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Atmosphere
Special Issues
Wildfire Spread and Weather: Theory, Models and Reality
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Wildfire Spread and Weather: Theory, Models and Reality

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: closed (30 November 2020) | Viewed by 15849

Special Issue Editor

Dr. Theodore M. Giannaros

E-Mail Website
Guest Editor
National Observatory of Athens, Institute for Environmental Research and Sustainable Development, 15236 Athens, Greece
Interests: fire spread modeling; fire–atmosphere interactions; fire weather; pyro-meteorology

Special Issue Information

Dear Colleagues,

Wildfires are a high-impact societal problem, posing a major threat to life and property, damaging natural resources, and inducing adverse primary and secondary environmental effects. Contributing to the increasing concern about wildfires is the increase in both their frequency and spatial extent, attributed to climate change and other anthropogenic factors, such as the expansion of the wildland–urban interface. However, although a warmer climate may set the stage for more frequent and larger wildfires, each wildfire ultimately responds to the nexus of terrain, fuels, and weather. While terrain is a constant and fuels are typically seasonally cured, variable meteorological conditions can have a profound impact on the spread of wildfires. In addition, wildfires also generate their own circulations, which subsequently feed back to external weather forces. Understanding the influence of weather on wildfire spread and the two-way coupling between the two is essential for effective wildfire management, in particular for promoting safe and effective prevention and suppression activities. In this Special Issue, we encourage the submission of studies covering all aspects of wildfire spread research that are related to the influence of weather, including studies on fire–atmosphere interactions.

Dr. Theodore M. Giannaros
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • fire spread
  • fire behavior
  • weather
  • fire–atmosphere interactions
  • fire weather

Published Papers (4 papers)

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Research

14 pages, 6325 KiB  
Article
Rare and Extreme Wildland Fire in Sakha in 2021
by Hiroshi Hayasaka
Atmosphere 2021, 12(12), 1572; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12121572 - 27 Nov 2021
Cited by 16 | Viewed by 1590
Abstract
A large-scale wildland fire occurred in Sakha in 2021. The results of fire analysis showed that the total number of hotspots in 2021 exceeded 267,000. This is about 5.8 times the average number of fires over the last 19 years since 2002. The [...] Read more.
A large-scale wildland fire occurred in Sakha in 2021. The results of fire analysis showed that the total number of hotspots in 2021 exceeded 267,000. This is about 5.8 times the average number of fires over the last 19 years since 2002. The largest daily number of hotspots in 2021 was 16,226, detected on 2 August. On 7 August, about half of the daily hotspots (52.6% = 8175/15,537 × 100) were detected in a highest fire density area (HFA, 62.5–65° N, 125–130° E) near Yakutsk under strong southeasterly wind (wind velocity about 12 m/s (43 km/h)). The results of weather analysis using various weather maps are as follows: The large meandering westerlies due to stagnant low-pressure systems in the Barents Sea brought high-pressure systems and warm air masses from the south to high latitudes, creating warm, dry conditions that are favorable conditions for fire. In addition to these, strong southeasterly winds at lower air levels blew which were related to the development of high-pressure systems in the Arctic Ocean. The HFA was located in the strong wind region (>8 m/s) of the v-wind map. The record-breaking Sakha fire season of 2021 is an example of extreme phenomena wrought by rapid climate change. Full article
(This article belongs to the Special Issue Wildfire Spread and Weather: Theory, Models and Reality)
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19 pages, 6086 KiB  
Article
Data-Driven Wildfire Risk Prediction in Northern California
by Ashima Malik, Megha Rajam Rao, Nandini Puppala, Prathusha Koouri, Venkata Anil Kumar Thota, Qiao Liu, Sen Chiao and Jerry Gao
Atmosphere 2021, 12(1), 109; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12010109 - 13 Jan 2021
Cited by 28 | Viewed by 7112
Abstract
Over the years, rampant wildfires have plagued the state of California, creating economic and environmental loss. In 2018, wildfires cost nearly 800 million dollars in economic loss and claimed more than 100 lives in California. Over 1.6 million acres of land has burned [...] Read more.
Over the years, rampant wildfires have plagued the state of California, creating economic and environmental loss. In 2018, wildfires cost nearly 800 million dollars in economic loss and claimed more than 100 lives in California. Over 1.6 million acres of land has burned and caused large sums of environmental damage. Although, recently, researchers have introduced machine learning models and algorithms in predicting the wildfire risks, these results focused on special perspectives and were restricted to a limited number of data parameters. In this paper, we have proposed two data-driven machine learning approaches based on random forest models to predict the wildfire risk at areas near Monticello and Winters, California. This study demonstrated how the models were developed and applied with comprehensive data parameters such as powerlines, terrain, and vegetation in different perspectives that improved the spatial and temporal accuracy in predicting the risk of wildfire including fire ignition. The combined model uses the spatial and the temporal parameters as a single combined dataset to train and predict the fire risk, whereas the ensemble model was fed separate parameters that were later stacked to work as a single model. Our experiment shows that the combined model produced better results compared to the ensemble of random forest models on separate spatial data in terms of accuracy. The models were validated with Receiver Operating Characteristic (ROC) curves, learning curves, and evaluation metrics such as: accuracy, confusion matrices, and classification report. The study results showed and achieved cutting-edge accuracy of 92% in predicting the wildfire risks, including ignition by utilizing the regional spatial and temporal data along with standard data parameters in Northern California. Full article
(This article belongs to the Special Issue Wildfire Spread and Weather: Theory, Models and Reality)
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11 pages, 4870 KiB  
Article
Drought-Modulated Boreal Forest Fire Occurrence and Linkage with La Nina Events in Altai Mountains, Northwest China
by Chunming Shi, Ying Liang, Cong Gao, Qiuhua Wang and Lifu Shu
Atmosphere 2020, 11(9), 956; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos11090956 - 07 Sep 2020
Cited by 6 | Viewed by 2632
Abstract
Warming-induced drought stress and El Nino-associated summer precipitation failure are responsible for increased forest fire intensities of tropical and temperate forests in Asia and Australia. However, both effects are unclear for boreal forests, the largest biome and carbon stock over land. Here, we [...] Read more.
Warming-induced drought stress and El Nino-associated summer precipitation failure are responsible for increased forest fire intensities of tropical and temperate forests in Asia and Australia. However, both effects are unclear for boreal forests, the largest biome and carbon stock over land. Here, we combined fire frequency, burned area, and climate data in the Altai boreal forests, the southmost extension of Siberia’s boreal forest into China, and explored their link with El Nino–Southern Oscillation (ENSO). Surprisingly, both summer drought severity and fire occurrence showed significant (p < 0.05) correlation with La Nina events of the previous year and therefore provide an important reference for forest fire prediction and prevention in Altai. Despite a significant warming trend, the increased moisture over Altai has largely offset the effect of warming-induced drought stress and led to an insignificant fire frequency trend in the last decades, resulting in largely reduced burned area since the 1980s. The reduced burned area can also be attributed to fire suppression efforts and greatly increased investment in fire prevention since 1987. Full article
(This article belongs to the Special Issue Wildfire Spread and Weather: Theory, Models and Reality)
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18 pages, 8160 KiB  
Article
Wildfire Pyroconvection and CAPE: Buoyancy’s Drying and Atmospheric Intensification—Fort McMurray
by Atoossa Bakhshaii, Edward A. Johnson and Kiana Nayebi
Atmosphere 2020, 11(7), 763; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos11070763 - 18 Jul 2020
Cited by 3 | Viewed by 3586
Abstract
The accurate prediction of wildfire behavior and spread is possible only when fire and atmosphere simulations are coupled. In this work, we present a mechanism that causes a small fire to intensify by altering the atmosphere. These alterations are caused by fire-related fluxes [...] Read more.
The accurate prediction of wildfire behavior and spread is possible only when fire and atmosphere simulations are coupled. In this work, we present a mechanism that causes a small fire to intensify by altering the atmosphere. These alterations are caused by fire-related fluxes at the surface. The fire plume and fluxes increase the convective available potential energy (CAPE) and the chance of the development of a strong pyroconvection system. To study this possible mechanism, we used WRF-Fire to capture fire line propagation as the result of interactions between heat and moisture fluxes, pressure perturbations, wind shear development and dry air downdraft. The wind patterns and dynamics of the pyroconvection system are simulated for the Horse River wildfire at Fort McMurray, Canada. The results revealed that the updraft speed reached up to 12 m/s. The entrainment mixed the mid and upper-level dry air and lowered the atmospheric moisture. The mid-level and upper-level dew point temperature changed by 5–10 ∘ C in a short period of time. The buoyant air strengthened the ascent as soon as the nocturnal inversion was eliminated by daytime heating. The 887 J/kg total increase of CAPE in less than 5 h and the high bulk Richardson number (BRN) of 93 were indicators of the growing pyro-cumulus cell. The presented simulation has not improved the original model or supported leading-edge numerical weather prediction (NWP) achievements, except for adapting WRF-Fire for Canadian biomass fuel. However, we were able to present a great deal of improvements in wildfire nowcasting and short-term forecasting to save lives and costs associated with wildfires. The simulation is sufficiently fast and efficient to be considered for a real-time operational model. While the project was designed and succeeded as an NWP application, we are still searching for a solution for the intractable problems associated with political borders and the current liable authorities for the further development of a new generation of national atmosphere–wildfire forecasting systems. Full article
(This article belongs to the Special Issue Wildfire Spread and Weather: Theory, Models and Reality)
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