scholarly journals Multi-variable bias correction: application of forest fire risk in present and future climate in Sweden

2015 ◽  
Vol 15 (9) ◽  
pp. 2037-2057 ◽  
Author(s):  
W. Yang ◽  
M. Gardelin ◽  
J. Olsson ◽  
T. Bosshard
Keyword(s):  
Forest Fire ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate Model ◽  
Fire Risk ◽  
Future Climate ◽  
Climate Modelling ◽  
Post Processing ◽  
Fire Weather Index ◽  
Forest Fire Risk

Abstract. As the risk of a forest fire is largely influenced by weather, evaluating its tendency under a changing climate becomes important for management and decision making. Currently, biases in climate models make it difficult to realistically estimate the future climate and consequent impact on fire risk. A distribution-based scaling (DBS) approach was developed as a post-processing tool that intends to correct systematic biases in climate modelling outputs. In this study, we used two projections, one driven by historical reanalysis (ERA40) and one from a global climate model (ECHAM5) for future projection, both having been dynamically downscaled by a regional climate model (RCA3). The effects of the post-processing tool on relative humidity and wind speed were studied in addition to the primary variables precipitation and temperature. Finally, the Canadian Fire Weather Index system was used to evaluate the influence of changing meteorological conditions on the moisture content in fuel layers and the fire-spread risk. The forest fire risk results using DBS are proven to better reflect risk using observations than that using raw climate outputs. For future periods, southern Sweden is likely to have a higher fire risk than today, whereas northern Sweden will have a lower risk of forest fire.

scholarly journals Forest fire risk assessment in Sweden using climate model data: bias correction and future changes

2015 ◽  
Vol 3 (1) ◽  
pp. 837-890 ◽  
Author(s):  
W. Yang ◽  
M. Gardelin ◽  
J. Olsson ◽  
T. Bosshard
Keyword(s):  
Forest Fire ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Fire Risk ◽  
Climate Modelling ◽  
Post Processing ◽  
Fire Weather Index ◽  
Forest Fire Risk

Abstract. As the risk for a forest fire is largely influenced by weather, evaluating its tendency under a changing climate becomes important for management and decision making. Currently, biases in climate models make it difficult to realistically estimate the future climate and consequent impact on fire risk. A distribution-based scaling (DBS) approach was developed as a post-processing tool that intends to correct systematic biases in climate modelling outputs. In this study, we used two projections, one driven by historical reanalysis (ERA40) and one from a global climate model (ECHAM5) for future projection, both having been dynamically downscaled by a regional climate model (RCA3). The effects of the post-processing tool on relative humidity and wind speed were studied in addition to the primary variables precipitation and temperature. Finally, the Canadian Fire Weather Index system was used to evaluate the influence of changing meteorological conditions on the moisture content in fuel layers and the fire-spread risk. The forest fire risk results using DBS are proven to better reflect risk using observations than that using raw climate outputs. For future periods, southern Sweden is likely to have a higher fire risk than today, whereas northern Sweden will have a lower risk of forest fire.

scholarly journals Mapping Forest Fire Risk—A Case Study in Galicia (Spain)

2020 ◽  
Vol 12 (22) ◽  
pp. 3705
Author(s):  
Ana Novo ◽  
Noelia Fariñas-Álvarez ◽  
Joaquín Martínez-Sánchez ◽  
Higinio González-Jorge ◽  
José María Fernández-Alonso ◽  
...  
Keyword(s):  
Forest Fire ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Fire Risk ◽  
Fire Regimes ◽  
Slope Aspect ◽  
Fire Weather Index ◽  
Novel Approach ◽  
Fuel Model ◽  
Forest Fire Risk

The optimization of forest management in roadsides is a necessary task in terms of wildfire prevention in order to mitigate their effects. Forest fire risk assessment identifies high-risk locations, while providing a decision-making support about vegetation management for firefighting. In this study, nine relevant parameters: elevation, slope, aspect, road distance, settlement distance, fuel model types, normalized difference vegetation index (NDVI), fire weather index (FWI), and historical fire regimes, were considered as indicators of the likelihood of a forest fire occurrence. The parameters were grouped in five categories: topography, vegetation, FWI, historical fire regimes, and anthropogenic issues. This paper presents a novel approach to forest fire risk mapping the classification of vegetation in fuel model types based on the analysis of light detection and ranging (LiDAR) was incorporated. The criteria weights that lead to fire risk were computed by the analytic hierarchy process (AHP) and applied to two datasets located in NW Spain. Results show that approximately 50% of the study area A and 65% of the study area B are characterized as a 3-moderate fire risk zone. The methodology presented in this study will allow road managers to determine appropriate vegetation measures with regards to fire risk. The automation of this methodology is transferable to other regions for forest prevention planning and fire mitigation.

Estimation of Forest Fire Risk by Using Fire Weather Index in the MENA Region

2020 ◽  
Author(s):  
Burcu Calda ◽  
Kamil Collu ◽  
Aytac Pacal ◽  
Mehmet Levent Kurnaz
Keyword(s):  
Observational Data ◽  
Forest Fire ◽  
Forest Fires ◽  
Control Period ◽  
Fire Risk ◽  
Fire Weather ◽  
Weather Index ◽  
Fire Weather Index ◽  
The Mediterranean ◽  
Forest Fire Risk

<p>Forest fires are naturals in the Mediterranean ecosystems. However, in the last decade, the number of wildfires has significantly increased in the Mediterranean basin along with climate change. Therefore, forecasts of this region by using fire indices are crucial to take necessary precautions. In the present study, the projected changes for the period 2070 - 2099 concerning the control period 1971 - 2000 were used to estimate forest fire risk by the Canadian Fire Weather Index (FWI). RCP4.5 and RCP8.5 emission scenarios (IPCC) outputs of MPI-ESM-MR and HadGEM2-ES dynamically downscaled to 50 km for the CORDEX-MENA domain with the use of the RegCM4 were utilized. ERA-Interim observational data from ECMWF covering the period 1980-2012 were also used to test the performances of models. The output of MPI-ESM-MR gave more similar fire risk prediction with the reforecast of observational data (ERA-Interim). Thus, the MPI-ESM-MR model could be more suitable to estimate fire risk by FWI. According to future projection, forest fire risk will significantly increase throughout the region for the last 30 years of this century.</p>

scholarly journals weather@home 2: validation of an improved global–regional climate modelling system

2017 ◽  
Vol 10 (5) ◽  
pp. 1849-1872 ◽  
Author(s):  
Benoit P. Guillod ◽  
Richard G. Jones ◽  
Andy Bowery ◽  
Karsten Haustein ◽  
Neil R. Massey ◽  
...  
Keyword(s):  
Climate Change ◽  
Extreme Events ◽  
Land Surface ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate Model ◽  
Regional Climate ◽  
Extreme Weather Events ◽  
Climate Modelling ◽  
Modelling System

Abstract. Extreme weather events can have large impacts on society and, in many regions, are expected to change in frequency and intensity with climate change. Owing to the relatively short observational record, climate models are useful tools as they allow for generation of a larger sample of extreme events, to attribute recent events to anthropogenic climate change, and to project changes in such events into the future. The modelling system known as weather@home, consisting of a global climate model (GCM) with a nested regional climate model (RCM) and driven by sea surface temperatures, allows one to generate a very large ensemble with the help of volunteer distributed computing. This is a key tool to understanding many aspects of extreme events. Here, a new version of the weather@home system (weather@home 2) with a higher-resolution RCM over Europe is documented and a broad validation of the climate is performed. The new model includes a more recent land-surface scheme in both GCM and RCM, where subgrid-scale land-surface heterogeneity is newly represented using tiles, and an increase in RCM resolution from 50 to 25 km. The GCM performs similarly to the previous version, with some improvements in the representation of mean climate. The European RCM temperature biases are overall reduced, in particular the warm bias over eastern Europe, but large biases remain. Precipitation is improved over the Alps in summer, with mixed changes in other regions and seasons. The model is shown to represent the main classes of regional extreme events reasonably well and shows a good sensitivity to its drivers. In particular, given the improvements in this version of the weather@home system, it is likely that more reliable statements can be made with regards to impact statements, especially at more localized scales.

Climate services for forest fire risk management

2020 ◽  
Author(s):  
Céline Deandreis ◽  
Gwendoline Lacressonière ◽  
Marc Chiapero ◽  
Miguel Mendes ◽  
Humberto Diaz Fidalgo ◽  
...  
Keyword(s):  
Forest Fire ◽  
Fire Risk ◽  
Propagation Model ◽  
Economic Losses ◽  
Main Role ◽  
Climate Services ◽  
Fire Weather Index ◽  
Probable Maximum Loss ◽  
Forest Fire Risk

<p>The weather and its climatic evolution play the main role in generating hazard profiles of forest fires. The increased in magnitude and damage of last forest fire seasons has caused a larger concern of the insurance sector for this peril. Due to the lack of knowledge of this risk, there is a widespread low level of insurance coverage of forest fire risk. A first step forward is clearly needed to (1) propose simplified approaches showing how the risk links with its main weather drivers, and (2) re-incentivize the use of insurance by forest managers.</p><p>To answer this objective, ARIA Technologies and its partners have developed a geospatial web-based decision tool to support both forest owners and forest insurance actors in managing the vulnerability of their asset/portfolios to fire risk. RiskFP includes:</p><ul><li>A “realistic disaster scenarios generator module” that allows the generation of hundreds of scenarios of extreme wildfires to complete information from historical fires databases. This information can be used in damage and loss modelling to improve the estimation of the probable maximum loss (PML). In addition, the risk FP “impact module” provides to the users information on the different potential impact like the amount of biomass burnt or the economic losses.</li> <li>A precise mapping of the local forest fire risk through the graphical representation of an index including five risk levels (from low to extreme) that provides an overview of the most critical locations regarding the potential behavior of the fire in case of an hypothetical ignition.</li> <li>A forecasting/projection module to inform the users on the frequency of the severe-extreme days in the mid- and long-term horizons. It can be used by the forestry sector to better anticipate and prepare the next fire season and as a planning tool for long-term operation/investment.</li> </ul><p>At the heart of the platform lies the concept of critical landscape weather patterns (CLP), an empirical fire weather index that identifies severe-extreme weather days derived from hourly records of a representative weather station (Gellie, 2019). It could be computed from past records, seasonal forecast or climate projection allowing to provide fire risk assessment for these different time scales. The CLP module is coupled with a propagation model, the Wildfire Analyst® forest fire simulator at the resolution of about 40m, that is used to estimate the progression and behavior of the fire in space and time. It is based on the standardized and validated semi-empirical Rothermel propagation model (1972).</p><p><strong>Acknowledgements:</strong></p><p>We acknowledge the European Commission for sponsoring this work in the framework of the H2020-insurance project (Grant Agreement number 730381).</p>

Future Climate Change Impact on Wildfire Danger over the Mediterranean: the case of Greece

2021 ◽  
Author(s):  
Anastasios Rovithakis ◽  
Apostolos Voulgarakis ◽  
Manolis Grillakis ◽  
Christos Giannakopoulos ◽  
Anna Karali
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Fire Risk ◽  
Fire Danger ◽  
Future Climate ◽  
Future Climate Change ◽  
Fire Weather Index ◽  
The Mediterranean ◽  
The Impact ◽  
Of Greece

<p>The Canadian Fire Weather Index (FWI) is a meteorologically based index designed initially to be used in Canada but it can also be used worldwide, including the Mediterranean, to estimate fire danger in a generalized fuel type based solely on weather observations. The four weather variables are measured and used as inputs to the FWI (rain accumulated over 24 h, temperature, relative humidity, and wind speed) are generally taken daily at noon local standard time.</p><p>Recent studies have shown that temperature and precipitation in the Mediterranean, and more specifically in Greece are expected to change, indicating longer and more intense summer droughts that even extend out of season. In connection to this, the frequency of forest fire occurrence and intensity is on the rise. In the present study, the FWI index is used in order to assess changes in future fire danger conditions.</p><p>To represent meteorological conditions, regional EURO-CORDEX climate model simulations over the Mediterranean and mainly Greece at a spatial resolution of 11 km, were utilized. In order to assess the impact of future climate change, we used two Representative Concentration Pathway (RCP) scenarios consisting of an optimistic emission scenario where emissions peak and decline beyond 2020 (RCP2.6) and a pessimistic scenario where emissions continue to rise throughout the century (RCP8.5).  We compare the FWI projections for two future time periods, 2021-2050 and 2071-2100 with reference to the historical time period 1971-2000. Based on the critical fire risk threshold values that have been established in previous studies for the area of Greece, the days with critical fire risk were calculated for different Greek domains.</p>

The meteorological conditions associated with extreme fire risk in Italy and Greece: relevance to climate model studies

2008 ◽  
Vol 17 (2) ◽  
pp. 155 ◽  
Author(s):  
P. Good ◽  
M. Moriondo ◽  
C. Giannakopoulos ◽  
M. Bindi
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Risk Model ◽  
Fire Risk ◽  
Meteorological Conditions ◽  
Fire Weather ◽  
Fire Weather Index ◽  
Model Studies ◽  
Short Timescale ◽  
Extreme Fire

The meteorological conditions associated with elevated and extreme long- and short-timescale forest fire risk are investigated by validating and diagnosing the Canadian Fire Weather Index (FWI) in the context of Tuscany in Italy, and Thessaloniki, Athens and Heraklion in Greece. The aim is to provide information to assist diagnosing experiments that use output from climate models to calculate FWI values. Links are made from fire risk to the widely used FWI, and then to the underlying meteorology, complementing other more complex fire risk model studies. First, the information about Mediterranean fire risk provided by the FWI is assessed by comparing the observed number of fires per day with FWI values based on the locally observed meteorology. This shows that the FWI provides some relatively consistent information for different locations, and suggests useful FWI thresholds indicating elevated and extreme fire risk. Then, the FWI system is split according to contributions from long- and short-timescale components, in a different way than usually adopted in the literature. Using the FWI thresholds suggested above, the long- and short-timescale meteorological conditions causing elevated and extreme FWI values are diagnosed. The results may help studies that investigate what aspects of projected climate change drive changes in fire weather risk, compare fire risk calculations from different climate models, or assess how climate models can be improved to provide better fire risk projections.

scholarly journals Forest fire risk analysis via integration of GIS, RS and AHP: The Case of Çanakkale, Turkey

2018 ◽  
Vol 15 (4) ◽  
pp. 2127 ◽  
Author(s):  
Cengiz Akbulak ◽  
Hasan Tatlı ◽  
Gurcu Aygün ◽  
Bülent Sağlam
Keyword(s):  
Human Factors ◽  
Forest Fire ◽  
Forest Fires ◽  
Risk Model ◽  
Vegetation Type ◽  
Fire Risk ◽  
Western Anatolia ◽  
Physical Factors ◽  
Fire Weather Index ◽  
Forest Fire Risk

Forest fire is one of the high-risk natural disasters in the north-western Anatolia section of Turkey. This paper suggests a new approach based on Geographic Information Systems (GIS), Remote Sensing (RS) and Analytical Hierarchy Process (AHP) for the development of forest fire-risk model. The proposed approach includes human factors as well as environmental factors. In this context, the 12 variables defined under anthropogenic and physical factors in the proposed model are the slope, elevation, aspect, vegetation type, crown closure, Normalized Difference Vegetation Index (NDVI), distance to road, settlement, and agricultural areas, population density, previous fires, and Canadian Forest Fire Weather Index (FWI). For each variable, a layer was created in the GIS database environment. GIS-layers were classified, considering the risk of potentially generating forest-fire of the relevant variables. In addition, to generate risk maps, the weights used in these GIS-layers were obtained by applying the AHP technique. One of the major results of the study shows that the rates of “extreme”, “very high”, “high”, and “moderate” risk areas are 3.87%, 63.46%, 32.13% and 0.53%, respectively. Another important result is that there are not observed the so called “no risk" and "low risk" classes in the region. The results let us to make a conclusion that the natural and human factors having significant contributions the region to be fire-prone. Yet, these results also indicate that rather than emphasizing forest-fire preparedness and mitigation, policy-makers manage forest-fires through reactive, crisis-oriented approaches. In contrast to crisis-based management plans, this study suggests that risk-based preventive plans should be developed and implemented.

scholarly journals Development of a national index for the purpose of forest fire risk assessments on the example of southern Serbia

2019 ◽  
Vol 23 (6 Part A) ◽  
pp. 3307-3316 ◽  
Author(s):  
Tatjana Ratknic ◽  
Mihailo Ratknic ◽  
Nikola Rakonjac ◽  
Ivana Zivanovic ◽  
Zoran Poduska
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Fire Risk ◽  
Risk Assessments ◽  
Fire Weather ◽  
Moderate Correlation ◽  
Weather Index ◽  
Fire Weather Index ◽  
Forest Fire Risk ◽  
Future Concepts

The paper presents the results on the study of the possible application of the Canadian Forest Fire Weather Index and the Modified Angstrom Index in forest fire risk assessments. The daily values of these indices for the period 2005-2015 were related to the forest fire database. It was found that there is a relatively weak to moderate correlation between forest fires and the values of the Canadian Forest Fire Weather Index. In order to improve the wildfire risk assessments (including forest fires), the index was modified. The modified index has a significantly greater correlation with the actual events of forest fires and consequently a much wider application in southern Serbia. The modified index can be of great importance in the future concepts of forest fire risk management.

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