The influence of environmental parameters on active and maturing oceanic whitecaps

Scanlon, Brian; Ward, Brian

doi:10.1002/2015jc011230

Cited by 28 publications

(28 citation statements)

References 64 publications

(130 reference statements)

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“…Wind speed is here used as a proxy for the fraction of breaking waves. No wave breaking is expected to occur at wind speeds below 4 m s −1 , and 8.5 m s −1 was chosen as a threshold because it lies in the range of wind speeds for which whitecapping parameterizations start to diverge (Scanlon & Ward, , Figure ). Figure shows that for both the low and higher wind speeds, the depth dependency of the observed ϵ follow closer to the classical wall layer scaling of

| z |^{- 1}

than a suggested

| z |^{- 2}

(

| z |^{- 1.14}

above h ϵ and

| z |^{- 1.34}

above z t for low‐wind speeds and

| z |^{- 1.12}

above h ϵ and

| z |^{- 1.20}

above z t for higher wind speeds).…”

Section: Resultsmentioning

confidence: 99%

“…The Knorr11 cruise was carried out in the North Atlantic aboard the R/V Knorr from late June to mid‐July 2011 (see Bell et al, ; Christensen et al, ; Esters et al, ; O'Sullivan et al, ; Scanlon et al, ; Scanlon & Ward, ; Sutherland et al, , for further details). It is shown by Bell et al () (in their supporting information) for this cruise, that the eddy covariance

u_{*_{a}}

and wind speed measurements agree with the drag determined using the COARE algorithm.…”

Section: Methodsmentioning

confidence: 99%

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Turbulence Scaling Comparisons in the Ocean Surface Boundary Layer

et al. 2018

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Direct observations of the dissipation rate of turbulent kinetic energy, ϵ, under open ocean conditions are limited. Consequently, our understanding of what chiefly controls dissipation in the open ocean, and its functional form with depth, is poorly constrained. In this study, we report direct open ocean measurements of ϵ from the Air‐Sea Interaction Profiler (ASIP) collected during five different cruises in the Atlantic Ocean. We then combine these data with ocean‐atmosphere flux measurements and wave information in order to evaluate existing turbulence scaling theories under a diverse set of open ocean conditions. Our results do not support the presence of a “breaking” or a “transition layer,” which has been previously suggested. Instead, ϵ decays as |z|−1.29 over the depth interval, which was previously defined as “transition layer,” and as |z|−1.15 over the mixing layer. This depth dependency does not significantly vary between nonbreaking or breaking wave conditions. A scaling relationship based on the friction velocity, the wave age, and the significant wave height describes the observations best for daytime conditions. For conditions during which convection is important, it is necessary to take buoyancy forcing into account.

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| z |^{- 1}

than a suggested

| z |^{- 2}

(

| z |^{- 1.14}

above h ϵ and

| z |^{- 1.34}

above z t for low‐wind speeds and

| z |^{- 1.12}

above h ϵ and

| z |^{- 1.20}

above z t for higher wind speeds).…”

Section: Resultsmentioning

confidence: 99%

u_{*_{a}}

and wind speed measurements agree with the drag determined using the COARE algorithm.…”

Section: Methodsmentioning

confidence: 99%

Turbulence Scaling Comparisons in the Ocean Surface Boundary Layer

et al. 2018

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“…The ship went from Woods Hole MA toward the south of Greenland (Figure ). The main goal of this campaign was to acquire an observational data set of surface ocean properties and air‐sea fluxes during phytoplankton blooms through a combination of meteorological, wave, and whitecap measurements, as well as direct measurements of temperature, salinity, and turbulence in the near‐surface layer of the ocean (see also Bell et al, , ; Esters et al, ; Scanlon & Ward, ; Scanlon et al, ; Sutherland et al, ).…”

Section: Datamentioning

confidence: 99%

Upper Ocean Response to Rain Observed From a Vertical Profiler

et al. 2019

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Rainfall induces a vertical salinity gradient directly below the ocean surface, the strength and lifetime of which depend on the size of the rain event, the availability of mixing, and the air‐sea heat fluxes. The presence of rain in turn influences the near‐surface turbulent mixing and air‐sea exchange processes. During a campaign in the midlatitude North Atlantic, the Air‐Sea Interaction Profiler (ASIP) was used to investigate changes in the vertical distribution of salinity (S), temperature (T), and turbulent kinetic energy dissipation rate (ϵ) caused by four rain events. During one of the rain events a strong shallow stratification was formed. The buoyancy effect of this freshwater lens changes the dominant wind‐driven turbulent mixing. The surface momentum flux was limited to a shallow layer, and below it ϵ is reduced by 2 orders of magnitude. For a different rain event of higher‐peak rain rate, the salinity anomaly is smaller and is dispersed deeper into the water column. The difference in ocean response shows that the upper ocean is sensitive to changes in the atmospheric forcing associated with the rain events. The observed salinity anomalies as a function of rain rate and wind speed are compared to relationships from studies with the 1‐D turbulence model GOTM and satellite validation. The observations suggest that the vertical salinity anomaly is best described as a function of total rain. A higher‐resolution prognostic model for sea surface salinity and temperature is shown to perform well in predicting the observed S and T anomalies.

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“…Concurrent EC flux measurement for DMS and CO 2 also provided an opportunity to assess other influences on k. The DMS flux data indicate that the k DMS -wind-speed relationship was relatively insensitive to surface biogeochemistry or wave action during SOAP (Bell et al, 2015). In addition, SOAP data were used to parameterize whitecap coverage against wind speed and identify the fact that maturing waves may obscure and lead to underestimation of the variability of breaking waves (Scanlon and Ward, 2016).…”

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confidence: 99%

“…This permitted comparison of k DMS estimates with near-surface upper-ocean turbulence at a distance from the vessel . Wave-breaking whitecap coverage was monitored using a Campbell Scientific 5-megapixel camera (cc5mpx) located on the starboard side of the vessel (Scanlon and Ward, 2016). This provided an indicator of bubble entrainment, which contributes to the differential transfer rate of DMS and CO 2 due to their different solubilities (Blomquist et al, 2006;.…”

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confidence: 99%

Overview and preliminary results of the Surface Ocean Aerosol Production (SOAP) campaign

et al. 2017

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Abstract. Establishing the relationship between marine boundary layer (MBL) aerosols and surface water biogeochemistry is required to understand aerosol and cloud production processes over the remote ocean and represent them more accurately in earth system models and global climate projections. This was addressed by the SOAP (Surface Ocean Aerosol Production) campaign, which examined air-sea interaction over biologically productive frontal waters east of New Zealand. This overview details the objectives, regional context, sampling strategy and provisional findings of a pilot study, PreSOAP, in austral summer 2011 and the following SOAP voyage in late austral summer 2012. Both voyages characterized surface water and MBL composition in three phytoplankton blooms of differing species composition and biogeochemistry, with significant regional correlation observed between chlorophyll a and DMSsw. Surface seawater dimethylsulfide (DMSsw) and associated air-sea DMS flux showed spatial variation during the SOAP voyage, with maxima of 25 nmol L −1 and 100 µmol m −2 d −1 , respectively, recorded in a dinoflagellate bloom. Inclusion of SOAP data in a regional DMSsw compilation indicates that the current climatological mean is an underestimate for this region of the southwest Pacific. Estimation of the DMS gas transfer velocity (k DMS ) by independent techniques of eddy covariance and gradient flux showed good agreement, although both exhibited periodic deviations from model estimates. Flux anomalies were related to surface warming and sea surface microlayer enrichment and also reflected the heterogeneous distribution of DMSsw and the associated flux footprint. Other aerosol precursors measured included the halides and various volatile organic carbon compounds, with first measurements of the short-lived gases glyoxal and methylglyoxal in pristine Southern Ocean marine air indicating an unidentified local source. The application of a real-time clean sector, contaminant markers and a common aerosol inlet facilitated multi-sensor measurement of uncontaminated air. Aerosol characterization identified variable Aitken mode and consistent submicron-sized accumulation and coarse modes. Submicron aerosol mass was dominated by secondary particles containing ammonium sulfate/bisulfate under light winds, with an increase in sea salt under higher wind speeds. MBL measurements and chamber experiments identified a significant organic component in primary and secondary aerosols. Comparison of SOAP aerosol number and size distributionsPublished by Copernicus Publications on behalf of the European Geosciences Union. 13646 C. S. Law et al.: Overview and preliminary results of the SOAP campaign reveals an underprediction in GLOMAP (GLObal Model of Aerosol Processes)-mode aerosol number in clean marine air masses, suggesting a missing marine aerosol source in the model. The SOAP data will be further examined for evidence of nucleation events and also to identify relationships between MBL composition and surface ocean biogeochemistry that may pr...

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The influence of environmental parameters on active and maturing oceanic whitecaps

Cited by 28 publications

References 64 publications

Turbulence Scaling Comparisons in the Ocean Surface Boundary Layer

Turbulence Scaling Comparisons in the Ocean Surface Boundary Layer

Upper Ocean Response to Rain Observed From a Vertical Profiler

Overview and preliminary results of the Surface Ocean Aerosol Production (SOAP) campaign

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