Uncertainties in eddy covariance air–sea CO2 flux measurements and implications for gas transfer velocity parameterisations

Dong, Yuanxu ORCID: https://orcid.org/0000-0002-1468-1623, Yang, Mingxi, Bakker, Dorothee C. E. ORCID: https://orcid.org/0000-0001-9234-5337, Kitidis, Vassilis and Bell, Thomas G. (2021) Uncertainties in eddy covariance air–sea CO2 flux measurements and implications for gas transfer velocity parameterisations. Atmospheric Chemistry and Physics, 21 (10). pp. 8089-8110. ISSN 1680-7324

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Abstract

Air–sea carbon dioxide (CO2) flux is often indirectly estimated by the bulk method using the air–sea difference in CO2 fugacity (ΔfCO2) and a parameterisation of the gas transfer velocity (K). Direct flux measurements by eddy covariance (EC) provide an independent reference for bulk flux estimates and are often used to study processes that drive K. However, inherent uncertainties in EC air–sea CO2 flux measurements from ships have not been well quantified and may confound analyses of K. This paper evaluates the uncertainties in EC CO2 fluxes from four cruises. Fluxes were measured with two state-of-the-art closed-path CO2 analysers on two ships. The mean bias in the EC CO2 flux is low, but the random error is relatively large over short timescales. The uncertainty (1 standard deviation) in hourly averaged EC air–sea CO2 fluxes (cruise mean) ranges from 1.4 to 3.2 mmolm−2d−1. This corresponds to a relative uncertainty of ∼ 20 % during two Arctic cruises that observed large CO2 flux magnitude. The relative uncertainty was greater (∼ 50 %) when the CO2 flux magnitude was small during two Atlantic cruises. Random uncertainty in the EC CO2 flux is mostly caused by sampling error. Instrument noise is relatively unimportant. Random uncertainty in EC CO2 fluxes can be reduced by averaging for longer. However, averaging for too long will result in the inclusion of more natural variability. Auto-covariance analysis of CO2 fluxes suggests that the optimal timescale for averaging EC CO2 flux measurements ranges from 1 to 3 h, which increases the mean signal-to-noise ratio of the four cruises to higher than 3. Applying an appropriate averaging timescale and suitable ΔfCO2 threshold (20 µatm) to EC flux data enables an optimal analysis of K.

Item Type: Article
Uncontrolled Keywords: atmospheric science ,/dk/atira/pure/subjectarea/asjc/1900/1902
Faculty \ School: Faculty of Science > School of Environmental Sciences
University of East Anglia Research Groups/Centres > Theme - ClimateUEA
UEA Research Groups: Faculty of Science > Research Groups > Centre for Ocean and Atmospheric Sciences
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 09 Jun 2021 00:17
Last Modified: 30 Oct 2024 00:47
URI: https://ueaeprints.uea.ac.uk/id/eprint/80229
DOI: 10.5194/acp-21-8089-2021

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