Uncertainties in eddy covariance air–sea CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; flux measurements and implications for gas transfer velocity parameterisations

Yuanxu Dong,Thomas G Bell,Dorothee C E Bakker,Vassilis Kitidis,Mingxi Yang

doi:10.5194/acp-21-8089-2021

Uncertainties in eddy covariance air–sea CO&lt;sub&gt;2&lt;/sub&gt; flux measurements and implications for gas transfer velocity parameterisations

Yuanxu Dong, Thomas G Bell + Show 3 more

Open Access

https://doi.org/10.5194/acp-21-8089-2021

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Abstract

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.

Highlights

Since the Industrial Revolution, atmospheric CO2 levels have risen steeply due to human activities (Broecker and Peng, 1998)
These two Atlantic cruises transited across the same tropical region (Fig. A2, Appendix A) in October 2018 and September 2019 with different eddy covariance systems (Sect. 2.1)
The similar total random uncertainty in the AMT28 and AMT29 fluxes shows that both gas analysers are suitable for air–sea eddy covariance (EC) CO2 flux measurements

Summary

Introduction

Since the Industrial Revolution, atmospheric CO2 levels have risen steeply due to human activities (Broecker and Peng, 1998). Accurate estimates of air–sea CO2 flux are vital to forecast climate change and to quantify the effects of ocean CO2 uptake on the marine biosphere. Air–sea CO2 flux (F , e.g. in mmol m−2 d−1) is typically estimated indirectly by the bulk equation:. Nightingale et al, 2000); Sc (dimensionless) is the Schmidt number (Wanninkhof, 2014); and α (mol L−1 atm−1) is the solubility (Weiss, 1974). Sc is equal to 660 for CO2 at 20 ◦C and 35 ‰ saltwater (Wanninkhof et al, 2009). Uncertainties in the K660 parameterisation and limited coverage of f CO2w measurements result in considerable uncertainties in global bulk flux estimates (Takahashi et al, 2009; Woolf et al., 2019)

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