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Title: Representativeness assessment of the pan-Arctic eddy covariance site network and optimized future enhancements
Abstract. Large changes in the Arctic carbon balance are expectedas warming linked to climate change threatens to destabilize ancientpermafrost carbon stocks. The eddy covariance (EC) method is an establishedtechnique to quantify net losses and gains of carbon between the biosphereand atmosphere at high spatiotemporal resolution. Over the past decades, agrowing network of terrestrial EC tower sites has been established acrossthe Arctic, but a comprehensive assessment of the network'srepresentativeness within the heterogeneous Arctic region is still lacking.This creates additional uncertainties when integrating flux data acrosssites, for example when upscaling fluxes to constrain pan-Arctic carbonbudgets and changes therein. This study provides an inventory of Arctic (here > = 60∘ N)EC sites, which has also been made available online(https://cosima.nceas.ucsb.edu/carbon-flux-sites/, last access: 25 January 2022). Our database currentlycomprises 120 EC sites, but only 83 are listed as active, and just 25 ofthese active sites remain operational throughout the winter. To map therepresentativeness of this EC network, we evaluated the similarity betweenenvironmental conditions observed at the tower locations and those withinthe larger Arctic study domain based on 18 bioclimatic and edaphicvariables. This allows us to assess a general level of similarity betweenecosystem conditions within the domain, while not necessarily reflectingchanges in greenhouse gas flux rates directly. We define two metrics basedon this representativeness score: one that measures whether a location isrepresented by an EC tower with similar characteristics (ER1) and a secondfor which we assess if a minimum level of representation for statisticallyrigorous extrapolation is met (ER4). We find that while half of the domainis represented by at least one tower, only a third has enough towers insimilar locations to allow reliable extrapolation. When we consider methanemeasurements or year-round (including wintertime) measurements, the valuesdrop to about 1/5 and 1/10 of the domain, respectively. With themajority of sites located in Fennoscandia and Alaska, these regions wereassigned the highest level of network representativeness, while large partsof Siberia and patches of Canada were classified as underrepresented.Across the Arctic, mountainous regions were particularly poorly representedby the current EC observation network. We tested three different strategies to identify new site locations orupgrades of existing sites that optimally enhance the representativeness ofthe current EC network. While 15 new sites can improve therepresentativeness of the pan-Arctic network by 20 %, upgrading as fewas 10 existing sites to capture methane fluxes or remain active duringwintertime can improve their respective ER1 network coverage by 28 % to 33 %. This targeted network improvement could be shown to be clearlysuperior to an unguided selection of new sites, therefore leading tosubstantial improvements in network coverage based on relatively smallinvestments.  more » « less
Award ID(s):
1931333
NSF-PAR ID:
10352231
Author(s) / Creator(s):
; ; ; ; ; ; ;
Date Published:
Journal Name:
Biogeosciences
Volume:
19
Issue:
3
ISSN:
1726-4189
Page Range / eLocation ID:
559 to 583
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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