Preprints
https://doi.org/10.5194/tc-2019-9
https://doi.org/10.5194/tc-2019-9
20 Feb 2019
 | 20 Feb 2019
Status: this preprint was under review for the journal TC. A final paper is not foreseen.

Assessing snow cover changes in the Kola Peninsula, Arctic Russia, using a synthesis of MODIS snow products and station observations

Rebecca M. Vignols, Gareth J. Marshall, W. Gareth Rees, Yulia Zaika, Tony Phillips, and Ilona Blinova

Abstract. The very high albedo of snow means that changes in its coverage have a significant impact on the Earth's global energy budget. Thus, Northern Hemisphere snow cover, which comprises approximately 98 % of the global total area of seasonal snow, is responsible for the largest annual and inter-annual contrasts in land surface albedo. Here, we examine recent changes in snow cover (2000–2016) in the western mountain regions (hereinafter WMR) of the Kola Peninsula in Arctic Russia, an area that has undergone significant climate change in recent decades. Future changes in snow cover have the potential to have a major socio-economic impact in this region, which is primarily dependent on mining and tourism for its economy. We used a combination of remote sensing data, the first time it has been used to assess snow cover in this region, and meteorological observations in our analysis. The snow cover products were processed to maximise the number of cloud-free days. First and last days of snow cover were derived for each year from snow depth observations at meteorological stations. MODIS-derived snow cover dates were compared to these station-derived dates to look for systematic biases in the satellite data. We find that for 85.8 % of pixels investigated the deviation between the MODIS-derived and station-derived snow cover start and end dates is less than 20 days. These locally calibrated MODIS data were then used in combination with data from meteorological stations to determine the trends and variability in the duration of the snow season in the WMR in the past half century. Snow cover was found to be highly variable both spatially and at inter-annual timescales. Overall, the duration of the snow season decreased at higher altitudes and increased in valleys and plains. High spatial variability in trends in the snow cover season and snow depth across the region can be partially explained by the effect of orography and wind scouring. Between 2000 and 2016, opposing trends in the duration of the snow cover season occur at different stations within the WMR, though more consistent trends appear over a 25-year common interval wherein the snow cover duration has decreased statistically significantly at four of five stations. Finally, MODIS is shown to provide a highly reliable snow dataset for assessing regional snow cover changes, being able to identify correctly the only statistically significant trend observed at meteorological station.

This preprint has been withdrawn.

Rebecca M. Vignols, Gareth J. Marshall, W. Gareth Rees, Yulia Zaika, Tony Phillips, and Ilona Blinova

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
Rebecca M. Vignols, Gareth J. Marshall, W. Gareth Rees, Yulia Zaika, Tony Phillips, and Ilona Blinova
Rebecca M. Vignols, Gareth J. Marshall, W. Gareth Rees, Yulia Zaika, Tony Phillips, and Ilona Blinova

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Latest update: 22 Apr 2024
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This preprint has been withdrawn.

Short summary
We examine recent changes in snow cover (2000–2016) in the western mountain regions of the Kola Peninsula in Arctic Russia. Using a combination of remote sensing data and meteorological observations, we demonstrate that the region has high inter-annual and spatial variability in the long-term snow cover trends and that overall the snow cover duration has been decreasing at higher altitudes and increasing at lower altitudes. We find that MODIS provides a highly reliable snow parameter dataset.