Next Article in Journal
On the Development and Optimization of an Urban Design Comfort Model (UDCM) on a Passive Solar Basis at Mid-Latitude Sites
Next Article in Special Issue
Statistical Analysis of Recent and Future Rainfall and Temperature Variability in the Mono River Watershed (Benin, Togo)
Previous Article in Journal
Analysis of the Impact of Values and Perception on Climate Change Skepticism and Its Implication for Public Policy
Previous Article in Special Issue
Objective Definition of Climatologically Homogeneous Areas in the Southern Balkans Based on the ERA5 Data Set
Article Menu
Issue 4 (December) cover image

Export Article

Open AccessArticle
Climate 2018, 6(4), 100; https://doi.org/10.3390/cli6040100

Multi-Model Forecasts of Very-Large Fire Occurences during the End of the 21st Century

1
College of the Environment Special Programs, Quantitative Ecology & Resource Management (QERM), University of Washington, Seattle, WA 98195, USA
2
Pacific Wildland Fire Sciences Laboratory, U.S. Forest Service, 400 N. 34th St #201, Seattle, WA 98103, USA
3
Department of Statistics and School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98195, USA
4
Daniel J. Evans School of Public Policy and Governance, University of Washington, Seattle, WA 98195, USA
5
Pacific Wildland Fire Sciences Laboratory, School of Environmental and Forest Sciences, University of Washington, Seattle, WA 98195, USA
*
Author to whom correspondence should be addressed.
Received: 9 November 2018 / Revised: 12 December 2018 / Accepted: 13 December 2018 / Published: 19 December 2018
(This article belongs to the Special Issue Climate Variability and Change in the 21th Century)
Full-Text   |   PDF [3221 KB, uploaded 19 December 2018]   |  

Abstract

Climate change is anticipated to influence future wildfire activity in complicated, and potentially unexpected ways. Specifically, the probability distribution of wildfire size may change so that incidents that were historically rare become more frequent. Given that fires in the upper tails of the size distribution are associated with serious economic, public health, and environmental impacts, it is important for decision-makers to plan for these anticipated changes. However, at least two kinds of structural uncertainties hinder reliable estimation of these quantities—those associated with the future climate and those associated with the impacts. In this paper, we incorporate these structural uncertainties into projections of very-large fire (VLF)—those in the upper 95th percentile of the regional size distribution—frequencies in the Continental United States during the last half of the 21st century by using Bayesian model averaging. Under both moderate and high carbon emission scenarios, large increases in VLF frequency are predicted, with larger increases typically observed under the highest carbon emission scenarios. We also report other changes to future wildfire characteristics such as large fire frequency, seasonality, and the conditional likelihood of very-large fire events. View Full-Text
Keywords: mega-fires; Bayesian-model averaging; model uncertainty; climate-fire models mega-fires; Bayesian-model averaging; model uncertainty; climate-fire models
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Supplementary material

SciFeed

Share & Cite This Article

MDPI and ACS Style

Podschwit, H.R.; Larkin, N.K.; Steel, E.A.; Cullen, A.; Alvarado, E. Multi-Model Forecasts of Very-Large Fire Occurences during the End of the 21st Century. Climate 2018, 6, 100.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Climate EISSN 2225-1154 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top