scholarly journals Impacts of changing fire weather conditions on reconstructed trends in U.S. wildland fire activity from 1979 to 2014

2016 ◽  
Vol 121 (11) ◽  
pp. 2856-2876 ◽  
Author(s):  
Patrick H. Freeborn ◽  
W. Matt Jolly ◽  
Mark A. Cochrane
2014 ◽  
Vol 23 (8) ◽  
pp. 1147 ◽  
Author(s):  
Colin C. Simpson ◽  
H. Grant Pearce ◽  
Andrew P. Sturman ◽  
Peyman Zawar-Reza

The Weather Research and Forecasting mesoscale atmospheric model was used to investigate fire weather conditions during the 2009–10 New Zealand wildland fire season. The analysis considered New Zealand's version of the Fire Weather Index used in the Canadian Forest Fire Danger Rating System, the Haines Index (HI) and the Continuous Haines Index (CHI). This represents the first investigation in New Zealand of the HI and CHI, which rate the potential for extreme fire behaviour or large fire growth based on the lower tropospheric atmospheric stability and humidity. The wildland fire activity during the 2009–10 fire season was typical of New Zealand, and there was considerable spatial and temporal variability in the fire weather conditions. The most frequent severe fire weather conditions as quantified by the fire weather indices occurred to the east of the dividing mountain ranges in both the North Island and South Island, and were associated with the hot, dry and windy north-westerly foehn winds that commonly affect New Zealand. The 36 wildland fires greater in area than 5 ha during the 2009–10 fire season occurred under a range of fire weather conditions, and no correlation was found between the wildland fire size and each individual weather variable.


1991 ◽  
Vol 1 (2) ◽  
pp. 97 ◽  
Author(s):  
R Mees

Under severe fire weather conditions arson is believed to be the primary cause of large wildland fires in southern California. Wildland fire suppression personnel and the public use the the expression "This weather brings out the arsonists" to indicate their awareness of the high potential for large arson-caused fires under these conditions. To determine the accuracy of this statement, fire occurrence and weather data were analyzed for four southern California National Forests for a 10-year period (1975–1984). The results showed that the proportion of arson and non-arson person-caused fires remained the same under most fire-danger conditions; however, a much higher percentage of arson fires became large fires when fire danger was severe. Furthermore, the timing of the arsonist contributed to the frequent occurrence of large arson fires. The data presented here refute the idea that most arson fires occur under severe weather conditions and at the same time-validate the utility of maintaining arson prevention programs during most weather conditions.


Atmosphere ◽  
2018 ◽  
Vol 9 (7) ◽  
pp. 279 ◽  
Author(s):  
Alan Srock ◽  
Joseph Charney ◽  
Brian Potter ◽  
Scott Goodrick

Fire weather indices are commonly used by fire weather forecasters to predict when weather conditions will make a wildland fire difficult to manage. Complex interactions at multiple scales between fire, fuels, topography, and weather make these predictions extremely difficult. We define a new fire weather index called the Hot-Dry-Windy Index (HDW). HDW uses the basic science of how the atmosphere can affect a fire to define the meteorological variables that can be predicted at synoptic-and meso-alpha-scales that govern the potential for the atmosphere to affect a fire. The new index is formulated to account for meteorological conditions both at the Earth’s surface and in a 500-m layer just above the surface. HDW is defined and then compared with the Haines Index (HI) for four historical fires. The Climate Forecast System Reanalysis (CFSR) is used to provide the meteorological data for calculating the indices. Our results indicate that HDW can identify days on which synoptic-and meso-alpha-scale weather processes can contribute to especially dangerous fire behavior. HDW is shown to perform better than the HI for each of the four historical fires. Additionally, since HDW is based on the meteorological variables that govern the potential for the atmosphere to affect a fire, it is possible to speculate on why HDW would be more or less effective based on the conditions that prevail in a given fire case. The HI, in contrast, does not have a physical basis, which makes speculation on why it works or does not work difficult because the mechanisms are not clear.


2020 ◽  
Author(s):  
Mark Parrington ◽  
Francesca Di Giuseppe ◽  
Thomas Smith ◽  
Claudia Vitolo ◽  
Sebastien Garrigues ◽  
...  

<p>Effective monitoring of global wildfire activity requires comprehensive knowledge of changing environmental (including atmospheric and hydrological) conditions, fuel availability and routine observations of fire locations and intensity. The European Centre for Medium-Range Weather Forecasts (ECMWF) through its operation of, and contribution to, different Copernicus Services is in a unique position to provide detailed information on the conditions leading to wildland fire activity, the evolution of wildfires, and their potential impacts, when they occur. Fire weather forecasts from the Copernicus Emergency Management Service, and surface climate anomalies from the Copernicus Climate Change Service both provide context to the environmental conditions required for wildfires to persist. Analyses based on observations of fire radiative power, along with analyses and forecasts of associated atmospheric pollutants, from the Copernicus Atmosphere Monitoring Service aid in quantifying the scale and intensity in near-real-time and the subsequent atmospheric impacts. During 2019, regions of anomalously hot and dry surface conditions in Arctic Siberia and southeast Australia experienced large-scale, long-duration wildfires which burned thousands of square kilometres with a total intensity that was significantly above the average of the previous 16 years of data in those regions. We present an overview of the evolution of fire activity in Siberia between June-August 2019, and Australia between September 2019-January 2020, based on ECMWF/Copernicus data for fire weather, climate anomalies and active fires. We will show that the different datasets, while being relatively independent, show a strong correspondence and provide a wealth of information vital to understanding global wildfires, their underlying causes and environmental impacts.</p>


2014 ◽  
Vol 2 (7) ◽  
pp. 4711-4742 ◽  
Author(s):  
T. Chu ◽  
X. Guo

Abstract. Wildfire is the dominant natural disturbance in Eurasian boreal region, which acts as a major driver of the global carbon cycle. An effectiveness of wildfire management requires suitable tools for fire prevention and fire risk assessment. This study aims to investigate fire occurrence patterns in relation to fire weather conditions in the remote south central Siberia region. The Canadian Fire Weather Index derived from large-scale meteorological reanalysis data was evaluated with respects to fire regimes during 14 consecutive fire seasons in south central Siberian environment. All the fire weather codes and indices, including the Fine Fuel Moisture Code (FFMC), the Duff Moisture Code (DMC), the Drought Code (DC), the Buildup Index (BUI), the Initial Spread Index (ISI), and the Fire Weather Index (FWI), were highly reflected inter-annual variation of fire activity in south central Siberia. Even though human-caused fires were major events in Russian boreal forest including south central Siberia, extreme fire years were strongly correlated with ambient weather conditions (e.g. Arctic Oscillation, air temperature, relative humidity and wind), showing by in-phase (or positive linear relationship) and significant wavelet coherence between fire activity and DMC, ISI, BUI, and FWI. Time series observation of 14 fire seasons showed that there was an average of about 3 months lags between the peaks of fire weather conditions and fire activity, which should take into account when using coarse scale fire weather indices in the assessment of fire danger in the study area. The results are expected to contribute to a better reconstruction and prediction of fire activity using large-scale reanalysis data in remote regions in which station data are very few.


2022 ◽  
Author(s):  
Nicholas Wilson ◽  
Ross A. Bradstock ◽  
Michael Bedward

2021 ◽  
Author(s):  
Jiaying He ◽  
Tatiana Loboda ◽  
Nancy French ◽  
Dong Chen

<p>Tundra fires are common across the pan-Arctic region, particularly in Alaska. Fires lead to significant impacts on terrestrial carbon balance and ecosystem functioning in the tundra. They can even affect the forage availability of herbivorous wildlife and living resources of local human communities. Also, interactions between fire and climate change can enhance the fire impacts on the Arctic ecosystems. However, the drivers and mechanisms of wildland fire occurrences in Alaskan tundra are still poorly understood. Research on modeling contemporary fire probability in the tundra is also lacking. This study focuses on exploring the critical environmental factors controlling wildfire occurrences in Alaskan tundra and modeled the fire ignition probability, accounting for ignition source, fuel types, fire weather conditions, and topography. The fractional cover maps of fuel type components developed Chapter 2 serve as input data for fuel type distribution. The probability of cloud-to-ground (CG) lightning and fire weather conditions are simulated using WRF. Topographic features are also calculated from the Digital Elevation Model (DEM) data. Additionally, fire ignition locations are extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) active fire product for Alaskan tundra from 2001 to 2019. Empirical modeling methods, including RF and logistic regression, are then utilized to model the relationships between environmental factors and wildfire occurrences in the tundra and to evaluate the roles of these factors. Our results suggested that CG lightning is the primary driver controlling fire ignitions in the tundra, while warmer and drier weather conditions also support fires. We also projected future potential of wildland fires in this tundra region with Coupled Model Intercomparison Projects Phase 6 (CMIP6) data. The results of this study highlight the important role of CG lightning in driving tundra fires and that incorporating CG lightning modeling is necessary and essential for fire monitoring and management efforts in the High Northern Latitudes (HNL).</p>


2020 ◽  
Vol 12 (19) ◽  
pp. 3204
Author(s):  
Hiroshi Hayasaka ◽  
Galina V. Sokolova ◽  
Andrey Ostroukhov ◽  
Daisuke Naito

Most wildland fires in boreal forests occur during summer, but major fires in the lower Amur River Basin of the southern Khabarovsk Krai (SKK) mainly occur in spring. To reduce active fires in the SKK, we carried out daily analysis of MODIS (Moderate Resolution Imaging Spectroradiometer) hotspot (HS) data and various weather charts. HS data of 17 years from 2003 were used to identify the average seasonal fire occurrence. Active fire-periods were extracted by considering the number of daily HSs and their continuity. Weather charts, temperature maps, and wind maps during the top 12 active fire-periods were examined to clarify each fire weather condition. Analysis results showed that there were four active fire-periods that occurred in April, May, July, and October. Weather charts during the top active fire-periods showed active fires in April and October occurred under strong wind conditions (these wind velocities were over 30 km h−1) related to low-pressure systems. The very active summer fire at the end of June 2012 occurred related to warm air mass advection promoted by large westerly meandering. We showed clear fire weather conditions in the SKK from March to October. If a proper fire weather forecast is developed based on our results, more efficient and timely firefighting can be carried out.


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