scholarly journals Accounting for surface waves improves gas flux estimation at high wind speed in a large lake

2021 ◽  
Vol 12 (4) ◽  
pp. 1169-1189
Author(s):  
Pascal Perolo ◽  
Bieito Fernández Castro ◽  
Nicolas Escoffier ◽  
Thibault Lambert ◽  
Damien Bouffard ◽  
...  
Keyword(s):  
Surface Waves ◽  
Wind Shear ◽  
Diffusion Flux ◽  
Gas Transfer ◽  
Co2 Fluxes ◽  
Large Lake ◽  
Lake Geneva ◽  
Transfer Velocity ◽  
Near Surface ◽  
Gas Transfer Velocity

Abstract. The gas transfer velocity (k) is a major source of uncertainty when assessing the magnitude of lake gas exchange with the atmosphere. For the diversity of existing empirical and process-based k models, the transfer velocity increases with the level of turbulence near the air–water interface. However, predictions for k can vary by a factor of 2 among different models. Near-surface turbulence results from the action of wind shear, surface waves, and buoyancy-driven convection. Wind shear has long been identified as a key driver, but recent lake studies have shifted the focus towards the role of convection, particularly in small lakes. In large lakes, wind fetch can, however, be long enough to generate surface waves and contribute to enhance gas transfer, as widely recognised in oceanographic studies. Here, field values for gas transfer velocity were computed in a large hard-water lake, Lake Geneva, from CO2 fluxes measured with an automated (forced diffusion) flux chamber and CO2 partial pressure measured with high-frequency sensors. k estimates were compared to a set of reference limnological and oceanic k models. Our analysis reveals that accounting for surface waves generated during windy events significantly improves the accuracy of k estimates in this large lake. The improved k model is then used to compute k over a 1-year time period. Results show that episodic extreme events with surface waves (6 % occurrence, significant wave height > 0.4 m) can generate more than 20 % of annual cumulative k and more than 25 % of annual net CO2 fluxes in Lake Geneva. We conclude that for lakes whose fetch can exceed 15 km, k models need to integrate the effect of surface waves.

scholarly journals Accounting for surface waves improves gas flux estimation at high wind speed in a large lake

2021 ◽  
Author(s):  
Pascal Perolo ◽  
Bieito Fernández Castro ◽  
Nicolas Escoffier ◽  
Thibault Lambert ◽  
Damien Bouffard ◽  
...  
Keyword(s):  
Surface Waves ◽  
Wind Shear ◽  
Diffusion Flux ◽  
Gas Transfer ◽  
Co2 Fluxes ◽  
Large Lake ◽  
Lake Geneva ◽  
Transfer Velocity ◽  
Near Surface ◽  
Gas Transfer Velocity

Abstract. The gas transfer velocity (k) is a major source of uncertainty when assessing the magnitude of lake gas exchange with the atmosphere. For the diversity of existing empirical and process-based k models, the transfer velocity increases with the level of turbulence near the air-water interface. However, predictions for k can vary by a factor of 2 among different models. Near-surface turbulence results from the action of wind shear, surface waves and buoyancy-driven convection. Wind shear has long been identified as a key driver, while recent lake studies have shifted the focus towards the role of convection, particularly in small lakes. In large lakes, wind fetch can however be long enough to generate surface waves and contribute to enhance gas transfer, as widely recognised in oceanographic studies. Here, field values for gas transfer velocity were computed in a large hardwater lake, Lake Geneva, from CO2 fluxes measured with an automated (forced diffusion) flux chamber and CO2 partial pressure measured with high frequency sensors. k estimates were compared to a set of reference limnological and oceanic k models. Our analysis reveals that accounting for surface waves generated during windy events significantly improves the accuracy of k estimates in this large lake. The improved k model is then used to compute k over a one-year time-period. Results show that episodic extreme events with surface waves (6 % occurrence, significant wave height > 0.4 m) can generate more than 20 % of annual cumulative k and more than 25 % of annual net CO2 fluxes in Lake Geneva. We conclude that for lakes whose fetch can exceed 15 km, k-models need to integrate the effect of surface waves.

scholarly journals Evidence for surface organic matter modulation of air-sea CO<sub>2</sub> gas exchange

2009 ◽  
Vol 6 (6) ◽  
pp. 1105-1114 ◽  
Author(s):  
M. Ll. Calleja ◽  
C. M. Duarte ◽  
Y. T. Prairie ◽  
S. Agustí ◽  
G. J. Herndl
Keyword(s):  
Organic Matter ◽  
Wind Speed ◽  
Gas Exchange ◽  
Co2 Exchange ◽  
Open Ocean ◽  
Gas Transfer ◽  
Co2 Fluxes ◽  
Transfer Velocity ◽  
Gas Transfer Velocity

Abstract. Air-sea CO2 exchange depends on the air-sea CO2 gradient and the gas transfer velocity (k), computed as a function of wind speed. Large discrepancies among relationships predicting k from wind suggest that other processes also contribute significantly to modulate CO2 exchange. Here we report, on the basis of the relationship between the measured gas transfer velocity and the organic carbon concentration at the ocean surface, a significant role of surface organic matter in suppressing air-sea gas exchange, at low and intermediate winds, in the open ocean, confirming previous observations. The potential role of total surface organic matter concentration (TOC) on gas transfer velocity (k) was evaluated by direct measurements of air-sea CO2 fluxes at different wind speeds and locations in the open ocean. According to the results obtained, high surface organic matter contents may lead to lower air-sea CO2 fluxes, for a given air-sea CO2 partial pressure gradient and wind speed below 5 m s−1, compared to that observed at low organic matter contents. We found the bias in calculated gas fluxes resulting from neglecting TOC to co-vary geographically and seasonally with marine productivity. These results support previous evidences that consideration of the role of organic matter in modulating air-sea CO2 exchange may improve flux estimates and help avoid possible bias associated to variability in surface organic concentration across the ocean.

scholarly journals Estimate of gas transfer velocity between water-air interface in a large lake based on different models: A case study of Lake Taihu

2018 ◽  
Vol 30 (3) ◽  
pp. 790-801
Author(s):  
XIAO Qitao ◽  
◽  
ZHANG Mi ◽  
HU Zhenghua ◽  
XIAO Wei ◽  
...  
Keyword(s):  
Lake Taihu ◽  
Gas Transfer ◽  
Large Lake ◽  
Transfer Velocity ◽  
Gas Transfer Velocity ◽  
Air Interface

scholarly journals Uncertainties in eddy covariance air-sea CO<sub>2</sub> flux measurements and implications for gas transfer velocity parameterisations

2021 ◽  
Author(s):  
Yuanxu Dong ◽  
Mingxi Yang ◽  
Dorothee C. E. Bakker ◽  
Vassilis Kitidis ◽  
Thomas G. Bell
Keyword(s):  
Eddy Covariance ◽  
Co2 Flux ◽  
Gas Transfer ◽  
Co2 Fluxes ◽  
Relative Uncertainty ◽  
Transfer Velocity ◽  
Gas Transfer Velocity ◽  
Random Uncertainty ◽  
Flux Measurements ◽  
The Mean

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 time scales. The uncertainty (1 standard deviation) in hourly averaged EC air-sea CO2 fluxes (cruise-mean) ranges from 1.4 to 3.2 mmol m−2 day−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 1–3 hours, 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.

scholarly journals Uncertainties in eddy covariance air–sea CO<sub>2</sub> flux measurements and implications for gas transfer velocity parameterisations

2021 ◽  
Vol 21 (10) ◽  
pp. 8089-8110
Author(s):  
Yuanxu Dong ◽  
Mingxi Yang ◽  
Dorothee C. E. Bakker ◽  
Vassilis Kitidis ◽  
Thomas G. Bell
Keyword(s):  
Eddy Covariance ◽  
Co2 Flux ◽  
Gas Transfer ◽  
Co2 Fluxes ◽  
Relative Uncertainty ◽  
Transfer Velocity ◽  
Gas Transfer Velocity ◽  
Random Uncertainty ◽  
Flux Measurements ◽  
The Mean

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.

scholarly journals A model study on the sensitivity of surface ocean CO<sub>2</sub> pressure with respect to the CO<sub>2</sub> gas exchange rate

2011 ◽  
Vol 8 (6) ◽  
pp. 10797-10821
Author(s):  
P. Landschützer ◽  
J. F. Tjiputra ◽  
K. Assmann ◽  
C. Heinze
Keyword(s):  
Exchange Rate ◽  
Gas Exchange ◽  
Co2 Flux ◽  
Gas Transfer ◽  
Co2 Fluxes ◽  
Transfer Velocity ◽  
Carbon Cycle Model ◽  
Spatial And Temporal Scales ◽  
Gas Transfer Velocity ◽  
Gas Exchange Rate

Abstract. Rising CO2 concentrations in the atmosphere and a changing climate are expected to alter the air-sea CO2 flux through changes in the respective control factors for gas exchange. In this study we determine the sensitivity of the CO2 fluxes on the gas transfer velocity using the MICOM-HAMOCC isopycnic carbon cycle model. The monthly generated MICOM-HAMOCC output data are suitable to investigate seasonal variabilities concerning the exchange of CO2. In a series of 3 sensitivity runs the wind dependent gas exchange rate is increased by 44%, both in the northern and southern westerly regions, as well as in the equatorial area to investigate the effect of regional variations of the gas transfer rate on the air-sea fluxes and the distribution of the ocean surface pCO2. For the period between 1948–2009, the results show that locally increasing gas transfer rates do not play an important role concerning the global uptake of carbon from the atmosphere. While effects on a global and annual scale are low, the regional and intra-annual variability shows remarkable variations in the gas fluxes and the surface pCO2. An accurate quantification of the variable gas transfer velocity therefore provides a potential source to enhance model predictions over small spatial and temporal scales and to successfully reconcile model results on surface pCO2 and air-sea CO2 fluxes with observations.

scholarly journals Sniffle: a step forward to measure in situ CO2 fluxes with the floating chamber technique

Elem Sci Anth ◽  
2018 ◽  
Vol 6 ◽  
Author(s):  
M. Ribas-Ribas ◽  
L. F. Kilcher ◽  
O. Wurl
Keyword(s):  
Gas Transfer ◽  
Tidal Basin ◽  
Co2 Fluxes ◽  
Spatiotemporal Resolution ◽  
Transfer Velocity ◽  
Gas Transfer Velocity ◽  
Wind Speeds ◽  
Drifting Buoy ◽  
Floating Chamber

Understanding how the ocean absorbs anthropogenic CO2 is critical for predicting climate change. We designed Sniffle, a new autonomous drifting buoy with a floating chamber, to measure gas transfer velocities and air–sea CO2 fluxes with high spatiotemporal resolution. Currently, insufficient in situ data exist to verify gas transfer parameterizations at low wind speeds (&lt;4 m s–1), which leads to underestimation of gas transfer velocities and, therefore, of air–sea CO2 fluxes. The Sniffle is equipped with a sensor to consecutively measure aqueous and atmospheric pCO2 and to monitor increases or decreases of CO2 inside the chamber. During autonomous operation, a complete cycle lasts 40 minutes, with a new cycle initiated after flushing the chamber. The Sniffle can be deployed for up to 15 hours at wind speeds up to 10 m s–1. Floating chambers often overestimate fluxes because they create additional turbulence at the water surface. We correct fluxes by measuring turbulence with two acoustic Doppler velocimeters, one positioned directly under the floating chamber and the other positioned sideways, to compare artificial disturbance caused by the chamber and natural turbulence. The first results of deployment in the North Sea during the summer of 2016 demonstrate that the new drifting buoy is a useful tool that can improve our understanding of gas transfer velocity with in situ measurements. At low and moderate wind speeds and different conditions, the results obtained indicate that the observed tidal basin was acting as a source of atmospheric CO2. Wind speed and turbulence alone could not fully explain the variance in gas transfer velocity. We suggest that other factors like surfactants, rain or tidal current will have an impact on gas transfer parameterizations.

scholarly journals Impact of Nonzero Intercept Gas Transfer Velocity Parameterizations on Global and Regional Ocean–Atmosphere CO2 Fluxes

Geosciences ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. 230
Author(s):  
Mariana Ribas-Ribas ◽  
Gianna Battaglia ◽  
Matthew P. Humphreys ◽  
Oliver Wurl
Keyword(s):  
Wind Speed ◽  
Ocean Model ◽  
Global Ocean ◽  
Gas Transfer ◽  
Co2 Fluxes ◽  
Average Wind Speed ◽  
Transfer Velocity ◽  
Gas Transfer Velocity ◽  
Wind Speeds

Carbon dioxide (CO2) fluxes between the ocean and atmosphere (FCO2) are commonly computed from differences between their partial pressures of CO2 (ΔpCO2) and the gas transfer velocity (k). Commonly used wind-based parameterizations for k imply a zero intercept, although in situ field data below 4 m s−1 are scarce. Considering a global average wind speed over the ocean of 6.6 m s−1, a nonzero intercept might have a significant impact on global FCO2. Here, we present a database of 245 in situ measurements of k obtained with the floating chamber technique (Sniffle), 190 of which have wind speeds lower than 4 m s−1. A quadratic parameterization with wind speed and a nonzero intercept resulted in the best fit for k. We further tested FCO2 calculated with a different parameterization with a complementary pCO2 observation-based product. Furthermore, we ran a simulation in a well-tested ocean model of intermediate complexity to test the implications of different gas transfer velocity parameterizations for the natural carbon cycle. The global ocean observation-based analysis suggests that ignoring a nonzero intercept results in an ocean-sink increase of 0.73 Gt C yr−1. This corresponds to a 28% higher uptake of CO2 compared with the flux calculated from a parameterization with a nonzero intercept. The differences in FCO2 were higher in the case of low wind conditions and large ΔpCO2 between the ocean and atmosphere. Such conditions occur frequently in the Tropics.

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