# Pollution and Climatic Influence on Trees in the Siberian Arctic Wetlands
## 2 Materials and Methods
### Eco-Climate Variables  
Tree GI was analyzed against the pollution (SO\({}_{2}\)) emissions, monthly air and soil temperatures, precipitation, SPEI drought index (standardized precipitation-evapotranspiration index), soil moisture (volumetric soil water layer depth until to 7 cm), and EWTA (equivalent water thickness anomalies, or terrestrial water storage). Air temperature, precipitation, and soil moisture were obtained from ERA-5 database ([[https://cds.climate.copernicus.eu/cdsapp#](https://cds.climate.copernicus.eu/cdsapp#)]([https://cds.climate.copernicus.eu/cdsapp#](https://cds.climate.copernicus.eu/cdsapp#))!/dataset/reanalysis-era5-land-monthly-means?tab=overview, accessed on 15 October 2022; spatial resolution 0.1\({}^{\circ}\)\(\times\) 0.1\({}^{\circ}\)[15]).  
Drought index SPEI is the difference between precipitation and potential evapotranspiration [16]. Decreased SPEI indicated increased drought severity. We calculated SPEI based on ERA5-Land data by R-script ([[https://github.com/sbegueria/SPEI](https://github.com/sbegueria/SPEI)]([https://github.com/sbegueria/SPEI](https://github.com/sbegueria/SPEI)) (accessed on 1 December 2022)). SO\({}_{2}\) emissions were obtained from scientific literature and official reports [5; 17; 18].  
The EWTA is the product of gravimetric measurements made by the GRACE satellite with on-ground resolution 1\({}^{\circ}\)\(\times\) 1\({}^{\circ}\)[19]. This is characteristic of the moisture regime and represents total terrestrial water storage. EWTA data were obtained from NASA-JPL database ([[https://podaac-opendap.jpl.nasa.gov/opendap/hyrax/allData/tellus/L3](https://podaac-opendap.jpl.nasa.gov/opendap/hyrax/allData/tellus/L3)]([https://podaac-opendap.jpl.nasa.gov/opendap/hyrax/allData/tellus/L3](https://podaac-opendap.jpl.nasa.gov/opendap/hyrax/allData/tellus/L3)), accessed on 15 October 2022).  
GPP data (C, kg/ha) were obtained from the Terra/MODIS product MOD17A2H version 6.0 ([[https://lpdaac.usgs.gov/products/mod17a2](https://lpdaac.usgs.gov/products/mod17a2) hv006/]([https://lpdaac.usgs.gov/products/mod17a2](https://lpdaac.usgs.gov/products/mod17a2) hv006/), accessed on 15 October 2022). Data temporal and spatial resolutions were 8 days and 500 m, correspondingly [20]. Mosaics of GPP (as well as NPP and NDVI) composites were compiled based on median values from 8-day composites over summer periods. NPP annual values were obtained from the Terra/MODIS product MOD17A3 HGF version 6.0 ([[https://lpdaac.usgs.gov/products/mod17a3](https://lpdaac.usgs.gov/products/mod17a3) hgfv006/]([https://lpdaac.usgs.gov/products/mod17a3](https://lpdaac.usgs.gov/products/mod17a3) hgfv006/), accessed on 15 October 2022). The database contained annual NPP values with a spatial resolution of 500 m [21]. NDVI were calculated based on data from the Terra/MODIS products MOD09Q1 \(\mathrm{n}\) MOD09A1 version 6.1 ([[https://lpdaac.usgs.gov/products/mod09q1v006/](https://lpdaac.usgs.gov/products/mod09q1v006/)]([https://lpdaac.usgs.gov/products/mod09q1v006/](https://lpdaac.usgs.gov/products/mod09q1v006/)) [22], accessed on 15 October 2022 and [[https://lpdaac.usgs.gov/products/mod09a1v006](https://lpdaac.usgs.gov/products/mod09a1v006)]([https://lpdaac.usgs.gov/products/mod09a1v006](https://lpdaac.usgs.gov/products/mod09a1v006)) [23], accessed on 15 October 2022; spatial resolution 250 m).  
Wind rise was generated based on wind direction hourly data that were obtained from the nearest of the Norilsk stations (station 23077 and 23078; coordinates 69.33\({}^{\circ}\) N/87.95\({}^{\circ}\) E and 69.33\({}^{\circ}\) N 88.25\({}^{\circ}\) E, correspondingly).