Pan-Arctic climate and land cover trends derived from multi-variate and multi-scale analyses (1981-2012)
Research output: Contribution to journal › Research article › Contributed › peer-review
Contributors
Abstract
Arctic ecosystems have been afflicted by vast changes in recent decades. Changes in temperature, as well as precipitation, are having an impact on snow cover, vegetation productivity and coverage, vegetation seasonality, surface albedo, and permafrost dynamics. The coupled climate-vegetation change in the arctic is thought to be a positive feedback in the Earth system, which can potentially further accelerate global warming. This study focuses on the co-occurrence of temperature, precipitation, snow cover, and vegetation greenness trends between 1981 and 2012 in the pan-arctic region based on coarse resolution climate and remote sensing data, as well as ground stations. Precipitation significantly increased during summer and fall. Temperature had the strongest increase during the winter months (twice than during the summer months). The snow water equivalent had the highest trends during the transition seasons of the year. Vegetation greenness trends are characterized by a constant increase during the vegetation-growing period. High spatial resolution remote sensing data were utilized to map structural vegetation changes between 1973 and 2012 for a selected test region in Northern Siberia. An intensification of woody vegetation cover at the taiga-tundra transition area was found. The observed co-occurrence of climatic and ecosystem changes is an example of the multi-scale feedbacks in the arctic ecosystems.
Details
Original language | English |
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Pages (from-to) | 2296-2316 |
Number of pages | 21 |
Journal | Remote sensing |
Volume | 6 |
Issue number | 3 |
Publication status | Published - 12 Mar 2014 |
Peer-reviewed | Yes |
Externally published | Yes |
External IDs
ORCID | /0000-0003-0363-9697/work/142252098 |
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Keywords
Sustainable Development Goals
ASJC Scopus subject areas
Keywords
- Arctic, CRU, Landsat, NDVI3g, Precipitation, RapidEye, Snow water equivalent, Temperature, Tree line, Trends