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Understanding how weather and climate influence fire risk is important for many purposes, including climate adaptation planning and decision-making in sectors such as emergency management, finance, health and infrastructure (e.g., for…

Atmospheric and Oceanic Physics · Physics 2026-03-27 Soubhik Biswas , Andrew Dowdy , Savin Chand

Large wildfires pose a major environmental concern, and precise maps of fire risk can improve disaster relief planning. Fosberg Fire Weather Index (FFWI) is often used to measure wildfire risk; FFWI exhibits non-Gaussian marginal…

Methodology · Statistics 2020-11-17 Arnab Hazra , Brian J. Reich , Benjamin A. Shaby , Ana-Maria Staicu

Wildfires are frequent, devastating events in Australia that regularly cause significant loss of life and widespread property damage. Fire weather indices are a widely-adopted method for measuring fire danger and they play a significant…

Computers and Society · Computer Science 2014-11-11 Lianli Gao , Michael Bruenig , Jane Hunter

In recent decades, the intensification of wildfire activity in western Canada has resulted in substantial socio-economic and environmental losses. Accurate wildfire risk prediction is hindered by the intrinsic stochasticity of ignition and…

Investigating the health impacts of wildfire smoke requires data on people's exposure to fine particulate matter (PM$_{2.5}$) across space and time. In recent years, it has become common to use machine learning models to fill gaps in…

The Burning Index (BI) produced daily by the United States government's National Fire Danger Rating System is commonly used in forecasting the hazard of wildfire activity in the United States. However, recent evaluations have shown the BI…

Applications · Statistics 2011-08-04 Haiyong Xu , Frederic Paik Schoenberg

A growing body of literature has focused on predicting wildfire occurrence using machine learning methods, capitalizing on high-resolution data and fire predictors that canonical process-based frameworks largely ignore. Standard evaluation…

Machine Learning · Computer Science 2026-03-27 Shahbaz Alvi , Italo Epicoco , Jose Maria Costa Saura

We theoretically study long-term trends in the statistics of record-breaking daily temperatures and validate these predictions using Monte Carlo simulations and data from the city of Philadelphia, for which 126 years of daily temperature…

Data Analysis, Statistics and Probability · Physics 2007-05-23 S. Redner , Mark R. Petersen

The Global Historical Climatology Network-Daily database contains, among other variables, daily maximum and minimum temperatures from weather stations around the globe. It is long known that climatological summary statistics based on daily…

Applications · Statistics 2018-05-30 Maxime Rischard , Natesh Pillai , Karen A. McKinnon

Urban overheating, exacerbated by climate change, threatens public health and urban sustainability. Traditional approaches, such as numerical simulations and field measurements, face challenges due to uncertainties in input data. This study…

Applications · Statistics 2025-02-27 Jiwei Zou , Lin Wang , Senwen Yang , Michael Lacasse , Liangzhu , Wang

With increased frequency and intensity due to climate change, wildfires have become a growing global concern. This creates severe challenges for fire and emergency services as well as communities in the wildland-urban interface (WUI). To…

Computers and Society · Computer Science 2021-09-17 Xilei Zhao , Yiming Xu , Ruggiero Lovreglio , Erica Kuligowski , Daniel Nilsson , Thomas Cova , Alex Wu , Xiang Yan

Increasing wildfire occurrence has spurred growing interest in wildfire spread prediction. However, even the most complex wildfire models diverge from observed progression during multi-day simulations, motivating need for data assimilation.…

Extreme heat is the deadliest weather-related hazard in the United States. Furthermore, it is increasing in intensity, frequency, and duration, making skillful forecasts vital to protecting life and property. Traditional numerical weather…

Atmospheric and Oceanic Physics · Physics 2025-05-01 Kelsey E. Ennis , Elizabeth A. Barnes , Marybeth C. Arcodia , Martin A. Fernandez , Eric D. Maloney

Carbon offset programs are critical in the fight against climate change. One emerging threat to the long-term stability and viability of forest carbon offset projects is wildfires, which can release large amounts of carbon and limit the…

Machine Learning · Computer Science 2023-05-05 Tristan Ballard , Matthew Cooper , Chris Lowrie , Gopal Erinjippurath

The policy environment of countries changes rapidly, influencing macro-level indicators such as the Energy Security Index. However, this index is only reported annually, limiting its responsiveness to short-term fluctuations. To address…

Machine Learning · Computer Science 2025-11-11 Mahdi Goldani

Climate change is commonly associated with an overall increase in mean temperature in a defined past time period. Many studies consider temperature trends at the global scale, but the literature is lacking in in-depth analysis of the…

Applications · Statistics 2022-10-12 Qibin Duan , Clare A. McGrory , Glenn Brown , Kerrie Mengersen , You-Gan Wang

A nonanticipative analog method is used for the long-term forecast of air temperature extremes. The data to be used for prediction include average daily air temperature, mean visibility, mean wind speed, mean dew point, maximum and minimum…

Applications · Statistics 2015-07-14 Dmytro Zubov , Humberto A. Barbosa , Gregory S. Duane

Due to climate change and the disruption of ecosystems worldwide, wildfires are increasingly impacting environment, infrastructure, and human lives globally. Additionally, an exacerbating climate crisis means that these losses would…

Machine Learning · Computer Science 2025-09-16 Rohan Tan Bhowmik , Youn Soo Jung , Juan Aguilera , Mary Prunicki , Kari Nadeau

Heat waves are projected to increase in frequency and severity with global warming. Improved warning systems would help reduce the associated loss of lives, wildfires, power disruptions, and reduction in crop yields. In this work, we…

Atmospheric and Oceanic Physics · Physics 2023-01-13 Ignacio Lopez-Gomez , Amy McGovern , Shreya Agrawal , Jason Hickey

Wildfire is an important system process of the earth that occurs across a wide range of spatial and temporal scales. A variety of methods have been used to predict wildfire phenomena during the past century to better our understanding of…

Applications · Statistics 2013-12-24 S. W. Taylor , Douglas G. Woolford , C. B. Dean , David L. Martell
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