A Synoptic Climatology for Forest-Fires in the NE US and Future Implications From GCM Simulations

1994 ◽  
Vol 4 (4) ◽  
pp. 217 ◽  
Author(s):  
ES Takle ◽  
DJ Bramer ◽  
WE Heilman ◽  
MR Thompson
Keyword(s):  
West Virginia ◽  
Forest Fire ◽  
Surface Pressure ◽  
Forest Fires ◽  
Circulation Model ◽  
Synoptic Climatology ◽  
Global Circulation Model ◽  
Weather Patterns ◽  
Forest Fire Danger ◽  
Drying Conditions

We studied surface-pressure patterns corresponding to reduced precipitation, high evaporation potential, and enhanced forest-fire danger for West Virginia, which experienced extensive forest-fire damage in November 1987. From five years of daily weather maps we identified eight weather patterns that describe distinctive flow situations throughout the year. Map patterns labeled extended-high, back-of-high, and pre-high were the most frequently occurring patterns that accompany forest fires in West Virginia and the nearby four-stare region. Of these, back-of-high accounted for a disproportionately large amount of fire-related damage. Examination of evaporation acid precipitation data showed that these three patterns and high-to-the-south patterns ail led to drying conditions and all other patterns led to moistening conditions. Surface-pressure fields generated by the Canadian Climate Centre global circulation model for simulations of the present (1xCO2) climate and 2xCO2 climate were studied to determine whether forest-fire potential would change under increased atmospheric CO2. The analysis showed a tendency for increased frequency of drying in the NE US, but the results were not statistically significant.

scholarly journals Empirical Research on Climate Warming Risks for Forest Fires: A Case Study of Grade I Forest Fire Danger Zone, Sichuan Province, China

2021 ◽  
Vol 13 (14) ◽  
pp. 7773
Author(s):  
San Wang ◽  
Hongli Li ◽  
Shukui Niu
Keyword(s):  
Wind Speed ◽  
Forest Fire ◽  
Climate Warming ◽  
Forest Fires ◽  
Meteorological Factors ◽  
Sichuan Province ◽  
Danger Zone ◽  
Climatic Regions ◽  
Area Burned ◽  
Forest Fire Danger

The Sichuan province is a key area for forest and grassland fire prevention in China. Forest resources contribute significantly not only to the biological gene pool in the mid latitudes but also in reducing the concentration of greenhouse gases and slowing down global warming. To study and forecast forest fire change trends in a grade I forest fire danger zone in the Sichuan province under climate change, the dynamic impacts of meteorological factors on forest fires in different climatic regions were explored and a model between them was established by using an integral regression in this study. The results showed that the dominant factor behind the area burned was wind speed in three climatic regions, particularly in Ganzi and A’ba with plateau climates. In Ganzi and A’ba, precipitation was mainly responsible for controlling the number of forest fires while it was mainly affected by temperature in Panzhihua and Liangshan with semi-humid subtropical mountain climates. Moreover, the synergistic effect of temperature, precipitation and wind speed was responsible in basin mid-subtropical humid climates with Chengdu as the center and the influence of temperature was slightly higher. The differential forest fire response to meteorological factors was observed in different climatic regions but there was some regularity. The influence of monthly precipitation in the autumn on the area burned in each climatic region was more significant than in other seasons, which verified the hypothesis of a precipitation lag effect. Climate warming and the combined impact of warming effects may lead to more frequent and severe fires.

scholarly journals Temporal variations and change in forest fire danger in Europe for 1960–2012

2014 ◽  
Vol 14 (6) ◽  
pp. 1477-1490 ◽  
Author(s):  
A. Venäläinen ◽  
N. Korhonen ◽  
O. Hyvärinen ◽  
N. Koutsias ◽  
F. Xystrakis ◽  
...  
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
National Level ◽  
Temporal Variations ◽  
Fire Danger ◽  
Fire Season ◽  
Fire Weather ◽  
Fire Weather Index ◽  
Current Season ◽  
Forest Fire Danger

Abstract. Understanding how fire weather danger indices changed in the past and how such changes affected forest fire activity is important in a changing climate. We used the Canadian Fire Weather Index (FWI), calculated from two reanalysis data sets, ERA-40 and ERA Interim, to examine the temporal variation of forest fire danger in Europe in 1960–2012. Additionally, we used national forest fire statistics from Greece, Spain and Finland to examine the relationship between fire danger and fires. There is no obvious trend in fire danger for the time period covered by ERA-40 (1960–1999), whereas for the period 1980–2012 covered by ERA Interim, the mean FWI shows an increasing trend for southern and eastern Europe which is significant at the 99% confidence level. The cross correlations calculated at the national level in Greece, Spain and Finland between total area burned and mean FWI of the current season is of the order of 0.6, demonstrating the extent to which the current fire-season weather can explain forest fires. To summarize, fire risk is multifaceted, and while climate is a major determinant, other factors can contribute to it, either positively or negatively.

scholarly journals Long-term temporal changes in the occurrence of a high forest fire danger in Finland

2012 ◽  
Vol 12 (8) ◽  
pp. 2591-2601 ◽  
Author(s):  
H. M. Mäkelä ◽  
M. Laapas ◽  
A. Venäläinen
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Large Scale ◽  
Weather Conditions ◽  
Temporal Variations ◽  
Fire Danger ◽  
Specific Information ◽  
Climate Data ◽  
Forest Fire Danger

Abstract. Climate variation and change influence several ecosystem components including forest fires. To examine long-term temporal variations of forest fire danger, a fire danger day (FDD) model was developed. Using mean temperature and total precipitation of the Finnish wildfire season (June–August), the model describes the climatological preconditions of fire occurrence and gives the number of fire danger days during the same time period. The performance of the model varied between different regions in Finland being best in south and west. In the study period 1908–2011, the year-to-year variation of FDD was large and no significant increasing or decreasing tendencies could be found. Negative slopes of linear regression lines for FDD could be explained by the simultaneous, mostly not significant increases in precipitation. Years with the largest wildfires did not stand out from the FDD time series. This indicates that intra-seasonal variations of FDD enable occurrence of large-scale fires, despite the whole season's fire danger is on an average level. Based on available monthly climate data, it is possible to estimate the general fire conditions of a summer. However, more detailed input data about weather conditions, land use, prevailing forestry conventions and socio-economical factors would be needed to gain more specific information about a season's fire risk.

scholarly journals Introducing a New Remote Sensing-Based Model for Forecasting Forest Fire Danger Conditions at a Four-Day Scale

2019 ◽  
Vol 11 (18) ◽  
pp. 2101 ◽  
Author(s):  
M. Ahmed ◽  
Quazi Hassan ◽  
Masoud Abdollahi ◽  
Anil Gupta
Keyword(s):  
Remote Sensing ◽  
Forest Fire ◽  
Forest Fires ◽  
Land Surface ◽  
Vegetation Index ◽  
Significant Risk ◽  
Fire Danger ◽  
Area Of Interest ◽  
Forest Fire Danger ◽  
Very High

Forest fires are natural disasters that create a significant risk to the communities living in the vicinity of forested landscape. To minimize the risk of forest fires for the resilience of such urban communities and forested ecosystems, we proposed a new remote sensing-based medium-term (i.e., four-day) forest fire danger forecasting system (FFDFS) based on an existing framework, and applied the system over the forested regions in the northern Alberta, Canada. Hence, we first employed moderate resolution imaging spectroradiometer (MODIS)-derived daily land surface temperature (Ts) and surface reflectance products along with the annual land cover to generate three four-day composite for Ts, normalized difference vegetation index (NDVI), and normalized difference water index (NDWI) at 500 m spatial resolution for the next four days over the forest-dominant regions. Upon generating these four-day composites, we calculated the variable-specific mean values to determine variable-specific fire danger maps with two danger classes (i.e., high and low). Then, by assuming the cloud-contaminated pixels as the low fire danger areas, we combined these three danger maps to generate a four-day fire danger map with four danger classes (i.e., low, moderate, high, and very high) over our study area of interest, which was further enhanced by incorporation of a human-caused static fire danger map. Finally, the four-day scale fire danger maps were evaluated using observed/ground-based forest fire occurrences during the 2015–2017 fire seasons. The results revealed that our proposed system was able to detect about 75% of the fire events in the top two danger classes (i.e., high and very high). The system was also able to predict the 2016 Horse River wildfire, the worst fire event in Albertian and Canadian history, with about 67% agreement. The higher accuracy outputs from our proposed model indicated that it could be implemented in the operational management, which would be very useful for lessening the adverse impact of such fire events.

Classification of Territory on Forest Fire Danger Level Using GIS and Remote Sensing

2020 ◽  
pp. 258-267 ◽  
Author(s):  
Elena Petrovna Yankovich ◽  
Ksenia S. Yankovich
Keyword(s):  
Remote Sensing ◽  
Forest Fire ◽  
Forest Fires ◽  
Vegetation Cover ◽  
Remote Sensing Data ◽  
Fire Danger ◽  
Gis And Remote Sensing ◽  
Forest Fuels ◽  
Forest Fire Danger

The vegetation cover is the most important factor in forest fires, because it reflects the presence of forest fuels. The study of the variability of the vegetation cover, as well as observation of its condition, allows estimating the level of fire danger of the forest quarter. The work presents a geo-information system containing a set of tools to determine the level of fire danger of the forest quarter. The system is able to predict (determine the probability) and classify forest quarters according to the level of fire danger. The assessment of forest fire danger of Tomsk forestry of Tomsk region has been carried out. Fire probability maps of forest quarters were created based on remote sensing data and ArcGIS software.

scholarly journals Deterministic-Probabilistic Approach to Predict Lightning-Caused Forest Fires in Mounting Areas

Forecasting ◽  
2021 ◽  
Vol 3 (4) ◽  
pp. 695-715
Author(s):  
Nikolay Baranovskiy
Keyword(s):  
Mathematical Models ◽  
Forest Fire ◽  
Forest Fires ◽  
Lightning Discharge ◽  
Probabilistic Approach ◽  
Lightning Activity ◽  
Cloud To Ground Lightning ◽  
The Republic ◽  
Forest Fire Danger ◽  
Probabilistic Criteria

Forest fires from lightnings create a tense situation in various regions of states with forested areas. It is noted that in mountainous areas this is especially important in view of the geophysical processes of lightning activity. The aim of the study is to develop a deterministic-probabilistic approach to predicting forest fire danger due to lightning activity in mountainous regions. To develop a mathematical model, the main provisions of the theory of probability and mathematical statistics, as well as the general theory of heat transfer, were used. The scientific novelty of the research is due to the complex use of probabilistic criteria and deterministic mathematical models of tree ignition by a cloud-to-ground lightning discharge. The paper presents probabilistic criteria for predicting forest fire danger, taking into account the lightning activity, meteorological data, and forest growth conditions, as well as deterministic mathematical models of ignition of deciduous and coniferous trees by electric current of a cloud-to-ground lightning discharge. The work uses synthetic data on the discharge parameters and characteristics of the forest-covered area, which correspond to the forest fire situation in the Republic of Altay and the Republic of Buryatia (Russian Federation). The dependences of the probability for occurrence of forest fires on various parameters have been obtained.

scholarly journals WWLLN Data Cluster Analysis Methods for Lightning-Caused Forest Fires Monitoring

2016 ◽  
Vol 6 (6) ◽  
pp. 3112
Author(s):  
Baranovskiy Nikolay ◽  
Krechetova Svetlana ◽  
Belikova Marina ◽  
Perelygin Anton
Keyword(s):  
Cluster Analysis ◽  
Forest Fire ◽  
Forest Fires ◽  
Research Area ◽  
Fire Danger ◽  
Storm Activity ◽  
Lightning Discharges ◽  
Current Article ◽  
Forest Fire Danger ◽  
New Generation

<p>Storm activity is the main reason for forest fires to occur in remote forested territories. The current article presents the results for cluster analysis of WWLLN data on lightning discharges. It provides the description for clusterization algorithms of lightning discharges over the controlled territory. Research area is Timiryazevskiy forestry of the Tomsk region (Siberia, Russia). We analyzed the applicability of cluster analysis results for monitoring of the forest fire danger caused by storm activity. As a result of the conducted research, we established that the following characteristics of storm activity can be included in deterministic-probabilistic criterion to assess the forest fire danger. The article gives the recommendations how to create new generation information-computer and geoinformation systems for monitoring of the forest fire danger caused by storm activity in the controlled forested territory.</p>

Future fire in Canada's boreal forest: paleoecology results and general circulation model - regional climate model simulations

2001 ◽  
Vol 31 (5) ◽  
pp. 854-864 ◽  
Author(s):  
Mike Flannigan ◽  
Ian Campbell ◽  
Mike Wotton ◽  
Christopher Carcaillet ◽  
Pierre Richard ◽  
...  
Keyword(s):  
Boreal Forest ◽  
General Circulation Model ◽  
Forest Fire ◽  
Forest Fires ◽  
General Circulation ◽  
Climate Model ◽  
Circulation Model ◽  
Regional Variability ◽  
Fire Weather Index ◽  
Model Simulations

General circulation model simulations suggest the Earth's climate will be 1–3.5°C warmer by AD 2100. This will influence disturbances such as forest fires, which are important to circumpolar boreal forest dynamics and, hence, the global carbon cycle. Many suggest climate warming will cause increased fire activity and area burned. Here, we use the Canadian Forest Fire Weather Index to simulate future forest fire danger, showing the expected increase in most of Canada but with significant regional variability including a decrease in much of eastern Canada. These results are in general agreement with paleoecological data and general circulation model results from the 6000 calendar years BP interval, which was a time of a warmer climate that may be an analogue for a future climate.

Predicting Forest Fire Numbers Using Deterministic-Probabilistic Approach

2020 ◽  
pp. 89-100
Author(s):  
Nikolay Viktorovich Baranovskiy
Keyword(s):  
Global Warming ◽  
Forest Fire ◽  
Forest Fires ◽  
Probabilistic Method ◽  
Probabilistic Approach ◽  
Retrospective Data ◽  
Surface Fires ◽  
Crown Fires ◽  
Vegetation Fires ◽  
Forest Fire Danger

The annual task of forecasting forest fire danger is becoming increasingly relevant, especially in the context of global warming. The forecast of surface fires is most important, as more than 80% of all vegetation fires are surface fires. Practically all crown fires develop from surface fires. This chapter discusses the deterministic-probabilistic method for predicting the number of forest fires in a controlled forest area. This methodology is based on the assumption that the number of registered and projected forest fires is related to the probability of their occurrence. The influence of forest fire retrospective data on the predicted number of forest fires for some sites of the Timiryazevskiy forestry of the Tomsk region was studied. This chapter presents the results of a comparative analysis of forecast data and statistics.

Forest fires in Russia: carbon dioxide emissions to the atmosphere

1993 ◽  
Vol 23 (4) ◽  
pp. 700-705 ◽  
Author(s):  
Robert K. Dixon ◽  
Olga N. Krankina
Keyword(s):  
Greenhouse Gases ◽  
General Circulation Model ◽  
Forest Fire ◽  
Forest Fires ◽  
General Circulation ◽  
Vegetation Change ◽  
Circulation Model ◽  
Fire Control ◽  
Fire Emissions ◽  
Biogenic Carbon

Boreal forests of Russia play a prominent role in the global carbon cycle and the flux of greenhouse gases to the atmosphere. Large areas of Russian forest burn annually, and contributions to the net flux of carbon to the atmosphere may be significant. Forest fire emissions were calculated for the years 1971–1991 using fire frequency and distribution data and fuel and carbon density for different forest ecoregions of Russia. Both direct carbon release and indirect post-fire biogenic carbon flux were estimated. From 1971 to 1991 the annual total forest area burned by wildfire ranged from 1.41 × 106 to 10.0 × 106 ha. Approximately 15 000–25 000 forest fires occurred annually during this period. Mean annual direct CO2-C emissions from wildfire was approximately 0.05 Pg over this 21-year period. Total post-fire biogenic CO2-C emissions for 1971–1991 ranged from 2.5 to 5.9 Pg (0.12–0.28 Pg annually). Forest fires and other disturbances are expected to be a primary mechanism driving vegetation change associated with projected global climate change. Future forest fire scenarios in Russia based on general circulation model projections suggest that up to 30–50% of the land surface area, or 334 × 106 to 631 × 106 ha of forest, will be affected. An additional 6.7 × 106 to 12.6 × 106 ha of Russian boreal forest are projected to burn annually if general circulation model based vegetation-change scenarios are achieved within the next 50 years. The direct flux of CO2-C from future forest fires is estimated to total 6.1–10.7 Pg over a 50-year period. Indirect post-fire biogenic release of greenhouse gases in the future is expected to be two to six times greater than direct emissions. Forest management and fire-control activities may help reduce wildfire severity and mitigate the associated pulse of greenhouse gases into the atmosphere.

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