Representativeness assessment of the pan-Arctic eddy covariance site network and optimized future enhancements
Authors: Pallandt Martijn M. T. A. , Kumar Jitendra , Mauritz Marguerite , Schuur Edward A. G. , Virkkala Anna-Maria , Celis Gerardo , Hoffman Forrest M. , Göckede Mathias 
Published: February 2022

Abstract. Large changes in the Arctic carbon balance are expected
as warming linked to climate change threatens to destabilize ancient
permafrost carbon stocks. The eddy covariance (EC) method is an established
technique to quantify net losses and gains of carbon between the biosphere
and atmosphere at high spatiotemporal resolution. Over the past decades, a
growing network of terrestrial EC tower sites has been established across
the Arctic, but a comprehensive assessment of the network's
representativeness within the heterogeneous Arctic region is still lacking.
This creates additional uncertainties when integrating flux data across
sites, for example when upscaling fluxes to constrain pan-Arctic carbon
budgets 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 currently
comprises 120 EC sites, but only 83 are listed as active, and just 25 of
these active sites remain operational throughout the winter. To map the
representativeness of this EC network, we evaluated the similarity between
environmental conditions observed at the tower locations and those within
the larger Arctic study domain based on 18 bioclimatic and edaphic
variables. This allows us to assess a general level of similarity between
ecosystem conditions within the domain, while not necessarily reflecting
changes in greenhouse gas flux rates directly. We define two metrics based
on this representativeness score: one that measures whether a location is
represented by an EC tower with similar characteristics (ER1) and a second
for which we assess if a minimum level of representation for statistically
rigorous extrapolation is met (ER4). We find that while half of the domain
is represented by at least one tower, only a third has enough towers in
similar locations to allow reliable extrapolation. When we consider methane
measurements or year-round (including wintertime) measurements, the values
drop to about 1/5 and 1/10 of the domain, respectively. With the
majority of sites located in Fennoscandia and Alaska, these regions were
assigned the highest level of network representativeness, while large parts
of Siberia and patches of Canada were classified as underrepresented.
Across the Arctic, mountainous regions were particularly poorly represented
by the current EC observation network. We tested three different strategies to identify new site locations or
upgrades of existing sites that optimally enhance the representativeness of
the current EC network. While 15 new sites can improve the
representativeness of the pan-Arctic network by 20 %, upgrading as few
as 10 existing sites to capture methane fluxes or remain active during
wintertime can improve their respective ER1 network coverage by 28 % to 33 %. This targeted network improvement could be shown to be clearly
superior to an unguided selection of new sites, therefore leading to
substantial improvements in network coverage based on relatively small
investments.