Impacts of Arctic and tropical climate variability on spring wildfires in West Siberia and the predictive role

Extreme wildfires have devastating impacts on multiple fronts, and associated carbon greatly heat earth climate. The important meteorological conditions for the wildfires include high temperatures and drought. The climate state in the semi-arid regions further provide a favorable background condition. The southern part of the West Siberia is a crucial semi-arid area, yet the research on the climate driving mechanisms of wildfires in this region is still limited. West Siberia faces severe wildfire risks and carbon emissions in the future. Therefore, how to effectively predict wildfires in this region also become a critical problem.

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 a dry and exposed-vegetation West Siberia in spring. The January stratospheric variability over mid-high latitude Eurasia also can modulate the tropospheric atmospheric circulation anomalies through downward propagation of signals, causing the reduced winter snow and increasing the spring wildfire risk. Apart from the influence of the Arctic, the tropical sea-air interaction is also of great significance. The March Maritime Continent SST anomaly can cause an earlier retreat of the spring snowline through a Rossby wave, and leads to vegetation exposure and surface drying, which favors wildfire occurrence.

These three factors provide the prediction information for the spring wildfire burned area in West Siberia. A multiple linear regression model is constructed to successfully predict the spring burned area in West Siberia (R=0.90), evaluating by “leave-one-out” cross validation. The same predictors also well predict the corresponding fire carbon emissions (R=0.73). Findings of this study provide a possibility for guarding human against extreme wildfires and foreknowing sharp rises in carbon emissions.