scholarly journals Mesoscale Temporal Wind Variability Biases Global Air–Sea Gas Transfer Velocity of CO2 and Other Slightly Soluble Gases

2021 ◽  
Vol 13 (7) ◽  
pp. 1328
Author(s):  
Yuanyuan Gu ◽  
Gabriel G. Katul ◽  
Nicolas Cassar
Keyword(s):  
Wind Speed ◽  
Climate Models ◽  
Taylor Series Expansion ◽  
Random Variable ◽  
Gas Transfer ◽  
Time Averaging ◽  
Transfer Velocity ◽  
Gas Transfer Velocity ◽  
Wind Variability ◽  
Non Linear

The significance of the water-side gas transfer velocity for air–sea CO2 gas exchange (k) and its non-linear dependence on wind speed (U) is well accepted. What remains a subject of inquiry are biases associated with the form of the non-linear relation linking k to U (hereafter labeled as f(U), where f(.) stands for an arbitrary function of ), the distributional properties of (treated as a random variable) along with other external factors influencing k, and the time-averaging period used to determine k from . To address the latter issue, a Taylor series expansion is applied to separate f(U) into a term derived from time-averaging wind speed (labeled as ⟨U⟩ where indicates averaging over a monthly time scale) as currently employed in climate models and additive bias corrections that vary with the statistics of . The method was explored for nine widely used f(U) parameterizations based on remotely-sensed 6-hourly global wind products at 10 m above the sea-surface. The bias in k of monthly estimates compared to the reference 6-hourly product was shown to be mainly associated with wind variability captured by the standard deviation around or, more preferably, a dimensionless coefficient of variation [...]

scholarly journals Systematic errors in global air-sea CO<sub>2</sub> flux caused by temporal averaging of sea-level pressure

2005 ◽  
Vol 5 (6) ◽  
pp. 1459-1466 ◽  
Author(s):  
H. Kettle ◽  
C. J. Merchant
Keyword(s):  
Wind Speed ◽  
Carbon Flux ◽  
Air Pressure ◽  
Gas Transfer ◽  
Time Averaging ◽  
Pressure Data ◽  
Fractional Change ◽  
Transfer Velocity ◽  
Gas Transfer Velocity ◽  
Temporal Averaging

Abstract. Long-term temporal averaging of meteorological data, such as wind speed and air pressure, can cause large errors in air-sea carbon flux estimates. Other researchers have already shown that time averaging of wind speed data creates large errors in flux due to the non-linear dependence of the gas transfer velocity on wind speed (Bates and Merlivat, 2001). However, in general, wind speed is negatively correlated with air pressure, and a given fractional change in the pressure of dry air produces an equivalent fractional change in the atmospheric partial pressure of carbon dioxide (pCO2air). Thus low pressure systems cause a drop in pCO2air, which together with the associated high winds, promotes outgassing/reduces uptake of CO2 from the ocean. Here we quantify the errors in global carbon flux estimates caused by using monthly or climatological pressure data to calculate pCO2air (and thus ignoring the covariance of wind and pressure) over the period 1990-1999, using two common parameterisations for gas transfer velocity. Results show that on average, compared with estimates made using 6 hourly pressure data, the global oceanic sink is systematically overestimated by 7% (W92) and 10% (WM99) when monthly mean pressure is used, and 9% (W92) and 12% (WM99) when climatological pressure is used.

scholarly journals Systematic errors in global air-sea CO<sub>2</sub> flux caused by temporal averaging of sea-level pressure

2005 ◽  
Vol 5 (1) ◽  
pp. 325-346 ◽  
Author(s):  
H. Kettle ◽  
C. J. Merchant
Keyword(s):  
Wind Speed ◽  
Carbon Flux ◽  
Air Pressure ◽  
Gas Transfer ◽  
Time Averaging ◽  
Pressure Data ◽  
Fractional Change ◽  
Transfer Velocity ◽  
Gas Transfer Velocity ◽  
Temporal Averaging

Abstract. Long-term temporal averaging of meteorological data, such as wind speed and air pressure, can cause large errors in air-sea carbon flux estimates. Other researchers have already shown that time averaging of wind speed data creates large errors in flux due to the non-linear dependence of the gas transfer velocity on wind speed (Bates and Merlivat, 2001). However, in general, wind speed is negatively correlated with air pressure, and a given fractional change in the pressure of dry air produces an equivalent fractional change in the atmospheric partial pressure of carbon dioxide (pCO2air). Thus low pressure systems cause a drop in pCO2air, which together with the associated high winds, promotes outgassing/reduces uptake of CO2 from the ocean. Here we quantify the errors in global carbon flux estimates caused by using monthly or climatological pressure data to calculate pCO2air (and thus ignoring the covariance of wind and pressure) over the period 1990–1999, using two common parameterisations for gas transfer velocity (Wanninkhof, 1992 (W92) and Wanninkhof and McGillis, 1999 (WM99)). Results show that on average, compared with estimates made using 6 hourly pressure data, the global oceanic sink is systematically overestimated by 7% (W92) and 10% (WM99) when monthly mean pressure is used, and 9% (W92) and 12% (WM99) when climatological pressure is used.

The gas transfer velocity —wind speed relationship at Siblyback Lake: A reply to comments by Kwan and Taylor

Tellus B ◽  
1993 ◽  
Vol 45 (3) ◽  
pp. 299-300 ◽  
Author(s):  
Robert C. Upstill-Goddard ◽  
Andrew J. Watson ◽  
Peter S. Liss
Keyword(s):  
Wind Speed ◽  
Gas Transfer ◽  
Transfer Velocity ◽  
Gas Transfer Velocity

scholarly journals DMS gas transfer coefficients from algal blooms in the Southern Ocean

2014 ◽  
Vol 14 (21) ◽  
pp. 28453-28482
Author(s):  
T. G. Bell ◽  
W. De Bruyn ◽  
C. A. Marandino ◽  
S. D. Miller ◽  
C. S. Law ◽  
...  
Keyword(s):  
Wind Speed ◽  
Southern Ocean ◽  
Eddy Covariance ◽  
Algal Blooms ◽  
Biologically Active ◽  
Gas Transfer ◽  
Transfer Coefficients ◽  
Transfer Velocity ◽  
Gas Transfer Velocity ◽  
Wind Speeds

Abstract. Air/sea dimethylsulfide (DMS) fluxes and bulk air/sea gradients were measured over the Southern Ocean in February/March 2012 during the Surface Ocean Aerosol Production (SOAP) study. The cruise encountered three distinct phytoplankton bloom regions, consisting of two blooms with moderate DMS levels, and a high biomass, dinoflagellate-dominated bloom with high seawater DMS levels (>15 nM). Gas transfer coefficients were considerably scattered at wind speeds above 5 m s−1. Bin averaging the data resulted in a linear relationship between wind speed and mean gas transfer velocity consistent with that previously observed. However, the wind speed-binned gas transfer data distribution at all wind speeds is positively skewed. The flux and seawater DMS distributions were also positively skewed, which suggests that eddy covariance-derived gas transfer velocities are consistently influenced by additional, log-normal noise. A~flux footprint analysis was conducted during a transect into the prevailing wind and through elevated DMS levels in the dinoflagellate bloom. Accounting for the temporal/spatial separation between flux and seawater concentration significantly reduces the scatter in computed transfer velocity. The SOAP gas transfer velocity data shows no obvious modification of the gas transfer-wind speed relationship by biological activity or waves. This study highlights the challenges associated with eddy covariance gas transfer measurements in biologically active and heterogeneous bloom environments.

scholarly journals Net sea-air CO<sub>2</sub> flux uncertainties in the Bay of Biscay based on the choice of wind speed products and gas transfer parameterizations

2012 ◽  
Vol 9 (8) ◽  
pp. 9993-10017
Author(s):  
P. Otero ◽  
X. A. Padín ◽  
M. Ruiz-Villarreal ◽  
L. M. García-García ◽  
A. F. Ríos ◽  
...  
Keyword(s):  
Wind Speed ◽  
Co2 Flux ◽  
Forecast Model ◽  
Gas Transfer ◽  
Co2 Uptake ◽  
Bay Of Biscay ◽  
Transfer Velocity ◽  
Gas Transfer Velocity ◽  
Different Sources ◽  
Meteorological Models

Abstract. The estimation of sea-air CO2 fluxes are largely dependent on wind speed through the gas transfer velocity parameterization. In this paper, we quantify uncertainties in the estimation of the CO2 uptake in the Bay of Biscay resulting from using different sources of wind speed such as three different global reanalysis meteorological models (NCEP/NCAR 1, NCEP/DOE 2 and ERA-Interim), one regional high-resolution forecast model (HIRLAM-AEMet) and QuikSCAT winds, in combination with some of the most widely used gas transfer velocity parameterizations. Results show that net CO2 flux estimations during an entire seasonal cycle may differ up to 240% depending on the wind speed product and the gas exchange parameterization. The comparison of satellite and model derived winds with observations at buoys advises against the systematic overestimation of NCEP-2 and the underestimation of NCEP-1. In this region, QuikSCAT has the best performing, although ERA-Interim becomes the best choice in areas near the coastline or when the time resolution is the constraint.

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 Insights from year-long measurements of air–water CH<sub>4</sub> and CO<sub>2</sub> exchange in a coastal environment

2019 ◽  
Vol 16 (5) ◽  
pp. 961-978 ◽  
Author(s):  
Mingxi Yang ◽  
Thomas G. Bell ◽  
Ian J. Brown ◽  
James R. Fishwick ◽  
Vassilis Kitidis ◽  
...  
Keyword(s):  
Wind Speed ◽  
Co2 Flux ◽  
Open Water ◽  
Gas Transfer ◽  
Co2 Efflux ◽  
Water Sector ◽  
Transfer Velocity ◽  
Ch4 Flux ◽  
Gas Transfer Velocity

Abstract. Air–water CH4 and CO2 fluxes were directly measured using the eddy covariance technique at the Penlee Point Atmospheric Observatory on the southwest coast of the United Kingdom from September 2015 to August 2016. The high-frequency, year-long measurements provide unprecedented detail on the variability of these greenhouse gas fluxes from seasonal to diurnal and to semi-diurnal (tidal) timescales. Depending on the wind sector, fluxes measured at this site are indicative of air–water exchange in coastal seas as well as in an outer estuary. For the open-water sector when winds were off the Atlantic Ocean, CH4 flux was almost always positive (annual mean of ∼0.05 mmol m−2 d−1) except in December and January, when CH4 flux was near zero. At times of high rainfall and river flow rate, CH4 emission from the estuarine-influenced Plymouth Sound sector was several times higher than emission from the open-water sector. The implied CH4 saturation (derived from the measured fluxes and a wind-speed-dependent gas transfer velocity parameterization) of over 1000 % in the Plymouth Sound is within range of in situ dissolved CH4 measurements near the mouth of the river Tamar. CO2 flux from the open-water sector was generally from sea to air in autumn and winter and from air to sea in late spring and summer, with an annual mean flux of near zero. A diurnal signal in CO2 flux and implied partial pressure of CO2 in water (pCO2) are clearly observed for the Plymouth Sound sector and also evident for the open-water sector during biologically productive periods. These observations suggest that coastal CO2 efflux may be underestimated if sampling strategies are limited to daytime only. Combining the flux data with seawater pCO2 measurements made in situ within the flux footprint allows us to estimate the CO2 transfer velocity. The gas transfer velocity and wind speed relationship at this coastal location agrees reasonably well with previous open-water parameterizations in the mean but demonstrates considerable variability. We discuss the influences of biological productivity, bottom-driven turbulence and rainfall on coastal air–water gas exchange.

The ecosystem size and shape dependence of gas transfer velocity versus wind speed relationships in lakes

2013 ◽  
Vol 70 (12) ◽  
pp. 1757-1764 ◽  
Author(s):  
Dominic Vachon ◽  
Yves T. Prairie
Keyword(s):  
Wind Speed ◽  
Predictor Variable ◽  
System Size ◽  
Aquatic Systems ◽  
Velocity Versus ◽  
Gas Transfer ◽  
Lake Area ◽  
Transfer Velocity ◽  
Gas Transfer Velocity ◽  
Ecosystem Size

Air–water diffusive gas flux is commonly determined using measurements of gas concentrations and an estimate of gas transfer velocity (k600) usually derived from wind speed. The great heterogeneity of aquatic systems raises questions about the appropriateness of using a single wind-based model to predict k600 in all aquatic systems. Theoretical considerations suggest that wind speed to k600 relationships should instead be system-specific. Using data collected from aquatic systems of different sizes, we show that k600 is related to fetch and other measures of ecosystem size. Lake area together with wind speed provided the best predictive model of gas transfer velocity and explained 68% of the variability in individual k600 measurements. For a moderate wind speed of 5 m·s−1, predicted k600 varied from 6 cm·h−1 in a small 1 ha lake to over 13 cm·h−1 in a 100 km2 system. Wave height is also shown to be a promising integrative predictor variable. The modulating influence of system size on wind speed – gas transfer velocity relationships can have a large impact on upscaling exercises of gas exchange at the whole landscape level.

scholarly journals Carbon isotope evidence for the latitudinal distribution and wind speed dependence of the air–sea gas transfer velocity

Tellus B ◽  
2006 ◽  
Vol 58 (5) ◽  
Author(s):  
Nir Y. Krakauer ◽  
James T. Randerson ◽  
François W. Primeau ◽  
Nicolas Gruber ◽  
Dimitris Menemenlis
Keyword(s):  
Wind Speed ◽  
Carbon Isotope ◽  
Gas Transfer ◽  
Latitudinal Distribution ◽  
Transfer Velocity ◽  
Gas Transfer Velocity ◽  
Speed Dependence ◽  
Isotope Evidence
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