Forest fire spreading is a complex burning phenomenon, and it is difficult to build a general spreading model for the fires occurred in different area over the world, even in the same country. Accordingly, predicting the burned area of forest fires is also a challenging task. In this work, five attributes (i.e. forest fuel moisture content, forest fuel inflammability, forest fuel load ,slope and burning time) are selected as input to predict burned area of forest fires occurred in the area of Guangzhou City in China. Next, using Data Mining (DM) technique, an SVM (Support Vector Machine) model was built and applied to deal with this type of a regression task, predicting burned area. Results showed that the selection of input attributes was reasonable, and the proposed SVM model was suitable for prediction of burned area, with higher precision, better generalization. This work provided a new way to deal with predictions for burned area of forest fires.

scholarly journals GISCIENCE FOR FOREST FIRE MODELING: NEW ADVANCES IN WILDLAND FIRES WITH MANAGEMENT

2021 ◽  
Vol 21 (no 1) ◽  
Author(s):  
Jagpal Singh Tomar ◽  
Shruti Kanga ◽  
Suraj Kumar Singh
Keyword(s):  
Climate Change ◽  
Forest Fire ◽  
Spatial Data ◽  
Forest Fires ◽  
Fire Risk ◽  
Fire Regimes ◽  
Spatial Data Analysis ◽  
Mitigation And Adaptation ◽  
The World ◽  
Urban Rural

Wildfire is one of the complex and damaging natural phenomena in the world. Wildfires pose an enormous challenge to predict and monitor complicated integration chemistry with the physical aspects of solid-gas stage combustion and heat transmission spatially diverse vegetations, topography, and detailed time and space conditions at various spatial and time scales. The research community has greatly enhanced its efforts in the last 25 years to better understand wildfires by improving observation, measurement, analysis and modelling. The fast development of spatial data analysis and computer technology has been facilitated. This combination allowed new decision promotion systems, information collection, analysis methods, growth, and existing fire management instruments. In several countries, despite this activity, forest fires remain a serious problem. Factors that raise the world risk of wildfires are climate change, urban-rural migration and the creation of the interface between urban and wildlands. These events demonstrate the tremendous destructive force of wildfires of great magnitude, sometimes well beyond our concrete containment and control capability. In addition to firefighters, foresters and other organised systems, the scientific community is key to addressing the problems of fire recognition in the countryside. Advances in our understanding of fire-fighting mechanisms and the relationship between fire activity and the natural and constructed environment can lead to successful fire risk decision support systems, the predictions for fire propagation and the reduction of fire risk. The convergence of forest ecosystems and forest fires has become the growing threat posed by human influences and other factors to ecosystems, resources and even human lives. Climate change will change forest fire regimes to enhance forest fire understanding and to build strategies for mitigation and adaptation. The study highlights broad aspects of forest fire in combination with

Soft Computing Modeling of Wild Fire Risk Indices

2013 ◽  
pp. 1073-1087
Author(s):  
L. Iliadis ◽  
T. Betsidou
Keyword(s):  
Soft Computing ◽  
Forest Fire ◽  
Forest Fires ◽  
Fuzzy Inference ◽  
Research Effort ◽  
Fire Risk ◽  
Geographic Area ◽  
Burned Area ◽  
Wild Fire ◽  
Risk Indices

It is essential to find ways that can reduce the risk of devastating forest fires which have multiple negative ecological and financial consequences. This preliminary research effort focuses on the implementation of an intelligent rule based fuzzy inference system evaluating wild fire risk in the forest departments of Greece. The system uses soft computing techniques and was built in the Matlab integrated environment. The whole research is related to the wild fires in Greece during the period 1983-1997 with data coming from the general forest management service. It classifies all Greek forest departments (by assigning three labels) according to their forest fire risk due to distinct parameters. The estimation of the risk indices was done by using fuzzy triangular membership functions and Einstein fuzzy conjunction T-Norms. Moreover the system produces the profile of the forest departments located in the geographic area of “Peloponnesus.” This is a region located in the southern part of the country and it has a vast number of annual forest fire breakouts. Meteorological, topographic, and historical (total burned area and intervention time) features were considered for the determination of the risk indices. The system has shown a good performance which can be improved further if more data is gathered and used. Its main advantage is that it offers an innovative and reliable model that can be employed in any part of the world as a basis for natural disasters’ risk estimation.

Sign in / Sign up

Export Citation Format

Share Document