the air-sea gas transfer velocity - approaching it from multiple angles mingxi yang, t. bell, p....
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The Air-Sea Gas Transfer Velocity
- Approaching it from Multiple Angles
Mingxi Yang, T. Bell, P. Nightingale, J. Shutler
(Additional contributions from B. Blomquist)
Plymouth Marine Laboratory
ESA/EGU/SOLAS Conference, Frascati, Oct 2014
Gas Transfer Velocity (K) Controlled by Resistance on Airside/Waterside – Partitioning Depends on Solubility (α)
€
Ka = [1
ka+
1
αkw]−1 ≈ ka Large α
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Kw = [1
kw+α
ka]−1 ≈ kw Small α
Resistance on Airside/waterside analogous to two resistors in series
ra=1/ka
rw=1/kw
Highly soluble gases limited on airside
Sparingly soluble gases limited on waterside
7 m/s and 20 °C, COARE model
Momentum/heat transfer airside controlled
Acetone subject to both airside & waterside control
Motivation
Approximate Uncertainty 3 < U < 10 m/s U > 15 m/s ka 20% 50%
kw 30% 80%
ktangential 20% 50%
kbubble 20% 60%
• Reduce uncertainties in k (airside and waterside controlled gases), especially in high winds
• Improve process level understanding in gas transfer
ApproachMeasure k of multiple gases with varying solubility in
conjunction with observations of waves, bubbles, etc. Example: High Wind Gas Exchange Study (HiWinGS)
HiWinGS Cruise, Oct/Nov 2013
St Jude Storm25~28 Oct, 2013
Guardian
Telegraph
List of Observations
PML Contribution:
Directly quantify the air-sea transport of methanol & acetone
- Air concentration : PTR-MS w/ isotopic standard (Yang et al. ACP, 2013)
- Water concentration: PTR-MS w/ membrane inlet (Beale et al. ACA, 2011)
- Air-sea flux: Eddy Covariance w/ PTR-MS (Yang et al. ACP, 2013, 2014)
Sonic anemometer (10 Hz)
Motion sensor (~15 Hz)
Gas inlet to PTRMS housed in lab van
PML Eddy Covariance System
On Ship’s Foremast (~20 m amsl)
Methanol & Acetone Concentrations and FluxFrom High Resolution Proton-Transfer-Reaction
Mass Spectrometer (PTR-MS)
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H3O+ +CH3OH →H2O+CH3OH ⋅H
+
H3O+ +CD3OH →H2O+CD3OH ⋅H
+
• Measuring at ~2.2 Hz• Soft chemical ionization• Isotopic standards added at inlet tip
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Flux =Ca’W ’
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Ka ≈ Flux /(Cw /α −Ca )
Eddy covariance flux
Wind velocity corrected for ship motion (Edson et al 1998)
Total transfer velocity from air perspective
- Yang et al PNAS 110, 50, 20034–20039, 2013- Yang et al ACP 14, 7499-7517, 2014
Friction velocity consistent with COARE prediction
As is sensible heat
Measurements better described by COARE
model V3.5 than V3.0, especially in high winds
Greater scatter in calmer conditions, when winds
often came from the side of the ship (minor flow
distortion)
Momentum Transfer
Reduced sensible heat transfer during
25 Oct Storm
- Sea spray/precipitation attenuates sensible
heat flux?
Methanol & Acetone fluxes from air to sea Close to bulk predictions (~18% relative RMS error)
Transfer Velocities of Methanol & Acetone (Ka = Flux/ΔC)in general agreement with COARE Model on the mean
(some deviations in very high winds…)
Asymmetry between Airside and Waterside Transfer
Diffusion & Micro turbulence
Ca,0
Cw,0
Ca
Cw
Diffusion & Micro turbulence
Air
Water
Modified from Jaehne and Haussecker, 1998
Turbulence
Turbulence
~ 1 mm
~ 0.1 mm
Zw
Airside transfer (ka) significantly limited by both turbulent (aerodynamic) resistance and molecular diffusive resistance
Waterside transfer (kw) mostly limited by molecular diffusion/micro turbulence
KHeat ~12% higher than KMeOH
- Heat has higher diffusivity in air
KAcetone ~28% lowerthan KMeOH
- Acetone has lower solubility in water and lower diffusivity in air
Acetone Transfer Subject to Airside +Waterside Resistance- Estimation of kw by Difference
Ka : Total transfer velocity ka : Airside transfer velocitykw : Waterside transfer velocityα : Dimensionless solubility
At HiWinGs mean U10n of 12 m/s, we get:
kw = 9.1±4.3 cm/hr, normalized to Scw = 660
kw660 = 15.9±7.4 cm/hr
kw =1/(α(1/Ka – 1/ka))
Gas Kw660 (cm/hr) at U10n=12 m/s
Reference
Acetone 15.9±7.4 This work
DMS 18~22 Yang et al. 2011
Dual Tracer 34 Nightingale et al 2000
Dual Tracer 37 Ho et al 2006
CO2 48 McGillis et al 200114C 39 Sweeney et al 2007
Indirectly estimated kw close to kDMS Tangential transfer
Additional bubble-mediated transfer for less soluble gases
Conclusions thus far from HiWinGS [Yang et al. accepted in JGR Oceans]
• Turbulent transfer of momentum, sensible heat, methanol, and acetone largely follow expected trends up to U ~20 m/s– Reduction in heat/organics transfer in higher winds, possibly related to sea
spray/precipitation?
• Airside transfer velocity (ka) from methanol lower than that of sensible heat– Explained by difference in airside diffusivity
• Waterside transfer velocity (kw) indirectly estimated from measurements of acetone transfer – Close to previous estimates of kDMS (tangential transfer)
– Much lower than kw of less soluble gases
OutlookExpand the range of proxy tracers measured
to better understand physical processes
– Sparingly soluble• Carbon monoxide
(Blomquist et al. AMT, 2012)
• Terpenes?
– Intermediate solubility
• Acetaldehyde (Yang et al. ACP 2014)
• Organohalogens?
– Surface reactive• Ozone (e.g. Bariteau et
al. 2011)• Sulfur dioxide (e.g.
Faloona et al. 2010)
– Heat• Modified Controlled
Flux Technique (e.g. Nagel et al. 2014)Modified from
Wanninkhof et al. 2009
Sol. Sc No.
Flux
ΔC
K
Outlook (cont’)Remote sensing of other factors that control k
(Coincident to in situ multi-gas k measurements)
1. Satellite altimeter backscattering more directly related to surface turbulence than wind speed– EC kDMS correlated to Ku band backscattering; better correlation with difference
between Ku band and C band (Goddijn-Murphy et al. 2012, 2013)– How to increase overlap between altimetry data and in situ k observation?
• Copernicus programme: Sentinel-3 mission• Aircraft? Geostationary satellite?
OSSPRE CruiseU. Heidelberg, U. Washington
2. Mean squared wave slope• Scanning laser slope gauge (e.g. Bock
and Hara, 1995; Frew et al 2004)
• Reflective stereo slope gauge & medium angle slope gauge (e.g. Kiefhaber et al 2011)
• Accounts for surfactant effect
Questions & Comments?
More Insights from HiWinGs in the Near Future
• DMS– Comparison of kDMS with previous high wind measurements (e.g. SO
GasEx 2008, Knorr 2011). Suppression in high winds?
• CO2
– Intercomparison of two closed-path sensors and comparison with previous measurements. Which wind speed dependence?
• Multi-gas Comparisons– Difference between kDMS and kCO2 explained by bubbles?– Influence of wave state, bubble, and sea spray on waterside and
airside transfer?– …
UH, NOAA
PMLSonic anemometer
UH, NOAA
PML, UCSDSampling line
Instrument Setup
Airmass Back Trajectories (5-day HYSPLIT)
Sensible Heat Flux Mostly Consistent with COARE Model
Mean HiWinGs Cospectra Demonstrate Expected Behaviors of
Atmospheric Turbulence
Peak at 0.1~0.2 Hz due to wind-wave interaction or imperfect motion correction?
Attenuation of sensible heat transfer related to sea spray?
U’W’
U’T’
Higher atm. Acetone & methanol concentrations further south,
esp. in southerly/westerly winds
High degree of correlation between the two suggests
common sources (e.g. terrestrial emission)
Lower concentrations
In high humidity
Gas solubility affects bubble-mediated transport (kb)
NOAA-COARE Gas Transfer Model
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kb =Vo fwhα−1[1+ (eαSc−1/ 2)−1/1.2]−1.2
: Ostwald solubilityfwh: Whitecap fraction (~u3)
Woolf (97) model:
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kw = 360000u*(ρw /ρ a)−1/ 2[hwSc
1/ 2 + κ −1 ln(0.5 /δw )]−1 + Bkb
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hw =13.3/(Aφ)
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ka =100u*[13.3Sca1/ 2 +CD
−1/ 2 − 5 + 0.5κ −1 ln(Sca )]−1
Waterside
Airside
A & B are empirical constants
Motivation — Large Divergence in kw in High Winds
Obs rare in stormy seas
Existing obs suggest solubility dependence in kw
kw higher for CO2 than for dual tracer (not explained by COARE model)
Yang et al., JGR, 2011 & Unpublished Data
Motivation (cont’) —Why Apparent Attenuation of kDMS in High Winds?
Bell et al., ACP, 2013
S. Ocean, 2008N. Atlantic2011