# Wildfires in the Siberian Arctic
## 2 Materials and Methods
### Determination of Fire Frequency and Extent  
We analyzed the temporal dynamics of wildfire parameters in the Siberian Arctic including fire frequency, the extent of burnt area, fire season onset, and duration, and the position of the northern boundary or limit of wildfire occurrence. Fire season onset and duration and limit of wildfire occurrence were calculated based on the annual mean of three observed maximum values for each variable. We correlated wildfire parameters to June-August and May-September mean air temperature (\(T_{jia}\) and \(T_{mjias}\)), precipitation (\(P_{jia}\) and \(P_{mjias}\)), drought index (\(SPEI_{jia}\) and \(SPEI_{mjias}\)), ground cover moisture content (\(W_{jia}\), \(W_{mjias}\)), and lightning strike index (\(LSI\)).  
The annual fire frequency was calculated from analysis of thermal points (\"hotspots\") with a spatial resolution of 1 \(\times\) 1 km obtained from the MODIS Collection 6 database package MCD14 DL of the Fire Information for Resource Management System (FIRMS). The area investigated included the latitudinal range of 65-80\({}^{\circ}\) N for the years 2001-2021, which included about 165,300 hotspots. We excluded false (non-fire) thermal points from the initial dataset (ca. 240,000) by the following procedures. (1) In light of the topographic maps, hotspots from settlements or industrial infrastructures (in the Western Siberia mostly) were  
Figure 1: Geographic sectors of the Siberian Arctic: (1) Western Siberia (from the Ural Mountains eastward to the Yenisei River), (2) Eastern Siberia (eastward from the Yenisei River to the Kolyma River), (3) Far East (eastward from the Kolyma River to the easternmost. The locations of wildfires during the 2001–2021 period are marked by red.  
excluded. (2) In addition, we used expert comparison with high-resolution satellite scenes from Google Earth ([[https://earth.google.com/web](https://earth.google.com/web)]([https://earth.google.com/web](https://earth.google.com/web)) (accessed on 5 May 2022)), Bing Maps ([[https://www.bing.com/maps](https://www.bing.com/maps)]([https://www.bing.com/maps](https://www.bing.com/maps)) (accessed on 5 May 2022)), and Yandex Maps ([[https://yandex.ru/maps](https://yandex.ru/maps)]([https://yandex.ru/maps](https://yandex.ru/maps)) (accessed on 5 May 2022)). On-ground resolution of these satellite scenes enabled identification of hotspots from industrial infrastructure or settlements. (3) Then, we excluded mineralized stony surfaces that potentially could be the source of the false signals through comparison with Pro-Vega land cover maps ([[http://pro-vega.ru/maps](http://pro-vega.ru/maps)]([http://pro-vega.ru/maps](http://pro-vega.ru/maps)) (accessed on 5 May 2021); [33]).  
The annual burnt area extent was calculated from the FIRMS dataset MCD64A1 (DOI: 10.5067/MODIS/MCD64A1.006; [25]). Available data covered the 65-70\({}^{\circ}\) N latitudes for the 2001-2021 period with spatial resolution of 0.5 \(\times\) 0.5 km\({}^{2}\). Decadal ratios of fire frequency and burned area extent for the first two decades of the 21 st century were calculated as the quotient of cumulative annual values for the 2011-2021 period divided by the cumulative annual values for the 2001-2010 period.