Abstract
Extreme wildfires have devastating impacts on multiple fronts, and associated carbon greatly heats the earth's climate. Whether and how to predict wildfires becomes a critical question. In this study, we find that the preceding-winter "warm Arctic-cold Eurasia" (WACE) pattern significantly enlarges the spring burned area in West Siberia. The winter WACE and accompanying snow reduction result in dryness and vegetation exposure in West Siberia in spring, increasing fire risks. A multiple linear regression model is constructed that successfully predicts the spring burned area in West Siberia one season in advance (R-squared coefficient=0.64). The same predictors also well predict the corresponding fire carbon emissions. Independent predictions for spring burned area in 2019 and 2020 are very close to observations, with a mean absolute percentage error of only 3.0%. The findings of this study provide a possibility for guarding humans against extreme wildfires and predicting sharp rises in carbon emissions.