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Vegetation type is an important predictor of the arctic summer land surface energy budget
Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland; Department of Biology, McGill University, 1205 Docteur Penfield, QC, Montreal, Canada.
Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland.
Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland; Low-Carbon and Climate Impact Research Centre, School of Energy and Environment, City University of Hong Kong, Tat Chee Ave, Kowloon Tong, Hong Kong.
Department of Evolutionary Biology and Environmental Studies, University of Zurich, Winterthurerstrasse 190, Zurich, Switzerland.
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2022 (Engelska)Ingår i: Nature Communications, E-ISSN 2041-1723, Vol. 13, artikel-id 6379Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm−2) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.

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Springer Nature, 2022. Vol. 13, artikel-id 6379
Nationell ämneskategori
Klimatvetenskap
Identifikatorer
URN: urn:nbn:se:umu:diva-200996DOI: 10.1038/s41467-022-34049-3ISI: 000877943100002Scopus ID: 2-s2.0-85140941186OAI: oai:DiVA.org:umu-200996DiVA, id: diva2:1711481
Forskningsfinansiär
Europeiska kommissionen, 869471Vetenskapsrådet, 2017-05268Norges forskningsråd, 274711Norges forskningsråd, 301552Tillgänglig från: 2022-11-17 Skapad: 2022-11-17 Senast uppdaterad: 2025-02-07Bibliografiskt granskad

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Olofsson, Johan

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