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Temperature Proxies as a Solution to Biased Sampling of Lake Methane Emissions
Author(s) -
Jansen Joachim,
Thornton Brett F.,
Wik Martin,
MacIntyre Sally,
Crill Patrick M.
Publication year - 2020
Publication title -
geophysical research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.007
H-Index - 273
eISSN - 1944-8007
pISSN - 0094-8276
DOI - 10.1029/2020gl088647
Subject(s) - environmental science , subarctic climate , methane , flux (metallurgy) , atmospheric sciences , sampling (signal processing) , forcing (mathematics) , trace gas , climatology , geology , oceanography , chemistry , physics , organic chemistry , detector , optics
Lake emissions of the climate forcing trace gas methane (CH 4 ) are spatiotemporally variable, but biases in flux measurements arising from undersampling are poorly quantified. We use a multiyear data set (2009–2017) of ice‐free CH 4 emissions from three subarctic lakes obtained with bubble traps ( n = 14,677), floating chambers ( n = 1,306), and surface concentrations plus a gas transfer model ( n = 535) to quantify these biases and evaluate corrections. Sampling primarily in warmer summer months, as is common, overestimates the ice‐free season flux by a factor 1.4–1.8. Temperature proxies based on Arrhenius functions that closely fit measured fluxes ( R 2 ≥ 0.93) enable gap filling the colder months of the ice‐free season and reduce sampling bias. Ebullition (activation energy 1.36 eV) expressed greater temperature sensitivity than diffusion (1.00 eV). Resolving seasonal and interannual variability in fluxes with proxies requires ∼135 sampling days for ebullition, and 22 and 14 days for diffusion via models and chambers, respectively.