Warm Arctic-Cold Eurasia pattern helps predict spring wildfire burned area in West Siberia

Area of Science:

• Climatology
• Fire Science
• Ecology

Background:

• Extreme wildfires pose significant threats, impacting climate through carbon emissions.
• Predicting wildfire occurrence and intensity is a critical environmental challenge.

Purpose of the Study:

• To investigate the link between the winter "warm Arctic-cold Eurasia" (WACE) pattern and spring wildfire activity in West Siberia.
• To develop a predictive model for spring burned area and associated carbon emissions.

Main Methods:

• Utilized a multiple linear regression model.
• Analyzed the correlation between the WACE pattern, snow cover, and subsequent spring fire risk.
• Validated the model with independent data for 2019 and 2020.

Main Results:

• The WACE pattern significantly increases spring burned area in West Siberia.
• Reduced snow cover associated with WACE leads to drier conditions and heightened fire risk.
• The predictive model achieved a high R-squared value (0.64) and low prediction error (3.0% MAPE).

Conclusions:

• The WACE pattern serves as a reliable predictor for spring wildfire extent and carbon emissions in West Siberia.
• This research offers a method for seasonal wildfire forecasting and mitigating extreme fire impacts.
• Findings contribute to improved understanding of climate-driven wildfire dynamics.